(5231,7,'2014-03-14 17:31:17','2014-03-14 17:31:17','[content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n<p style=\"text-align: left;\">[column type=\"three-fifths\" fade=\"true\" fade_animation=\"in-from-left\"][custom_headline type=\"left\" class=\"mtn\" level=\"h2\"]If you want faster code, you\'ve come to the right place.[/custom_headline][gap size=\"12%\"][button  type=\"flat\" shape=\"rounded\" href=\"http://sandbox.arrayfire.com/shop\" size=\"jumbo\" block=\"true\"]Download ArrayFire[/button]</p>\r\n[gap size=\"10%\"]\r\n<p style=\"text-align: left;\">[button  type=\"flat\" block=\"true\" shape=\"rounded\" href=\"http://www.meetme.so/arrayfire\" size=\"jumbo\" ]Schedule a consultation[/button][/column][column fade=\"true\" type=\"two-fifths\" last=\"true\"]</p>\r\nhttp://accelereyes.wistia.com/medias/rj2bar3xxp?embedType=iframe&amp;videoWidth=640\r\n\r\n[/column][gap size=\"5%\"]\r\n\r\n[/content_band] [content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" bg_color=\"transparent\" ]<span style=\"line-height: 1.5em;\">[column type=\"two-fifths\" last=\"false\" ] [custom_headline type=\"left\" level=\"h3\"]An acceleration library for CUDA and OpenCL[/custom_headline]ArrayFire is a fast, hardware-neutral software library for GPU computing with an easy-to-use API. Its array-based function set makes GPU programming simple. A few lines of code in ArrayFire can replace dozens of lines of raw GPU code, saving you valuable time and lowering development costs.</span>\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/fire/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Learn more...[/button][/column]</span> [column class=\"center-text\" type=\"three-fifths\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Triumvirate_Exported.png\"][/column] <span style=\"line-height: 1.5em;\">[/content_band][content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" ]</span> [column class=\"center-text\" type=\"one-half\" fade=\"true\" fade_animation=\"in-from-left\"]<img class=\"aligncenter size-large wp-image-462\" alt=\"Bat signal\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Bat-signal-1024x639.png\" width=\"1024\" height=\"639\" />[/column][column type=\"one-half\" last=\"true\"][custom_headline type=\"left\" level=\"h3\"]Hire the gang![/custom_headline] Hire us to accelerate your code. Or to train your pros. Or to even write your code!\r\n\r\nWe\'ve already helped thousands of organizations speedup their code. We\'ve accelerated all sorts of algorithms, data sets, and challenging problems in the past and we\'re pretty sure that we can tackle your code, too.\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/consult/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Learn more...[/button][/column][/content_band]</span> <span style=\"line-height: 1.5em;\">[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\" ][column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"  ]The ArrayFire Blog[/custom_headline]</span> <span style=\"line-height: 1.5em;\">Check out our blog for the latest and greatest of GPU and accelerator computing. See how ArrayFire is delivering speedups in real applications.</span>\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/blog-2/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Check it out![/button][/column][column type=\"one-half\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][recent_posts count=\"3\"][/column][/content_band]</span>','Home','','inherit','open','closed','','245-revision-v1','','','2014-03-14 17:31:17','2014-03-14 17:31:17','',245,'http://sandbox.arrayfire.com/245-revision-v1/',0,'revision','',0),(5232,7,'2014-03-14 17:32:17','2014-03-14 17:32:17','[content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n<p style=\"text-align: left;\">[column type=\"one-half\" fade=\"true\" fade_animation=\"in-from-left\"][custom_headline type=\"left\" class=\"mtn\" level=\"h2\"]If you want faster code, you\'ve come to the right place.[/custom_headline][gap size=\"12%\"][button  type=\"flat\" shape=\"rounded\" href=\"http://sandbox.arrayfire.com/shop\" size=\"jumbo\" block=\"true\"]Download ArrayFire[/button]</p>\r\n[gap size=\"10%\"]\r\n<p style=\"text-align: left;\">[button  type=\"flat\" block=\"true\" shape=\"rounded\" href=\"http://www.meetme.so/arrayfire\" size=\"jumbo\" ]Schedule a consultation[/button][/column][column fade=\"true\" type=\"one-half\" last=\"true\"]</p>\r\nhttp://accelereyes.wistia.com/medias/rj2bar3xxp?embedType=iframe&amp;videoWidth=640\r\n\r\n[/column][gap size=\"5%\"]\r\n\r\n[/content_band] [content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" bg_color=\"transparent\" ]<span style=\"line-height: 1.5em;\">[column type=\"two-fifths\" last=\"false\" ] [custom_headline type=\"left\" level=\"h3\"]An acceleration library for CUDA and OpenCL[/custom_headline]ArrayFire is a fast, hardware-neutral software library for GPU computing with an easy-to-use API. Its array-based function set makes GPU programming simple. A few lines of code in ArrayFire can replace dozens of lines of raw GPU code, saving you valuable time and lowering development costs.</span>\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/fire/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Learn more...[/button][/column]</span> [column class=\"center-text\" type=\"three-fifths\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Triumvirate_Exported.png\"][/column] <span style=\"line-height: 1.5em;\">[/content_band][content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" ]</span> [column class=\"center-text\" type=\"one-half\" fade=\"true\" fade_animation=\"in-from-left\"]<img class=\"aligncenter size-large wp-image-462\" alt=\"Bat signal\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Bat-signal-1024x639.png\" width=\"1024\" height=\"639\" />[/column][column type=\"one-half\" last=\"true\"][custom_headline type=\"left\" level=\"h3\"]Hire the gang![/custom_headline] Hire us to accelerate your code. Or to train your pros. Or to even write your code!\r\n\r\nWe\'ve already helped thousands of organizations speedup their code. We\'ve accelerated all sorts of algorithms, data sets, and challenging problems in the past and we\'re pretty sure that we can tackle your code, too.\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/consult/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Learn more...[/button][/column][/content_band]</span> <span style=\"line-height: 1.5em;\">[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\" ][column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"  ]The ArrayFire Blog[/custom_headline]</span> <span style=\"line-height: 1.5em;\">Check out our blog for the latest and greatest of GPU and accelerator computing. See how ArrayFire is delivering speedups in real applications.</span>\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/blog-2/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Check it out![/button][/column][column type=\"one-half\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][recent_posts count=\"3\"][/column][/content_band]</span>','Home','','inherit','open','closed','','245-revision-v1','','','2014-03-14 17:32:17','2014-03-14 17:32:17','',245,'http://sandbox.arrayfire.com/245-revision-v1/',0,'revision','',0),(5233,7,'2014-03-14 17:33:14','2014-03-14 17:33:14','[content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n<p style=\"text-align: left;\">[column type=\"two-fifths\" fade=\"true\" fade_animation=\"in-from-left\"][custom_headline type=\"left\" class=\"mtn\" level=\"h2\"]If you want faster code, you\'ve come to the right place.[/custom_headline][gap size=\"12%\"][button  type=\"flat\" shape=\"rounded\" href=\"http://sandbox.arrayfire.com/shop\" size=\"jumbo\" block=\"true\"]Download ArrayFire[/button]</p>\r\n[gap size=\"10%\"]\r\n<p style=\"text-align: left;\">[button  type=\"flat\" block=\"true\" shape=\"rounded\" href=\"http://www.meetme.so/arrayfire\" size=\"jumbo\" ]Schedule a consultation[/button][/column][column fade=\"true\" type=\"three-fifths\" last=\"true\"]</p>\r\nhttp://accelereyes.wistia.com/medias/rj2bar3xxp?embedType=iframe&amp;videoWidth=640\r\n\r\n[/column][gap size=\"5%\"]\r\n\r\n[/content_band] [content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" bg_color=\"transparent\" ]<span style=\"line-height: 1.5em;\">[column type=\"two-fifths\" last=\"false\" ] [custom_headline type=\"left\" level=\"h3\"]An acceleration library for CUDA and OpenCL[/custom_headline]ArrayFire is a fast, hardware-neutral software library for GPU computing with an easy-to-use API. Its array-based function set makes GPU programming simple. A few lines of code in ArrayFire can replace dozens of lines of raw GPU code, saving you valuable time and lowering development costs.</span>\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/fire/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Learn more...[/button][/column]</span> [column class=\"center-text\" type=\"three-fifths\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Triumvirate_Exported.png\"][/column] <span style=\"line-height: 1.5em;\">[/content_band][content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" ]</span> [column class=\"center-text\" type=\"one-half\" fade=\"true\" fade_animation=\"in-from-left\"]<img class=\"aligncenter size-large wp-image-462\" alt=\"Bat signal\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Bat-signal-1024x639.png\" width=\"1024\" height=\"639\" />[/column][column type=\"one-half\" last=\"true\"][custom_headline type=\"left\" level=\"h3\"]Hire the gang![/custom_headline] Hire us to accelerate your code. Or to train your pros. Or to even write your code!\r\n\r\nWe\'ve already helped thousands of organizations speedup their code. We\'ve accelerated all sorts of algorithms, data sets, and challenging problems in the past and we\'re pretty sure that we can tackle your code, too.\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/consult/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Learn more...[/button][/column][/content_band]</span> <span style=\"line-height: 1.5em;\">[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\" ][column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"  ]The ArrayFire Blog[/custom_headline]</span> <span style=\"line-height: 1.5em;\">Check out our blog for the latest and greatest of GPU and accelerator computing. See how ArrayFire is delivering speedups in real applications.</span>\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/blog-2/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Check it out![/button][/column][column type=\"one-half\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][recent_posts count=\"3\"][/column][/content_band]</span>','Home','','inherit','open','closed','','245-revision-v1','','','2014-03-14 17:33:14','2014-03-14 17:33:14','',245,'http://sandbox.arrayfire.com/245-revision-v1/',0,'revision','',0),(5234,7,'2014-03-14 17:38:03','2014-03-14 17:38:03','[content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n<p style=\"text-align: left;\">[column type=\"two-fifths\" fade=\"true\" fade_animation=\"in-from-left\"][custom_headline type=\"left\" class=\"mtn\" level=\"h2\"]If you want faster code, you\'ve come to the right place.[/custom_headline][gap size=\"12%\"][button  type=\"flat\" shape=\"rounded\" href=\"http://sandbox.arrayfire.com/shop\" size=\"jumbo\" block=\"true\"]Download ArrayFire[/button]</p>\r\n[gap size=\"10%\"]\r\n<p style=\"text-align: left;\">[button  type=\"flat\" block=\"true\" shape=\"rounded\" href=\"http://www.meetme.so/arrayfire\" size=\"jumbo\" ]Schedule a consultation[/button][/column][column fade=\"true\" type=\"three-fifths\" last=\"true\"]</p>\r\n\r\n<iframe src=\"//fast.wistia.net/embed/iframe/rj2bar3xxp\" allowtransparency=\"true\" frameborder=\"0\" scrolling=\"no\" class=\"wistia_embed\" name=\"wistia_embed\" allowfullscreen mozallowfullscreen webkitallowfullscreen oallowfullscreen msallowfullscreen width=\"640\" height=\"388\"></iframe>\r\n\r\n[/column][gap size=\"5%\"]\r\n\r\n[/content_band] [content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" bg_color=\"transparent\" ]<span style=\"line-height: 1.5em;\">[column type=\"two-fifths\" last=\"false\" ] [custom_headline type=\"left\" level=\"h3\"]An acceleration library for CUDA and OpenCL[/custom_headline]ArrayFire is a fast, hardware-neutral software library for GPU computing with an easy-to-use API. Its array-based function set makes GPU programming simple. A few lines of code in ArrayFire can replace dozens of lines of raw GPU code, saving you valuable time and lowering development costs.</span>\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/fire/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Learn more...[/button][/column]</span> [column class=\"center-text\" type=\"three-fifths\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Triumvirate_Exported.png\"][/column] <span style=\"line-height: 1.5em;\">[/content_band][content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" ]</span> [column class=\"center-text\" type=\"one-half\" fade=\"true\" fade_animation=\"in-from-left\"]<img class=\"aligncenter size-large wp-image-462\" alt=\"Bat signal\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Bat-signal-1024x639.png\" width=\"1024\" height=\"639\" />[/column][column type=\"one-half\" last=\"true\"][custom_headline type=\"left\" level=\"h3\"]Hire the gang![/custom_headline] Hire us to accelerate your code. Or to train your pros. Or to even write your code!\r\n\r\nWe\'ve already helped thousands of organizations speedup their code. We\'ve accelerated all sorts of algorithms, data sets, and challenging problems in the past and we\'re pretty sure that we can tackle your code, too.\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/consult/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Learn more...[/button][/column][/content_band]</span> <span style=\"line-height: 1.5em;\">[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\" ][column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"  ]The ArrayFire Blog[/custom_headline]</span> <span style=\"line-height: 1.5em;\">Check out our blog for the latest and greatest of GPU and accelerator computing. See how ArrayFire is delivering speedups in real applications.</span>\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/blog-2/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Check it out![/button][/column][column type=\"one-half\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][recent_posts count=\"3\"][/column][/content_band]</span>','Home','','inherit','open','closed','','245-revision-v1','','','2014-03-14 17:38:03','2014-03-14 17:38:03','',245,'http://sandbox.arrayfire.com/245-revision-v1/',0,'revision','',0),(5235,1,'2014-03-18 03:35:46','2014-03-18 03:35:46','[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"10px\" padding_bottom=\"40px\"][column type=\"one-third\"][custom_headline type=\"left\" level=\"h2\"]Login[/custom_headline]\r\n\r\n[theme-my-login][/column]\r\n\r\n[column type=\"two-thirds\" last=\"true\"][gap size=\"10%\"]\r\n<h4>Get access to the ArrayFire download page by logging into your ArrayFire account. 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By accessing or using this Site, which includes your access to or use of any of the Services, you agree to the Terms of Use. AccelerEyes reserves the right to change the Terms of Use from time to time at its sole discretion. Your use of the Site will be subject to the most current version of the Terms of Use posted on the Site at the time of such use. In addition, when using particular Services or Materials on this Site, you shall be subject to any posted guidelines or rules applicable to such Services or Materials that may contain terms and conditions in addition to those in the Terms of Use. All such guidelines or rules are hereby incorporated by reference into the Terms of Use. If you breach any of the Terms of Use, your authorization to use this Site automatically terminates and you must immediately destroy any Materials Downloaded or printed from the Site.\r\n\r\n<strong>Copyright / Limited License</strong>\r\n\r\nThe Materials and Services on this Site are protected by copyright and/or other intellectual property laws and any unauthorized use of the Materials or Services at this Site may violate such laws. Except as expressly provided herein, AccelerEyes and its suppliers do not grant any express or implied right to you under any patents, copyrights, trademarks, or trade secret information with respect to the Materials and Services.\r\n\r\nExcept as specifically permitted herein, no portion of the information or documents on this Site may be reproduced in any form or by any means without the prior written permission of AccelerEyes.\r\n\r\n<strong>Use of Software</strong>. The software and accompanying documentation that are made available to Download from this Site are the copyrighted work of AccelerEyes and/or its suppliers. Use of the software is governed by the terms of the end user license agreement that accompanies or is included with such software. You will not be able to Download or install any software that is accompanied by or includes an end user license agreement unless you agree to the terms of such end user license agreement. If you do not agree to such terms, you will not be able to use the software. You may not decompile, reverse engineer or otherwise attempt to discover the source code of the software available on the Site.\r\n\r\n<strong>Use of Site Information</strong>. Except as otherwise indicated elsewhere on this Site, you may view, Download and print the documents and information available on this Site subject to the following conditions:\r\n\r\nThe documents and information may be used solely for personal, informational, internal, non-commercial purposes. The documents and information may not be modified or altered in any way. The documents and information on the Site may not be distributed. You may not remove any copyright or other proprietary notices contained in the documents and information.\r\n\r\nAccelerEyes reserves the right to revoke the authorization to view, Download and print the documents and information available on this Site at any time, and any such use shall be discontinued immediately upon written notice from AccelerEyes. The rights granted to you constitute a license and not a transfer of title. The rights specified above to view, Download and print the documents and information available on this Site are not applicable to the design or layout of this Site. Elements of this Site are protected by trade dress and other laws and may not be copied or imitated in whole or in part.\r\n\r\n<strong>Use and Protection of Account Numbers and Password</strong>\r\n\r\nYou are responsible for maintaining the confidentiality of your account number and/or password, if applicable. You are responsible for all uses of your account, whether or not actually or expressly authorized by you.\r\n\r\n<strong>Warranty and Disclaimers</strong>\r\n\r\nEXCEPT AS EXPRESSLY PROVIDED OTHERWISE IN A WRITTEN AGREEMENT BETWEEN YOU AND AccelerEyes, ALL MATERIALS AND SERVICES ON THIS SITE ARE PROVIDED \"AS IS\" WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE, OR THE WARRANTY OF NON-INFRINGEMENT. WITHOUT LIMITING THE FOREGOING, AccelerEyes MAKES NO WARRANTY THAT (i) THE SERVICES AND MATERIALS WILL MEET YOUR REQUIREMENTS, (ii) THE SERVICES AND MATERIALS WILL BE UNINTERRUPTED, TIMELY, SECURE, OR ERROR-FREE, (iii) THE RESULTS THAT MAY BE OBTAINED FROM THE USE OF THE SERVICES OR MATERIALS WILL BE EFFECTIVE, ACCURATE OR RELIABLE, (iv) THE QUALITY OF ANY PRODUCTS, SERVICES, OR INFORMATION PURCHASED OR OBTAINED BY YOU FROM THE SITE WILL MEET YOUR EXPECTATIONS, AND (v) ANY ERRORS IN THE SOFTWARE OBTAINED FROM THE SITE WILL BE CORRECTED. SOME STATES OR JURISDICTIONS DO NOT ALLOW THE EXCLUSION OF IMPLIED WARRANTIES OR LIMITATIONS ON HOW LONG AN IMPLIED WARRANTY MAY LAST, SO THE ABOVE LIMITATIONS MAY NOT APPLY TO YOU. TO THE EXTENT PERMISSIBLE, ANY IMPLIED WARRANTIES ARE LIMITED TO NINETY (90) DAYS.\r\n\r\nTHIS SITE COULD INCLUDE TECHNICAL OR OTHER MISTAKES, INACCURACIES OR TYPOGRAPHICAL ERRORS. AccelerEyes MAY MAKE CHANGES TO THE MATERIALS AND SERVICES AT THIS SITE, INCLUDING THE PRICES AND DESCRIPTIONS OF ANY PRODUCTS LISTED HEREIN, AT ANY TIME WITHOUT NOTICE. THE MATERIALS OR SERVICES AT THIS SITE MAY BE OUT OF DATE, AND AccelerEyes MAKES NO COMMITMENT TO UPDATE SUCH MATERIALS OR SERVICES.\r\n\r\nAccelerEyes ASSUMES NO RESPONSIBILITY FOR ERRORS OR OMISSIONS IN THE INFORMATION, DOCUMENTS, SOFTWARE, MATERIALS AND/OR SERVICES WHICH ARE REFERENCED BY OR LINKED TO THIS SITE. REFERENCES TO OTHER CORPORATIONS, THEIR SERVICES AND PRODUCTS, ARE PROVIDED \"AS IS\" WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESS OR IMPLIED.\r\n\r\nIN NO EVENT SHALL AccelerEyes OR ITS SUPPLIERS BE LIABLE TO YOU OR ANY THIRD PARTY FOR ANY SPECIAL, PUNITIVE, INCIDENTAL, INDIRECT OR CONSEQUENTIAL DAMAGES OF ANY KIND, OR ANY DAMAGES WHATSOEVER, INCLUDING, WITHOUT LIMITATION, THOSE RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER OR NOT AccelerEyes HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES, AND ON ANY THEORY OF LIABILITY, ARISING OUT OF OR IN CONNECTION WITH THE USE OF THIS SITE OR OF ANY WEB SITE REFERENCED OR LINKED TO FROM THIS SITE. SOME JURISDICTIONS PROHIBIT THE EXCLUSION OR LIMITATION OF LIABILITY FOR CONSEQUENTIAL OR INCIDENTAL DAMAGES, SO THE ABOVE LIMITATIONS MAY NOT APPLY TO YOU.\r\n\r\nTHE USE OF THE SERVICES OR THE DOWNLOAD OR OTHER ACQUISITION OF ANY MATERIALS THROUGH THE SITE IS DONE AT YOUR OWN DISCRETION AND RISK AND WITH YOUR AGREEMENT THAT YOU WILL BE SOLELY RESPONSIBLE FOR ANY DAMAGE TO YOUR COMPUTER SYSTEM OR LOSS OF DATA THAT RESULTS FROM SUCH ACTIVITIES. NO ADVICE OR INFORMATION, WHETHER ORAL OR WRITTEN, OBTAINED BY YOU FROM AccelerEyes OR THROUGH OR FROM THE SITE SHALL CREATE ANY WARRANTY NOT EXPRESSLY STATED IN THE TERMS OF USE.\r\n\r\nThis Site contains links to third-party Web sites that are not under the control of AccelerEyes. AccelerEyes makes no representations whatsoever about any other Web site to which you may have access through this Site. When you access a non-AccelerEyes Web site, you do so at your own risk and AccelerEyes is not responsible for the accuracy or reliability of any information, data, opinions, advice, or statements made on these sites or for the quality of any products or services available on such sites. AccelerEyes provides these links merely as a convenience and the inclusion of such links does not imply that AccelerEyes endorses or accepts any responsibility for the content or uses of such Web sites.\r\n\r\nThis Site can be accessed from other countries around the world and may contain references to AccelerEyes products, services, and programs that have not been announced in your country. These references do not imply that AccelerEyes intends to announce such products, services or programs in your country.\r\n\r\n<strong>Personal Information and Privacy</strong>\r\n\r\nTo learn about how AccelerEyes protects your personal information, such as your name and address, refer to the AccelerEyes Online Privacy Policy. Please note that any non-personal information or material sent to AccelerEyes will be generally be deemed to NOT be confidential.\r\n\r\n<strong>License for User Content</strong>\r\n\r\nCertain Services offered on this Site accommodate or require user-supplied information, materials or communications (collectively, \'User Content\'). Depending upon the nature of the Service, by submitting User Content to this Site you grant AccelerEyes one of the following two types of licenses:\r\n\r\nFor User Content that is the result of your creative efforts, such as examples of work you have done using AccelerEyes products, you hereby grant AccelerEyes a worldwide, royalty-free, non-exclusive license to reproduce and modify (for purposes of formatting, maintenance or Site administration only) such User Content. You also grant AccelerEyes the right to distribute and publicly display and perform such User Content for the purpose for which such User Content was submitted to the Service. This license will be in effect until such User Content is removed from the Site.\r\n\r\nFor User Content such as comments to the AccelerEyes User to User Forums, bug reports, piracy reports or product suggestions, you grant AccelerEyes an unrestricted, worldwide, irrevocable license to use, reproduce, display, perform, modify, transmit and distribute such User Content, and you also agree that AccelerEyes is free to use any ideas, concepts, know-how or techniques that you send us for any purpose. However, we will not release your name or otherwise publicize the fact that you submitted such User Content to us unless: (a) you grant us permission to do so; (b) we first notify you that the User Content you submit to a particular part of the Site will be published or otherwise used with your name on it; or (c) we are required to do so by law.\r\n\r\n<strong>Prohibited Communications</strong>\r\n\r\nYou may only submit to the Site, User Content that is (a) owned by you, (b) submitted with the express permission of the owner, or (c) in the public domain. You are prohibited from posting or transmitting to or from this Site any unlawful, threatening, libelous, defamatory, obscene, pornographic, or other materials that would violate any law or the rights of others, including without limitation, laws against copyright infringement. Violation of these restrictions may result in limitations on access by you to this Site.\r\n\r\n<strong>Managing User Content and Communications</strong>\r\n\r\nAccelerEyes reserves the right, in its sole discretion, to delete or remove your User Content from the Site and to restrict, suspend or terminate your access to all or part of this Site, at any time for any reason without prior notice or liability.\r\n\r\nAccelerEyes may establish general practices and limits on the use of any Service, including, but not limited to, limits on retention time, file size, and storage space for User Content. AccelerEyes shall have no liability or responsibility for the deletion or failure to store any information or materials in connection with any Service.\r\n\r\nAccelerEyes may, but is not obligated to, monitor or review (i) any areas on the Site where users transmit or post User Content, including but not limited to areas where Services are available, or chat rooms, bulletin boards or other user forums, and (ii) the substance of any User Content.\r\n\r\nTo the maximum extent permitted by law, AccelerEyes will have no liability related to User Content arising under the laws of copyright, libel, privacy, obscenity, or otherwise. AccelerEyes also disclaims all liability with respect to the misuse, loss, modification, or unavailability of any User Content.\r\n\r\n<strong>User Forums</strong>\r\n\r\nIn addition to these Terms of Use, users of the AccelerEyes User To User Forums must agree to a separate legal agreement located within the Forums Registration area of the Site. Your access to the User to User Forums will be denied for violation of the prohibitions set forth in this Terms of Use under the Section entitled PROHIBITED COMMUNICATIONS.\r\n\r\n<strong>Notification of Copyright Infringement</strong>\r\n\r\nAccelerEyes will, in appropriate circumstances, terminate the accounts of users who infringe the intellectual property rights of others. If you believe that your work has been used or copied in a way that constitutes copyright infringement and such infringement is occurring on this Site or on sites linked to from this Site, please provide AccelerEyes\' Copyright Agent a Notice containing the following elements:\r\n\r\na physical or electronic signature of the person authorized to act on behalf of the owner of the copyright interest that is alleged to have been infringed; a description of the copyrighted work or works that you claim have been infringed and identification of what material in such work(s) is claimed to be infringing and which you request to be removed or access to which is to be disabled; a description of where the material that you claim is infringing is located on the AccelerEyes site; information sufficient to permit AccelerEyes to contact you, such as your physical address, telephone number, and email address; a statement by you that you have a good faith belief that the use of the material identified in your Notice in the manner complained of is not authorized by the copyright owner, its agent, or the law; a statement by you that the information in your Notice is accurate and, under penalty of perjury, that you are the copyright owner or authorized to act on the copyright owner\'s behalf.\r\n\r\n<strong>Indemnity</strong>\r\n\r\nYou agree to indemnify and hold AccelerEyes, and its subsidiaries, affiliates, officers, agents, co-branders or other partners, and employees, harmless from any claim or demand, including reasonable attorneys\' fees, made by any third party due to or arising out of content you submit, post to or transmit through the Site (including, without limitation, any User Content), your use of the Site, your connection to the Site, your violation of the Terms of Use, or your violation of any rights of another person or entity.\r\n\r\n<strong>Compliance with Local Laws</strong>\r\n\r\nThis site (excluding linked sites) is controlled by AccelerEyes from its offices in Austell, GA, USA. AccelerEyes makes no representation that materials or services available on this site are appropriate or available for use in specific locations. Accessing them from territories where their contents are illegal is prohibited. Those who choose to access this site from any location do so on their own initiative and are responsible for compliance with local laws.\r\n\r\n<strong>Trademark Information</strong>\r\n\r\nThe trademarks, logos and service marks (\"Marks\") displayed on this Site are the property of AccelerEyes or other third parties. You are not permitted to use the Marks without the prior written consent of AccelerEyes or such third party which may own the Marks. AccelerEyes and the AccelerEyes logo are trademarks of AccelerEyes LLC. [/content_band][content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\"  ]\r\n<h3>Online Privacy Policy</h3>\r\nBy accessing or using the AccelerEyes.com Web site, you agree to the terms of the AccelerEyes Online Privacy Policy, as outlined below. If you do not agree to these terms, please do not access or use this site. AccelerEyes reserves the right to change the Online Privacy Policy from time to time at its sole discretion. Your use of this site will be subject to the most current version of the Online Privacy Policy at the time of such use.\r\n\r\nCollection of personal information\r\n\r\nWhen you engage in certain activities on this site, such as ordering or registering products, Download software, or entering contests, AccelerEyes may ask you to provide certain information about yourself by filling out and submitting an online form. It is completely optional for you to engage in these activities. If you elect to engage in these activities, however, AccelerEyes may ask that you provide us personal information, such as your first and last name, mailing address (including zip code), e-mail address, employer, job title and department, telephone and facsimile numbers, and other personal identifying information. When ordering products or services on the site, you may be asked to provide a credit card number. Depending upon the activity, some of the information that we ask you to provide is identified as mandatory and some as voluntary. If you do not provide the mandatory data with respect to a particular activity, you will not be able to engage in that activity.\r\n\r\nWhen you submit personal information to AccelerEyes on this site, you understand and agree that this information may be transferred across national boundaries and may be stored and processed in any of the countries in which AccelerEyes and its affiliates and subsidiaries maintain offices, including without limitation, the United States. You also acknowledge that in certain countries or with respect to certain activities, the collection, transferring, storage and processing of your information may be undertaken by trusted vendors of AccelerEyes.\r\n\r\nHow your personal information is used AccelerEyes collects your information in order to record and support your participation in the activities you select. If you order a product that is to be electronically Download, for example, the information is used to register your license and rights, if any, to technical support, upgrade discounts, or other benefits that may be made available to registered users. If you enter a contest, information is collected to qualify the entry and contact you regarding the contest or prize awards. The information that you provide is also used as part of our effort to keep you informed about product upgrades, special offers, and other products and services of AccelerEyes and selected third parties.\r\n\r\nYour choices with respect to personal information AccelerEyes recognizes and appreciates the importance of responsible use of information collected on this site. If you do not want the information you provide to AccelerEyes to be used to inform you of other products, services and special offers available from AccelerEyes, and you indicate this preference when you provide your personal information to AccelerEyes, AccelerEyes will honor your preference. AccelerEyes reserves the right to provide aggregate data to third parties for statistical analysis. Such data will not be linked to any particular individuals.\r\n\r\nProtection of your personal information\r\n\r\nThe personal information that you provide in connection with registering yourself as an AccelerEyes user or registering an AccelerEyes product is classified as Registration Information. Registration Information is protected. Your Registration Information resides on a secure server that only selected AccelerEyes personnel and contractors have access to via password. AccelerEyes encrypts your personal information and thereby prevents unauthorized parties from viewing such information when it is transmitted to AccelerEyes.\r\n\r\nPersonal information that you provide that is not Registration Information also resides on a secure server and is only accessible via password. Since this information is not accessible from outside AccelerEyes, you will not be asked to select a password in order to view or modify such information.\r\n\r\nPlease note that any information you post to a public bulletin board or chat room, such as the AccelerEyes User to User Forums, is available to all persons accessing that site.\r\n\r\nUse of cookies\r\n\r\nThe rights specified above to view, Download and print the documents and information available on this Site are not applicable to the design or layout of this Site. Elements of this Site are protected by trade dress and other laws and may not be copied or imitated in whole or in part. When you visit AccelerEyes.com, you can surf the site anonymously and access important information without revealing your identity. In order to improve our site, we use \"cookies\" to track your visit. A cookie is small amount of data that is transferred to your browser by a Web server and can only be read by the server that gave it to you. It functions as your identification card, recording your passwords, purchases, and preferences. It cannot be executed as code or deliver viruses.\r\n\r\nMost browsers are initially set to accept cookies. You can set your browser to notify you when you receive a cookie, giving you the chance to decide whether or not to accept it. (For some Web pages that require an authorization, cookies are not optional. Users choosing not to accept cookies will probably not be able to access those pages.)\r\n\r\nWhile AccelerEyes uses cookies to track your visit to AccelerEyes.com, and our Web servers automatically log the IP/Internet address of your computer, this information does not identify you personally and you remain anonymous unless you have otherwise provided AccelerEyes with personal information.\r\n\r\nPrivacy related complaints\r\n\r\nIf you believe that AccelerEyes has not complied with this Online Privacy Policy with respect to your personal information, you may write the AccelerEyes Privacy Officer at the address indicated above.\r\n\r\nIn your letter, please describe in as much detail as possible the ways in which you believe that the AccelerEyes Online Privacy Policy has not been complied with. We will investigate your complaint promptly.\r\n\r\nPlease note that if you provide AccelerEyes with inconsistent privacy preferences (for example, by indicating on one occasion that third parties may contact you with marketing offers and indicating on another occasion that they may not), AccelerEyes cannot guarantee that your most recent privacy preference will be honored.\r\n\r\nAlso, please note that AccelerEyes is not responsible for the content or privacy practices of non-AccelerEyes Web sites to which AccelerEyes.com or any other AccelerEyes Web site may link.<span style=\"color: #ffffff;\"><span style=\"color: #000000;\">[/content_band]</span></span>[content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n<h3>Imprint</h3>\r\n<strong>AccelerEyes LLC</strong>\r\n3423 Piedmont Rd NE STE 330\r\nAtlanta, GA  30305\r\nUSA\r\nPhone: (800) 570-1941\r\nEmail: <a href=\"mailto:sales@accelereyes.com\">sales@accelereyes.com</a>\r\nEditor: AccelerEyes LLC, Atlanta, GA.\r\nState of Incorporation: Georgia, USA.\r\n\r\n<strong>Disclaimer</strong>\r\n\r\n<strong>Contents of the Website</strong>\r\n\r\nAccelerEyes makes every effort to ensure that the material contained in its web site is current, complete and correct. Despite this errors and mistakes cannot be completely ruled out. AccelerEyes does not accept liability for the relevance, accuracy or completeness of the information and material offered in its website unless the mistake occurred intentionally or through gross negligence. This refers to any loss, additional costs or damage of any kind suffered as a result of any use of any material in this website.\r\n\r\n<strong>Copyright</strong>\r\n\r\nThe Layout of the Homepage, graphics and pictures used and the collection of individual contributions are protected by copyright. AccelerEyes reserves all rights including the rights of reproduction, the duplication and distribution via special processes.\r\n\r\n<strong>Trademarks</strong>\r\n\r\nThe following are either registered trademarks or trademarks of the named company in the United States, United Kingdom and/or other countries.\r\n\r\n\"Personal Supercomputing\" - AccelerEyes LLC.\r\n\"Simple Software for Powerful Visual Computing\" - AccelerEyes LLC.\r\n\"AccelerEyes\", the AccelerEyes logo - AccelerEyes LLC.\r\n\"Jacket\", \"LibJacket\", \"ArrayFire\", and their respective logos - AccelerEyes LLC.\r\nthe NVIDIA logo - NVIDIA.\r\n\"Windows\" - Microsoft Corporation.\r\n\"OpenCL\" - Apple.\r\n\"Adobe\" and \"Acrobat\" - Adobe Systems Inc.\r\nAerospace Blockset™, Bioinformatics Toolbox™, Communications Blockset™, Communications Toolbox™, Control System Toolbox™, Curve Fitting Toolbox™, Data Acquisition Toolbox™, Database Toolbox™, Datafeed Toolbox™, Econometrics Toolbox™, EDA Simulator Link™, Embedded IDE Link™, Embedded MATLAB®, Extended Symbolic Math Toolbox™, Filter Design HDL Coder™, Filter Design Toolbox™, Financial Derivatives Toolbox™, Financial Toolbox™, Fixed-Income Toolbox™, Fixed-Point Toolbox™, Fuzzy Logic Toolbox™, GARCH Toolbox™, Gauges Blockset™, Genetic Algorithm and Direct Search Toolbox™, Handle Graphics®, Image Acquisition Toolbox™, Image Processing Toolbox™, Instrument Control Toolbox™, L-shaped membrane logo (graphic only)®, Mapping Toolbox™, MathWorks®, MATLAB®, MATLAB® Builder™ EX, MATLAB® Builder™ JA, MATLAB® Builder™ NE, MATLAB® Compiler™, MATLAB® Connector™, MATLAB® Distributed Computing Server™, MATLAB® Mobile™, MATLAB® Report Generator™, Model Predictive Control Toolbox™, Model-Based Calibration Toolbox™, Neural Network Toolbox™, OPC Toolbox™, Optimization Toolbox™, Parallel Computing Toolbox™, Partial Differential Equation Toolbox™, Polyspace®, Polyspace® Client™ for Ada, Polyspace® Client™ for C/C++, Polyspace® Model Link™ SL, Polyspace® Model Link™ TL, Polyspace® Server™ for Ada, Polyspace® Server™ for C/C++, Polyspace® UML Link™ RH, Real-Time Windows Target™, Real-Time Workshop®, Real-Time Workshop® Embedded Coder™, RF Blockset™, RF Toolbox™, Robust Control Toolbox™, Signal Processing Blockset™, Signal Processing Toolbox™, SimBiology®, SimDriveline™, SimElectronics®, SimEvents®, SimHydraulics®, SimMechanics™, SimPowerSystems™, SimRF™, Simscape™, Simulink®, Simulink® 3D Animation™, Simulink® Accelerator™, Simulink® Control Design™, Simulink® Design Optimization™, Simulink® Design Verifier™, Simulink® Fixed Point™, Simulink® HDL Coder™, Simulink® Parameter Estimation™, Simulink® PLC Coder™, Simulink® Report Generator™, Simulink® Response Optimization™, Simulink® Verification and Validation™, Spline Toolbox™, Spreadsheet Link™ EX, Stateflow®, Stateflow® Coder™, Statistics Toolbox™, Symbolic Math Toolbox™, System Identification Toolbox™, SystemTest™, Target Support Package™, Vehicle Network Toolbox™, Video and Image Processing Blockset™, Virtual Reality Toolbox™, Wavelet Toolbox™, xPC Target™, xPC TargetBox™, xPC Target™ Embedded Option™ - The MathWorks, Inc.\r\n\r\nIf you notice the use of a trademark on this site which is not accredited herein, please contact our Marketing Department at <a href=\"mailto:sales@accelereyes.com\">sales@accelereyes.com</a>.\r\n\r\n<strong>Links to Third Party Information</strong>\r\n\r\nThe AccelerEyes website links to third party information providers. AccelerEyes has no influence on the contents or reliability of the websites of these third party information providers. The following therefore applies to all links:\r\n\r\nAccelerEyes has no influence on the design and contents of third party internet websites. AccelerEyes therefore expressly distances itself from the material of all third party internet websites, even if the AccelerEyes website links to these external sites. The declaration is valid for all links given on our website and the material of all sites reached via links on the AccelerEyes website. Privacy Where you are invited to submit personal information (eMail address, names, postal addresses) the submission of this information is purely voluntary.\r\n\r\n<strong>Legal validity</strong>\r\n\r\nThis general disclaimer is part of the material offered on the AccelerEyes website. If any of the terms and conditions should be determined invalid by reason of the relevant laws then the remaining terms and conditions shall remain in full effect.[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\" ]<div id=\"eula\"></div>\r\n<h3>End User License Agreement</h3>\r\nPLEASE READ THIS LICENSE CAREFULLY BEFORE USING THE SOFTWARE. BY USING THE SOFTWARE, YOU ARE AGREEING TO BE BOUND BY THE TERMS OF THIS LICENSE. THE TERMS OF THIS LICENSE MAY CHANGE AT ANY TIME UPON ACTUAL OR CONSTRUCTIVE NOTICE TO YOU, AND YOU AGREE TO SUCH CHANGES UPON USING THE SOFTWARE. YOU AGREE TO MONITOR THE ACCELEREYES WEBSITE FOR SUCH CHANGES. IF YOU DO NOT AGREE TO THESE TERMS AND CONDITIONS, DO NOT USE THE SOFTWARE.\r\n\r\n1. License. AccelerEyes LLC (“AccelerEyes”) hereby grants to you a non-exclusive, non-transferable, non-sublicensable, personal license to use the enclosed software program(s) and the accompanying documentation and any related documentation (the software program(s) and any documentation, including and any updates thereto, if any, are collectively referred to as the \"Software\") solely for your internal business purposes (the \"License\"). You own the medium on which the Software is recorded, but AccelerEyes and AccelerEyes\' licensors (referred to collectively as \"AccelerEyes\") retain title to the Software and related documentation. Under the License, you may only:\r\n\r\na) use the Software; and\r\n\r\nb) make a reasonable number of copies necessary for the purposes of this License. You must reproduce on such copy AccelerEyes\' copyright notice and any other proprietary legends that were on the original copy of the Software.\r\n\r\n2. Restrictions on License. The Software contains copyrighted and patented material, trade secrets and other proprietary material. In order to protect them, and except as permitted by applicable legislation, you may not:\r\n\r\na) decompile, reverse engineer, disassemble or otherwise reduce the Software to a human-perceivable form;\r\n\r\nb) modify, network, rent, lend, loan, distribute or create derivative works based upon the Software in whole or in part; or\r\n\r\nc) electronically transmit the Software from one computer to another or over a network or otherwise transfer the Software except as permitted by this License.\r\n\r\n3. Error Reporting and Usage Statistics. AccelerEyes may monitor and collect information on your use of the Software.\r\n\r\n4. Terms for ArrayFire Free Software Subscription.\r\n\r\na) AccelerEyes “ArrayFire Free” Subscription. Subject to the terms of this agreement, the AccelerEyes ArrayFire Free Software is freely available for single GPU usage with a shared license and requires an internet connection. ArrayFire Free automatically connects to AccelerEyes\' online license server.\r\n\r\nb) Availability of the ArrayFire Free Software Subscription. While the ArrayFire Free Subscription is generally available, AccelerEyes reserves the right to determine in its sole discretion who may or may not receive the ArrayFire Free Subscription. The ArrayFire Free subscription is only available for use through the shared license and requires an internet connection.\r\n\r\n5. Terms for AccelerEyes 12 Month Annual (Purchased) Software Subscriptions.\r\n\r\na) AccelerEyes 12 Month Annual “ArrayFire Pro” Subscription. Subject to the terms of this agreement, the AccelerEyes ArrayFire Pro Software is a perpetual, subscription-based License. License updates, maintenance, and support are sold as 12 month annual subscriptions (1-year from the purchase date of the subscription).\r\n\r\nb) AccelerEyes 12 Month Annual “ArrayFire Developer” Subscription. Subject to the terms of this agreement, the AccelerEyes ArrayFire Developer Software is a perpetual, subscription-based License. License updates, maintenance, and support are sold as 12 month annual subscriptions (1-year from the purchase date of the subscription).\r\n\r\nc) AccelerEyes 12 Month Annual “ArrayFire Enterprise” Subscription. Subject to the terms of this agreement, the AccelerEyes ArrayFire Enterprise Software is a perpetual, subscription-based License. License updates, maintenance, and support are sold as 12 month annual subscriptions (1-year from the purchase date of the subscription).\r\n\r\nd) Availability of 12 Month Annual Software Subscription. While the “ArrayFire Pro,” “ArrayFire Developer,” and “ArrayFire Enterprise” 12 month annual Subscriptions are generally available, AccelerEyes reserves the right to determine in its sole discretion who may or may not receive the ArrayFire Subscription.\r\n\r\n6. END OF SOFTWARE SUBSCRIPTION. Non-renewal and Cancellation. AccelerEyes reserves the right to cancel or terminate the “ArrayFire Free” Software Subscription at any time without prior notice to you. For the “ArrayFire Pro,” “ArrayFire Developer,” and “ArrayFire Enterprise” Software Subscriptions, at the end of the 12 month annual subscription period (1-year from the purchase date of the subscription), you may either renew the annual subscription or continue using the ArrayFire Software without future license updates, maintenance, or support. Failure to renew the 12 month annual subscription will automatically terminate the subscription and all future software license updates, maintenance and support.\r\n\r\n7. Renewal of Software Subscription. On or about the expiration of the 12 month annual subscription period, you must provide notice to AccelerEyes of your desire to renew the subscription. AccelerEyes will not automatically renew or bill you for a subsequent subscription after termination without your prior consent. You may renew the “ArrayFire Pro,” “ArrayFire Developer,” or “ArrayFire Enterprise” 12 month annual subscription at any time after the end of the subscription period. The 12 month annual subscription shall be renewed upon your full payment, pro-rated from the date of the end of your last 12 month annual subscription period.\r\n\r\n8. Termination. AccelerEyes may terminate this agreement if, in AccelerEyes’ sole determination, you fail to comply with these terms. Upon termination you must destroy the Software, related documentation and all copies thereof. AccelerEyes reserves the right to revoke this License at any time, and may, at its discretion, cease to provide free license checkouts over the internet.\r\n\r\n9. Government End Users. If you are acquiring the Software on behalf of any unit or agency of the United States Government, the following provisions apply. The Government agrees the Software and documentation were developed at private expense and are provided with \"RESTRICTED RIGHTS\". Use, duplication, or disclosure by the Government is subject to restrictions as set forth in DFARS 227.7202-1(a) and 227.7202-3(a) (1995), DFARS 252.227-7013(c)(1) (ii) (Oct 1988), FAR 12.212(a)(1995), FAR 52.227-19, (June 1987) or FAR 52.227-14(ALT III) (June 1987), as amended from time to time. In the event that this License, or any part thereof, is deemed inconsistent with the minimum rights identified in the Restricted Rights provisions, the minimum rights shall prevail.\r\n\r\n10. No Other License. No rights or licenses are granted by AccelerEyes under this License, expressly or by implication, with respect to any proprietary information or patent, copyright, trade secret or other intellectual property right owned or controlled by AccelerEyes, except as expressly provided in this License.\r\n\r\n11. Additional Licenses. DISTRIBUTION OR USE OF THE SOFTWARE WITH AN OPERATING SYSTEM MAY REQUIRE ADDITIONAL LICENSES FROM THE OPERATING SYSTEM VENDOR. Additional third party licenses may also be required and you agree that you shall be solely responsible for obtaining such license rights.\r\n\r\n12. Disclaimer of Warranty on Software. You expressly acknowledge and agree that use of the Software is at your sole risk. The Software and related documentation are provided \"AS IS\" and without warranty of any kind and AccelerEyes EXPRESSLY DISCLAIMS ALL WARRANTIES, EXPRESS AND IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, ACCURACY, CONDITION, OWNERSHIP, FITNESS FOR A PARTICULAR PURPOSE, AND/OR OF NON-INFRINGEMENT OF THIRD PARTY INTELLECTUAL PROPERTY RIGHTS, AND THOSE ARISING FROM CUSTOM OR TRADE OR COURSE OF USAGE. AccelerEyes DOES NOT WARRANT THAT THE FUNCTIONS CONTAINED IN THE SOFTWARE WILL MEET YOUR REQUIREMENTS, OR THAT THE OPERATION OF THE SOFTWARE WILL BE UNINTERRUPTED OR ERROR-FREE, OR THAT DEFECTS IN THE SOFTWARE WILL BE CORRECTED. THE ENTIRE RISK AS TO THE RESULTS AND PERFORMANCE OF THE SOFTWARE IS ASSUMED BY YOU. FURTHERMORE, AccelerEyes DOES NOT WARRANT OR MAKE ANY REPRESENTATIONS REGARDING THE USE OR THE RESULTS OF THE USE OF THE SOFTWARE OR RELATED DOCUMENTATION IN TERMS OF THEIR CORRECTNESS, ACCURACY, RELIABILITY, CURRENTNESS, OR OTHERWISE. NO ORAL OR WRITTEN INFORMATION OR ADVICE GIVEN BY AccelerEyes OR AccelerEyes\' AUTHORIZED REPRESENTATIVE SHALL CREATE A WARRANTY OR IN ANY WAY INCREASE THE SCOPE OF THIS WARRANTY. SHOULD THE SOFTWARE PROVE DEFECTIVE, YOU (AND NOT AccelerEyes OR AccelerEyes\' AUTHORIZED REPRESENTATIVE(S)) ASSUME THE ENTIRE COST OF ALL NECESSARY SERVICING, REPAIR OR CORRECTION. THE SOFTWARE IS NOT INTENDED FOR USE IN MEDICAL, LIFE SAVING OR LIFE SUSTAINING APPLICATIONS. SOME JURISDICTIONS DO NOT ALLOW THE EXCLUSION OF IMPLIED WARRANTIES, SO THE ABOVE EXCLUSION MAY NOT APPLY TO YOU.\r\n\r\n13. Limitation of Liability. UNDER NO CIRCUMSTANCES, INCLUDING NEGLI GENCE, GROSS NEGLIGENCE, RECKLESS DISREGARD, OR ANY OTHER CONDITION, SHALL AccelerEyes, OR ITS DIRECTORS, OFFICERS, EMPLOYEES OR AGENTS (\"AUTHORIZED REPRESENTATIVES\"), BE LIABLE TO YOU FOR ANY PUNITIVE, EXEMPLARY, DIRECT, INCIDENTAL, INDIRECT, SPECIAL OR CONSEQUENTIAL DAMAGES (INCLUDING DAMAGES FOR LOSS OF BUSINESS PROFITS, BUSINESS INTERRUPTION, LOSS OF BUSINESS INFORMATION, AND THE LIKE) ARISING OUT OF THE USE, MISUSE OR INABILITY TO USE THE SOFTWARE OR RELATED DOCUMENTATION, BREACH OR DEFAULT, INCLUDING THOSE ARISING FROM INFRINGEMENT OR ALLEGED INFRINGEMENT OF ANY PATENT, TRADEMARK, COPYRIGHT OR OTHER INTELLECTUAL PROPERTY RIGHT, BY AccelerEyes, EVEN IF AccelerEyes OR AccelerEyes\' AUTHORIZED REPRESENTATIVE HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES. SOME JURISDICTIONS DO NOT ALLOW THE LIMITATION OR EXCLUSION OF LIABILITY FOR INCIDENTAL OR CONSEQUENTIAL DAMAGES, SO THE ABOVE LIMITATION OR EXCLUSION MAY NOT APPLY TO YOU. AccelerEyes will not be liable for: 1) loss of, or damage to, your records or data; or 2) any damages claimed by you based on any third party claim. In no event shall AccelerEyes\' total liability to you for all damages, losses, and causes of action (whether in contract, tort (including negligence) or otherwise) exceed the dollar (or other applicable financial currency) amount paid by you for the Software.\r\n\r\n14. Export Restrictions. You shall adhere to all U.S. and other applicable export laws, including but not limited to the U.S. Export Administration Regulations (EAR), currently found at 15 C.F.R. Sections 730 through 744. Further, pursuant to 15 C.F.R Section 740.6, You hereby certifies that, except pursuant to a license granted by the United States Department of Commerce Bureau of Industry and Security or as otherwise permitted pursuant to a License Exception under the U.S. Export Administration Regulations (\"EAR\"), You will not (1) export, re-export or release to a national of a country in Country Groups D:1 or E:2 any restricted technology, software, or source code it receives from AccelerEyes, or (2) export to Country Groups D:1 or E:2 the direct product of such technology or software, if such foreign produced direct product is subject to national security controls as identified on the Commerce Control List (currently found in Supplement 1 to Part 774 of EAR). For the most current Country Group listings, or for additional information about the EAR or Recipient\'s obligations under those regulations, please refer to the U.S. Bureau of Industry and Security\'s website at http://www.bis.doc.gov/. These export requirements shall survive any expiration or termination of this Agreement.\r\n\r\n15. Controlling Law and Severability. This Agreement will be governed by and construed under the laws of the State of Georgia without reference to its conflicts of law principles. The rights and obligations under this Agreement shall not be governed by the United Nations Convention on Contracts or the International Sale of Goods, the application of which is expressly excluded. Each party hereto submits to the jurisdiction of the state and federal courts of Fulton County and the Northern District of Georgia for the purpose of all legal proceedings arising out of or relating to this Agreement or the subject matter hereof. Each party waives any objection which it may have to contest such forum.\r\n\r\n16. Complete Agreement. This License constitutes the entire agreement between the parties with respect to the use of the Software and the related documentation, and supersedes all prior or contemporaneous understandings or agreements, written or oral, regarding such subject matter. No amendment to or modification of this License will be binding unless in writing and signed by a duly authorized representative of AccelerEyes.\r\n\r\n---------------------------------------------\r\n\r\nCULA Basic and CULA Premium Software License Agreement\r\n\r\n---------------------------------------------\r\n\r\nThe contents of this file are subject to the Software License Agreement (the \"Agreement\"). You may not use this file except in compliance with the Agreement. You may obtain a copy of the Agreement at http://www.culatools.com/legal. Software distributed under the Agreement is distributed on an \"AS IS\" basis, WITHOUT WARRANTY OF ANY KIND, either express or implied. See the Agreement for the specific language governing rights and limitations under the Agreement. The developer of the CULA Basic and CULA Premium is EM Photonics, Inc., a Delaware corporation. 2008-2009 (c) EM Photonics, Inc. All Rights Reserved. CULATOOLS(tm), CULA(tm), the EM Photonics logo, and certain other trademarks and logos are trademarks or registered trademarks of EM Photonics, Inc. in the United States and other countries.\r\n\r\n---------------------------------------------\r\n\r\nThis software uses the FreeImage open source image library. See http://freeimage.sourceforge.net for details. FreeImage is used under the (GNU GPL or FIPL), version (license version).\r\n\r\nFreeImage Public License - Version 1.0\r\n\r\n---------------------------------------------\r\n\r\n1. Definitions.\r\n\r\n1.1. \"Contributor\" means each entity that creates or contributes to the creation of Modifications.\r\n\r\n1.2. \"Contributor Version\" means the combination of the Original Code, prior Modifications used by a Contributor, and the Modifications made by that particular Contributor.\r\n\r\n1.3. \"Covered Code\" means the Original Code or Modifications or the combination of the Original Code and Modifications, in each case including portions thereof.\r\n\r\n1.4. \"Electronic Distribution Mechanism\" means a mechanism generally accepted in the software development community for the electronic transfer of data.\r\n\r\n1.5. \"Executable\" means Covered Code in any form other than Source Code.\r\n\r\n1.6. \"Initial Developer\" means the individual or entity identified as the Initial Developer in the Source Code notice required by Exhibit A.\r\n\r\n1.7. \"Larger Work\" means a work which combines Covered Code or portions thereof with code not governed by the terms of this License.\r\n\r\n1.8. \"License\" means this document.\r\n\r\n1.9. \"Modifications\" means any addition to or deletion from the substance or structure of either the Original Code or any previous Modifications. When Covered Code is released as a series of files, a Modification is:\r\n\r\nA. Any addition to or deletion from the contents of a file containing Original Code or previous Modifications.\r\n\r\nB. Any new file that contains any part of the Original Code or previous Modifications.\r\n\r\n1.10. \"Original Code\" means Source Code of computer software code which is described in the Source Code notice required by Exhibit A as Original Code, and which, at the time of its release under this License is not already Covered Code governed by this License.\r\n\r\n1.11. \"Source Code\" means the preferred form of the Covered Code for making modifications to it, including all modules it contains, plus any associated interface definition files, scripts used to control compilation and installation of an Executable, or a list of source code differential comparisons against either the Original Code or another well known, available Covered Code of the Contributor\'s choice. The Source Code can be in a compressed or archival form, provided the appropriate decompression or de-archiving software is widely available for no charge.\r\n\r\n1.12. \"You\" means an individual or a legal entity exercising rights under, and complying with all of the terms of, this License or a future version of this License issued under Section 6.1. For legal entities, \"You\" includes any entity which controls, is controlled by, or is under common control with You. For purposes of this definition, \"control\" means (a) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (b) ownership of fifty percent (50%) or more of the outstanding shares or beneficial ownership of such entity.\r\n\r\n2. Source Code License.\r\n\r\n2.1. The Initial Developer Grant. The Initial Developer hereby grants You a world-wide, royalty-free, non-exclusive license, subject to third party intellectual property claims:\r\n\r\n(a) to use, reproduce, modify, display, perform, sublicense and distribute the Original Code (or portions thereof) with or without Modifications, or as part of a Larger Work; and\r\n\r\n(b) under patents now or hereafter owned or controlled by Initial Developer, to make, have made, use and sell (\"Utilize\") the Original Code (or portions thereof), but solely to the extent that any such patent is reasonably necessary to enable You to Utilize the Original Code (or portions thereof) and not to any greater extent that may be necessary to Utilize further Modifications or combinations.\r\n\r\n2.2. Contributor Grant. Each Contributor hereby grants You a world-wide, royalty-free, non-exclusive license, subject to third party intellectual property claims:\r\n\r\n(a) to use, reproduce, modify, display, perform, sublicense and distribute the Modifications created by such Contributor (or portions thereof) either on an unmodified basis, with other Modifications, as Covered Code or as part of a Larger Work; and\r\n\r\n(b) under patents now or hereafter owned or controlled by Contributor, to Utilize the Contributor Version (or portions thereof), but solely to the extent that any such patent is reasonably necessary to enable You to Utilize the Contributor Version (or portions thereof), and not to any greater extent that may be necessary to Utilize further Modifications or combinations.\r\n\r\n3. Distribution Obligations.\r\n\r\n3.1. Application of License.\r\n\r\nThe Modifications which You create or to which You contribute are governed by the terms of this License, including without limitation Section 2.2. The Source Code version of Covered Code may be distributed only under the terms of this License or a future version of this License released under Section 6.1, and You must include a copy of this License with every copy of the Source Code You distribute. You may not offer or impose any terms on any Source Code version that alters or restricts the applicable version of this License or the recipients\' rights hereunder. However, You may include an additional document offering the additional rights described in Section 3.5.\r\n\r\n3.2. Availability of Source Code.\r\n\r\nAny Modification which You create or to which You contribute must be made available in Source Code form under the terms of this License either on the same media as an Executable version or via an accepted Electronic Distribution Mechanism to anyone to whom you made an Executable version available; and if made available via Electronic Distribution Mechanism, must remain available for at least twelve (12) months after the date it initially became available, or at least six (6) months after a subsequent version of that particular Modification has been made available to such recipients. You are responsible for ensuring that the Source Code version remains available even if the Electronic Distribution Mechanism is maintained by a third party.\r\n\r\n3.3. Description of Modifications.\r\n\r\nYou must cause all Covered Code to which you contribute to contain a file documenting the changes You made to create that Covered Code and the date of any change. You must include a prominent statement that the Modification is derived, directly or indirectly, from Original Code provided by the Initial Developer and including the name of the Initial Developer in (a) the Source Code, and (b) in any notice in an Executable version or related documentation in which You describe the origin or ownership of the Covered Code.\r\n\r\n3.4. Intellectual Property Matters\r\n\r\n(a) Third Party Claims.\r\n\r\nIf You have knowledge that a party claims an intellectual property right in particular functionality or code (or its utilization under this License), you must include a text file with the source code distribution titled \"LEGAL\" which describes the claim and the party making the claim in sufficient detail that a recipient will know whom to contact. If you obtain such knowledge after You make Your Modification available as described in Section 3.2, You shall promptly modify the LEGAL file in all copies You make available thereafter and shall take other steps (such as notifying appropriate mailing lists or newsgroups) reasonably calculated to inform those who received the Covered Code that new knowledge has been obtained.\r\n\r\n(b) Contributor APIs.\r\n\r\nIf Your Modification is an application programming interface and You own or control patents which are reasonably necessary to implement that API, you must also include this information in the LEGAL file.\r\n\r\n3.5. Required Notices.\r\n\r\nYou must duplicate the notice in Exhibit A in each file of the Source Code, and this License in any documentation for the Source Code, where You describe recipients\' rights relating to Covered Code. If You created one or more Modification(s), You may add your name as a Contributor to the notice described in Exhibit A. If it is not possible to put such notice in a particular Source Code file due to its structure, then you must include such notice in a location (such as a relevant directory file) where a user would be likely to look for such a notice. You may choose to offer, and to charge a fee for, warranty, support, indemnity or liability obligations to one or more recipients of Covered Code. However, You may do so only on Your own behalf, and not on behalf of the Initial Developer or any Contributor. You must make it absolutely clear than any such warranty, support, indemnity or liability obligation is offered by You alone, and You hereby agree to indemnify the Initial Developer and every Contributor for any liability incurred by the Initial Developer or such Contributor as a result of warranty, support, indemnity or liability terms You offer.\r\n\r\n3.6. Distribution of Executable Versions.\r\n\r\nYou may distribute Covered Code in Executable form only if the requirements of Section 3.1-3.5 have been met for that Covered Code, and if You include a notice stating that the Source Code version of the Covered Code is available under the terms of this License, including a description of how and where You have fulfilled the obligations of Section 3.2. The notice must be conspicuously included in any notice in an Executable version, related documentation or collateral in which You describe recipients\' rights relating to the Covered Code. You may distribute the Executable version of Covered Code under a license of Your choice, which may contain terms different from this License, provided that You are in compliance with the terms of this License and that the license for the Executable version does not attempt to limit or alter the recipient\'s rights in the Source Code version from the rights set forth in this License. If You distribute the Executable version under a different license You must make it absolutely clear that any terms which differ from this License are offered by You alone, not by the Initial Developer or any Contributor. You hereby agree to indemnify the Initial Developer and every Contributor for any liability incurred by the Initial Developer or such Contributor as a result of any such terms You offer.\r\n\r\n3.7. Larger Works.\r\n\r\nYou may create a Larger Work by combining Covered Code with other code not governed by the terms of this License and distribute the Larger Work as a single product. In such a case, You must make sure the requirements of this License are fulfilled for the Covered Code.\r\n\r\n4. Inability to Comply Due to Statute or Regulation.\r\n\r\nIf it is impossible for You to comply with any of the terms of this License with respect to some or all of the Covered Code due to statute or regulation then You must: (a) comply with the terms of this License to the maximum extent possible; and (b) describe the limitations and the code they affect. Such description must be included in the LEGAL file described in Section 3.4 and must be included with all distributions of the Source Code. Except to the extent prohibited by statute or regulation, such description must be sufficiently detailed for a recipient of ordinary skill to be able to understand it.\r\n\r\n5. Application of this License.\r\n\r\nThis License applies to code to which the Initial Developer has attached the notice in Exhibit A, and to related Covered Code.\r\n\r\n6. Versions of the License.\r\n\r\n6.1. New Versions.\r\n\r\nFloris van den Berg may publish revised and/or new versions of the License from time to time. Each version will be given a distinguishing version number.\r\n\r\n6.2. Effect of New Versions.\r\n\r\nOnce Covered Code has been published under a particular version of the License, You may always continue to use it under the terms of that version. You may also choose to use such Covered Code under the terms of any subsequent version of the License published by Floris van den Berg No one other than Floris van den Berg has the right to modify the terms applicable to Covered Code created under this License.\r\n\r\n6.3. Derivative Works.\r\n\r\nIf you create or use a modified version of this License (which you may only do in order to apply it to code which is not already Covered Code governed by this License), you must (a) rename Your license so that the phrases \"FreeImage\", `FreeImage Public License\", \"FIPL\", or any confusingly similar phrase do not appear anywhere in your license and (b) otherwise make it clear that your version of the license contains terms which differ from the FreeImage Public License. (Filling in the name of the Initial Developer, Original Code or Contributor in the notice described in Exhibit A shall not of themselves be deemed to be modifications of this License.)\r\n\r\n7. DISCLAIMER OF WARRANTY.\r\n\r\nCOVERED CODE IS PROVIDED UNDER THIS LICENSE ON AN \"AS IS\" BASIS, WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, WITHOUT LIMITATION, WARRANTIES THAT THE COVERED CODE IS FREE OF DEFECTS, MERCHANTABLE, FIT FOR A PARTICULAR PURPOSE OR NON-INFRINGING. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE COVERED CODE IS WITH YOU. SHOULD ANY COVERED CODE PROVE DEFECTIVE IN ANY RESPECT, YOU (NOT THE INITIAL DEVELOPER OR ANY OTHER CONTRIBUTOR) ASSUME THE COST OF ANY NECESSARY SERVICING, REPAIR OR CORRECTION. THIS DISCLAIMER OF WARRANTY CONSTITUTES AN ESSENTIAL PART OF THIS LICENSE. NO USE OF ANY COVERED CODE IS AUTHORIZED HEREUNDER EXCEPT UNDER THIS DISCLAIMER.\r\n\r\n8. TERMINATION.\r\n\r\nThis License and the rights granted hereunder will terminate automatically if You fail to comply with terms herein and fail to cure such breach within 30 days of becoming aware of the breach. All sublicenses to the Covered Code which are properly granted shall survive any termination of this License. Provisions which, by their nature, must remain in effect beyond the termination of this License shall survive.\r\n\r\n9. LIMITATION OF LIABILITY.\r\n\r\nUNDER NO CIRCUMSTANCES AND UNDER NO LEGAL THEORY, WHETHER TORT (INCLUDING NEGLIGENCE), CONTRACT, OR OTHERWISE, SHALL THE INITIAL DEVELOPER, ANY OTHER CONTRIBUTOR, OR ANY DISTRIBUTOR OF COVERED CODE, OR ANY SUPPLIER OF ANY OF SUCH PARTIES, BE LIABLE TO YOU OR ANY OTHER PERSON FOR ANY INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES OF ANY CHARACTER INCLUDING, WITHOUT LIMITATION, DAMAGES FOR LOSS OF GOODWILL, WORK STOPPAGE, COMPUTER FAILURE OR MALFUNCTION, OR ANY AND ALL OTHER COMMERCIAL DAMAGES OR LOSSES, EVEN IF SUCH PARTY SHALL HAVE BEEN INFORMED OF THE POSSIBILITY OF SUCH DAMAGES. THIS LIMITATION OF LIABILITY SHALL NOT APPLY TO LIABILITY FOR DEATH OR PERSONAL INJURY RESULTING FROM SUCH PARTY\'S NEGLIGENCE TO THE EXTENT APPLICABLE LAW PROHIBITS SUCH LIMITATION. SOME JURISDICTIONS DO NOT ALLOW THE EXCLUSION OR LIMITATION OF INCIDENTAL OR CONSEQUENTIAL DAMAGES, SO THAT EXCLUSION AND LIMITATION MAY NOT APPLY TO YOU.\r\n\r\n10. U.S. GOVERNMENT END USERS.\r\n\r\nThe Covered Code is a \"commercial item,\" as that term is defined in 48 C.F.R. 2.101 (Oct. 1995), consisting of \"commercial computer software\" and \"commercial computer software documentation,\" as such terms are used in 48 C.F.R. 12.212 (Sept. 1995). Consistent with 48 C.F.R. 12.212 and 48 C.F.R. 227.7202-1 through 227.7202-4 (June 1995), all U.S. Government End Users acquire Covered Code with only those rights set forth herein.\r\n\r\n11. MISCELLANEOUS.\r\n\r\nThis License represents the complete agreement concerning subject matter hereof. If any provision of this License is held to be unenforceable, such provision shall be reformed only to the extent necessary to make it enforceable. This License shall be governed by Dutch law provisions (except to the extent applicable law, if any, provides otherwise), excluding its conflict-of-law provisions. With respect to disputes in which at least one party is a citizen of, or an entity chartered or registered to do business in, the The Netherlands: (a) unless otherwise agreed in writing, all disputes relating to this License (excepting any dispute relating to intellectual property rights) shall be subject to final and binding arbitration, with the losing party paying all costs of arbitration; (b) any arbitration relating to this Agreement shall be held in Almelo, The Netherlands; and (c) any litigation relating to this Agreement shall be subject to the jurisdiction of the court of Almelo, The Netherlands with the losing party responsible for costs, including without limitation, court costs and reasonable attorneys fees and expenses. Any law or regulation which provides that the language of a contract shall be construed against the drafter shall not apply to this License.\r\n\r\n12. RESPONSIBILITY FOR CLAIMS.\r\n\r\nExcept in cases where another Contributor has failed to comply with Section 3.4, You are responsible for damages arising, directly or indirectly, out of Your utilization of rights under this License, based on the number of copies of Covered Code you made available, the revenues you received from utilizing such rights, and other relevant factors. You agree to work with affected parties to distribute responsibility on an equitable basis.\r\n\r\nEXHIBIT A.\r\n\r\n\"The contents of this file are subject to the FreeImage Public License Version 1.0 (the \"License\"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://home.wxs.nl/~flvdberg/freeimage-license.txt\r\n\r\nSoftware distributed under the License is distributed on an \"AS IS\" basis, WITHOUT WARRANTY OF ANY KIND, either express or implied. See the License for the specific language governing rights and limitations under the License.\r\n\r\n---------------------------------------------\r\n\r\nclBLAS, clFFT LICENSES\r\n\r\n---------------------------------------------\r\n\r\nApache License - Version 2.0, January 2004 - http://www.apache.org/licenses/\r\n\r\nTERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION\r\n\r\n1. Definitions.\r\n\r\n\"License\" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document.\r\n\r\n\"Licensor\" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License.\r\n\r\n\"Legal Entity\" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, \"control\" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity.\r\n\r\n\"You\" (or \"Your\") shall mean an individual or Legal Entity exercising permissions granted by this License.\r\n\r\n\"Source\" form shall mean the preferred form for making modifications, including but not limited to software source code, documentation source, and configuration files.\r\n\r\n\"Object\" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation, and conversions to other media types.\r\n\r\n\"Work\" shall mean the work of authorship, whether in Source or Object form, made available under the License, as indicated by a copyright notice that is included in or attached to the work (an example is provided in the Appendix below).\r\n\r\n\"Derivative Works\" shall mean any work, whether in Source or Object form, that is based on (or derived from) the Work and for which the editorial revisions, annotations, elaborations, or other modifications represent, as a whole, an original work of authorship. For the purposes of this License, Derivative Works shall not include works that remain separable from, or merely link (or bind by name) to the interfaces of, the Work and Derivative Works thereof.\r\n\r\n\"Contribution\" shall mean any work of authorship, including the original version of the Work and any modifications or additions to that Work or Derivative Works thereof, that is intentionally submitted to Licensor for inclusion in the Work by the copyright owner or by an individual or Legal Entity authorized to submit on behalf of the copyright owner. For the purposes of this definition, \"submitted\" means any form of electronic, verbal, or written communication sent to the Licensor or its representatives, including but not limited to communication on electronic mailing lists, source code control systems, and issue tracking systems that are managed by, or on behalf of, the Licensor for the purpose of discussing and improving the Work, but excluding communication that is conspicuously marked or otherwise designated in writing by the copyright owner as \"Not a Contribution.\"\r\n\r\n\"Contributor\" shall mean Licensor and any individual or Legal Entity on behalf of whom a Contribution has been received by Licensor and subsequently incorporated within the Work.\r\n\r\n2. Grant of Copyright License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare Derivative Works of, publicly display, publicly perform, sublicense, and distribute the Work and such Derivative Works in Source or Object form.\r\n\r\n3. Grant of Patent License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this section) patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Work, where such license applies only to those patent claims licensable by such Contributor that are necessarily infringed by their Contribution(s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was submitted. If You institute patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Work or a Contribution incorporated within the Work constitutes direct or contributory patent infringement, then any patent licenses granted to You under this License for that Work shall terminate as of the date such litigation is filed.\r\n\r\n4. Redistribution. You may reproduce and distribute copies of the Work or Derivative Works thereof in any medium, with or without modifications, and in Source or Object form, provided that You meet the following conditions:\r\n\r\n(a) You must give any other recipients of the Work or Derivative Works a copy of this License; and\r\n\r\n(b) You must cause any modified files to carry prominent notices stating that You changed the files; and\r\n\r\n(c) You must retain, in the Source form of any Derivative Works that You distribute, all copyright, patent, trademark, and attribution notices from the Source form of the Work, excluding those notices that do not pertain to any part of the Derivative Works; and\r\n\r\n(d) If the Work includes a \"NOTICE\" text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding those notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed as part of the Derivative Works; within the Source form or documentation, if provided along with the Derivative Works; or, within a display generated by the Derivative Works, if and wherever such third-party notices normally appear. The contents of the NOTICE file are for informational purposes only and do not modify the License. You may add Your own attribution notices within Derivative Works that You distribute, alongside or as an addendum to the NOTICE text from the Work, provided that such additional attribution notices cannot be construed as modifying the License.\r\n\r\nYou may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions for use, reproduction, or distribution of Your modifications, or for any such Derivative Works as a whole, provided Your use, reproduction, and distribution of the Work otherwise complies with the conditions stated in this License.\r\n\r\n5. Submission of Contributions. Unless You explicitly state otherwise, any Contribution intentionally submitted for inclusion in the Work by You to the Licensor shall be under the terms and conditions of this License, without any additional terms or conditions. Notwithstanding the above, nothing herein shall supersede or modify the terms of any separate license agreement you may have executed with Licensor regarding such Contributions.\r\n\r\n6. Trademarks. This License does not grant permission to use the trade names, trademarks, service marks, or product names of the Licensor, except as required for reasonable and customary use in describing the origin of the Work and reproducing the content of the NOTICE file.\r\n\r\n7. Disclaimer of Warranty. Unless required by applicable law or agreed to in writing, Licensor provides the Work (and each Contributor provides its Contributions) on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied, including, without limitation, any warranties or conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A PARTICULAR PURPOSE. You are solely responsible for determining the appropriateness of using or redistributing the Work and assume any risks associated with Your exercise of permissions under this License.\r\n\r\n8. Limitation of Liability. In no event and under no legal theory, whether in tort (including negligence), contract, or otherwise, unless required by applicable law (such as deliberate and grossly negligent acts) or agreed to in writing, shall any Contributor be liable to You for damages, including any direct, indirect, special, incidental, or consequential damages of any character arising as a result of this License or out of the use or inability to use the Work (including but not limited to damages for loss of goodwill, work stoppage, computer failure or malfunction, or any and all other commercial damages or losses), even if such Contributor has been advised of the possibility of such damages.\r\n\r\n9. Accepting Warranty or Additional Liability. While redistributing the Work or Derivative Works thereof, You may choose to offer, and charge a fee for, acceptance of support, warranty, indemnity, or other liability obligations and/or rights consistent with this License. However, in accepting such obligations, You may act only on Your own behalf and on Your sole responsibility, not on behalf of any other Contributor, and only if You agree to indemnify, defend, and hold each Contributor harmless for any liability incurred by, or claims asserted against, such Contributor by reason of your accepting any such warranty or additional liability.\r\n\r\nEND OF TERMS AND CONDITIONS\r\n\r\nAPPENDIX: How to apply the Apache License to your work.\r\n\r\nTo apply the Apache License to your work, attach the following boilerplate notice, with the fields enclosed by brackets \"[]\" replaced with your own identifying information. (Don\'t include the brackets!) The text should be enclosed in the appropriate comment syntax for the file format. We also recommend that a file or class name and description of purpose be included on the same \"printed page\" as the copyright notice for easier identification within third-party archives.\r\n\r\nCopyright [yyyy] [name of copyright owner]\r\n\r\nLicensed under the Apache License, Version 2.0 (the \"License\"); you may not use this file except in compliance with the License. You may obtain a copy of the License at\r\n\r\nhttp://www.apache.org/licenses/LICENSE-2.0\r\n\r\nUnless required by applicable law or agreed to in writing, software distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.\r\n\r\n---------------------------------------------\r\n\r\nRANDOM123 LICENSE AGREEMENT\r\n\r\n---------------------------------------------\r\n\r\nCopyright 2010-2011, D. E. Shaw Research. All rights reserved.\r\n\r\nRedistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:\r\n\r\n* Redistributions of source code must retain the above copyright notice, this list of conditions, and the following disclaimer.\r\n\r\n* Redistributions in binary form must reproduce the above copyright notice, this list of conditions, and the following disclaimer in the documentation and/or other materials provided with the distribution.\r\n\r\nNeither the name of D. E. Shaw Research nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.\r\n\r\nTHIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.<span style=\"color: #ffffff;\"><span style=\"color: #000000;\">[/content_band]</span></span>','Legal','','inherit','open','closed','','319-revision-v1','','','2014-03-18 20:01:06','2014-03-18 20:01:06','',319,'http://sandbox.arrayfire.com/319-revision-v1/',0,'revision','',0),(5251,7,'2014-03-18 20:02:39','2014-03-18 20:02:39','[content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" bg_color=\"#FFF\" ]\r\n<h3>Terms of Use</h3>\r\n<strong>Acceptance of Terms</strong>\r\n\r\nAccelerEyes makes available for your use on this Web site (the \"Site\") information, documents, software and products (collectively, the \"Materials\") and various services operated by AccelerEyes (collectively, the \"Services\"), subject to the terms and conditions set forth in this document (the \"Terms of Use\"). By accessing or using this Site, which includes your access to or use of any of the Services, you agree to the Terms of Use. AccelerEyes reserves the right to change the Terms of Use from time to time at its sole discretion. Your use of the Site will be subject to the most current version of the Terms of Use posted on the Site at the time of such use. In addition, when using particular Services or Materials on this Site, you shall be subject to any posted guidelines or rules applicable to such Services or Materials that may contain terms and conditions in addition to those in the Terms of Use. All such guidelines or rules are hereby incorporated by reference into the Terms of Use. If you breach any of the Terms of Use, your authorization to use this Site automatically terminates and you must immediately destroy any Materials Downloaded or printed from the Site.\r\n\r\n<strong>Copyright / Limited License</strong>\r\n\r\nThe Materials and Services on this Site are protected by copyright and/or other intellectual property laws and any unauthorized use of the Materials or Services at this Site may violate such laws. Except as expressly provided herein, AccelerEyes and its suppliers do not grant any express or implied right to you under any patents, copyrights, trademarks, or trade secret information with respect to the Materials and Services.\r\n\r\nExcept as specifically permitted herein, no portion of the information or documents on this Site may be reproduced in any form or by any means without the prior written permission of AccelerEyes.\r\n\r\n<strong>Use of Software</strong>. The software and accompanying documentation that are made available to Download from this Site are the copyrighted work of AccelerEyes and/or its suppliers. Use of the software is governed by the terms of the end user license agreement that accompanies or is included with such software. You will not be able to Download or install any software that is accompanied by or includes an end user license agreement unless you agree to the terms of such end user license agreement. If you do not agree to such terms, you will not be able to use the software. You may not decompile, reverse engineer or otherwise attempt to discover the source code of the software available on the Site.\r\n\r\n<strong>Use of Site Information</strong>. Except as otherwise indicated elsewhere on this Site, you may view, Download and print the documents and information available on this Site subject to the following conditions:\r\n\r\nThe documents and information may be used solely for personal, informational, internal, non-commercial purposes. The documents and information may not be modified or altered in any way. The documents and information on the Site may not be distributed. You may not remove any copyright or other proprietary notices contained in the documents and information.\r\n\r\nAccelerEyes reserves the right to revoke the authorization to view, Download and print the documents and information available on this Site at any time, and any such use shall be discontinued immediately upon written notice from AccelerEyes. The rights granted to you constitute a license and not a transfer of title. The rights specified above to view, Download and print the documents and information available on this Site are not applicable to the design or layout of this Site. Elements of this Site are protected by trade dress and other laws and may not be copied or imitated in whole or in part.\r\n\r\n<strong>Use and Protection of Account Numbers and Password</strong>\r\n\r\nYou are responsible for maintaining the confidentiality of your account number and/or password, if applicable. You are responsible for all uses of your account, whether or not actually or expressly authorized by you.\r\n\r\n<strong>Warranty and Disclaimers</strong>\r\n\r\nEXCEPT AS EXPRESSLY PROVIDED OTHERWISE IN A WRITTEN AGREEMENT BETWEEN YOU AND AccelerEyes, ALL MATERIALS AND SERVICES ON THIS SITE ARE PROVIDED \"AS IS\" WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE, OR THE WARRANTY OF NON-INFRINGEMENT. WITHOUT LIMITING THE FOREGOING, AccelerEyes MAKES NO WARRANTY THAT (i) THE SERVICES AND MATERIALS WILL MEET YOUR REQUIREMENTS, (ii) THE SERVICES AND MATERIALS WILL BE UNINTERRUPTED, TIMELY, SECURE, OR ERROR-FREE, (iii) THE RESULTS THAT MAY BE OBTAINED FROM THE USE OF THE SERVICES OR MATERIALS WILL BE EFFECTIVE, ACCURATE OR RELIABLE, (iv) THE QUALITY OF ANY PRODUCTS, SERVICES, OR INFORMATION PURCHASED OR OBTAINED BY YOU FROM THE SITE WILL MEET YOUR EXPECTATIONS, AND (v) ANY ERRORS IN THE SOFTWARE OBTAINED FROM THE SITE WILL BE CORRECTED. SOME STATES OR JURISDICTIONS DO NOT ALLOW THE EXCLUSION OF IMPLIED WARRANTIES OR LIMITATIONS ON HOW LONG AN IMPLIED WARRANTY MAY LAST, SO THE ABOVE LIMITATIONS MAY NOT APPLY TO YOU. TO THE EXTENT PERMISSIBLE, ANY IMPLIED WARRANTIES ARE LIMITED TO NINETY (90) DAYS.\r\n\r\nTHIS SITE COULD INCLUDE TECHNICAL OR OTHER MISTAKES, INACCURACIES OR TYPOGRAPHICAL ERRORS. AccelerEyes MAY MAKE CHANGES TO THE MATERIALS AND SERVICES AT THIS SITE, INCLUDING THE PRICES AND DESCRIPTIONS OF ANY PRODUCTS LISTED HEREIN, AT ANY TIME WITHOUT NOTICE. THE MATERIALS OR SERVICES AT THIS SITE MAY BE OUT OF DATE, AND AccelerEyes MAKES NO COMMITMENT TO UPDATE SUCH MATERIALS OR SERVICES.\r\n\r\nAccelerEyes ASSUMES NO RESPONSIBILITY FOR ERRORS OR OMISSIONS IN THE INFORMATION, DOCUMENTS, SOFTWARE, MATERIALS AND/OR SERVICES WHICH ARE REFERENCED BY OR LINKED TO THIS SITE. REFERENCES TO OTHER CORPORATIONS, THEIR SERVICES AND PRODUCTS, ARE PROVIDED \"AS IS\" WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESS OR IMPLIED.\r\n\r\nIN NO EVENT SHALL AccelerEyes OR ITS SUPPLIERS BE LIABLE TO YOU OR ANY THIRD PARTY FOR ANY SPECIAL, PUNITIVE, INCIDENTAL, INDIRECT OR CONSEQUENTIAL DAMAGES OF ANY KIND, OR ANY DAMAGES WHATSOEVER, INCLUDING, WITHOUT LIMITATION, THOSE RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER OR NOT AccelerEyes HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES, AND ON ANY THEORY OF LIABILITY, ARISING OUT OF OR IN CONNECTION WITH THE USE OF THIS SITE OR OF ANY WEB SITE REFERENCED OR LINKED TO FROM THIS SITE. SOME JURISDICTIONS PROHIBIT THE EXCLUSION OR LIMITATION OF LIABILITY FOR CONSEQUENTIAL OR INCIDENTAL DAMAGES, SO THE ABOVE LIMITATIONS MAY NOT APPLY TO YOU.\r\n\r\nTHE USE OF THE SERVICES OR THE DOWNLOAD OR OTHER ACQUISITION OF ANY MATERIALS THROUGH THE SITE IS DONE AT YOUR OWN DISCRETION AND RISK AND WITH YOUR AGREEMENT THAT YOU WILL BE SOLELY RESPONSIBLE FOR ANY DAMAGE TO YOUR COMPUTER SYSTEM OR LOSS OF DATA THAT RESULTS FROM SUCH ACTIVITIES. NO ADVICE OR INFORMATION, WHETHER ORAL OR WRITTEN, OBTAINED BY YOU FROM AccelerEyes OR THROUGH OR FROM THE SITE SHALL CREATE ANY WARRANTY NOT EXPRESSLY STATED IN THE TERMS OF USE.\r\n\r\nThis Site contains links to third-party Web sites that are not under the control of AccelerEyes. AccelerEyes makes no representations whatsoever about any other Web site to which you may have access through this Site. When you access a non-AccelerEyes Web site, you do so at your own risk and AccelerEyes is not responsible for the accuracy or reliability of any information, data, opinions, advice, or statements made on these sites or for the quality of any products or services available on such sites. AccelerEyes provides these links merely as a convenience and the inclusion of such links does not imply that AccelerEyes endorses or accepts any responsibility for the content or uses of such Web sites.\r\n\r\nThis Site can be accessed from other countries around the world and may contain references to AccelerEyes products, services, and programs that have not been announced in your country. These references do not imply that AccelerEyes intends to announce such products, services or programs in your country.\r\n\r\n<strong>Personal Information and Privacy</strong>\r\n\r\nTo learn about how AccelerEyes protects your personal information, such as your name and address, refer to the AccelerEyes Online Privacy Policy. Please note that any non-personal information or material sent to AccelerEyes will be generally be deemed to NOT be confidential.\r\n\r\n<strong>License for User Content</strong>\r\n\r\nCertain Services offered on this Site accommodate or require user-supplied information, materials or communications (collectively, \'User Content\'). Depending upon the nature of the Service, by submitting User Content to this Site you grant AccelerEyes one of the following two types of licenses:\r\n\r\nFor User Content that is the result of your creative efforts, such as examples of work you have done using AccelerEyes products, you hereby grant AccelerEyes a worldwide, royalty-free, non-exclusive license to reproduce and modify (for purposes of formatting, maintenance or Site administration only) such User Content. You also grant AccelerEyes the right to distribute and publicly display and perform such User Content for the purpose for which such User Content was submitted to the Service. This license will be in effect until such User Content is removed from the Site.\r\n\r\nFor User Content such as comments to the AccelerEyes User to User Forums, bug reports, piracy reports or product suggestions, you grant AccelerEyes an unrestricted, worldwide, irrevocable license to use, reproduce, display, perform, modify, transmit and distribute such User Content, and you also agree that AccelerEyes is free to use any ideas, concepts, know-how or techniques that you send us for any purpose. However, we will not release your name or otherwise publicize the fact that you submitted such User Content to us unless: (a) you grant us permission to do so; (b) we first notify you that the User Content you submit to a particular part of the Site will be published or otherwise used with your name on it; or (c) we are required to do so by law.\r\n\r\n<strong>Prohibited Communications</strong>\r\n\r\nYou may only submit to the Site, User Content that is (a) owned by you, (b) submitted with the express permission of the owner, or (c) in the public domain. You are prohibited from posting or transmitting to or from this Site any unlawful, threatening, libelous, defamatory, obscene, pornographic, or other materials that would violate any law or the rights of others, including without limitation, laws against copyright infringement. Violation of these restrictions may result in limitations on access by you to this Site.\r\n\r\n<strong>Managing User Content and Communications</strong>\r\n\r\nAccelerEyes reserves the right, in its sole discretion, to delete or remove your User Content from the Site and to restrict, suspend or terminate your access to all or part of this Site, at any time for any reason without prior notice or liability.\r\n\r\nAccelerEyes may establish general practices and limits on the use of any Service, including, but not limited to, limits on retention time, file size, and storage space for User Content. AccelerEyes shall have no liability or responsibility for the deletion or failure to store any information or materials in connection with any Service.\r\n\r\nAccelerEyes may, but is not obligated to, monitor or review (i) any areas on the Site where users transmit or post User Content, including but not limited to areas where Services are available, or chat rooms, bulletin boards or other user forums, and (ii) the substance of any User Content.\r\n\r\nTo the maximum extent permitted by law, AccelerEyes will have no liability related to User Content arising under the laws of copyright, libel, privacy, obscenity, or otherwise. AccelerEyes also disclaims all liability with respect to the misuse, loss, modification, or unavailability of any User Content.\r\n\r\n<strong>User Forums</strong>\r\n\r\nIn addition to these Terms of Use, users of the AccelerEyes User To User Forums must agree to a separate legal agreement located within the Forums Registration area of the Site. Your access to the User to User Forums will be denied for violation of the prohibitions set forth in this Terms of Use under the Section entitled PROHIBITED COMMUNICATIONS.\r\n\r\n<strong>Notification of Copyright Infringement</strong>\r\n\r\nAccelerEyes will, in appropriate circumstances, terminate the accounts of users who infringe the intellectual property rights of others. If you believe that your work has been used or copied in a way that constitutes copyright infringement and such infringement is occurring on this Site or on sites linked to from this Site, please provide AccelerEyes\' Copyright Agent a Notice containing the following elements:\r\n\r\na physical or electronic signature of the person authorized to act on behalf of the owner of the copyright interest that is alleged to have been infringed; a description of the copyrighted work or works that you claim have been infringed and identification of what material in such work(s) is claimed to be infringing and which you request to be removed or access to which is to be disabled; a description of where the material that you claim is infringing is located on the AccelerEyes site; information sufficient to permit AccelerEyes to contact you, such as your physical address, telephone number, and email address; a statement by you that you have a good faith belief that the use of the material identified in your Notice in the manner complained of is not authorized by the copyright owner, its agent, or the law; a statement by you that the information in your Notice is accurate and, under penalty of perjury, that you are the copyright owner or authorized to act on the copyright owner\'s behalf.\r\n\r\n<strong>Indemnity</strong>\r\n\r\nYou agree to indemnify and hold AccelerEyes, and its subsidiaries, affiliates, officers, agents, co-branders or other partners, and employees, harmless from any claim or demand, including reasonable attorneys\' fees, made by any third party due to or arising out of content you submit, post to or transmit through the Site (including, without limitation, any User Content), your use of the Site, your connection to the Site, your violation of the Terms of Use, or your violation of any rights of another person or entity.\r\n\r\n<strong>Compliance with Local Laws</strong>\r\n\r\nThis site (excluding linked sites) is controlled by AccelerEyes from its offices in Austell, GA, USA. AccelerEyes makes no representation that materials or services available on this site are appropriate or available for use in specific locations. Accessing them from territories where their contents are illegal is prohibited. Those who choose to access this site from any location do so on their own initiative and are responsible for compliance with local laws.\r\n\r\n<strong>Trademark Information</strong>\r\n\r\nThe trademarks, logos and service marks (\"Marks\") displayed on this Site are the property of AccelerEyes or other third parties. You are not permitted to use the Marks without the prior written consent of AccelerEyes or such third party which may own the Marks. AccelerEyes and the AccelerEyes logo are trademarks of AccelerEyes LLC. [/content_band][content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\"  ]\r\n<h3>Online Privacy Policy</h3>\r\nBy accessing or using the AccelerEyes.com Web site, you agree to the terms of the AccelerEyes Online Privacy Policy, as outlined below. If you do not agree to these terms, please do not access or use this site. AccelerEyes reserves the right to change the Online Privacy Policy from time to time at its sole discretion. Your use of this site will be subject to the most current version of the Online Privacy Policy at the time of such use.\r\n\r\nCollection of personal information\r\n\r\nWhen you engage in certain activities on this site, such as ordering or registering products, Download software, or entering contests, AccelerEyes may ask you to provide certain information about yourself by filling out and submitting an online form. It is completely optional for you to engage in these activities. If you elect to engage in these activities, however, AccelerEyes may ask that you provide us personal information, such as your first and last name, mailing address (including zip code), e-mail address, employer, job title and department, telephone and facsimile numbers, and other personal identifying information. When ordering products or services on the site, you may be asked to provide a credit card number. Depending upon the activity, some of the information that we ask you to provide is identified as mandatory and some as voluntary. If you do not provide the mandatory data with respect to a particular activity, you will not be able to engage in that activity.\r\n\r\nWhen you submit personal information to AccelerEyes on this site, you understand and agree that this information may be transferred across national boundaries and may be stored and processed in any of the countries in which AccelerEyes and its affiliates and subsidiaries maintain offices, including without limitation, the United States. You also acknowledge that in certain countries or with respect to certain activities, the collection, transferring, storage and processing of your information may be undertaken by trusted vendors of AccelerEyes.\r\n\r\nHow your personal information is used AccelerEyes collects your information in order to record and support your participation in the activities you select. If you order a product that is to be electronically Download, for example, the information is used to register your license and rights, if any, to technical support, upgrade discounts, or other benefits that may be made available to registered users. If you enter a contest, information is collected to qualify the entry and contact you regarding the contest or prize awards. The information that you provide is also used as part of our effort to keep you informed about product upgrades, special offers, and other products and services of AccelerEyes and selected third parties.\r\n\r\nYour choices with respect to personal information AccelerEyes recognizes and appreciates the importance of responsible use of information collected on this site. If you do not want the information you provide to AccelerEyes to be used to inform you of other products, services and special offers available from AccelerEyes, and you indicate this preference when you provide your personal information to AccelerEyes, AccelerEyes will honor your preference. AccelerEyes reserves the right to provide aggregate data to third parties for statistical analysis. Such data will not be linked to any particular individuals.\r\n\r\nProtection of your personal information\r\n\r\nThe personal information that you provide in connection with registering yourself as an AccelerEyes user or registering an AccelerEyes product is classified as Registration Information. Registration Information is protected. Your Registration Information resides on a secure server that only selected AccelerEyes personnel and contractors have access to via password. AccelerEyes encrypts your personal information and thereby prevents unauthorized parties from viewing such information when it is transmitted to AccelerEyes.\r\n\r\nPersonal information that you provide that is not Registration Information also resides on a secure server and is only accessible via password. Since this information is not accessible from outside AccelerEyes, you will not be asked to select a password in order to view or modify such information.\r\n\r\nPlease note that any information you post to a public bulletin board or chat room, such as the AccelerEyes User to User Forums, is available to all persons accessing that site.\r\n\r\nUse of cookies\r\n\r\nThe rights specified above to view, Download and print the documents and information available on this Site are not applicable to the design or layout of this Site. Elements of this Site are protected by trade dress and other laws and may not be copied or imitated in whole or in part. When you visit AccelerEyes.com, you can surf the site anonymously and access important information without revealing your identity. In order to improve our site, we use \"cookies\" to track your visit. A cookie is small amount of data that is transferred to your browser by a Web server and can only be read by the server that gave it to you. It functions as your identification card, recording your passwords, purchases, and preferences. It cannot be executed as code or deliver viruses.\r\n\r\nMost browsers are initially set to accept cookies. You can set your browser to notify you when you receive a cookie, giving you the chance to decide whether or not to accept it. (For some Web pages that require an authorization, cookies are not optional. Users choosing not to accept cookies will probably not be able to access those pages.)\r\n\r\nWhile AccelerEyes uses cookies to track your visit to AccelerEyes.com, and our Web servers automatically log the IP/Internet address of your computer, this information does not identify you personally and you remain anonymous unless you have otherwise provided AccelerEyes with personal information.\r\n\r\nPrivacy related complaints\r\n\r\nIf you believe that AccelerEyes has not complied with this Online Privacy Policy with respect to your personal information, you may write the AccelerEyes Privacy Officer at the address indicated above.\r\n\r\nIn your letter, please describe in as much detail as possible the ways in which you believe that the AccelerEyes Online Privacy Policy has not been complied with. We will investigate your complaint promptly.\r\n\r\nPlease note that if you provide AccelerEyes with inconsistent privacy preferences (for example, by indicating on one occasion that third parties may contact you with marketing offers and indicating on another occasion that they may not), AccelerEyes cannot guarantee that your most recent privacy preference will be honored.\r\n\r\nAlso, please note that AccelerEyes is not responsible for the content or privacy practices of non-AccelerEyes Web sites to which AccelerEyes.com or any other AccelerEyes Web site may link.<span style=\"color: #ffffff;\"><span style=\"color: #000000;\">[/content_band]</span></span>[content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n<h3>Imprint</h3>\r\n<strong>AccelerEyes LLC</strong>\r\n3423 Piedmont Rd NE STE 330\r\nAtlanta, GA  30305\r\nUSA\r\nPhone: (800) 570-1941\r\nEmail: <a href=\"mailto:sales@accelereyes.com\">sales@accelereyes.com</a>\r\nEditor: AccelerEyes LLC, Atlanta, GA.\r\nState of Incorporation: Georgia, USA.\r\n\r\n<strong>Disclaimer</strong>\r\n\r\n<strong>Contents of the Website</strong>\r\n\r\nAccelerEyes makes every effort to ensure that the material contained in its web site is current, complete and correct. Despite this errors and mistakes cannot be completely ruled out. AccelerEyes does not accept liability for the relevance, accuracy or completeness of the information and material offered in its website unless the mistake occurred intentionally or through gross negligence. This refers to any loss, additional costs or damage of any kind suffered as a result of any use of any material in this website.\r\n\r\n<strong>Copyright</strong>\r\n\r\nThe Layout of the Homepage, graphics and pictures used and the collection of individual contributions are protected by copyright. AccelerEyes reserves all rights including the rights of reproduction, the duplication and distribution via special processes.\r\n\r\n<strong>Trademarks</strong>\r\n\r\nThe following are either registered trademarks or trademarks of the named company in the United States, United Kingdom and/or other countries.\r\n\r\n\"Personal Supercomputing\" - AccelerEyes LLC.\r\n\"Simple Software for Powerful Visual Computing\" - AccelerEyes LLC.\r\n\"AccelerEyes\", the AccelerEyes logo - AccelerEyes LLC.\r\n\"Jacket\", \"LibJacket\", \"ArrayFire\", and their respective logos - AccelerEyes LLC.\r\nthe NVIDIA logo - NVIDIA.\r\n\"Windows\" - Microsoft Corporation.\r\n\"OpenCL\" - Apple.\r\n\"Adobe\" and \"Acrobat\" - Adobe Systems Inc.\r\nAerospace Blockset™, Bioinformatics Toolbox™, Communications Blockset™, Communications Toolbox™, Control System Toolbox™, Curve Fitting Toolbox™, Data Acquisition Toolbox™, Database Toolbox™, Datafeed Toolbox™, Econometrics Toolbox™, EDA Simulator Link™, Embedded IDE Link™, Embedded MATLAB®, Extended Symbolic Math Toolbox™, Filter Design HDL Coder™, Filter Design Toolbox™, Financial Derivatives Toolbox™, Financial Toolbox™, Fixed-Income Toolbox™, Fixed-Point Toolbox™, Fuzzy Logic Toolbox™, GARCH Toolbox™, Gauges Blockset™, Genetic Algorithm and Direct Search Toolbox™, Handle Graphics®, Image Acquisition Toolbox™, Image Processing Toolbox™, Instrument Control Toolbox™, L-shaped membrane logo (graphic only)®, Mapping Toolbox™, MathWorks®, MATLAB®, MATLAB® Builder™ EX, MATLAB® Builder™ JA, MATLAB® Builder™ NE, MATLAB® Compiler™, MATLAB® Connector™, MATLAB® Distributed Computing Server™, MATLAB® Mobile™, MATLAB® Report Generator™, Model Predictive Control Toolbox™, Model-Based Calibration Toolbox™, Neural Network Toolbox™, OPC Toolbox™, Optimization Toolbox™, Parallel Computing Toolbox™, Partial Differential Equation Toolbox™, Polyspace®, Polyspace® Client™ for Ada, Polyspace® Client™ for C/C++, Polyspace® Model Link™ SL, Polyspace® Model Link™ TL, Polyspace® Server™ for Ada, Polyspace® Server™ for C/C++, Polyspace® UML Link™ RH, Real-Time Windows Target™, Real-Time Workshop®, Real-Time Workshop® Embedded Coder™, RF Blockset™, RF Toolbox™, Robust Control Toolbox™, Signal Processing Blockset™, Signal Processing Toolbox™, SimBiology®, SimDriveline™, SimElectronics®, SimEvents®, SimHydraulics®, SimMechanics™, SimPowerSystems™, SimRF™, Simscape™, Simulink®, Simulink® 3D Animation™, Simulink® Accelerator™, Simulink® Control Design™, Simulink® Design Optimization™, Simulink® Design Verifier™, Simulink® Fixed Point™, Simulink® HDL Coder™, Simulink® Parameter Estimation™, Simulink® PLC Coder™, Simulink® Report Generator™, Simulink® Response Optimization™, Simulink® Verification and Validation™, Spline Toolbox™, Spreadsheet Link™ EX, Stateflow®, Stateflow® Coder™, Statistics Toolbox™, Symbolic Math Toolbox™, System Identification Toolbox™, SystemTest™, Target Support Package™, Vehicle Network Toolbox™, Video and Image Processing Blockset™, Virtual Reality Toolbox™, Wavelet Toolbox™, xPC Target™, xPC TargetBox™, xPC Target™ Embedded Option™ - The MathWorks, Inc.\r\n\r\nIf you notice the use of a trademark on this site which is not accredited herein, please contact our Marketing Department at <a href=\"mailto:sales@accelereyes.com\">sales@accelereyes.com</a>.\r\n\r\n<strong>Links to Third Party Information</strong>\r\n\r\nThe AccelerEyes website links to third party information providers. AccelerEyes has no influence on the contents or reliability of the websites of these third party information providers. The following therefore applies to all links:\r\n\r\nAccelerEyes has no influence on the design and contents of third party internet websites. AccelerEyes therefore expressly distances itself from the material of all third party internet websites, even if the AccelerEyes website links to these external sites. The declaration is valid for all links given on our website and the material of all sites reached via links on the AccelerEyes website. Privacy Where you are invited to submit personal information (eMail address, names, postal addresses) the submission of this information is purely voluntary.\r\n\r\n<strong>Legal validity</strong>\r\n\r\nThis general disclaimer is part of the material offered on the AccelerEyes website. If any of the terms and conditions should be determined invalid by reason of the relevant laws then the remaining terms and conditions shall remain in full effect.[/content_band]<div id=\"eula\"></div>\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n<h3>End User License Agreement</h3>\r\nPLEASE READ THIS LICENSE CAREFULLY BEFORE USING THE SOFTWARE. BY USING THE SOFTWARE, YOU ARE AGREEING TO BE BOUND BY THE TERMS OF THIS LICENSE. THE TERMS OF THIS LICENSE MAY CHANGE AT ANY TIME UPON ACTUAL OR CONSTRUCTIVE NOTICE TO YOU, AND YOU AGREE TO SUCH CHANGES UPON USING THE SOFTWARE. YOU AGREE TO MONITOR THE ACCELEREYES WEBSITE FOR SUCH CHANGES. IF YOU DO NOT AGREE TO THESE TERMS AND CONDITIONS, DO NOT USE THE SOFTWARE.\r\n\r\n1. License. AccelerEyes LLC (“AccelerEyes”) hereby grants to you a non-exclusive, non-transferable, non-sublicensable, personal license to use the enclosed software program(s) and the accompanying documentation and any related documentation (the software program(s) and any documentation, including and any updates thereto, if any, are collectively referred to as the \"Software\") solely for your internal business purposes (the \"License\"). You own the medium on which the Software is recorded, but AccelerEyes and AccelerEyes\' licensors (referred to collectively as \"AccelerEyes\") retain title to the Software and related documentation. Under the License, you may only:\r\n\r\na) use the Software; and\r\n\r\nb) make a reasonable number of copies necessary for the purposes of this License. You must reproduce on such copy AccelerEyes\' copyright notice and any other proprietary legends that were on the original copy of the Software.\r\n\r\n2. Restrictions on License. The Software contains copyrighted and patented material, trade secrets and other proprietary material. In order to protect them, and except as permitted by applicable legislation, you may not:\r\n\r\na) decompile, reverse engineer, disassemble or otherwise reduce the Software to a human-perceivable form;\r\n\r\nb) modify, network, rent, lend, loan, distribute or create derivative works based upon the Software in whole or in part; or\r\n\r\nc) electronically transmit the Software from one computer to another or over a network or otherwise transfer the Software except as permitted by this License.\r\n\r\n3. Error Reporting and Usage Statistics. AccelerEyes may monitor and collect information on your use of the Software.\r\n\r\n4. Terms for ArrayFire Free Software Subscription.\r\n\r\na) AccelerEyes “ArrayFire Free” Subscription. Subject to the terms of this agreement, the AccelerEyes ArrayFire Free Software is freely available for single GPU usage with a shared license and requires an internet connection. ArrayFire Free automatically connects to AccelerEyes\' online license server.\r\n\r\nb) Availability of the ArrayFire Free Software Subscription. While the ArrayFire Free Subscription is generally available, AccelerEyes reserves the right to determine in its sole discretion who may or may not receive the ArrayFire Free Subscription. The ArrayFire Free subscription is only available for use through the shared license and requires an internet connection.\r\n\r\n5. Terms for AccelerEyes 12 Month Annual (Purchased) Software Subscriptions.\r\n\r\na) AccelerEyes 12 Month Annual “ArrayFire Pro” Subscription. Subject to the terms of this agreement, the AccelerEyes ArrayFire Pro Software is a perpetual, subscription-based License. License updates, maintenance, and support are sold as 12 month annual subscriptions (1-year from the purchase date of the subscription).\r\n\r\nb) AccelerEyes 12 Month Annual “ArrayFire Developer” Subscription. Subject to the terms of this agreement, the AccelerEyes ArrayFire Developer Software is a perpetual, subscription-based License. License updates, maintenance, and support are sold as 12 month annual subscriptions (1-year from the purchase date of the subscription).\r\n\r\nc) AccelerEyes 12 Month Annual “ArrayFire Enterprise” Subscription. Subject to the terms of this agreement, the AccelerEyes ArrayFire Enterprise Software is a perpetual, subscription-based License. License updates, maintenance, and support are sold as 12 month annual subscriptions (1-year from the purchase date of the subscription).\r\n\r\nd) Availability of 12 Month Annual Software Subscription. While the “ArrayFire Pro,” “ArrayFire Developer,” and “ArrayFire Enterprise” 12 month annual Subscriptions are generally available, AccelerEyes reserves the right to determine in its sole discretion who may or may not receive the ArrayFire Subscription.\r\n\r\n6. END OF SOFTWARE SUBSCRIPTION. Non-renewal and Cancellation. AccelerEyes reserves the right to cancel or terminate the “ArrayFire Free” Software Subscription at any time without prior notice to you. For the “ArrayFire Pro,” “ArrayFire Developer,” and “ArrayFire Enterprise” Software Subscriptions, at the end of the 12 month annual subscription period (1-year from the purchase date of the subscription), you may either renew the annual subscription or continue using the ArrayFire Software without future license updates, maintenance, or support. Failure to renew the 12 month annual subscription will automatically terminate the subscription and all future software license updates, maintenance and support.\r\n\r\n7. Renewal of Software Subscription. On or about the expiration of the 12 month annual subscription period, you must provide notice to AccelerEyes of your desire to renew the subscription. AccelerEyes will not automatically renew or bill you for a subsequent subscription after termination without your prior consent. You may renew the “ArrayFire Pro,” “ArrayFire Developer,” or “ArrayFire Enterprise” 12 month annual subscription at any time after the end of the subscription period. The 12 month annual subscription shall be renewed upon your full payment, pro-rated from the date of the end of your last 12 month annual subscription period.\r\n\r\n8. Termination. AccelerEyes may terminate this agreement if, in AccelerEyes’ sole determination, you fail to comply with these terms. Upon termination you must destroy the Software, related documentation and all copies thereof. AccelerEyes reserves the right to revoke this License at any time, and may, at its discretion, cease to provide free license checkouts over the internet.\r\n\r\n9. Government End Users. If you are acquiring the Software on behalf of any unit or agency of the United States Government, the following provisions apply. The Government agrees the Software and documentation were developed at private expense and are provided with \"RESTRICTED RIGHTS\". Use, duplication, or disclosure by the Government is subject to restrictions as set forth in DFARS 227.7202-1(a) and 227.7202-3(a) (1995), DFARS 252.227-7013(c)(1) (ii) (Oct 1988), FAR 12.212(a)(1995), FAR 52.227-19, (June 1987) or FAR 52.227-14(ALT III) (June 1987), as amended from time to time. In the event that this License, or any part thereof, is deemed inconsistent with the minimum rights identified in the Restricted Rights provisions, the minimum rights shall prevail.\r\n\r\n10. No Other License. No rights or licenses are granted by AccelerEyes under this License, expressly or by implication, with respect to any proprietary information or patent, copyright, trade secret or other intellectual property right owned or controlled by AccelerEyes, except as expressly provided in this License.\r\n\r\n11. Additional Licenses. DISTRIBUTION OR USE OF THE SOFTWARE WITH AN OPERATING SYSTEM MAY REQUIRE ADDITIONAL LICENSES FROM THE OPERATING SYSTEM VENDOR. Additional third party licenses may also be required and you agree that you shall be solely responsible for obtaining such license rights.\r\n\r\n12. Disclaimer of Warranty on Software. You expressly acknowledge and agree that use of the Software is at your sole risk. The Software and related documentation are provided \"AS IS\" and without warranty of any kind and AccelerEyes EXPRESSLY DISCLAIMS ALL WARRANTIES, EXPRESS AND IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, ACCURACY, CONDITION, OWNERSHIP, FITNESS FOR A PARTICULAR PURPOSE, AND/OR OF NON-INFRINGEMENT OF THIRD PARTY INTELLECTUAL PROPERTY RIGHTS, AND THOSE ARISING FROM CUSTOM OR TRADE OR COURSE OF USAGE. AccelerEyes DOES NOT WARRANT THAT THE FUNCTIONS CONTAINED IN THE SOFTWARE WILL MEET YOUR REQUIREMENTS, OR THAT THE OPERATION OF THE SOFTWARE WILL BE UNINTERRUPTED OR ERROR-FREE, OR THAT DEFECTS IN THE SOFTWARE WILL BE CORRECTED. THE ENTIRE RISK AS TO THE RESULTS AND PERFORMANCE OF THE SOFTWARE IS ASSUMED BY YOU. FURTHERMORE, AccelerEyes DOES NOT WARRANT OR MAKE ANY REPRESENTATIONS REGARDING THE USE OR THE RESULTS OF THE USE OF THE SOFTWARE OR RELATED DOCUMENTATION IN TERMS OF THEIR CORRECTNESS, ACCURACY, RELIABILITY, CURRENTNESS, OR OTHERWISE. NO ORAL OR WRITTEN INFORMATION OR ADVICE GIVEN BY AccelerEyes OR AccelerEyes\' AUTHORIZED REPRESENTATIVE SHALL CREATE A WARRANTY OR IN ANY WAY INCREASE THE SCOPE OF THIS WARRANTY. SHOULD THE SOFTWARE PROVE DEFECTIVE, YOU (AND NOT AccelerEyes OR AccelerEyes\' AUTHORIZED REPRESENTATIVE(S)) ASSUME THE ENTIRE COST OF ALL NECESSARY SERVICING, REPAIR OR CORRECTION. THE SOFTWARE IS NOT INTENDED FOR USE IN MEDICAL, LIFE SAVING OR LIFE SUSTAINING APPLICATIONS. SOME JURISDICTIONS DO NOT ALLOW THE EXCLUSION OF IMPLIED WARRANTIES, SO THE ABOVE EXCLUSION MAY NOT APPLY TO YOU.\r\n\r\n13. Limitation of Liability. UNDER NO CIRCUMSTANCES, INCLUDING NEGLI GENCE, GROSS NEGLIGENCE, RECKLESS DISREGARD, OR ANY OTHER CONDITION, SHALL AccelerEyes, OR ITS DIRECTORS, OFFICERS, EMPLOYEES OR AGENTS (\"AUTHORIZED REPRESENTATIVES\"), BE LIABLE TO YOU FOR ANY PUNITIVE, EXEMPLARY, DIRECT, INCIDENTAL, INDIRECT, SPECIAL OR CONSEQUENTIAL DAMAGES (INCLUDING DAMAGES FOR LOSS OF BUSINESS PROFITS, BUSINESS INTERRUPTION, LOSS OF BUSINESS INFORMATION, AND THE LIKE) ARISING OUT OF THE USE, MISUSE OR INABILITY TO USE THE SOFTWARE OR RELATED DOCUMENTATION, BREACH OR DEFAULT, INCLUDING THOSE ARISING FROM INFRINGEMENT OR ALLEGED INFRINGEMENT OF ANY PATENT, TRADEMARK, COPYRIGHT OR OTHER INTELLECTUAL PROPERTY RIGHT, BY AccelerEyes, EVEN IF AccelerEyes OR AccelerEyes\' AUTHORIZED REPRESENTATIVE HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES. SOME JURISDICTIONS DO NOT ALLOW THE LIMITATION OR EXCLUSION OF LIABILITY FOR INCIDENTAL OR CONSEQUENTIAL DAMAGES, SO THE ABOVE LIMITATION OR EXCLUSION MAY NOT APPLY TO YOU. AccelerEyes will not be liable for: 1) loss of, or damage to, your records or data; or 2) any damages claimed by you based on any third party claim. In no event shall AccelerEyes\' total liability to you for all damages, losses, and causes of action (whether in contract, tort (including negligence) or otherwise) exceed the dollar (or other applicable financial currency) amount paid by you for the Software.\r\n\r\n14. Export Restrictions. You shall adhere to all U.S. and other applicable export laws, including but not limited to the U.S. Export Administration Regulations (EAR), currently found at 15 C.F.R. Sections 730 through 744. Further, pursuant to 15 C.F.R Section 740.6, You hereby certifies that, except pursuant to a license granted by the United States Department of Commerce Bureau of Industry and Security or as otherwise permitted pursuant to a License Exception under the U.S. Export Administration Regulations (\"EAR\"), You will not (1) export, re-export or release to a national of a country in Country Groups D:1 or E:2 any restricted technology, software, or source code it receives from AccelerEyes, or (2) export to Country Groups D:1 or E:2 the direct product of such technology or software, if such foreign produced direct product is subject to national security controls as identified on the Commerce Control List (currently found in Supplement 1 to Part 774 of EAR). For the most current Country Group listings, or for additional information about the EAR or Recipient\'s obligations under those regulations, please refer to the U.S. Bureau of Industry and Security\'s website at http://www.bis.doc.gov/. These export requirements shall survive any expiration or termination of this Agreement.\r\n\r\n15. Controlling Law and Severability. This Agreement will be governed by and construed under the laws of the State of Georgia without reference to its conflicts of law principles. The rights and obligations under this Agreement shall not be governed by the United Nations Convention on Contracts or the International Sale of Goods, the application of which is expressly excluded. Each party hereto submits to the jurisdiction of the state and federal courts of Fulton County and the Northern District of Georgia for the purpose of all legal proceedings arising out of or relating to this Agreement or the subject matter hereof. Each party waives any objection which it may have to contest such forum.\r\n\r\n16. Complete Agreement. This License constitutes the entire agreement between the parties with respect to the use of the Software and the related documentation, and supersedes all prior or contemporaneous understandings or agreements, written or oral, regarding such subject matter. No amendment to or modification of this License will be binding unless in writing and signed by a duly authorized representative of AccelerEyes.\r\n\r\n---------------------------------------------\r\n\r\nCULA Basic and CULA Premium Software License Agreement\r\n\r\n---------------------------------------------\r\n\r\nThe contents of this file are subject to the Software License Agreement (the \"Agreement\"). You may not use this file except in compliance with the Agreement. You may obtain a copy of the Agreement at http://www.culatools.com/legal. Software distributed under the Agreement is distributed on an \"AS IS\" basis, WITHOUT WARRANTY OF ANY KIND, either express or implied. See the Agreement for the specific language governing rights and limitations under the Agreement. The developer of the CULA Basic and CULA Premium is EM Photonics, Inc., a Delaware corporation. 2008-2009 (c) EM Photonics, Inc. All Rights Reserved. CULATOOLS(tm), CULA(tm), the EM Photonics logo, and certain other trademarks and logos are trademarks or registered trademarks of EM Photonics, Inc. in the United States and other countries.\r\n\r\n---------------------------------------------\r\n\r\nThis software uses the FreeImage open source image library. See http://freeimage.sourceforge.net for details. FreeImage is used under the (GNU GPL or FIPL), version (license version).\r\n\r\nFreeImage Public License - Version 1.0\r\n\r\n---------------------------------------------\r\n\r\n1. Definitions.\r\n\r\n1.1. \"Contributor\" means each entity that creates or contributes to the creation of Modifications.\r\n\r\n1.2. \"Contributor Version\" means the combination of the Original Code, prior Modifications used by a Contributor, and the Modifications made by that particular Contributor.\r\n\r\n1.3. \"Covered Code\" means the Original Code or Modifications or the combination of the Original Code and Modifications, in each case including portions thereof.\r\n\r\n1.4. \"Electronic Distribution Mechanism\" means a mechanism generally accepted in the software development community for the electronic transfer of data.\r\n\r\n1.5. \"Executable\" means Covered Code in any form other than Source Code.\r\n\r\n1.6. \"Initial Developer\" means the individual or entity identified as the Initial Developer in the Source Code notice required by Exhibit A.\r\n\r\n1.7. \"Larger Work\" means a work which combines Covered Code or portions thereof with code not governed by the terms of this License.\r\n\r\n1.8. \"License\" means this document.\r\n\r\n1.9. \"Modifications\" means any addition to or deletion from the substance or structure of either the Original Code or any previous Modifications. When Covered Code is released as a series of files, a Modification is:\r\n\r\nA. Any addition to or deletion from the contents of a file containing Original Code or previous Modifications.\r\n\r\nB. Any new file that contains any part of the Original Code or previous Modifications.\r\n\r\n1.10. \"Original Code\" means Source Code of computer software code which is described in the Source Code notice required by Exhibit A as Original Code, and which, at the time of its release under this License is not already Covered Code governed by this License.\r\n\r\n1.11. \"Source Code\" means the preferred form of the Covered Code for making modifications to it, including all modules it contains, plus any associated interface definition files, scripts used to control compilation and installation of an Executable, or a list of source code differential comparisons against either the Original Code or another well known, available Covered Code of the Contributor\'s choice. The Source Code can be in a compressed or archival form, provided the appropriate decompression or de-archiving software is widely available for no charge.\r\n\r\n1.12. \"You\" means an individual or a legal entity exercising rights under, and complying with all of the terms of, this License or a future version of this License issued under Section 6.1. For legal entities, \"You\" includes any entity which controls, is controlled by, or is under common control with You. For purposes of this definition, \"control\" means (a) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (b) ownership of fifty percent (50%) or more of the outstanding shares or beneficial ownership of such entity.\r\n\r\n2. Source Code License.\r\n\r\n2.1. The Initial Developer Grant. The Initial Developer hereby grants You a world-wide, royalty-free, non-exclusive license, subject to third party intellectual property claims:\r\n\r\n(a) to use, reproduce, modify, display, perform, sublicense and distribute the Original Code (or portions thereof) with or without Modifications, or as part of a Larger Work; and\r\n\r\n(b) under patents now or hereafter owned or controlled by Initial Developer, to make, have made, use and sell (\"Utilize\") the Original Code (or portions thereof), but solely to the extent that any such patent is reasonably necessary to enable You to Utilize the Original Code (or portions thereof) and not to any greater extent that may be necessary to Utilize further Modifications or combinations.\r\n\r\n2.2. Contributor Grant. Each Contributor hereby grants You a world-wide, royalty-free, non-exclusive license, subject to third party intellectual property claims:\r\n\r\n(a) to use, reproduce, modify, display, perform, sublicense and distribute the Modifications created by such Contributor (or portions thereof) either on an unmodified basis, with other Modifications, as Covered Code or as part of a Larger Work; and\r\n\r\n(b) under patents now or hereafter owned or controlled by Contributor, to Utilize the Contributor Version (or portions thereof), but solely to the extent that any such patent is reasonably necessary to enable You to Utilize the Contributor Version (or portions thereof), and not to any greater extent that may be necessary to Utilize further Modifications or combinations.\r\n\r\n3. Distribution Obligations.\r\n\r\n3.1. Application of License.\r\n\r\nThe Modifications which You create or to which You contribute are governed by the terms of this License, including without limitation Section 2.2. The Source Code version of Covered Code may be distributed only under the terms of this License or a future version of this License released under Section 6.1, and You must include a copy of this License with every copy of the Source Code You distribute. You may not offer or impose any terms on any Source Code version that alters or restricts the applicable version of this License or the recipients\' rights hereunder. However, You may include an additional document offering the additional rights described in Section 3.5.\r\n\r\n3.2. Availability of Source Code.\r\n\r\nAny Modification which You create or to which You contribute must be made available in Source Code form under the terms of this License either on the same media as an Executable version or via an accepted Electronic Distribution Mechanism to anyone to whom you made an Executable version available; and if made available via Electronic Distribution Mechanism, must remain available for at least twelve (12) months after the date it initially became available, or at least six (6) months after a subsequent version of that particular Modification has been made available to such recipients. You are responsible for ensuring that the Source Code version remains available even if the Electronic Distribution Mechanism is maintained by a third party.\r\n\r\n3.3. Description of Modifications.\r\n\r\nYou must cause all Covered Code to which you contribute to contain a file documenting the changes You made to create that Covered Code and the date of any change. You must include a prominent statement that the Modification is derived, directly or indirectly, from Original Code provided by the Initial Developer and including the name of the Initial Developer in (a) the Source Code, and (b) in any notice in an Executable version or related documentation in which You describe the origin or ownership of the Covered Code.\r\n\r\n3.4. Intellectual Property Matters\r\n\r\n(a) Third Party Claims.\r\n\r\nIf You have knowledge that a party claims an intellectual property right in particular functionality or code (or its utilization under this License), you must include a text file with the source code distribution titled \"LEGAL\" which describes the claim and the party making the claim in sufficient detail that a recipient will know whom to contact. If you obtain such knowledge after You make Your Modification available as described in Section 3.2, You shall promptly modify the LEGAL file in all copies You make available thereafter and shall take other steps (such as notifying appropriate mailing lists or newsgroups) reasonably calculated to inform those who received the Covered Code that new knowledge has been obtained.\r\n\r\n(b) Contributor APIs.\r\n\r\nIf Your Modification is an application programming interface and You own or control patents which are reasonably necessary to implement that API, you must also include this information in the LEGAL file.\r\n\r\n3.5. Required Notices.\r\n\r\nYou must duplicate the notice in Exhibit A in each file of the Source Code, and this License in any documentation for the Source Code, where You describe recipients\' rights relating to Covered Code. If You created one or more Modification(s), You may add your name as a Contributor to the notice described in Exhibit A. If it is not possible to put such notice in a particular Source Code file due to its structure, then you must include such notice in a location (such as a relevant directory file) where a user would be likely to look for such a notice. You may choose to offer, and to charge a fee for, warranty, support, indemnity or liability obligations to one or more recipients of Covered Code. However, You may do so only on Your own behalf, and not on behalf of the Initial Developer or any Contributor. You must make it absolutely clear than any such warranty, support, indemnity or liability obligation is offered by You alone, and You hereby agree to indemnify the Initial Developer and every Contributor for any liability incurred by the Initial Developer or such Contributor as a result of warranty, support, indemnity or liability terms You offer.\r\n\r\n3.6. Distribution of Executable Versions.\r\n\r\nYou may distribute Covered Code in Executable form only if the requirements of Section 3.1-3.5 have been met for that Covered Code, and if You include a notice stating that the Source Code version of the Covered Code is available under the terms of this License, including a description of how and where You have fulfilled the obligations of Section 3.2. The notice must be conspicuously included in any notice in an Executable version, related documentation or collateral in which You describe recipients\' rights relating to the Covered Code. You may distribute the Executable version of Covered Code under a license of Your choice, which may contain terms different from this License, provided that You are in compliance with the terms of this License and that the license for the Executable version does not attempt to limit or alter the recipient\'s rights in the Source Code version from the rights set forth in this License. If You distribute the Executable version under a different license You must make it absolutely clear that any terms which differ from this License are offered by You alone, not by the Initial Developer or any Contributor. You hereby agree to indemnify the Initial Developer and every Contributor for any liability incurred by the Initial Developer or such Contributor as a result of any such terms You offer.\r\n\r\n3.7. Larger Works.\r\n\r\nYou may create a Larger Work by combining Covered Code with other code not governed by the terms of this License and distribute the Larger Work as a single product. In such a case, You must make sure the requirements of this License are fulfilled for the Covered Code.\r\n\r\n4. Inability to Comply Due to Statute or Regulation.\r\n\r\nIf it is impossible for You to comply with any of the terms of this License with respect to some or all of the Covered Code due to statute or regulation then You must: (a) comply with the terms of this License to the maximum extent possible; and (b) describe the limitations and the code they affect. Such description must be included in the LEGAL file described in Section 3.4 and must be included with all distributions of the Source Code. Except to the extent prohibited by statute or regulation, such description must be sufficiently detailed for a recipient of ordinary skill to be able to understand it.\r\n\r\n5. Application of this License.\r\n\r\nThis License applies to code to which the Initial Developer has attached the notice in Exhibit A, and to related Covered Code.\r\n\r\n6. Versions of the License.\r\n\r\n6.1. New Versions.\r\n\r\nFloris van den Berg may publish revised and/or new versions of the License from time to time. Each version will be given a distinguishing version number.\r\n\r\n6.2. Effect of New Versions.\r\n\r\nOnce Covered Code has been published under a particular version of the License, You may always continue to use it under the terms of that version. You may also choose to use such Covered Code under the terms of any subsequent version of the License published by Floris van den Berg No one other than Floris van den Berg has the right to modify the terms applicable to Covered Code created under this License.\r\n\r\n6.3. Derivative Works.\r\n\r\nIf you create or use a modified version of this License (which you may only do in order to apply it to code which is not already Covered Code governed by this License), you must (a) rename Your license so that the phrases \"FreeImage\", `FreeImage Public License\", \"FIPL\", or any confusingly similar phrase do not appear anywhere in your license and (b) otherwise make it clear that your version of the license contains terms which differ from the FreeImage Public License. (Filling in the name of the Initial Developer, Original Code or Contributor in the notice described in Exhibit A shall not of themselves be deemed to be modifications of this License.)\r\n\r\n7. DISCLAIMER OF WARRANTY.\r\n\r\nCOVERED CODE IS PROVIDED UNDER THIS LICENSE ON AN \"AS IS\" BASIS, WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, WITHOUT LIMITATION, WARRANTIES THAT THE COVERED CODE IS FREE OF DEFECTS, MERCHANTABLE, FIT FOR A PARTICULAR PURPOSE OR NON-INFRINGING. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE COVERED CODE IS WITH YOU. SHOULD ANY COVERED CODE PROVE DEFECTIVE IN ANY RESPECT, YOU (NOT THE INITIAL DEVELOPER OR ANY OTHER CONTRIBUTOR) ASSUME THE COST OF ANY NECESSARY SERVICING, REPAIR OR CORRECTION. THIS DISCLAIMER OF WARRANTY CONSTITUTES AN ESSENTIAL PART OF THIS LICENSE. NO USE OF ANY COVERED CODE IS AUTHORIZED HEREUNDER EXCEPT UNDER THIS DISCLAIMER.\r\n\r\n8. TERMINATION.\r\n\r\nThis License and the rights granted hereunder will terminate automatically if You fail to comply with terms herein and fail to cure such breach within 30 days of becoming aware of the breach. All sublicenses to the Covered Code which are properly granted shall survive any termination of this License. Provisions which, by their nature, must remain in effect beyond the termination of this License shall survive.\r\n\r\n9. LIMITATION OF LIABILITY.\r\n\r\nUNDER NO CIRCUMSTANCES AND UNDER NO LEGAL THEORY, WHETHER TORT (INCLUDING NEGLIGENCE), CONTRACT, OR OTHERWISE, SHALL THE INITIAL DEVELOPER, ANY OTHER CONTRIBUTOR, OR ANY DISTRIBUTOR OF COVERED CODE, OR ANY SUPPLIER OF ANY OF SUCH PARTIES, BE LIABLE TO YOU OR ANY OTHER PERSON FOR ANY INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES OF ANY CHARACTER INCLUDING, WITHOUT LIMITATION, DAMAGES FOR LOSS OF GOODWILL, WORK STOPPAGE, COMPUTER FAILURE OR MALFUNCTION, OR ANY AND ALL OTHER COMMERCIAL DAMAGES OR LOSSES, EVEN IF SUCH PARTY SHALL HAVE BEEN INFORMED OF THE POSSIBILITY OF SUCH DAMAGES. THIS LIMITATION OF LIABILITY SHALL NOT APPLY TO LIABILITY FOR DEATH OR PERSONAL INJURY RESULTING FROM SUCH PARTY\'S NEGLIGENCE TO THE EXTENT APPLICABLE LAW PROHIBITS SUCH LIMITATION. SOME JURISDICTIONS DO NOT ALLOW THE EXCLUSION OR LIMITATION OF INCIDENTAL OR CONSEQUENTIAL DAMAGES, SO THAT EXCLUSION AND LIMITATION MAY NOT APPLY TO YOU.\r\n\r\n10. U.S. GOVERNMENT END USERS.\r\n\r\nThe Covered Code is a \"commercial item,\" as that term is defined in 48 C.F.R. 2.101 (Oct. 1995), consisting of \"commercial computer software\" and \"commercial computer software documentation,\" as such terms are used in 48 C.F.R. 12.212 (Sept. 1995). Consistent with 48 C.F.R. 12.212 and 48 C.F.R. 227.7202-1 through 227.7202-4 (June 1995), all U.S. Government End Users acquire Covered Code with only those rights set forth herein.\r\n\r\n11. MISCELLANEOUS.\r\n\r\nThis License represents the complete agreement concerning subject matter hereof. If any provision of this License is held to be unenforceable, such provision shall be reformed only to the extent necessary to make it enforceable. This License shall be governed by Dutch law provisions (except to the extent applicable law, if any, provides otherwise), excluding its conflict-of-law provisions. With respect to disputes in which at least one party is a citizen of, or an entity chartered or registered to do business in, the The Netherlands: (a) unless otherwise agreed in writing, all disputes relating to this License (excepting any dispute relating to intellectual property rights) shall be subject to final and binding arbitration, with the losing party paying all costs of arbitration; (b) any arbitration relating to this Agreement shall be held in Almelo, The Netherlands; and (c) any litigation relating to this Agreement shall be subject to the jurisdiction of the court of Almelo, The Netherlands with the losing party responsible for costs, including without limitation, court costs and reasonable attorneys fees and expenses. Any law or regulation which provides that the language of a contract shall be construed against the drafter shall not apply to this License.\r\n\r\n12. RESPONSIBILITY FOR CLAIMS.\r\n\r\nExcept in cases where another Contributor has failed to comply with Section 3.4, You are responsible for damages arising, directly or indirectly, out of Your utilization of rights under this License, based on the number of copies of Covered Code you made available, the revenues you received from utilizing such rights, and other relevant factors. You agree to work with affected parties to distribute responsibility on an equitable basis.\r\n\r\nEXHIBIT A.\r\n\r\n\"The contents of this file are subject to the FreeImage Public License Version 1.0 (the \"License\"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://home.wxs.nl/~flvdberg/freeimage-license.txt\r\n\r\nSoftware distributed under the License is distributed on an \"AS IS\" basis, WITHOUT WARRANTY OF ANY KIND, either express or implied. See the License for the specific language governing rights and limitations under the License.\r\n\r\n---------------------------------------------\r\n\r\nclBLAS, clFFT LICENSES\r\n\r\n---------------------------------------------\r\n\r\nApache License - Version 2.0, January 2004 - http://www.apache.org/licenses/\r\n\r\nTERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION\r\n\r\n1. Definitions.\r\n\r\n\"License\" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document.\r\n\r\n\"Licensor\" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License.\r\n\r\n\"Legal Entity\" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, \"control\" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity.\r\n\r\n\"You\" (or \"Your\") shall mean an individual or Legal Entity exercising permissions granted by this License.\r\n\r\n\"Source\" form shall mean the preferred form for making modifications, including but not limited to software source code, documentation source, and configuration files.\r\n\r\n\"Object\" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation, and conversions to other media types.\r\n\r\n\"Work\" shall mean the work of authorship, whether in Source or Object form, made available under the License, as indicated by a copyright notice that is included in or attached to the work (an example is provided in the Appendix below).\r\n\r\n\"Derivative Works\" shall mean any work, whether in Source or Object form, that is based on (or derived from) the Work and for which the editorial revisions, annotations, elaborations, or other modifications represent, as a whole, an original work of authorship. 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Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare Derivative Works of, publicly display, publicly perform, sublicense, and distribute the Work and such Derivative Works in Source or Object form.\r\n\r\n3. Grant of Patent License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this section) patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Work, where such license applies only to those patent claims licensable by such Contributor that are necessarily infringed by their Contribution(s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was submitted. 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You may reproduce and distribute copies of the Work or Derivative Works thereof in any medium, with or without modifications, and in Source or Object form, provided that You meet the following conditions:\r\n\r\n(a) You must give any other recipients of the Work or Derivative Works a copy of this License; and\r\n\r\n(b) You must cause any modified files to carry prominent notices stating that You changed the files; and\r\n\r\n(c) You must retain, in the Source form of any Derivative Works that You distribute, all copyright, patent, trademark, and attribution notices from the Source form of the Work, excluding those notices that do not pertain to any part of the Derivative Works; and\r\n\r\n(d) If the Work includes a \"NOTICE\" text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding those notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed as part of the Derivative Works; within the Source form or documentation, if provided along with the Derivative Works; or, within a display generated by the Derivative Works, if and wherever such third-party notices normally appear. The contents of the NOTICE file are for informational purposes only and do not modify the License. You may add Your own attribution notices within Derivative Works that You distribute, alongside or as an addendum to the NOTICE text from the Work, provided that such additional attribution notices cannot be construed as modifying the License.\r\n\r\nYou may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions for use, reproduction, or distribution of Your modifications, or for any such Derivative Works as a whole, provided Your use, reproduction, and distribution of the Work otherwise complies with the conditions stated in this License.\r\n\r\n5. Submission of Contributions. Unless You explicitly state otherwise, any Contribution intentionally submitted for inclusion in the Work by You to the Licensor shall be under the terms and conditions of this License, without any additional terms or conditions. Notwithstanding the above, nothing herein shall supersede or modify the terms of any separate license agreement you may have executed with Licensor regarding such Contributions.\r\n\r\n6. Trademarks. This License does not grant permission to use the trade names, trademarks, service marks, or product names of the Licensor, except as required for reasonable and customary use in describing the origin of the Work and reproducing the content of the NOTICE file.\r\n\r\n7. Disclaimer of Warranty. Unless required by applicable law or agreed to in writing, Licensor provides the Work (and each Contributor provides its Contributions) on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied, including, without limitation, any warranties or conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A PARTICULAR PURPOSE. You are solely responsible for determining the appropriateness of using or redistributing the Work and assume any risks associated with Your exercise of permissions under this License.\r\n\r\n8. Limitation of Liability. In no event and under no legal theory, whether in tort (including negligence), contract, or otherwise, unless required by applicable law (such as deliberate and grossly negligent acts) or agreed to in writing, shall any Contributor be liable to You for damages, including any direct, indirect, special, incidental, or consequential damages of any character arising as a result of this License or out of the use or inability to use the Work (including but not limited to damages for loss of goodwill, work stoppage, computer failure or malfunction, or any and all other commercial damages or losses), even if such Contributor has been advised of the possibility of such damages.\r\n\r\n9. Accepting Warranty or Additional Liability. While redistributing the Work or Derivative Works thereof, You may choose to offer, and charge a fee for, acceptance of support, warranty, indemnity, or other liability obligations and/or rights consistent with this License. However, in accepting such obligations, You may act only on Your own behalf and on Your sole responsibility, not on behalf of any other Contributor, and only if You agree to indemnify, defend, and hold each Contributor harmless for any liability incurred by, or claims asserted against, such Contributor by reason of your accepting any such warranty or additional liability.\r\n\r\nEND OF TERMS AND CONDITIONS\r\n\r\nAPPENDIX: How to apply the Apache License to your work.\r\n\r\nTo apply the Apache License to your work, attach the following boilerplate notice, with the fields enclosed by brackets \"[]\" replaced with your own identifying information. (Don\'t include the brackets!) The text should be enclosed in the appropriate comment syntax for the file format. We also recommend that a file or class name and description of purpose be included on the same \"printed page\" as the copyright notice for easier identification within third-party archives.\r\n\r\nCopyright [yyyy] [name of copyright owner]\r\n\r\nLicensed under the Apache License, Version 2.0 (the \"License\"); you may not use this file except in compliance with the License. You may obtain a copy of the License at\r\n\r\nhttp://www.apache.org/licenses/LICENSE-2.0\r\n\r\nUnless required by applicable law or agreed to in writing, software distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.\r\n\r\n---------------------------------------------\r\n\r\nRANDOM123 LICENSE AGREEMENT\r\n\r\n---------------------------------------------\r\n\r\nCopyright 2010-2011, D. E. Shaw Research. All rights reserved.\r\n\r\nRedistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:\r\n\r\n* Redistributions of source code must retain the above copyright notice, this list of conditions, and the following disclaimer.\r\n\r\n* Redistributions in binary form must reproduce the above copyright notice, this list of conditions, and the following disclaimer in the documentation and/or other materials provided with the distribution.\r\n\r\nNeither the name of D. E. Shaw Research nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.\r\n\r\nTHIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.<span style=\"color: #ffffff;\"><span style=\"color: #000000;\">[/content_band]</span></span>','Legal','','inherit','open','closed','','319-revision-v1','','','2014-03-18 20:02:39','2014-03-18 20:02:39','',319,'http://sandbox.arrayfire.com/319-revision-v1/',0,'revision','',0),(5253,7,'2014-03-18 20:24:14','2014-03-18 20:24:14','[content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n<p style=\"text-align: left;\">[column type=\"two-fifths\" fade=\"true\" fade_animation=\"in-from-left\"][custom_headline type=\"left\" class=\"mtn\" level=\"h3\"]If you want faster code, you\'ve come to the right place.[/custom_headline][gap size=\"12%\"][button  type=\"flat\" shape=\"rounded\" href=\"http://sandbox.arrayfire.com/shop\" size=\"jumbo\" block=\"true\"]Download ArrayFire[/button]</p>\r\n[gap size=\"10%\"]\r\n<p style=\"text-align: left;\">[button  type=\"flat\" block=\"true\" shape=\"rounded\" href=\"http://www.meetme.so/arrayfire\" size=\"jumbo\" ]Schedule a consultation[/button][/column][column fade=\"true\" type=\"three-fifths\" last=\"true\"]</p>\r\n<iframe name=\"wistia_embed\" src=\"//fast.wistia.net/embed/iframe/rj2bar3xxp\" height=\"388\" width=\"640\" allowfullscreen=\"\" frameborder=\"0\" scrolling=\"no\"></iframe>\r\n\r\n[/column][gap size=\"5%\"]\r\n\r\n[/content_band] [content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" bg_color=\"transparent\" ]<span style=\"line-height: 1.5em;\">[column type=\"two-fifths\" last=\"false\" ] [custom_headline type=\"left\" level=\"h3\"]An acceleration library for CUDA and OpenCL[/custom_headline]ArrayFire is a fast, hardware-neutral software library for GPU computing with an easy-to-use API. Its array-based function set makes GPU programming simple. A few lines of code in ArrayFire can replace dozens of lines of raw GPU code, saving you valuable time and lowering development costs.</span>\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/fire/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Learn more...[/button][/column]</span> [column class=\"center-text\" type=\"three-fifths\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Triumvirate_Exported.png\"][/column] <span style=\"line-height: 1.5em;\">[/content_band][content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" ]</span> [column class=\"center-text\" type=\"one-half\" fade=\"true\" fade_animation=\"in-from-left\"]<img class=\"aligncenter size-large wp-image-462\" alt=\"Bat signal\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Bat-signal-1024x639.png\" width=\"1024\" height=\"639\" />[/column][column type=\"one-half\" last=\"true\"][custom_headline type=\"left\" level=\"h3\"]Hire the gang![/custom_headline] Hire us to accelerate your code. Or to train your pros. Or to even write your code!\r\n\r\nWe\'ve already helped thousands of organizations speedup their code. We\'ve accelerated all sorts of algorithms, data sets, and challenging problems in the past and we\'re pretty sure that we can tackle your code, too.\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/consult/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Learn more...[/button][/column][/content_band]</span> <span style=\"line-height: 1.5em;\">[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\" ][column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"  ]The ArrayFire Blog[/custom_headline]</span> <span style=\"line-height: 1.5em;\">Check out our blog for the latest and greatest of GPU and accelerator computing. See how ArrayFire is delivering speedups in real applications.</span>\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/blog-2/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Check it out![/button][/column][column type=\"one-half\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][recent_posts count=\"3\"][/column][/content_band]</span>','Home','','inherit','open','closed','','245-revision-v1','','','2014-03-18 20:24:14','2014-03-18 20:24:14','',245,'http://sandbox.arrayfire.com/245-revision-v1/',0,'revision','',0),(5254,7,'2014-03-18 20:27:24','2014-03-18 20:27:24','[content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n<p style=\"text-align: left;\">[column type=\"two-fifths\" fade=\"true\" fade_animation=\"in-from-left\"][custom_headline type=\"left\" class=\"mtn\" level=\"h3\"]If you want faster code, you\'ve come to the right place.[/custom_headline][gap size=\"12%\"][button  type=\"flat\" shape=\"rounded\" href=\"http://sandbox.arrayfire.com/shop\" size=\"jumbo\" block=\"true\"]Download ArrayFire[/button]</p>\r\n[gap size=\"10%\"]\r\n<p style=\"text-align: left;\">[button  type=\"flat\" block=\"true\" shape=\"rounded\" href=\"http://www.meetme.so/arrayfire\" size=\"jumbo\" ]Schedule a consultation[/button][/column][column fade=\"true\" type=\"three-fifths\" last=\"true\"]</p>\r\n<iframe name=\"wistia_embed\" src=\"//fast.wistia.net/embed/iframe/rj2bar3xxp\" height=\"388\" width=\"640\" allowfullscreen=\"\" frameborder=\"0\" scrolling=\"no\"></iframe>\r\n\r\n[/column][gap size=\"5%\"]\r\n\r\n[/content_band] [content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" bg_color=\"transparent\" ]<span style=\"line-height: 1.5em;\">[column type=\"two-fifths\" last=\"false\" ] [custom_headline type=\"left\" level=\"h3\"]An acceleration library for CUDA and OpenCL[/custom_headline]ArrayFire is a fast, hardware-neutral software library for GPU computing with an easy-to-use API. Its array-based function set makes GPU programming simple. A few lines of code in ArrayFire can replace dozens of lines of raw GPU code, saving you valuable time and lowering development costs.</span>\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/fire/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Learn more...[/button][/column]</span> [column class=\"center-text\" type=\"three-fifths\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Triumvirate_Exported.png\"][/column] <span style=\"line-height: 1.5em;\">[/content_band][content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" ]</span> [column class=\"center-text\" type=\"one-half\" fade=\"true\" fade_animation=\"in-from-left\"]<img class=\"aligncenter size-large wp-image-462\" alt=\"Bat signal\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Bat-signal-1024x639.png\" width=\"1024\" height=\"639\" />[/column][column type=\"one-half\" last=\"true\"][custom_headline type=\"left\" level=\"h3\"]Hire our acceleration gang[/custom_headline] Hire us to accelerate your code. Or to train your pros. Or to even write your code!\r\n\r\nWe\'ve already helped thousands of organizations speedup their code. We\'ve accelerated all sorts of algorithms, data sets, and challenging problems in the past and we\'re pretty sure that we can tackle your code, too.\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/consult/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Learn more...[/button][/column][/content_band]</span> <span style=\"line-height: 1.5em;\">[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\" ][column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"  ]The ArrayFire Blog[/custom_headline]</span> <span style=\"line-height: 1.5em;\">Check out our blog for the latest and greatest of GPU and accelerator computing. See how ArrayFire is delivering speedups in real applications.</span>\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/blog-2/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Check it out![/button][/column][column type=\"one-half\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][recent_posts count=\"3\"][/column][/content_band]</span>','Home','','inherit','open','closed','','245-revision-v1','','','2014-03-18 20:27:24','2014-03-18 20:27:24','',245,'http://sandbox.arrayfire.com/245-revision-v1/',0,'revision','',0),(5255,4,'2014-03-18 20:38:31','2014-03-18 20:38:31','[content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n<p style=\"text-align: left;\">[column type=\"two-fifths\" fade=\"true\" fade_animation=\"in-from-left\"][custom_headline type=\"left\" class=\"mtn\" level=\"h3\"]If you want faster code, you\'ve come to the right place.[/custom_headline][gap size=\"12%\"][button  type=\"flat\" shape=\"rounded\" href=\"http://sandbox.arrayfire.com/shop\" size=\"jumbo\" block=\"true\"]Download ArrayFire[/button]</p>\r\n[gap size=\"10%\"]\r\n<p style=\"text-align: left;\">[button  type=\"flat\" block=\"true\" shape=\"rounded\" href=\"http://www.meetme.so/arrayfire\" size=\"jumbo\" ]Schedule a consultation[/button][/column][column fade=\"true\" type=\"three-fifths\" last=\"true\"]</p>\r\n<iframe name=\"wistia_embed\" src=\"//fast.wistia.net/embed/iframe/rj2bar3xxp\" height=\"388\" width=\"640\" allowfullscreen=\"\" frameborder=\"0\" scrolling=\"no\"></iframe>\r\n\r\n[/column][gap size=\"5%\"]\r\n\r\n[/content_band] [content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" bg_color=\"transparent\" ]<span style=\"line-height: 1.5em;\">[column type=\"two-fifths\" last=\"false\" ] [custom_headline type=\"left\" level=\"h3\"]An acceleration library for CUDA and OpenCL[/custom_headline]ArrayFire is a fast and easy-to-use software library for GPU or accelerator computing. Its array-based function set makes programming with CUDA or OpenCL simple, saving valuable time and lowering development costs.</span>\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/fire/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Learn more...[/button][/column]</span> [column class=\"center-text\" type=\"three-fifths\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Triumvirate_Exported.png\"][/column] <span style=\"line-height: 1.5em;\">[/content_band][content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" ]</span> [column class=\"center-text\" type=\"one-half\" fade=\"true\" fade_animation=\"in-from-left\"]<img class=\"aligncenter size-large wp-image-462\" alt=\"Bat signal\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Bat-signal-1024x639.png\" width=\"1024\" height=\"639\" />[/column][column type=\"one-half\" last=\"true\"][custom_headline type=\"left\" level=\"h3\"]Hire our acceleration gang[/custom_headline] Hire us to accelerate your code. Or to train your pros. Or to even write new code for your organization!\r\n\r\nWe\'ve already helped thousands of organizations speedup their code. We\'ve accelerated all algorithms, data sets, and challenging problems of all types in the past, and we\'re confident that we can accelerate your code too.\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/consult/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Learn more...[/button][/column][/content_band]</span> <span style=\"line-height: 1.5em;\">[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\" ][column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"  ]The ArrayFire Blog[/custom_headline]</span> <span style=\"line-height: 1.5em;\">Check out our blog for the latest and greatest of GPU and accelerator computing. See how ArrayFire is delivering speedups in real applications.</span>\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/blog-2/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Check it out![/button][/column][column type=\"one-half\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][recent_posts count=\"3\"][/column][/content_band]</span>','Home','','inherit','open','closed','','245-autosave-v1','','','2014-03-18 20:38:31','2014-03-18 20:38:31','',245,'http://sandbox.arrayfire.com/245-autosave-v1/',0,'revision','',0),(5258,4,'2014-03-18 20:39:53','2014-03-18 20:39:53','[content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n<p style=\"text-align: left;\">[column type=\"two-fifths\" fade=\"true\" fade_animation=\"in-from-left\"][custom_headline type=\"left\" class=\"mtn\" level=\"h3\"]If you want faster code, you\'ve come to the right place.[/custom_headline][gap size=\"12%\"][button  type=\"flat\" shape=\"rounded\" href=\"http://sandbox.arrayfire.com/shop\" size=\"jumbo\" block=\"true\"]Download ArrayFire[/button]</p>\r\n[gap size=\"10%\"]\r\n<p style=\"text-align: left;\">[button  type=\"flat\" block=\"true\" shape=\"rounded\" href=\"http://www.meetme.so/arrayfire\" size=\"jumbo\" ]Schedule a consultation[/button][/column][column fade=\"true\" type=\"three-fifths\" last=\"true\"]</p>\r\n<iframe name=\"wistia_embed\" src=\"//fast.wistia.net/embed/iframe/rj2bar3xxp\" height=\"388\" width=\"640\" allowfullscreen=\"\" frameborder=\"0\" scrolling=\"no\"></iframe>\r\n\r\n[/column][gap size=\"5%\"]\r\n\r\n[/content_band] [content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" bg_color=\"transparent\" ]<span style=\"line-height: 1.5em;\">[column type=\"two-fifths\" last=\"false\" ] [custom_headline type=\"left\" level=\"h3\"]An acceleration library for CUDA and OpenCL[/custom_headline]ArrayFire is a fast and easy-to-use software library for GPU or accelerator computing. Its array-based function set makes programming with CUDA or OpenCL simple, saving valuable time and lowering development costs.</span>\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/fire/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Learn more...[/button][/column]</span> [column class=\"center-text\" type=\"three-fifths\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Triumvirate_Exported.png\"][/column] <span style=\"line-height: 1.5em;\">[/content_band][content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" ]</span> [column class=\"center-text\" type=\"one-half\" fade=\"true\" fade_animation=\"in-from-left\"]<img class=\"aligncenter size-large wp-image-462\" alt=\"Bat signal\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Bat-signal-1024x639.png\" width=\"1024\" height=\"639\" />[/column][column type=\"one-half\" last=\"true\"][custom_headline type=\"left\" level=\"h3\"]Hire our acceleration gang[/custom_headline] Hire us to accelerate your code. Or to train your pros. Or even to write new code for your organization!\r\n\r\nWe\'ve already helped thousands of organizations speedup their code. We\'ve accelerated all algorithms, data sets, and challenging problems of all types in the past, and we\'re confident that we can accelerate your code too.\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/consult/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Learn more...[/button][/column][/content_band]</span> <span style=\"line-height: 1.5em;\">[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\" ][column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"  ]The ArrayFire Blog[/custom_headline]</span> <span style=\"line-height: 1.5em;\">Check out our blog for the latest updates in GPU and accelerator computing. See how ArrayFire is delivering speedups in real applications.</span>\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/blog-2/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Check it out![/button][/column][column type=\"one-half\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][recent_posts count=\"3\"][/column][/content_band]</span>','Home','','inherit','open','closed','','245-revision-v1','','','2014-03-18 20:39:53','2014-03-18 20:39:53','',245,'http://sandbox.arrayfire.com/245-revision-v1/',0,'revision','',0),(5270,1,'2014-03-19 21:13:59','2014-03-19 21:13:59','[theme-my-login]','Log In','','inherit','open','closed','','5235-revision-v1','','','2014-03-19 21:13:59','2014-03-19 21:13:59','',5235,'http://sandbox.arrayfire.com/5235-revision-v1/',0,'revision','',0),(5272,1,'2014-03-19 21:15:21','2014-03-19 21:15:21','[theme-my-login]','Register','','inherit','open','closed','','5237-revision-v1','','','2014-03-19 21:15:21','2014-03-19 21:15:21','',5237,'http://sandbox.arrayfire.com/5237-revision-v1/',0,'revision','',0),(5273,1,'2014-03-19 21:17:14','2014-03-19 21:17:14','[theme-my-login]','Lost Password','','inherit','open','closed','','5238-revision-v1','','','2014-03-19 21:17:14','2014-03-19 21:17:14','',5238,'http://sandbox.arrayfire.com/5238-revision-v1/',0,'revision','',0),(5274,1,'2014-03-19 21:19:51','2014-03-19 21:19:51',' ','','','publish','open','closed','','5274','','','2014-03-19 21:19:51','2014-03-19 21:19:51','',0,'http://sandbox.arrayfire.com/?p=5274',9,'nav_menu_item','',0),(5276,7,'2014-03-19 21:30:04','2014-03-19 21:30:04','[content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n<p style=\"text-align: left;\">[column type=\"two-fifths\" fade=\"true\" fade_animation=\"in-from-left\"][custom_headline type=\"left\" class=\"mtn\" level=\"h3\"]If you want faster code, you\'ve come to the right place.[/custom_headline][gap size=\"12%\"][button  type=\"flat\" shape=\"rounded\" href=\"http://www.accelereyes.com/arrayfire/c/installation.htm\" size=\"jumbo\" block=\"true\"]Download ArrayFire[/button]</p>\r\n[gap size=\"10%\"]\r\n<p style=\"text-align: left;\">[button  type=\"flat\" block=\"true\" shape=\"rounded\" href=\"http://www.meetme.so/arrayfire\" size=\"jumbo\" ]Schedule a consultation[/button][/column][column fade=\"true\" type=\"three-fifths\" last=\"true\"]</p>\r\n<iframe name=\"wistia_embed\" src=\"//fast.wistia.net/embed/iframe/rj2bar3xxp\" height=\"388\" width=\"640\" allowfullscreen=\"\" frameborder=\"0\" scrolling=\"no\"></iframe>\r\n\r\n[/column][gap size=\"5%\"]\r\n\r\n[/content_band] [content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" bg_color=\"transparent\" ]<span style=\"line-height: 1.5em;\">[column type=\"two-fifths\" last=\"false\" ] [custom_headline type=\"left\" level=\"h3\"]An acceleration library for CUDA and OpenCL[/custom_headline]ArrayFire is a fast and easy-to-use software library for GPU or accelerator computing. Its array-based function set makes programming with CUDA or OpenCL simple, saving valuable time and lowering development costs.</span>\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/fire/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Learn more...[/button][/column]</span> [column class=\"center-text\" type=\"three-fifths\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Triumvirate_Exported.png\"][/column] <span style=\"line-height: 1.5em;\">[/content_band][content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" ]</span> [column class=\"center-text\" type=\"one-half\" fade=\"true\" fade_animation=\"in-from-left\"]<img class=\"aligncenter size-large wp-image-462\" alt=\"Bat signal\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Bat-signal-1024x639.png\" width=\"1024\" height=\"639\" />[/column][column type=\"one-half\" last=\"true\"][custom_headline type=\"left\" level=\"h3\"]Hire our acceleration gang[/custom_headline] Hire us to accelerate your code. Or to train your pros. Or even to write new code for your organization!\r\n\r\nWe\'ve already helped thousands of organizations speedup their code. We\'ve accelerated all algorithms, data sets, and challenging problems of all types in the past, and we\'re confident that we can accelerate your code too.\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/consult/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Learn more...[/button][/column][/content_band]</span> <span style=\"line-height: 1.5em;\">[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\" ][column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"  ]The ArrayFire Blog[/custom_headline]</span> <span style=\"line-height: 1.5em;\">Check out our blog for the latest updates in GPU and accelerator computing. See how ArrayFire is delivering speedups in real applications.</span>\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/blog-2/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Check it out![/button][/column][column type=\"one-half\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][recent_posts count=\"3\"][/column][/content_band]</span>','Home','','inherit','open','closed','','245-revision-v1','','','2014-03-19 21:30:04','2014-03-19 21:30:04','',245,'http://sandbox.arrayfire.com/245-revision-v1/',0,'revision','',0),(5277,7,'2014-03-19 21:30:25','2014-03-19 21:30:25','[content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n<p style=\"text-align: left;\">[column type=\"two-fifths\" fade=\"true\" fade_animation=\"in-from-left\"][custom_headline type=\"left\" class=\"mtn\" level=\"h3\"]If you want faster code, you\'ve come to the right place.[/custom_headline][gap size=\"12%\"][button  type=\"flat\" shape=\"rounded\" href=\"http://www.accelereyes.com/arrayfire/c/installation.htm\" size=\"jumbo\" block=\"true\"]Download ArrayFire[/button]</p>\r\n[gap size=\"10%\"]\r\n<p style=\"text-align: left;\">[button  type=\"flat\" block=\"true\" shape=\"rounded\" href=\"http://www.meetme.so/arrayfire\" size=\"jumbo\" ]Schedule a consultation[/button][/column][column fade=\"true\" type=\"three-fifths\" last=\"true\"]</p>\r\n<iframe name=\"wistia_embed\" src=\"//fast.wistia.net/embed/iframe/rj2bar3xxp\" height=\"388\" width=\"640\" allowfullscreen=\"\" frameborder=\"0\" scrolling=\"no\"></iframe>\r\n\r\n[/column][gap size=\"5%\"]\r\n\r\n[/content_band] [content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" bg_color=\"transparent\" ]<span style=\"line-height: 1.5em;\">[column type=\"two-fifths\" last=\"false\" ] [custom_headline type=\"left\" level=\"h3\"]An acceleration library for CUDA and OpenCL[/custom_headline]ArrayFire is a fast and easy-to-use software library for GPU or accelerator computing. Its array-based function set makes programming with CUDA or OpenCL simple, saving valuable time and lowering development costs.</span>\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/fire/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Learn more...[/button][/column]</span> [column class=\"center-text\" type=\"three-fifths\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Triumvirate_Exported.png\"][/column] <span style=\"line-height: 1.5em;\">[/content_band][content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" ]</span> [column class=\"center-text\" type=\"one-half\" fade=\"true\" fade_animation=\"in-from-left\"]<img class=\"aligncenter size-large wp-image-462\" alt=\"Bat signal\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Bat-signal-1024x639.png\" width=\"1024\" height=\"639\" />[/column][column type=\"one-half\" last=\"true\"][custom_headline type=\"left\" level=\"h3\"]Hire our acceleration gang[/custom_headline] Hire us to accelerate your code. Or to train your pros. Or even to write new code for your organization!\r\n\r\nWe\'ve already helped thousands of organizations speedup their code. We\'ve accelerated all algorithms, data sets, and challenging problems of all types in the past, and we\'re confident that we can accelerate your code too.\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/consult/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Learn more...[/button][/column][/content_band]</span> <span style=\"line-height: 1.5em;\">[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\" ][column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"  ]The ArrayFire Blog[/custom_headline]</span> <span style=\"line-height: 1.5em;\">Check out our blog for the latest updates in GPU and accelerator computing. See how ArrayFire is delivering speedups in real applications.</span>\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/blog/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Check it out![/button][/column][column type=\"one-half\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][recent_posts count=\"3\"][/column][/content_band]</span>','Home','','inherit','open','closed','','245-revision-v1','','','2014-03-19 21:30:25','2014-03-19 21:30:25','',245,'http://sandbox.arrayfire.com/245-revision-v1/',0,'revision','',0),(5278,7,'2014-03-19 21:40:11','2014-03-19 21:40:11','[woocommerce_my_account]','My Account','','inherit','open','closed','','7-revision-v1','','','2014-03-19 21:40:11','2014-03-19 21:40:11','',7,'http://sandbox.arrayfire.com/7-revision-v1/',0,'revision','',0),(5280,7,'2014-03-19 21:42:20','2014-03-19 21:42:20','[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\" ][woocommerce_my_account][/content_band]','My Account','','inherit','open','closed','','7-revision-v1','','','2014-03-19 21:42:20','2014-03-19 21:42:20','',7,'http://sandbox.arrayfire.com/7-revision-v1/',0,'revision','',0),(5281,7,'2014-03-19 21:44:38','2014-03-19 21:44:38','[woocommerce_my_account]','My Account','','inherit','open','closed','','7-revision-v1','','','2014-03-19 21:44:38','2014-03-19 21:44:38','',7,'http://sandbox.arrayfire.com/7-revision-v1/',0,'revision','',0),(5283,7,'2014-03-19 21:48:03','2014-03-19 21:48:03','[woocommerce_checkout]','Checkout','','inherit','open','closed','','6-revision-v1','','','2014-03-19 21:48:03','2014-03-19 21:48:03','',6,'http://sandbox.arrayfire.com/6-revision-v1/',0,'revision','',0),(5286,7,'2014-03-19 21:54:09','2014-03-19 21:54:09','[content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" ][gap size=\"6%\"]\r\n<p style=\"text-align: left;\">[column type=\"two-fifths\" fade=\"true\" fade_animation=\"in-from-left\"][custom_headline type=\"left\" class=\"mtn\" level=\"h3\"]If you want faster code, you\'ve come to the right place.[/custom_headline][gap size=\"12%\"][button  type=\"flat\" shape=\"rounded\" href=\"http://www.accelereyes.com/arrayfire/c/installation.htm\" size=\"jumbo\" block=\"true\"]Download ArrayFire[/button]</p>\r\n[gap size=\"10%\"]\r\n<p style=\"text-align: left;\">[button  type=\"flat\" block=\"true\" shape=\"rounded\" href=\"http://www.meetme.so/arrayfire\" size=\"jumbo\" ]Schedule a consultation[/button][/column][column fade=\"true\" type=\"three-fifths\" last=\"true\"]</p>\r\n<iframe name=\"wistia_embed\" src=\"//fast.wistia.net/embed/iframe/rj2bar3xxp\" height=\"388\" width=\"640\" allowfullscreen=\"\" frameborder=\"0\" scrolling=\"no\"></iframe>\r\n\r\n[/column][gap size=\"5%\"]\r\n\r\n[/content_band] [content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" bg_color=\"transparent\" ]<span style=\"line-height: 1.5em;\">[column type=\"two-fifths\" last=\"false\" ] [custom_headline type=\"left\" level=\"h3\"]An acceleration library for CUDA and OpenCL[/custom_headline]ArrayFire is a fast and easy-to-use software library for GPU or accelerator computing. Its array-based function set makes programming with CUDA or OpenCL simple, saving valuable time and lowering development costs.</span>\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/fire/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Learn more...[/button][/column]</span> [column class=\"center-text\" type=\"three-fifths\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Triumvirate_Exported.png\"][/column] <span style=\"line-height: 1.5em;\">[/content_band][content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" ]</span> [column class=\"center-text\" type=\"one-half\" fade=\"true\" fade_animation=\"in-from-left\"]<img class=\"aligncenter size-large wp-image-462\" alt=\"Bat signal\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Bat-signal-1024x639.png\" width=\"1024\" height=\"639\" />[/column][column type=\"one-half\" last=\"true\"][custom_headline type=\"left\" level=\"h3\"]Hire our acceleration gang[/custom_headline] Hire us to accelerate your code. Or to train your pros. Or even to write new code for your organization!\r\n\r\nWe\'ve already helped thousands of organizations speedup their code. We\'ve accelerated all algorithms, data sets, and challenging problems of all types in the past, and we\'re confident that we can accelerate your code too.\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/consult/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Learn more...[/button][/column][/content_band]</span> <span style=\"line-height: 1.5em;\">[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\" ][column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"  ]The ArrayFire Blog[/custom_headline]</span> <span style=\"line-height: 1.5em;\">Check out our blog for the latest updates in GPU and accelerator computing. See how ArrayFire is delivering speedups in real applications.</span>\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/blog/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Check it out![/button][/column][column type=\"one-half\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][recent_posts count=\"3\"][/column][/content_band]</span>','Home','','inherit','open','closed','','245-revision-v1','','','2014-03-19 21:54:09','2014-03-19 21:54:09','',245,'http://sandbox.arrayfire.com/245-revision-v1/',0,'revision','',0),(5287,7,'2014-03-20 19:21:08','2014-03-20 19:21:08','[theme-my-login]','Log Out','','inherit','open','closed','','5236-revision-v1','','','2014-03-20 19:21:08','2014-03-20 19:21:08','',5236,'http://sandbox.arrayfire.com/5236-revision-v1/',0,'revision','',0),(5289,7,'2014-03-20 19:23:59','2014-03-20 19:23:59','','Logout','','inherit','open','closed','','12-revision-v1','','','2014-03-20 19:23:59','2014-03-20 19:23:59','',12,'http://sandbox.arrayfire.com/12-revision-v1/',0,'revision','',0),(5290,7,'2014-03-20 19:24:20','2014-03-20 19:24:20','[theme-my-login]','Reset Password','','inherit','open','closed','','5239-revision-v1','','','2014-03-20 19:24:20','2014-03-20 19:24:20','',5239,'http://sandbox.arrayfire.com/5239-revision-v1/',0,'revision','',0),(5293,1,'2014-03-21 07:51:24','2014-03-21 07:51:24',' ','','','publish','open','closed','','5293','','','2014-03-21 07:51:24','2014-03-21 07:51:24','',0,'http://sandbox.arrayfire.com/?p=5293',9,'nav_menu_item','',0),(5294,7,'2014-03-21 14:16:33','2014-03-21 14:16:33','[content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" ][gap size=\"6%\"]\r\n<p style=\"text-align: left;\">[column type=\"two-fifths\" fade=\"true\" fade_animation=\"in-from-left\"][custom_headline type=\"left\" class=\"mtn\" level=\"h3\"]If you want faster code, you\'ve come to the right place.[/custom_headline][gap size=\"12%\"][button  type=\"flat\" shape=\"rounded\" href=\"http://www.accelereyes.com/arrayfire/c/installation.htm\" size=\"jumbo\" block=\"true\"]Download ArrayFire[/button]</p>\r\n[gap size=\"10%\"]\r\n<p style=\"text-align: left;\">[button  type=\"flat\" block=\"true\" shape=\"rounded\" href=\"http://www.meetme.so/arrayfire\" size=\"jumbo\" ]Schedule a consultation[/button][/column][column fade=\"true\" type=\"three-fifths\" last=\"true\"]</p>\r\n<iframe name=\"wistia_embed\" src=\"//fast.wistia.net/embed/iframe/rj2bar3xxp\" height=\"388\" width=\"640\" allowfullscreen=\"\" frameborder=\"0\" scrolling=\"no\"></iframe>\r\n\r\n[/column][gap size=\"5%\"]\r\n\r\n[/content_band] [content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" bg_color=\"transparent\" ]<span style=\"line-height: 1.5em;\">[column type=\"two-fifths\" last=\"false\" ] [custom_headline type=\"left\" level=\"h3\"]An acceleration library for CUDA and OpenCL[/custom_headline]ArrayFire is a fast and easy-to-use software library for GPU or accelerator computing. Its array-based function set makes programming with CUDA or OpenCL simple, saving valuable time and lowering development costs.</span>\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/arrayfire/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Learn more...[/button][/column]</span> [column class=\"center-text\" type=\"three-fifths\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Triumvirate_Exported.png\"][/column] <span style=\"line-height: 1.5em;\">[/content_band][content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\" ]</span> [column class=\"center-text\" type=\"one-half\" fade=\"true\" fade_animation=\"in-from-left\"]<img class=\"aligncenter size-large wp-image-462\" alt=\"Bat signal\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Bat-signal-1024x639.png\" width=\"1024\" height=\"639\" />[/column][column type=\"one-half\" last=\"true\"][custom_headline type=\"left\" level=\"h3\"]Hire our acceleration gang[/custom_headline] Hire us to accelerate your code. Or to train your pros. Or even to write new code for your organization!\r\n\r\nWe\'ve already helped thousands of organizations speedup their code. We\'ve accelerated all algorithms, data sets, and challenging problems of all types in the past, and we\'re confident that we can accelerate your code too.\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/consult/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Learn more...[/button][/column][/content_band]</span> <span style=\"line-height: 1.5em;\">[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\" ][column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"  ]The ArrayFire Blog[/custom_headline]</span> <span style=\"line-height: 1.5em;\">Check out our blog for the latest updates in GPU and accelerator computing. See how ArrayFire is delivering speedups in real applications.</span>\r\n\r\n<span style=\"line-height: 1.5em;\">[button href=\"http://sandbox.arrayfire.com/blog/\" title=\"Learn more\" target=\"blank\" shape=\"rounded\" size=\"large\" ]Check it out![/button][/column][column type=\"one-half\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][recent_posts count=\"3\"][/column][/content_band]</span>','Home','','inherit','open','closed','','245-revision-v1','','','2014-03-21 14:16:33','2014-03-21 14:16:33','',245,'http://sandbox.arrayfire.com/245-revision-v1/',0,'revision','',0),(5298,1,'2014-03-21 17:04:34','2014-03-21 17:04:34',' ','','','publish','open','closed','','5298','','','2014-03-21 17:04:34','2014-03-21 17:04:34','',0,'http://sandbox.arrayfire.com/?p=5298',9,'nav_menu_item','',0),(5300,1,'2014-03-21 19:30:47','2014-03-21 19:30:47',' ','','','publish','open','closed','','5300','','','2014-03-21 19:30:47','2014-03-21 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20:52:10','','Calendar_Exported','','inherit','open','closed','','calendar_exported','','','2014-03-21 20:52:10','2014-03-21 20:52:10','',0,'http://sandbox.arrayfire.com/wp-content/uploads/2014/02/Calendar_Exported.png',0,'attachment','image/png',0),(5306,7,'2014-03-21 20:52:33','2014-03-21 20:52:33','','Professor AF_Exported','','inherit','open','closed','','professor-af_exported','','','2014-03-21 20:52:33','2014-03-21 20:52:33','',0,'http://sandbox.arrayfire.com/wp-content/uploads/2014/02/Professor-AF_Exported.png',0,'attachment','image/png',0),(5310,1,'2014-03-23 12:17:17','2014-03-23 12:17:17',' ','','','publish','open','closed','','5310','','','2014-04-07 15:28:05','2014-04-07 15:28:05','',0,'http://sandbox.arrayfire.com/?p=5310',10,'nav_menu_item','',0),(5312,7,'2014-03-25 01:11:28','2014-03-25 01:11:28','[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n\r\n[column type=\"one-third\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"one-third\"]\r\n<p style=\"text-align: center;\"><img class=\"aligncenter  wp-image-259\" alt=\"arrayfire_logo_symbol\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/arrayfire_logo_symbol-300x300.png\" width=\"210\" height=\"210\" />[custom_headline type=\"center\" level=\"h3\" class=\"mtn\"]Looking for AccelerEyes?[/custom_headline]</p>\r\n<p style=\"text-align: center;\"><strong>AccelerEyes</strong> is now <strong>ArrayFire</strong>.</p>\r\n<p style=\"text-align: center;\">Don\'t worry, we\'ve still got the same awesome team with the same awesome stuff.\r\nJust better looking.</p>\r\n[button href=\"http://www.arrayfire.com\" title=\"To the Main Site\" shape=\"rounded\" size=\"large\" block=\"true\"]Continue to ArrayFire.com[/button][/column][column type=\"one-third\" last=\"true\"]<span style=\"color: #ffffff;\">.</span>[/column]\r\n\r\n[/content_band]\r\n\r\n&nbsp;\r\n\r\n&nbsp;','Splash page','','publish','open','closed','','welcome','','','2014-03-25 01:14:17','2014-03-25 01:14:17','',0,'http://sandbox.arrayfire.com/?page_id=5312',0,'page','',0),(5313,7,'2014-03-25 00:42:16','2014-03-25 00:42:16','Plus ça change, plus c\'est la même chose.\r\n\r\nAccelerEyes is now ArrayFire.\r\n\r\nDon\'t worry, we\'ve got the same awesome team with the same awesome stuff—only cooler.\r\n\r\n[button href=\"http://www.arrayfire.com\" title=\"To the Main Site\" shape=\"rounded\" size=\"jumbo\" block=\"true\"]Welcome to ArrayFire[/button]\r\n\r\n&nbsp;\r\n\r\n&nbsp;','Splash page','','inherit','open','closed','','5312-revision-v1','','','2014-03-25 00:42:16','2014-03-25 00:42:16','',5312,'http://sandbox.arrayfire.com/5312-revision-v1/',0,'revision','',0),(5314,7,'2014-03-25 00:45:09','2014-03-25 00:45:09','[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n\r\n[column type=\"one-third\"][/column][column type=\"one-third\"]Plus ça change, plus c\'est la même chose.\r\n\r\nAccelerEyes is now ArrayFire.\r\n\r\nDon\'t worry, we\'ve got the same awesome team with the same awesome stuff—only cooler.\r\n\r\n[button href=\"http://www.arrayfire.com\" title=\"To the Main Site\" shape=\"rounded\" size=\"jumbo\" block=\"true\"]Continue to ArrayFire.com[/button][/column][column type=\"one-third\" last=\"true\"][/column]\r\n\r\n[/content_band]\r\n\r\n&nbsp;\r\n\r\n&nbsp;','Splash page','','inherit','open','closed','','5312-revision-v1','','','2014-03-25 00:45:09','2014-03-25 00:45:09','',5312,'http://sandbox.arrayfire.com/5312-revision-v1/',0,'revision','',0),(5315,7,'2014-03-25 00:45:40','2014-03-25 00:45:40','[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n\r\n[column type=\"one-third\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"one-third\"]Plus ça change, plus c\'est la même chose.\r\n\r\nAccelerEyes is now ArrayFire.\r\n\r\nDon\'t worry, we\'ve got the same awesome team with the same awesome stuff—only cooler.\r\n\r\n[button href=\"http://www.arrayfire.com\" title=\"To the Main Site\" shape=\"rounded\" size=\"jumbo\" block=\"true\"]Continue to ArrayFire.com[/button][/column][column type=\"one-third\" last=\"true\"]<span style=\"color: #ffffff;\">.</span>[/column]\r\n\r\n[/content_band]\r\n\r\n&nbsp;\r\n\r\n&nbsp;','Splash page','','inherit','open','closed','','5312-revision-v1','','','2014-03-25 00:45:40','2014-03-25 00:45:40','',5312,'http://sandbox.arrayfire.com/5312-revision-v1/',0,'revision','',0),(5316,7,'2014-03-25 00:47:24','2014-03-25 00:47:24','[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n\r\n[column type=\"one-third\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"one-third\"]Plus ça change, plus c\'est la même chose.\r\n\r\nAccelerEyes is now ArrayFire.\r\n\r\nDon\'t worry, we\'ve still got the same awesome team with the same awesome stuff—just better looking now.\r\n\r\n[button href=\"http://www.arrayfire.com\" title=\"To the Main Site\" shape=\"rounded\" size=\"jumbo\" block=\"true\"]Continue to ArrayFire.com[/button][/column][column type=\"one-third\" last=\"true\"]<span style=\"color: #ffffff;\">.</span>[/column]\r\n\r\n[/content_band]\r\n\r\n&nbsp;\r\n\r\n&nbsp;','Splash page','','inherit','open','closed','','5312-revision-v1','','','2014-03-25 00:47:24','2014-03-25 00:47:24','',5312,'http://sandbox.arrayfire.com/5312-revision-v1/',0,'revision','',0),(5317,7,'2014-03-25 00:48:10','2014-03-25 00:48:10','[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n\r\n[column type=\"one-third\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"one-third\"]\r\n\r\n<a href=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/arrayfire_logo_symbol.png\"><img class=\"aligncenter size-medium wp-image-259\" alt=\"arrayfire_logo_symbol\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/arrayfire_logo_symbol-300x300.png\" width=\"300\" height=\"300\" /></a>Plus ça change, plus c\'est la même chose.\r\n\r\nAccelerEyes is now ArrayFire.\r\n\r\nDon\'t worry, we\'ve still got the same awesome team with the same awesome stuff—just better looking now.\r\n\r\n[button href=\"http://www.arrayfire.com\" title=\"To the Main Site\" shape=\"rounded\" size=\"jumbo\" block=\"true\"]Continue to ArrayFire.com[/button][/column][column type=\"one-third\" last=\"true\"]<span style=\"color: #ffffff;\">.</span>[/column]\r\n\r\n[/content_band]\r\n\r\n&nbsp;\r\n\r\n&nbsp;','Splash page','','inherit','open','closed','','5312-revision-v1','','','2014-03-25 00:48:10','2014-03-25 00:48:10','',5312,'http://sandbox.arrayfire.com/5312-revision-v1/',0,'revision','',0),(5318,7,'2014-03-25 00:48:58','2014-03-25 00:48:58','[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n\r\n[column type=\"one-third\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"one-third\"]\r\n\r\n<img class=\"aligncenter size-medium wp-image-259\" alt=\"arrayfire_logo_symbol\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/arrayfire_logo_symbol-300x300.png\" width=\"300\" height=\"300\" />Plus ça change, plus c\'est la même chose.\r\n\r\nAccelerEyes is now ArrayFire.\r\n\r\nDon\'t worry, we\'ve still got the same awesome team with the same awesome stuff—just better looking now.\r\n\r\n[button href=\"http://www.arrayfire.com\" title=\"To the Main Site\" shape=\"rounded\" size=\"jumbo\" block=\"true\"]Continue to ArrayFire.com[/button][/column][column type=\"one-third\" last=\"true\"]<span style=\"color: #ffffff;\">.</span>[/column]\r\n\r\n[/content_band]\r\n\r\n&nbsp;\r\n\r\n&nbsp;','Splash page','','inherit','open','closed','','5312-revision-v1','','','2014-03-25 00:48:58','2014-03-25 00:48:58','',5312,'http://sandbox.arrayfire.com/5312-revision-v1/',0,'revision','',0),(5319,7,'2014-03-25 00:49:52','2014-03-25 00:49:52','[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n\r\n[column type=\"one-third\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"one-third\"]\r\n<p style=\"text-align: center;\"><img class=\"aligncenter size-medium wp-image-259\" alt=\"arrayfire_logo_symbol\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/arrayfire_logo_symbol-300x300.png\" width=\"300\" height=\"300\" />Plus ça change, plus c\'est la même chose.</p>\r\n<p style=\"text-align: center;\">AccelerEyes is now ArrayFire.</p>\r\n<p style=\"text-align: center;\">Don\'t worry, we\'ve still got the same awesome team with the same awesome stuff—just better looking now.</p>\r\n[button href=\"http://www.arrayfire.com\" title=\"To the Main Site\" shape=\"rounded\" size=\"jumbo\" block=\"true\"]Continue to ArrayFire.com[/button][/column][column type=\"one-third\" last=\"true\"]<span style=\"color: #ffffff;\">.</span>[/column]\r\n\r\n[/content_band]\r\n\r\n&nbsp;\r\n\r\n&nbsp;','Splash page','','inherit','open','closed','','5312-revision-v1','','','2014-03-25 00:49:52','2014-03-25 00:49:52','',5312,'http://sandbox.arrayfire.com/5312-revision-v1/',0,'revision','',0),(5320,7,'2014-03-25 00:50:55','2014-03-25 00:50:55','[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n\r\n[column type=\"one-fifth\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"three-fifths\"]\r\n<p style=\"text-align: center;\"><img class=\"aligncenter size-medium wp-image-259\" alt=\"arrayfire_logo_symbol\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/arrayfire_logo_symbol-300x300.png\" width=\"300\" height=\"300\" />Plus ça change, plus c\'est la même chose.</p>\r\n<p style=\"text-align: center;\">AccelerEyes is now ArrayFire.</p>\r\n<p style=\"text-align: center;\">Don\'t worry, we\'ve still got the same awesome team with the same awesome stuff—just better looking now.</p>\r\n[button href=\"http://www.arrayfire.com\" title=\"To the Main Site\" shape=\"rounded\" size=\"jumbo\" block=\"true\"]Continue to ArrayFire.com[/button][/column][column type=\"one-fifth\" last=\"true\"]<span style=\"color: #ffffff;\">.</span>[/column]\r\n\r\n[/content_band]\r\n\r\n&nbsp;\r\n\r\n&nbsp;','Splash page','','inherit','open','closed','','5312-revision-v1','','','2014-03-25 00:50:55','2014-03-25 00:50:55','',5312,'http://sandbox.arrayfire.com/5312-revision-v1/',0,'revision','',0),(5321,7,'2014-03-25 00:51:44','2014-03-25 00:51:44','[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n\r\n[column type=\"one-fifth\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"three-fifths\"]\r\n<p style=\"text-align: center;\"><img class=\"aligncenter  wp-image-259\" alt=\"arrayfire_logo_symbol\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/arrayfire_logo_symbol-300x300.png\" width=\"210\" height=\"210\" />Plus ça change, plus c\'est la même chose.</p>\r\n<p style=\"text-align: center;\">AccelerEyes is now ArrayFire.</p>\r\n<p style=\"text-align: center;\">Don\'t worry, we\'ve still got the same awesome team with the same awesome stuff—just better looking now.</p>\r\n[button href=\"http://www.arrayfire.com\" title=\"To the Main Site\" shape=\"rounded\" size=\"jumbo\" block=\"true\"]Continue to ArrayFire.com[/button][/column][column type=\"one-fifth\" last=\"true\"]<span style=\"color: #ffffff;\">.</span>[/column]\r\n\r\n[/content_band]\r\n\r\n&nbsp;\r\n\r\n&nbsp;','Splash page','','inherit','open','closed','','5312-revision-v1','','','2014-03-25 00:51:44','2014-03-25 00:51:44','',5312,'http://sandbox.arrayfire.com/5312-revision-v1/',0,'revision','',0),(5322,7,'2014-03-25 00:52:19','2014-03-25 00:52:19','[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n\r\n[column type=\"one-third\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"one-third\"]\r\n<p style=\"text-align: center;\"><img class=\"aligncenter  wp-image-259\" alt=\"arrayfire_logo_symbol\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/arrayfire_logo_symbol-300x300.png\" width=\"210\" height=\"210\" />Plus ça change, plus c\'est la même chose.</p>\r\n<p style=\"text-align: center;\">AccelerEyes is now ArrayFire.</p>\r\n<p style=\"text-align: center;\">Don\'t worry, we\'ve still got the same awesome team with the same awesome stuff—just better looking now.</p>\r\n[button href=\"http://www.arrayfire.com\" title=\"To the Main Site\" shape=\"rounded\" size=\"jumbo\" block=\"true\"]Continue to ArrayFire.com[/button][/column][column type=\"one-third\" last=\"true\"]<span style=\"color: #ffffff;\">.</span>[/column]\r\n\r\n[/content_band]\r\n\r\n&nbsp;\r\n\r\n&nbsp;','Splash page','','inherit','open','closed','','5312-revision-v1','','','2014-03-25 00:52:19','2014-03-25 00:52:19','',5312,'http://sandbox.arrayfire.com/5312-revision-v1/',0,'revision','',0),(5323,7,'2014-03-25 00:52:41','2014-03-25 00:52:41','[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n\r\n[column type=\"one-third\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"one-third\"]\r\n<p style=\"text-align: center;\"><img class=\"aligncenter  wp-image-259\" alt=\"arrayfire_logo_symbol\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/arrayfire_logo_symbol-300x300.png\" width=\"210\" height=\"210\" />Plus ça change, plus c\'est la même chose.</p>\r\n<p style=\"text-align: center;\">AccelerEyes is now ArrayFire.</p>\r\n<p style=\"text-align: center;\">Don\'t worry, we\'ve still got the same awesome team with the same awesome stuff—just better looking now.</p>\r\n[button href=\"http://www.arrayfire.com\" title=\"To the Main Site\" shape=\"rounded\" size=\"large\" block=\"true\"]Continue to ArrayFire.com[/button][/column][column type=\"one-third\" last=\"true\"]<span style=\"color: #ffffff;\">.</span>[/column]\r\n\r\n[/content_band]\r\n\r\n&nbsp;\r\n\r\n&nbsp;','Splash page','','inherit','open','closed','','5312-revision-v1','','','2014-03-25 00:52:41','2014-03-25 00:52:41','',5312,'http://sandbox.arrayfire.com/5312-revision-v1/',0,'revision','',0),(5324,7,'2014-03-25 00:53:06','2014-03-25 00:53:06','[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n\r\n[column type=\"one-third\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"one-third\"]\r\n<p style=\"text-align: center;\"><img class=\"aligncenter  wp-image-259\" alt=\"arrayfire_logo_symbol\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/arrayfire_logo_symbol-300x300.png\" width=\"210\" height=\"210\" />Plus ça change, plus c\'est la même chose.</p>\r\n<p style=\"text-align: center;\"><strong>AccelerEyes</strong> is now <strong>ArrayFire</strong>.</p>\r\n<p style=\"text-align: center;\">Don\'t worry, we\'ve still got the same awesome team with the same awesome stuff—just better looking now.</p>\r\n[button href=\"http://www.arrayfire.com\" title=\"To the Main Site\" shape=\"rounded\" size=\"large\" block=\"true\"]Continue to ArrayFire.com[/button][/column][column type=\"one-third\" last=\"true\"]<span style=\"color: #ffffff;\">.</span>[/column]\r\n\r\n[/content_band]\r\n\r\n&nbsp;\r\n\r\n&nbsp;','Splash page','','inherit','open','closed','','5312-revision-v1','','','2014-03-25 00:53:06','2014-03-25 00:53:06','',5312,'http://sandbox.arrayfire.com/5312-revision-v1/',0,'revision','',0),(5325,7,'2014-03-25 00:53:35','2014-03-25 00:53:35','[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n\r\n[column type=\"one-third\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"one-third\"]\r\n<p style=\"text-align: center;\"><img class=\"aligncenter  wp-image-259\" alt=\"arrayfire_logo_symbol\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/arrayfire_logo_symbol-300x300.png\" width=\"210\" height=\"210\" />Plus ça change, plus c\'est la même chose.</p>\r\n<p style=\"text-align: center;\"><strong>AccelerEyes</strong> is now <strong>ArrayFire</strong>.</p>\r\n<p style=\"text-align: center;\">Don\'t worry, we\'ve still got the same awesome team with the same awesome stuff.\r\nJust better looking now.</p>\r\n[button href=\"http://www.arrayfire.com\" title=\"To the Main Site\" shape=\"rounded\" size=\"large\" block=\"true\"]Continue to ArrayFire.com[/button][/column][column type=\"one-third\" last=\"true\"]<span style=\"color: #ffffff;\">.</span>[/column]\r\n\r\n[/content_band]\r\n\r\n&nbsp;\r\n\r\n&nbsp;','Splash page','','inherit','open','closed','','5312-revision-v1','','','2014-03-25 00:53:35','2014-03-25 00:53:35','',5312,'http://sandbox.arrayfire.com/5312-revision-v1/',0,'revision','',0),(5326,7,'2014-03-25 00:53:49','2014-03-25 00:53:49','[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n\r\n[column type=\"one-third\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"one-third\"]\r\n<p style=\"text-align: center;\"><img class=\"aligncenter  wp-image-259\" alt=\"arrayfire_logo_symbol\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/arrayfire_logo_symbol-300x300.png\" width=\"210\" height=\"210\" />Plus ça change, plus c\'est la même chose.</p>\r\n<p style=\"text-align: center;\"><strong>AccelerEyes</strong> is now <strong>ArrayFire</strong>.</p>\r\n<p style=\"text-align: center;\">Don\'t worry, we\'ve still got the same awesome team with the same awesome stuff.\r\nJust better looking.</p>\r\n[button href=\"http://www.arrayfire.com\" title=\"To the Main Site\" shape=\"rounded\" size=\"large\" block=\"true\"]Continue to ArrayFire.com[/button][/column][column type=\"one-third\" last=\"true\"]<span style=\"color: #ffffff;\">.</span>[/column]\r\n\r\n[/content_band]\r\n\r\n&nbsp;\r\n\r\n&nbsp;','Splash page','','inherit','open','closed','','5312-revision-v1','','','2014-03-25 00:53:49','2014-03-25 00:53:49','',5312,'http://sandbox.arrayfire.com/5312-revision-v1/',0,'revision','',0),(5327,7,'2014-03-25 00:57:56','2014-03-25 00:57:56','[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n\r\n[column type=\"one-third\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"one-third\"]\r\n<p style=\"text-align: center;\"><img class=\"aligncenter  wp-image-259\" alt=\"arrayfire_logo_symbol\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/arrayfire_logo_symbol-300x300.png\" width=\"210\" height=\"210\" />Looking for AccelerEyes?</p>\r\n<p style=\"text-align: center;\"><strong>AccelerEyes</strong> is now <strong>ArrayFire</strong>.</p>\r\n<p style=\"text-align: center;\">Don\'t worry, we\'ve still got the same awesome team with the same awesome stuff.\r\nJust better looking.</p>\r\n[button href=\"http://www.arrayfire.com\" title=\"To the Main Site\" shape=\"rounded\" size=\"large\" block=\"true\"]Continue to ArrayFire.com[/button][/column][column type=\"one-third\" last=\"true\"]<span style=\"color: #ffffff;\">.</span>[/column]\r\n\r\n[/content_band]\r\n\r\n&nbsp;\r\n\r\n&nbsp;','Splash page','','inherit','open','closed','','5312-revision-v1','','','2014-03-25 00:57:56','2014-03-25 00:57:56','',5312,'http://sandbox.arrayfire.com/5312-revision-v1/',0,'revision','',0),(5328,7,'2014-03-25 00:58:23','2014-03-25 00:58:23','[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n\r\n[column type=\"one-third\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"one-third\"]\r\n<h3 style=\"text-align: center;\"><img class=\"aligncenter  wp-image-259\" alt=\"arrayfire_logo_symbol\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/arrayfire_logo_symbol-300x300.png\" width=\"210\" height=\"210\" />Looking for AccelerEyes?</h3>\r\n<p style=\"text-align: center;\"><strong>AccelerEyes</strong> is now <strong>ArrayFire</strong>.</p>\r\n<p style=\"text-align: center;\">Don\'t worry, we\'ve still got the same awesome team with the same awesome stuff.\r\nJust better looking.</p>\r\n[button href=\"http://www.arrayfire.com\" title=\"To the Main Site\" shape=\"rounded\" size=\"large\" block=\"true\"]Continue to ArrayFire.com[/button][/column][column type=\"one-third\" last=\"true\"]<span style=\"color: #ffffff;\">.</span>[/column]\r\n\r\n[/content_band]\r\n\r\n&nbsp;\r\n\r\n&nbsp;','Splash page','','inherit','open','closed','','5312-revision-v1','','','2014-03-25 00:58:23','2014-03-25 00:58:23','',5312,'http://sandbox.arrayfire.com/5312-revision-v1/',0,'revision','',0),(5329,7,'2014-03-25 01:05:36','2014-03-25 01:05:36','[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n\r\n[column type=\"one-third\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"one-third\"]\r\n<p style=\"text-align: center;\"><img class=\"aligncenter  wp-image-259\" alt=\"arrayfire_logo_symbol\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/arrayfire_logo_symbol-300x300.png\" width=\"210\" height=\"210\" />[custom_headline type=\"center\" level=\"h3\" ]Looking for AccelerEyes?[/custom_headline]</p>\r\n<p style=\"text-align: center;\"><strong>AccelerEyes</strong> is now <strong>ArrayFire</strong>.</p>\r\n<p style=\"text-align: center;\">Don\'t worry, we\'ve still got the same awesome team with the same awesome stuff.\r\nJust better looking.</p>\r\n[button href=\"http://www.arrayfire.com\" title=\"To the Main Site\" shape=\"rounded\" size=\"large\" block=\"true\"]Continue to ArrayFire.com[/button][/column][column type=\"one-third\" last=\"true\"]<span style=\"color: #ffffff;\">.</span>[/column]\r\n\r\n[/content_band]\r\n\r\n&nbsp;\r\n\r\n&nbsp;','Splash page','','inherit','open','closed','','5312-revision-v1','','','2014-03-25 01:05:36','2014-03-25 01:05:36','',5312,'http://sandbox.arrayfire.com/5312-revision-v1/',0,'revision','',0),(5330,7,'2014-03-25 01:06:00','2014-03-25 01:06:00','[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n\r\n[column type=\"one-third\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"one-third\"]\r\n<p style=\"text-align: center;\"><img class=\"aligncenter  wp-image-259\" alt=\"arrayfire_logo_symbol\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/arrayfire_logo_symbol-300x300.png\" width=\"210\" height=\"210\" />[custom_headline type=\"center\" level=\"h3\" class=\"mtn\"]Looking for AccelerEyes?[/custom_headline]</p>\r\n<p style=\"text-align: center;\"><strong>AccelerEyes</strong> is now <strong>ArrayFire</strong>.</p>\r\n<p style=\"text-align: center;\">Don\'t worry, we\'ve still got the same awesome team with the same awesome stuff.\r\nJust better looking.</p>\r\n[button href=\"http://www.arrayfire.com\" title=\"To the Main Site\" shape=\"rounded\" size=\"large\" block=\"true\"]Continue to ArrayFire.com[/button][/column][column type=\"one-third\" last=\"true\"]<span style=\"color: #ffffff;\">.</span>[/column]\r\n\r\n[/content_band]\r\n\r\n&nbsp;\r\n\r\n&nbsp;','Splash page','','inherit','open','closed','','5312-revision-v1','','','2014-03-25 01:06:00','2014-03-25 01:06:00','',5312,'http://sandbox.arrayfire.com/5312-revision-v1/',0,'revision','',0),(5332,7,'2014-03-25 21:11:22','2014-03-25 21:11:22','[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\"] [column type=\"one-third\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"one-third\"]\n<p style=\"text-align: center;\"><img class=\"aligncenter  wp-image-259\" alt=\"arrayfire_logo_symbol\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/arrayfire_logo_symbol-300x300.png\" width=\"210\" height=\"210\" />[custom_headline type=\"center\" level=\"h3\" class=\"mtn\"]Looking for AccelerEyes?[/custom_headline]</p>\n<p style=\"text-align: center;\"><strong>AccelerEyes</strong> is now <strong>ArrayFire</strong>.</p>\n<p style=\"text-align: center;\">Don\'t worry, we\'ve still got the same awesome team with the same awesome stuff. Just better looking.</p>\n[button href=\"http://www.arrayfire.com\" title=\"To the Main Site\" shape=\"rounded\" size=\"large\" block=\"true\"]Continue to ArrayFire.com[/button][/column][column type=\"one-third\" last=\"true\"]<span style=\"color: #ffffff;\">.</span>[/column] [/content_band]','Splash page','','inherit','open','closed','','5312-autosave-v1','','','2014-03-25 21:11:22','2014-03-25 21:11:22','',5312,'http://sandbox.arrayfire.com/5312-autosave-v1/',0,'revision','',0),(5341,7,'2014-05-07 14:32:32','2014-05-07 14:32:32','<a href=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/arrayfire_logo_whitebkgnd.png\"><img class=\"aligncenter size-medium wp-image-242\" alt=\"arrayfire_logo_whitebkgnd\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/arrayfire_logo_whitebkgnd-300x42.png\" width=\"300\" height=\"42\" /></a>\r\n\r\nIt\'s that time again—we\'re pleased to announce the release of our newest version of ArrayFire: <a href=\"http://www.sandbox.arrayfire.com/docs/installation.htm\"><strong>ArrayFire v2.1</strong></a>.\r\n\r\nArrayFire v2.1 is now bigger, faster, and stronger, thanks to some key function additions, API changes, feature improvements, and bug fixes.\r\n\r\nArrayFire is a CUDA and OpenCL library designed for maximum speed without the hassle of writing time-consuming CUDA and OpenCL device code.  With ArrayFire’s library functions, developers can maximize productivity and performance. Each of ArrayFire’s functions has been hand-tuned by CUDA and OpenCL experts.\r\n<h3>Major Updates</h3>\r\n[icon type=\"angle-double-right\"] Support for CUDA 6.0\r\n[icon type=\"angle-double-right\"] Support for Mac OS X\r\n[icon type=\"angle-double-right\"] New language support (<a href=\"https://github.com/arrayfire\">available on github</a>)\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[icon type=\"caret-right\"] <a href=\"https://github.com/arrayfire/arrayfire_java\">ArrayFire for Java</a>\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[icon type=\"caret-right\"] <a href=\"https://github.com/arrayfire/arrayfire_r\">ArrayFire for R!</a>\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[icon type=\"caret-right\"] <a href=\"https://github.com/arrayfire/arrayfire_fortran\">ArrayFire for Fortran</a>*\r\n[icon type=\"angle-double-right\"] <a href=\"https://github.com/arrayfire\">ArrayFire Extras on Github</a>\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[icon type=\"caret-right\"] All language wrappers\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[icon type=\"caret-right\"] <a href=\"https://github.com/arrayfire/arrayfire_examples\">Rolling updates to examples</a>\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[icon type=\"caret-right\"] <a href=\"https://github.com/arrayfire/arrayfire_opengl_interop\">OpenGL interop example</a>\r\n\r\n<em>*ArrayFire for Fortan has been removed from the installed library, but can be downloaded from the ArrayFire Extras GitHub page linked above.</em>\r\n<h3>Function Additions</h3>\r\n[icon type=\"angle-double-right\"] Image transformation (warp affine) functions\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[icon type=\"caret-right\"] <a href=\"http://www.sandbox.arrayfire.com/docs/group__image__func__cpp__transform.htm#ga886e586ee8e8c259202c06bd134d828a\">transform()</a>\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[icon type=\"angle-right\"] affine and inverse affine transform of an image\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[icon type=\"caret-right\"] <a href=\"http://www.sandbox.arrayfire.com/docs/group__image__func__cpp__translate.htm#ga1615c8ea000ad113a0dc7a9313d7b645\">translate()</a>\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[icon type=\"angle-right\"] translate an image using affine transforms\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[icon type=\"caret-right\"] <a href=\"http://www.sandbox.arrayfire.com/docs/group__image__func__cpp__scale.htm#ga288ebb8f3c3fb1c3a96260db4cc3b0cc\">scale()</a>\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[icon type=\"angle-right\"] scale an image using affine transforms\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[icon type=\"caret-right\"] <a href=\"http://www.sandbox.arrayfire.com/docs/group__image__func__cpp__skew.htm#gaacc7eb5f757a28d2e7d762f6b489fd5b\">skew()</a>\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[icon type=\"angle-right\"] skew an image using affine transforms\r\n[icon type=\"angle-double-right\"] Coordinate transformation (homogeneous transformation) functions\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[icon type=\"caret-right\"] transform_coords()\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[icon type=\"angle-right\"] Up to 3D homogeneous transformations\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[icon type=\"caret-right\"] rotate_coords()\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[icon type=\"angle-right\"] rotation matrix wrapper for homogeneous coordinate transformation\r\n<h3>API Changes</h3>\r\n[icon type=\"angle-double-right\"] <a href=\"http://www.sandbox.arrayfire.com/docs/group__image__func__cpp__rotate.htm#ga4e7771d3b41adcb8223aa043e2e31b98\">rotate()</a>\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[icon type=\"caret-right\"] Added optional 4th parameter `recenter`\r\n[icon type=\"angle-double-right\"] af_filter removed\r\n<h3>Feature Improvements</h3>\r\n[icon type=\"angle-double-right\"] <a href=\"http://www.sandbox.arrayfire.com/docs/group__signal__func__cpp__approx.htm#gadf7bb6bdd0fb3c9008096d47c349d073\">approx1()</a> and <a href=\"http://www.sandbox.arrayfire.com/docs/group__signal__func__cpp__approx.htm#ga33ead0c86faace1072a227cd82a19bc1\">approx2()</a> now support nearest interpolation\r\n[icon type=\"angle-double-right\"] <a href=\"http://www.sandbox.arrayfire.com/docs/group__image__func__cpp__rotate.htm#ga4e7771d3b41adcb8223aa043e2e31b98\">rotate()</a>, <a href=\"http://www.sandbox.arrayfire.com/docs/group__image__func__cpp__resize.htm#ga68a694d57cbb95ca74b6f9763fd6500b\">resize()</a>, <a href=\"http://www.sandbox.arrayfire.com/docs/group__signal__func__cpp__convolve.htm#ga7a76750edf6c2d200ce8adf0740574c5\">convolve()</a> work for stack of images(3D) and gfor\r\n[icon type=\"angle-double-right\"] new indexing functions to add support for 4-th dimension gfor\r\n[icon type=\"angle-double-right\"] host pinned memory support for OpenCL\r\n<h3>Bug Fixes</h3>\r\n[icon type=\"angle-double-right\"] <a href=\"http://www.sandbox.arrayfire.com/docs/group__image__func__cpp__loadimage.htm#gacd12e91d2760fe62fc6b781ae39d30be\">loadimage()</a>\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[icon type=\"caret-right\"] fixed bug with grayscale image reading\r\n[icon type=\"angle-double-right\"] <a href=\"http://www.sandbox.arrayfire.com/docs/group__image__func__cpp__gaussiankernel.htm#gad77314eb6df8aae428d52898b5b6a78e\">gaussiankernel()</a>\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[icon type=\"caret-right\"] fixed computation of gaussian kernel values\r\n[icon type=\"angle-double-right\"] <a href=\"http://www.sandbox.arrayfire.com/docs/group__image__func__cpp__resize.htm#ga68a694d57cbb95ca74b6f9763fd6500b\">resize()</a>\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[icon type=\"caret-right\"] fixed resize in OpenCL\r\n[icon type=\"angle-double-right\"] <a href=\"http://www.sandbox.arrayfire.com/docs/group__image__func__cpp__medfilt.htm#ga4bf90c566ac99adb38d679a5a598b65f\">medfilt()</a>\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[icon type=\"caret-right\"] fixed to handle more data types\r\n[icon type=\"angle-double-right\"] <a href=\"http://www.sandbox.arrayfire.com/docs/group__image__func__cpp__rotate.htm#ga4e7771d3b41adcb8223aa043e2e31b98\">rotate()</a>\r\n[icon type=\"caret-right\"] fixed rounding issue on Tahiti GPUs\r\n[icon type=\"angle-double-right\"] <a href=\"http://www.sandbox.arrayfire.com/docs/group__signal__func__cpp__approx.htm#gadf7bb6bdd0fb3c9008096d47c349d073\">approx1()</a>\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[icon type=\"caret-right\"] fixed for gfor use\r\n[icon type=\"angle-double-right\"] <a href=\"http://www.sandbox.arrayfire.com/docs/group__array__func__cpp__flip.htm#ga920af856ce0c993a929850149a289d60\">flip()</a>\r\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[icon type=\"caret-right\"] fixed launch configuration\r\n[icon type=\"angle-double-right\"] indexing now works on intel GPUs\r\n<h3>Performance Improvements</h3>\r\n[icon type=\"angle-double-right\"] <a href=\"http://www.sandbox.arrayfire.com/docs/group__image__func__cpp__rotate.htm#ga4e7771d3b41adcb8223aa043e2e31b98\">rotate()</a> rewritten to improve performance\r\n\r\n<span style=\"line-height: 1.5em;\">Visit our sleek, new <a href=\"http://www.sandbox.arrayfire.com/docs/\">documentation</a> to see ArrayFire in action and to view the complete list of all the enhancements available with ArrayFire v2.1.</span>\r\n\r\nWhile you\'re at it, be sure to check out our <a href=\"http://sandbox.arrayfire.com/#licensing\">ArrayFire licensing information</a>  to learn more about which licensing option would be the best for your needs.\r\n<div>\r\n\r\nJust getting started with GPU computing? Need an extra hand on a project? Tap into our deep parallel computing expertise and vast code base by setting up a free <a href=\"http://www.meetme.so/arrayfire\">technical consultation</a> today.\r\n\r\nWe’re always looking to make ArrayFire even better—let us know your thoughts through this short <a href=\"https://www.surveymonkey.com/s/arrayfire-new-feature\">survey</a>. We promise it’ll be worth your while!\r\n\r\n</div>','ArrayFire v2.1 Official Release','','publish','open','closed','','arrayfire-v2-1-official-release','','','2014-05-07 14:32:32','2014-05-07 14:32:32','',0,'http://sandbox.arrayfire.com/?p=5341',0,'post','',0),(5342,7,'2014-03-26 17:34:31','2014-03-26 17:34:31','<a href=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/arrayfire_logo_whitebkgnd1.png\"><img class=\"aligncenter size-medium wp-image-262\" alt=\"arrayfire_logo_whitebkgnd\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/arrayfire_logo_whitebkgnd1-300x42.png\" width=\"300\" height=\"42\" /></a>\r\n\r\nIt\'s that time again—we\'re pleased to announce the release of our newest version of ArrayFire: <strong>ArrayFire v2.1</strong>.\r\n\r\nArrayFire v2.1 is now bigger, faster, and stronger, thanks to some key function additions, API changes, feature improvements, and bug fixes.\r\n<h3>Major Updates</h3>\r\n[icon type=\"angle-double-right\"] Support for Mac OS X\r\n[icon type=\"angle-double-right\"] Language support\r\n[icon type=\"angle-double-right\"] ArrayFire for Java (https://github.com/arrayfire/arrayfire_java)\r\n[icon type=\"angle-double-right\"] ArrayFire for R! (https://github.com/arrayfire/arrayfire_r)\r\n[icon type=\"angle-double-right\"] ArrayFire for Fortran (https://github.com/arrayfire/arrayfire_fortran)&lt;sup&gt;#&lt;/sup&gt;\r\n[icon type=\"angle-double-right\"] ArrayFire Extras on Github (https://github.com/arrayfire)\r\n[icon type=\"angle-double-right\"] All language wrappers\r\n[icon type=\"angle-double-right\"] Rolling updates to examples (https://github.com/arrayfire/arrayfire_examples)\r\n[icon type=\"angle-double-right\"] OpenGL interop example (https://github.com/arrayfire/arrayfire_opengl_interop)\r\n\r\nNote: ArrayFire for Fortan has been removed from the installed library, but can be downloaded from the ArrayFire Extras GitHub page linked above.\r\n<h3>Function Additions</h3>\r\n[icon type=\"angle-double-right\"] Image transformation (warp affine) functions\r\n[icon type=\"angle-double-right\"] transform()\r\n[icon type=\"angle-double-right\"] affine and inverse affine transform of an image\r\n[icon type=\"angle-double-right\"] translate()\r\n[icon type=\"angle-double-right\"] translate an image using affine transforms\r\n[icon type=\"angle-double-right\"] scale()\r\n[icon type=\"angle-double-right\"] scale an image using affine transforms\r\n[icon type=\"angle-double-right\"] skew()\r\n[icon type=\"angle-double-right\"] skew an image using affine transforms\r\n[icon type=\"angle-double-right\"] Coordinate transformation (homogeneous transformation) functions\r\n[icon type=\"angle-double-right\"] transform_coords()\r\n[icon type=\"angle-double-right\"] Upto 3D homogeneous transformations\r\n[icon type=\"angle-double-right\"] rotate_coords()\r\n[icon type=\"angle-double-right\"] rotation matrix wrapper for homogeneous coordinate transformation\r\n<h3>API Changes</h3>\r\n[icon type=\"angle-double-right\"] rotate()\r\n[icon type=\"angle-double-right\"] Added optional 4th parameter `recenter`\r\n[icon type=\"angle-double-right\"] af_filter removed\r\n<h3>Feature Improvements</h3>\r\n[icon type=\"angle-double-right\"] approx1() and approx2() now support nearest interpolation\r\n[icon type=\"angle-double-right\"] rotate(), resize(), convolve() work for stack of images(3D) and gfor\r\n[icon type=\"angle-double-right\"] new indexing functions to add support for 4-th dimension gfor\r\n[icon type=\"angle-double-right\"] host pinned memory support for OpenCL\r\n<h3>Bug Fixes</h3>\r\n[icon type=\"angle-double-right\"] loadimage()\r\n[icon type=\"angle-double-right\"] fixed bug with grayscale image reading\r\n[icon type=\"angle-double-right\"] gaussiankernel()\r\n[icon type=\"angle-double-right\"] fixed computation of gaussian kernel values\r\n[icon type=\"angle-double-right\"] resize()\r\n[icon type=\"angle-double-right\"] fixed resize in OpenCL\r\n[icon type=\"angle-double-right\"] medfilt()\r\n[icon type=\"angle-double-right\"] fixed to handle more data types\r\n[icon type=\"angle-double-right\"] rotate()\r\n[icon type=\"angle-double-right\"] fixed rounding issue on Tahiti GPUs\r\n[icon type=\"angle-double-right\"] approx1()\r\n[icon type=\"angle-double-right\"] fixed for gfor use\r\n[icon type=\"angle-double-right\"] flip()\r\n[icon type=\"angle-double-right\"] fixed launch configuration\r\n[icon type=\"angle-double-right\"] indexing now works on intel GPUs\r\n<h3>Performance Improvements</h3>\r\n[icon type=\"angle-double-right\"] rotate() rewritten to improve performance','ArrayFire v2.1 Official Release','','inherit','open','closed','','5341-revision-v1','','','2014-03-26 17:34:31','2014-03-26 17:34:31','',5341,'http://sandbox.arrayfire.com/5341-revision-v1/',0,'revision','',0),(5343,7,'2014-03-26 17:36:11','2014-03-26 17:36:11','<a href=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/arrayfire_logo_whitebkgnd1.png\"><img class=\"aligncenter size-medium wp-image-262\" alt=\"arrayfire_logo_whitebkgnd\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/arrayfire_logo_whitebkgnd1-300x42.png\" width=\"300\" height=\"42\" /></a>\r\n\r\nIt\'s that time again—we\'re pleased to announce the release of our newest version of ArrayFire: <strong>ArrayFire v2.1</strong>.\r\n\r\nArrayFire v2.1 is now bigger, faster, and stronger, thanks to some key function additions, API changes, feature improvements, and bug fixes.\r\n<h3>Major Updates</h3>\r\n[icon type=\"angle-double-right\"] Support for Mac OS X\r\n[icon type=\"angle-double-right\"] Language support\r\n[icon type=\"angle-double-right\"] ArrayFire for Java (https://github.com/arrayfire/arrayfire_java)\r\n[icon type=\"angle-double-right\"] ArrayFire for R! (https://github.com/arrayfire/arrayfire_r)\r\n[icon type=\"angle-double-right\"] ArrayFire for Fortran (https://github.com/arrayfire/arrayfire_fortran)&lt;sup&gt;#&lt;/sup&gt;\r\n[icon type=\"angle-double-right\"] ArrayFire Extras on Github (https://github.com/arrayfire)\r\n[icon type=\"angle-double-right\"] All language wrappers\r\n[icon type=\"angle-double-right\"] Rolling updates to examples (https://github.com/arrayfire/arrayfire_examples)\r\n[icon type=\"angle-double-right\"] OpenGL interop example (https://github.com/arrayfire/arrayfire_opengl_interop)\r\n\r\n<em>Note: ArrayFire for Fortan has been removed from the installed library, but can be downloaded from the ArrayFire Extras GitHub page linked above.</em>\r\n<h3>Function Additions</h3>\r\n[icon type=\"angle-double-right\"] Image transformation (warp affine) functions\r\n[icon type=\"angle-double-right\"] transform()\r\n[icon type=\"angle-double-right\"] affine and inverse affine transform of an image\r\n[icon type=\"angle-double-right\"] translate()\r\n[icon type=\"angle-double-right\"] translate an image using affine transforms\r\n[icon type=\"angle-double-right\"] scale()\r\n[icon type=\"angle-double-right\"] scale an image using affine transforms\r\n[icon type=\"angle-double-right\"] skew()\r\n[icon type=\"angle-double-right\"] skew an image using affine transforms\r\n[icon type=\"angle-double-right\"] Coordinate transformation (homogeneous transformation) functions\r\n[icon type=\"angle-double-right\"] transform_coords()\r\n[icon type=\"angle-double-right\"] Upto 3D homogeneous transformations\r\n[icon type=\"angle-double-right\"] rotate_coords()\r\n[icon type=\"angle-double-right\"] rotation matrix wrapper for homogeneous coordinate transformation\r\n<h3>API Changes</h3>\r\n[icon type=\"angle-double-right\"] rotate()\r\n[icon type=\"angle-double-right\"] Added optional 4th parameter `recenter`\r\n[icon type=\"angle-double-right\"] af_filter removed\r\n<h3>Feature Improvements</h3>\r\n[icon type=\"angle-double-right\"] approx1() and approx2() now support nearest interpolation\r\n[icon type=\"angle-double-right\"] rotate(), resize(), convolve() work for stack of images(3D) and gfor\r\n[icon type=\"angle-double-right\"] new indexing functions to add support for 4-th dimension gfor\r\n[icon type=\"angle-double-right\"] host pinned memory support for OpenCL\r\n<h3>Bug Fixes</h3>\r\n[icon type=\"angle-double-right\"] loadimage()\r\n[icon type=\"angle-double-right\"] fixed bug with grayscale image reading\r\n[icon type=\"angle-double-right\"] gaussiankernel()\r\n[icon type=\"angle-double-right\"] fixed computation of gaussian kernel values\r\n[icon type=\"angle-double-right\"] resize()\r\n[icon type=\"angle-double-right\"] fixed resize in OpenCL\r\n[icon type=\"angle-double-right\"] medfilt()\r\n[icon type=\"angle-double-right\"] fixed to handle more data types\r\n[icon type=\"angle-double-right\"] rotate()\r\n[icon type=\"angle-double-right\"] fixed rounding issue on Tahiti GPUs\r\n[icon type=\"angle-double-right\"] approx1()\r\n[icon type=\"angle-double-right\"] fixed for gfor use\r\n[icon type=\"angle-double-right\"] flip()\r\n[icon type=\"angle-double-right\"] fixed launch configuration\r\n[icon type=\"angle-double-right\"] indexing now works on intel GPUs\r\n<h3>Performance Improvements</h3>\r\n[icon type=\"angle-double-right\"] rotate() rewritten to improve performance','ArrayFire v2.1 Official Release','','inherit','open','closed','','5341-revision-v1','','','2014-03-26 17:36:11','2014-03-26 17:36:11','',5341,'http://sandbox.arrayfire.com/5341-revision-v1/',0,'revision','',0),(5344,7,'2014-03-26 17:37:55','2014-03-26 17:37:55','<a href=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/arrayfire_logo_whitebkgnd.png\"><img class=\"aligncenter size-medium wp-image-242\" alt=\"arrayfire_logo_whitebkgnd\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/arrayfire_logo_whitebkgnd-300x42.png\" width=\"300\" height=\"42\" /></a>\r\n\r\nIt\'s that time again—we\'re pleased to announce the release of our newest version of ArrayFire: <strong>ArrayFire v2.1</strong>.\r\n\r\nArrayFire v2.1 is now bigger, faster, and stronger, thanks to some key function additions, API changes, feature improvements, and bug fixes.\r\n<h3>Major Updates</h3>\r\n[icon type=\"angle-double-right\"] Support for Mac OS X\r\n[icon type=\"angle-double-right\"] Language support\r\n[icon type=\"angle-double-right\"] ArrayFire for Java (https://github.com/arrayfire/arrayfire_java)\r\n[icon type=\"angle-double-right\"] ArrayFire for R! (https://github.com/arrayfire/arrayfire_r)\r\n[icon type=\"angle-double-right\"] ArrayFire for Fortran (https://github.com/arrayfire/arrayfire_fortran)&lt;sup&gt;#&lt;/sup&gt;\r\n[icon type=\"angle-double-right\"] ArrayFire Extras on Github (https://github.com/arrayfire)\r\n[icon type=\"angle-double-right\"] All language wrappers\r\n[icon type=\"angle-double-right\"] Rolling updates to examples (https://github.com/arrayfire/arrayfire_examples)\r\n[icon type=\"angle-double-right\"] OpenGL interop example (https://github.com/arrayfire/arrayfire_opengl_interop)\r\n\r\n<em>Note: ArrayFire for Fortan has been removed from the installed library, but can be downloaded from the ArrayFire Extras GitHub page linked above.</em>\r\n<h3>Function Additions</h3>\r\n[icon type=\"angle-double-right\"] Image transformation (warp affine) functions\r\n[icon type=\"angle-double-right\"] transform()\r\n[icon type=\"angle-double-right\"] affine and inverse affine transform of an image\r\n[icon type=\"angle-double-right\"] translate()\r\n[icon type=\"angle-double-right\"] translate an image using affine transforms\r\n[icon type=\"angle-double-right\"] scale()\r\n[icon type=\"angle-double-right\"] scale an image using affine transforms\r\n[icon type=\"angle-double-right\"] skew()\r\n[icon type=\"angle-double-right\"] skew an image using affine transforms\r\n[icon type=\"angle-double-right\"] Coordinate transformation (homogeneous transformation) functions\r\n[icon type=\"angle-double-right\"] transform_coords()\r\n[icon type=\"angle-double-right\"] Upto 3D homogeneous transformations\r\n[icon type=\"angle-double-right\"] rotate_coords()\r\n[icon type=\"angle-double-right\"] rotation matrix wrapper for homogeneous coordinate transformation\r\n<h3>API Changes</h3>\r\n[icon type=\"angle-double-right\"] rotate()\r\n[icon type=\"angle-double-right\"] Added optional 4th parameter `recenter`\r\n[icon type=\"angle-double-right\"] af_filter removed\r\n<h3>Feature Improvements</h3>\r\n[icon type=\"angle-double-right\"] approx1() and approx2() now support nearest interpolation\r\n[icon type=\"angle-double-right\"] rotate(), resize(), convolve() work for stack of images(3D) and gfor\r\n[icon type=\"angle-double-right\"] new indexing functions to add support for 4-th dimension gfor\r\n[icon type=\"angle-double-right\"] host pinned memory support for OpenCL\r\n<h3>Bug Fixes</h3>\r\n[icon type=\"angle-double-right\"] loadimage()\r\n[icon type=\"angle-double-right\"] fixed bug with grayscale image reading\r\n[icon type=\"angle-double-right\"] gaussiankernel()\r\n[icon type=\"angle-double-right\"] fixed computation of gaussian kernel values\r\n[icon type=\"angle-double-right\"] resize()\r\n[icon type=\"angle-double-right\"] fixed resize in OpenCL\r\n[icon type=\"angle-double-right\"] medfilt()\r\n[icon type=\"angle-double-right\"] fixed to handle more data types\r\n[icon type=\"angle-double-right\"] rotate()\r\n[icon type=\"angle-double-right\"] fixed rounding issue on Tahiti GPUs\r\n[icon type=\"angle-double-right\"] approx1()\r\n[icon type=\"angle-double-right\"] fixed for gfor use\r\n[icon type=\"angle-double-right\"] flip()\r\n[icon type=\"angle-double-right\"] fixed launch configuration\r\n[icon type=\"angle-double-right\"] indexing now works on intel GPUs\r\n<h3>Performance Improvements</h3>\r\n[icon type=\"angle-double-right\"] rotate() rewritten to improve performance','ArrayFire v2.1 Official Release','','inherit','open','closed','','5341-revision-v1','','','2014-03-26 17:37:55','2014-03-26 17:37:55','',5341,'http://sandbox.arrayfire.com/5341-revision-v1/',0,'revision','',0),(5347,7,'2014-03-31 19:46:18','2014-03-31 19:46:18','','Benchmarks','','publish','open','closed','','benchmarks','','','2014-04-01 13:51:19','2014-04-01 13:51:19','',0,'http://sandbox.arrayfire.com/?p=5347',5,'nav_menu_item','',0),(5350,7,'2014-03-31 20:01:52','2014-03-31 20:01:52','[content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\"][column type=\"one-half\"] [custom_headline type=\"left\" level=\"h3\" ]About[/custom_headline]ArrayFire is the software shop for CUDA and OpenCL. Since 2007, ArrayFire has offered the most productive solutions for accelerating code using GPUs. Today, ArrayFire delivers products which are used to accelerate C, C++, and Fortran codes on CUDA GPUs and OpenCL devices. ArrayFire has thousands of customers. These customers come from a wide range of industries, including defense and intelligence, life science, oil and gas, finance, manufacturing, media, and others.\r\n\r\nArrayFire has had success accelerating numerous application types, including math and numerical algorithms, image processing, signal processing, statistics, optimization, and more. Many ArrayFire customers are realizing 100X speed-up with much less effort than is typically required to accelerate code.[/column][column type=\"one-half\" last=\"true\" fade=\"true\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/dj-Flame.png\"] [/column]<div id=\"contact\"></div>\r\n\r\n[line][column type=\"one-third\"][custom_headline type=\"center\" level=\"h5\" accent=\"false\"]Email[/custom_headline]\r\n<p style=\"text-align: center;\">Sales: sales@arrayfire.com\r\nSupport: sales@arrayfire.com\r\nCareers: jobs@arrayfire.com[/column]</p>\r\n[column type=\"one-third\"][custom_headline type=\"center\" level=\"h5\" accent=\"false\"]Phone[/custom_headline]\r\n<p style=\"text-align: center;\">Sales: +1 (800) 570-1941 x 1\r\nTechnical Support: +1 (800) 570-1941 x 2 [/column]</p>\r\n[column type=\"one-third\" last=\"true\"][custom_headline type=\"center\" level=\"h5\" accent=\"false\"]Headquarters[/custom_headline]\r\n<p style=\"text-align: center;\">3423 Piedmont Rd NE STE 330\r\nAtlanta, GA 30305[/column] [/content_band]</p>\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\" ][column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\" ]Careers[/custom_headline]As a global leader in GPU computing software, our business opportunities are always expanding. We are constantly searching for talented, qualified individuals to join the ArrayFire team. ArrayFire is committed to providing employees with the opportunity to grow and learn, the freedom to express ideas and contribute to new developments, and the motivation to succeed. To start the application process, simply email us your resume and let us know which position(s) you\'re interested in.[/column][column type=\"one-half\" last=\"true\"][/column]\r\n\r\n&nbsp;\r\n\r\n[column type=\"one-third\"][promo image=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/little-boba-fett.png\" alt=\"Alt Text\"][custom_headline type=\"left\" level=\"h5\"  class=\"mtn\"]Software Engineer - Atlanta, GA[/custom_headline]\r\n\r\n<strong>Responsibilities:</strong> Develop in C/C++, Fortran, CUDA, and OpenCL. Respond to forum posts and customer support tickets.\r\n\r\n<strong>Qualifications</strong>: A background in any of high-performance computing, operating systems, or compilers. Several years of C/C++ and at least one year of CUDA or similar technology. Familiarity with Fortran is a plus. Undergraduate or graduate work in CS or related field. [/promo][/column]\r\n\r\n[column type=\"one-third\"][promo image=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/uncle-sam.png\" alt=\"Alt Text\"] [custom_headline type=\"left\" level=\"h5\"  class=\"mtn\"]Application Engineer - Atlanta, GA[/custom_headline]\r\n\r\n<strong>Responsibilities: </strong>Work closely with customers to develop software solutions using our products. Develop technical marketing materials including demos, webinars, tutorials, etc. Respond to forum posts and customer support tickets.\r\n\r\n<strong>Qualifications:</strong> Undergraduate or graduate work in CS or related field. Strong programming skills in C/C++. Excellent communication skills.[/promo][/column]\r\n\r\n[column type=\"one-third\" last=\"true\"][promo image=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/i-see-pride-i-see-power.png\" alt=\"Alt Text\"][custom_headline type=\"left\" level=\"h5\" class=\"mtn\"]Web/Dev Engineer - Atlanta, GA[/custom_headline]\r\n\r\n<strong>Responsibilities: </strong>Develop PHP/MySQL backend infrastructure with basic HTML/CSS/JavaScript frontend work. Developing lightweight webapps for system monitoring. Maintaining Wordpress and SalesForce integration. Maintaining server/cluster infrastructure.\r\n\r\n<strong>Qualifications:</strong> Strong PHP and MySQL experience. Very comfortable at a shell prompt. Proficient in HTML, CSS, and JavaScript. Familiarity with Wordpress or SalesForce is a plus.[/promo][/column][/content_band]','Company','','inherit','open','closed','','329-revision-v1','','','2014-03-31 20:01:52','2014-03-31 20:01:52','',329,'http://sandbox.arrayfire.com/329-revision-v1/',0,'revision','',0),(5351,7,'2014-03-31 20:25:09','2014-03-31 20:25:09','','Contact','','publish','open','open','','contact','','','2014-11-12 15:30:13','2014-11-12 15:30:13','',0,'http://sandbox.arrayfire.com/?p=5351',5,'nav_menu_item','',0),(5357,7,'2014-04-01 14:12:14','2014-04-01 14:12:14','','Mobile','','publish','open','closed','','mobile-2','','','2014-04-07 21:14:48','2014-04-07 21:14:48','',0,'http://sandbox.arrayfire.com/?p=5357',4,'nav_menu_item','',0),(5358,7,'2014-04-01 14:12:14','2014-04-01 14:12:14','','Documentation','','publish','open','closed','','documentation-2','','','2014-04-07 21:14:48','2014-04-07 21:14:48','',0,'http://sandbox.arrayfire.com/?p=5358',5,'nav_menu_item','',0),(5359,7,'2014-04-01 14:12:14','2014-04-01 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20:59:56','',0,'http://sandbox.arrayfire.com/wp-content/uploads/2014/04/koch.jpg',0,'attachment','image/jpeg',0),(5384,7,'2014-04-01 20:59:57','2014-04-01 20:59:57','','nasa','','inherit','open','closed','','nasa','','','2014-10-10 19:44:31','2014-10-10 19:44:31','',6613,'http://sandbox.arrayfire.com/wp-content/uploads/2014/04/nasa.png',0,'attachment','image/png',0),(5390,7,'2014-04-01 21:22:22','2014-04-01 21:22:22','','Koch-Industries','','inherit','open','closed','','koch-industries','','','2014-10-10 19:43:50','2014-10-10 19:43:50','',6613,'http://sandbox.arrayfire.com/wp-content/uploads/2014/04/Koch-Industries.jpg',0,'attachment','image/jpeg',0),(5395,7,'2014-04-02 14:11:45','2014-04-02 14:11:45','','1800contactlogo','','inherit','open','closed','','1800contactlogo','','','2014-10-10 19:43:30','2014-10-10 19:43:30','',6613,'http://sandbox.arrayfire.com/wp-content/uploads/2014/04/1800contactlogo.png',0,'attachment','image/png',0),(5396,7,'2014-04-02 14:11:54','2014-04-02 14:11:54','','LFG-B-HORZ_202_K','','inherit','open','closed','','lfg-b-horz_202_k','','','2014-10-10 19:46:38','2014-10-10 19:46:38','',6613,'http://sandbox.arrayfire.com/wp-content/uploads/2014/04/LFG-B-HORZ_202_K.jpg',0,'attachment','image/jpeg',0),(5403,7,'2014-04-02 17:29:33','2014-04-02 17:29:33','ArrayFire Enterprise Edition. ArrayFire Enterprise includes one (1) ArrayFire Pro dedicated license with support for 2 GPUs or devices. ArrayFire Enterprise also includes (1) free GPU consulting starter package, technical phone support with priority support response times, and prioritized feature requests. ArrayFire 2 GPU Designated computer licenses are sold as 1-year subscriptions that include updates. At the end of the year, customers may either renew the subscription or continue using ArrayFire Pro without future updates. License includes: Image Processing, Signal Processing, Statistics, Graphics Library, Linear Algebra, Sparse Matrices, and many other functions, as well as support in the ArrayFire forums.  All licenses are subject to the EULA found at <a href=\"http://sandbox.arrayfire.com/legal/#eula\" title=\"http://sandbox.arrayfire.com/legal/#eula\" target=\"_blank\">http://sandbox.arrayfire.com/legal/#eula</a>.','ArrayFire Enterprise (Includes Consulting Starter Package)','Support for 2 GPUs in a single designated computer.  Includes additional premium linear algebra and sparse functions.  Provides a perpetual dedicated license with a 1-year subscription to updates.  Enterprise support included.','inherit','open','closed','','42-autosave-v1','','','2014-04-02 17:29:33','2014-04-02 17:29:33','',42,'http://sandbox.arrayfire.com/42-autosave-v1/',0,'revision','',0),(5405,7,'2014-04-04 14:51:40','2014-04-04 14:51:40',' ','','','publish','open','closed','','5405','','','2014-04-07 21:14:48','2014-04-07 21:14:48','',0,'http://sandbox.arrayfire.com/?p=5405',18,'nav_menu_item','',0),(5406,7,'2014-04-04 14:51:40','2014-04-04 14:51:40',' ','','','publish','open','closed','','5406','','','2014-04-07 21:14:48','2014-04-07 21:14:48','',0,'http://sandbox.arrayfire.com/?p=5406',19,'nav_menu_item','',0),(5407,7,'2014-04-04 14:51:40','2014-04-04 14:51:40',' ','','','publish','open','closed','','5407','','','2014-04-07 21:14:48','2014-04-07 21:14:48','',0,'http://sandbox.arrayfire.com/?p=5407',20,'nav_menu_item','',0),(5408,7,'2014-04-04 14:51:40','2014-04-04 14:51:40',' ','','','publish','open','closed','','5408','','','2014-04-07 21:14:48','2014-04-07 21:14:48','',7,'http://sandbox.arrayfire.com/?p=5408',21,'nav_menu_item','',0),(5409,7,'2014-04-04 14:51:40','2014-04-04 14:51:40',' ','','','publish','open','closed','','5409','','','2014-04-07 21:14:48','2014-04-07 21:14:48','',0,'http://sandbox.arrayfire.com/?p=5409',22,'nav_menu_item','',0),(5410,7,'2014-04-04 14:51:40','2014-04-04 14:51:40',' ','','','publish','open','closed','','5410','','','2014-04-07 21:14:48','2014-04-07 21:14:48','',0,'http://sandbox.arrayfire.com/?p=5410',23,'nav_menu_item','',0),(5411,7,'2014-04-07 15:02:37','2014-04-07 15:02:37','[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\"][column type=\"two-fifths\"]\r\n\r\n[custom_headline type=\"left\" level=\"h3\"]If you want faster code, you\'ve come to the right place.[/custom_headline][gap size=\"15%\"][button  type=\"flat\" shape=\"rounded\" href=\"http://www.accelereyes.com/arrayfire/c/installation.htm\" size=\"x-large\" block=\"true\"]Download ArrayFire[/button]\r\n\r\n[gap size=\"10%\"]\r\n\r\n[button  type=\"flat\" block=\"true\" shape=\"rounded\" href=\"http://www.meetme.so/arrayfire\" size=\"x-large\" ]Schedule a consultation[/button]\r\n\r\n[/column][column type=\"three-fifths\" last=\"true\"][gap size=\"7%\"]\r\n<div class=\"wistia_embed\" id=\"wistia_rj2bar3xxp\" style=\"width: 640px; height: 388px;\"></div>\r\n<script charset=\"ISO-8859-1\" type=\"text/javascript\" src=\"//fast.wistia.com/assets/external/E-v1.js\"></script><script type=\"text/javascript\">// <![CDATA[\r\nwistiaEmbed = Wistia.embed(\"rj2bar3xxp\");\r\n// ]]></script>[/column]\r\n<div id=\"arrayfire\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"][column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"]Faster code[/custom_headline]\r\n\r\nArrayFire is a fast, hardware-neutral software library for GPU computing with an easy-to-use API. Its array-based function set makes GPU programming simple. A few lines of code in ArrayFire can replace dozens of lines of raw GPU code, saving you valuable time and lowering development costs.\r\n\r\n[gap size=\"10%\"][button  type=\"flat\" shape=\"rounded\" href=\"http://www.accelereyes.com/arrayfire/c/installation.htm\" size=\"x-large\" ]Download ArrayFire[/button][/column][column type=\"one-half\" last=\"true\" class=\"center-text\"][gap size=\"5%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Triumvirate_Exported.png\"][/column] [gap size=\"5%\"]\r\n\r\n[column type=\"one-third\" class=\"center-text\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/04/Googlelogo-e1396387097279.png\"][line]Video content analysis is the basis for categorizing videos and enabling search by content. Google used ArrayFire to extract motion features in video, improving performance by substantially accelerating the solution of the L1-regularized least-squares optimization problem.[/column][column type=\"one-third\" class=\"center-text\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/04/Koch-Industries-e1396387359637.jpg\"][line]Andrew Shin, Market Risk Manager of Koch Supply &amp; Trading, achieves significant performance increases on option pricing algorithms using ArrayFire software, \"My buddy and I are, at best, novice programmers and we couldn\'t imagine having to figure out how to code all this in CUDA.\"[/column][column type=\"one-third\" last=\"true\" class=\"center-text\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/04/nasa-e1396387230473.png\"][line]The main thrust of this research was improving Mars rover image compression via GPUs and genetic algorithms. With ArrayFire software and GPUs, the researchers were able to achieve 5X speedups on the larger data sizes.[/column]\r\n<div id=\"hardware\"></div>\r\n[/content_band]\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n\r\n[column type=\"one-half\"][gap size=\"15%\"]\r\n<p style=\"text-align: center;\"><img class=\"aligncenter\" alt=\"CUDA logo\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/CUDA-logo.jpg\" width=\"231\" height=\"140\" /></p>\r\n<img class=\"aligncenter\" alt=\"OpenCL\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/OpenCLLogo_678x452.png\" width=\"326\" height=\"217\" />\r\n\r\n[/column][column type=\"one-half\" last=\"true\"][gap size=\"10%\"]\r\n\r\n[custom_headline type=\"left\" level=\"h3\"] ArrayFire for CUDA and OpenCL[/custom_headline]\r\n\r\nArrayFire supports CUDA-capable NVIDIA GPUs and most OpenCL devices, including AMD GPUs/APUs and Intel Xeon Phi co-processors. It also supports mobile OpenCL devices from ARM, Qualcomm, and others.\r\n\r\n<span style=\"line-height: 1.5em;\">ArrayFire is a high-performance software library designed for maximum productivity and speed without the hassle of writing difficult low-level device code. Each of ArrayFire\'s functions has been hand-tuned by our CUDA and OpenCL experts.</span>\r\n\r\n[/column]\r\n<div id=\"mobile\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n[column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"  ]Mobile GPU Computing[/custom_headline]\r\n\r\nMobile GPUs offer accelerated performance. If you would like to use ArrayFire in a mobile application or if you would like to hire our mobile acceleration services, email us at <a href=\"mailto:sales@arrayfire.com\" target=\"_blank\">sales@arrayfire.com</a> and include a description of your application.\r\n\r\nOur clients have achieved between 5X to 30X speed boosts for convolutions and other compute functions on mobile devices. It enables:[icon_list][icon_list_item type=\"angle-double-right\"]Real-time video processing[/icon_list_item][icon_list_item type=\"angle-double-right\"]Better augmented reality [/icon_list_item][icon_list_item type=\"angle-double-right\"]Better computational photograph[/icon_list_item][icon_list_item type=\"angle-double-right\"]Faster data processing[/icon_list_item][/icon_list]\r\n\r\nAll mobile devices have a GPU which can deliver greater compute throughput than the CPU. Why not use the GPU to make your app faster?[/column][column type=\"one-half\" fade=\"true\" last=\"true\" fade_animation=\"in-from-right\" class=\"center-text\"][gap size=\"10%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/mobile_Exported1-e1395437261846.png\"][/column]\r\n<div id=\"documentation\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"][column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"]Documentation[/custom_headline]\r\n\r\n<strong>ArrayFire for C, C++, and Fortran\r\n</strong>Open the hood—take a look at the beautiful nitty-gritty.\r\n\r\n<strong></strong>[icon type=\"angle-double-right\"] <a href=\"http://www.accelereyes.com/arrayfire/c\" target=\"_blank\">CUDA &amp; OpenCL C/C++\r\n</a>[icon type=\"angle-double-right\"] <a href=\"http://www.accelereyes.com/arrayfire/fortran\" target=\"_blank\">CUDA &amp; OpenCL Fortran</a>\r\n\r\n<strong>Functions\r\n</strong>Hundreds of functions, hand-tuned and optimized by our engineers.\r\n\r\n[icon type=\"angle-double-right\"] <a title=\"ArrayFire Functions\" href=\"http://www.accelereyes.com/arrayfire/c/modules.htm\">ArrayFire Functions</a>\r\n\r\n<strong>User Forums</strong>\r\nEvery post gets a response from ArrayFire engineers.\r\n\r\n[icon type=\"angle-double-right\"] <a href=\"http://forums.accelereyes.com/\" target=\"_blank\">User Forums</a>\r\n\r\n[/column][column class=\"center-text\" type=\"one-half\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][gap size=\"5%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/gears1.png\"][/column]\r\n<div id=\"benchmarks\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n[column type=\"one-half\" fade=\"true\" fade_animation=\"in-from-left\" ][gap size=\"5%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/Benchmark-guy-torso-opposite-e1392155948298.png\"][/column]\r\n\r\n[column type=\"one-half\" last=\"true\"][custom_headline type=\"left\" level=\"h3\" ]Benchmarks[/custom_headline]\r\n\r\nAll benchmarks were performed on a NVIDIA Tesla C2050 with an Intel i7-950 processor. The benchmarks compare ArrayFire with several popular CPU-based acceleration libraries, including <a href=\"http://software.intel.com/en-us/articles/intel-mkl/\" target=\"_new\">Intel Math Kernel Library</a>, <a href=\"http://software.intel.com/en-us/articles/intel-ipp/\" target=\"_new\">Intel Integrated Performance Primitives</a>, <a href=\"http://eigen.tuxfamily.org/index.php?title=Main_Page\" target=\"_new\">Eigen</a>, and <a href=\"http://arma.sourceforge.net/\" target=\"_new\">Armadillo</a>.[/column]\r\n<p style=\"text-align: center;\">[column type=\"one-fifth\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"three-fifths\"][tab_nav type=\"four-up\"][tab_nav_item title=\"Base\" active=\"true\"][tab_nav_item title=\"Linear Algebra\" active=\"\"][tab_nav_item title=\"Convolution\" active=\"\"][tab_nav_item title=\"Utility\" active=\"\"][/tab_nav][tabs][tab active=\"true\"]<img class=\"aligncenter  wp-image-351\" alt=\"Matrix Multiply\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/matrix_multiply-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-352\" alt=\"Matrix Transpose\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/matrix_transpose-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-349\" alt=\"FFT\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/fft-1024x730.png\" width=\"491\" height=\"350\" />[/tab][tab]<img class=\"aligncenter  wp-image-350\" alt=\"LU\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/lu-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-357\" alt=\"SVD\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/svd-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-354\" alt=\"Solve\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/solve-1024x730.png\" width=\"491\" height=\"350\" />[/tab][tab]<img class=\"aligncenter  wp-image-348\" alt=\"Convs\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/convs-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-347\" alt=\"Conv\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/conv-1024x730.png\" width=\"491\" height=\"350\" />[/tab][tab]<img class=\"aligncenter  wp-image-356\" alt=\"sum\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/sum-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-355\" alt=\"sort\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/sort-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-353\" alt=\"scan\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/scan-1024x730.png\" width=\"491\" height=\"350\" />[/tab][/tabs][/column][column type=\"one-fifth\" last=\"true\"]<span style=\"color: #ffffff;\">.</span>[/column]</p>\r\n\r\n<div id=\"free\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n\r\n[column type=\"one-half\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"one-fourth\"]<span style=\"color: #ffffff;\">.</span>[custom_headline type=\"center\"  level=\"h3\" class=\"mtn\"]ArrayFire Free[/custom_headline][/column][column type=\"one-fourth\" last=\"true\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"one-fourth\"  fade=\"true\" fade_animation=\"in-from-left\" ][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/right-leaning-e1391788779101.png\"][/column][column type=\"one-fourth\"]\r\n<table>\r\n<tbody>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Functions[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Basic Operations</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Arithmetic</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Signal Processing</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Image Processing</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Statistics</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Visualization</td>\r\n</tr>\r\n</tbody>\r\n</table>\r\n[gap size=\"17%\"][button type=\"flat\" block=\"true\" shape=\"rounded\" size=\"large\"  href=\"http://www.accelereyes.com/arrayfire/c/installation.htm\"]Download ArrayFire[/button] [/column][column type=\"one-fourth\"]\r\n<table>\r\n<tbody>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Hardware[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] CUDA</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] OpenCL</td>\r\n</tr>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Languages[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] C/C++</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Fortran</td>\r\n</tr>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Advanced[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td> [icon type=\"check-circle\" style=\"color: #8cc540;\"] GFOR Loop</td>\r\n</tr>\r\n</tbody>\r\n</table>\r\n[/column][column type=\"one-fourth\" last=\"true\"]\r\n<table>\r\n<tbody>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Platforms[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Windows</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Linux</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Mac</td>\r\n</tr>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Data Types[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] All types</td>\r\n</tr>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Support[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td> [icon type=\"check-circle\" style=\"color: #8cc540;\"] Forums</td>\r\n</tr>\r\n</tbody>\r\n</table>\r\n<div id=\"licensing\"></div>\r\n[/column][gap size=\"8%\"]\r\n\r\n[pricing_table id=\"pricing\" columns=\"3\"][pricing_table_column  featured=\"false\" title=\"ArrayFire Developer\" currency=\"$\" price=\"499 / year\" interval=\"$149 / year (Academic)\"] [icon_list] [icon_list_item type=\"star\" ]Dedicated license [/icon_list_item] [icon_list_item  type=\"times-circle\"] Starts at 2 GPUs or devices [/icon_list_item] [icon_list_item type=\"times-circle\"] Linear algebra [/icon_list_item] [icon_list_item type=\"times-circle\"] Sparse matrices [/icon_list_item][icon_list_item type=\"times-circle\"] Phone support [/icon_list_item][icon_list_item type=\"times-circle\"] Premium support &amp; consulting [/icon_list_item][/icon_list] [button href=\"http://sandbox.arrayfire.com/shop\"] Purchase [/button] [/pricing_table_column] [pricing_table_column featured=\"true\" featured_sub=\"Most Popular\" title=\"ArrayFire Pro\" currency=\"$\" price=\"1,499 / year\" interval=\"$525 / year (Academic)\"] [icon_list] [icon_list_item type=\"star\"] Dedicated license [/icon_list_item] [icon_list_item type=\"star\"] Starts at 2 GPUs or devices [/icon_list_item] [icon_list_item type=\"star\"] Linear algebra [/icon_list_item][icon_list_item type=\"star\"] Sparse matrices [/icon_list_item][icon_list_item type=\"star\"] Phone support [/icon_list_item][icon_list_item type=\"times-circle\"] Premium support &amp; consulting [/icon_list_item] [/icon_list] [button href=\"http://sandbox.arrayfire.com/shop\"]Purchase [/button] [/pricing_table_column] [pricing_table_column featured=\"false\" title=\"ArrayFire Enterprise\" currency=\"$\" price=\"2,999 / year\" interval=\"$1,049 / year (Academic)\"] [icon_list] [icon_list_item type=\"star\"] Dedicated license [/icon_list_item] [icon_list_item type=\"star\"] Starts at 2 GPUs or devices [/icon_list_item] [icon_list_item type=\"star\"] Linear algebra [/icon_list_item][icon_list_item type=\"star\"]Sparse matrices [/icon_list_item][icon_list_item type=\"star\"] Phone support[/icon_list_item][icon_list_item type=\"star\"]Premium support &amp; consulting [/icon_list_item][/icon_list] [button href=\"http://sandbox.arrayfire.com/shop\"] Purchase [/button] [/pricing_table_column] [/pricing_table]\r\n<div id=\"whitepapers\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n\r\n[column type=\"one-half\"][gap size=\"20%\"][image type=\"thumbnail\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/wp2.jpg\"][button href=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/03/arrayfire_matrix_computations_chrzeszczyk.pdf\" shape=\"rounded\" size=\"regular\" block=\"true\"]Download <em>Matrix Computations on the GPU with ArrayFire for C/C++</em>[/button][/column][column type=\"one-half\" last=\"true\"]\r\n\r\n[custom_headline type=\"left\" level=\"h3\" ]Whitepapers[/custom_headline]\r\n\r\n<img alt=\"Whitepaper 1\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/Whitepaper-1.png\" width=\"466\" height=\"374\" />\r\n\r\n&nbsp;\r\n\r\n[/column][gap size=\"10%\"]\r\n\r\n[column type=\"one-half\"]<img alt=\"Whitepaper 2\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/Whitepaper-2.png\" width=\"442\" height=\"304\" />[/column][column type=\"one-half\" last=\"true\"][image type=\"thumbnail\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/wp1.jpg\"][button href=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/03/arrayfire_whitepaper.pdf\" shape=\"rounded\" size=\"regular\"  block=\"true\" float=\"right\"]Download <em>High-level GPU Computing in C, C++, and Fortran</em>[/button][/column]\r\n<div id=\"casestudies\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n\r\n[column type=\"one-half\"][gap size=\"12%\"][custom_headline type=\"left\" level=\"h3\" ]Case Studies[/custom_headline]\r\n\r\nLearn how ArrayFire has worked in real code, including applications in academia, finance, government, life sciences, manufacturing, media, and oil &amp; gas.[/column][column type=\"one-half\" last=\"true\" fade=\"true\" fade_animation=\"in-from right\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/model-A.png\"][/column][custom_headline type=\"left\" level=\"h5\"]Academia [/custom_headline][accordion][accordion_item title=\"<strong>Accelerating LTE Simulation | Tsinghua University</strong>\"]\r\n\r\n<strong>Authors:</strong> Yuan Gao, Yin Sun, Chun Hui Zhou, Xin Su, Xi Bin Xu, Shi Dong Zhou, Tsinghua University\r\n<strong>Speedup:</strong> 3X\r\n\r\nFast simulations are a driving force in several research projects. However, the accompanying long simulation times can tend to be a drag in many of these projects. In this article, we shall bring up the example of the work on 3GPP LTE System Simulation by Yuan Gao et al (from Tsinghua University, Beijing) and demonstrate how the use of ArrayFire software can significantly improve the simulator performance and lead to faster validation times in simulation projects.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>High Performance Compressive Sensing | Rice University</strong>\"]\r\n\r\n<strong>Authors:</strong> Nabor Reyna and Wotao Yin from Rice University\r\n<strong>Speedup:</strong> 5X\r\n\r\nThis work deals with reconstruction of signals using partial Fourier matrices (RecPF). The major computational components of the algorithm involve shrinkage and FFTs. ArrayFire software is employed to accelerate this compute-heavy code.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Power System Simulations | Indian Institute of Technology, Roorkee, India</strong>\"]\r\n<strong>Authors:</strong> Indian Institute of Technology, Roorkee\r\n<strong>Speedup:</strong> 35X\r\n\r\nPower flow studies are one of the most important aspects of power system planning and operation. The power flow reveals the sinusoidal steady state characteristics of the entire system - voltages, real and reactive power generated, and absorbed and line losses- elucidating the voltage magnitudes and angles at each bus, the generation of each generating unit, and real and reactive power losses in the system. All this is necessary to ensure the security, economy, and control of electrical energy distribution. Learn how ArrayFire software can deliver magnitudes of performance improvement over CPU-based solutions.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Antenna Array Simulations | University of Naples Federico II</strong>\"]\r\n\r\n<strong>Authors:</strong> A. Capozzoli, C. Cucio, A. Liseno at University of Naples Federico II\r\n<strong>Speedup:</strong> 24X\r\n\r\nAntenna array design involves repeated simulation to tune the many parameters involved, and waiting around for simulations to finish is no fun. Offloading the optimization problem onto the GPU cuts that time down significantly. In their recent paper, Capozzoli, Curcio, and Liseno of University of Naples Federico II demonstrated how a simple modification to their echo generator array simulation took advantage of the GPU to bring immediate speedups.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Laplace Transform Inversion | Acunum Algorithms and Simulations</strong>\"]\r\n\r\n<strong>Authors:</strong> Patrick Kano and Moysey Brio at Acunum Algorithms and Simulations\r\n<strong>Speedup:</strong> 3.8X\r\n\r\nThe numerical inversion of the Laplace transform is a long standing problem due its implicit ill-posedness. Patrick Kano and Moysey Brio of Acunum Algorithms and Simulations, with their experience in computational methods and algorithm development, found a solution that not only works, but is very fast.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Compressed Sensing for Image Reconstruction | College of Engineering, Roorkee, India</strong>\"]\r\n\r\n<strong>Authors:</strong> Kuldeep Yadav, Ankush Mittal, M. A. Ansar, and Avi Srivastava, College of Engineering, Roorkee, India\r\n<strong>Speedup:</strong> 8X\r\n\r\nCompressed sensing is very critical in the areas of medical image reconstruction, image acquisition or sensor networks. An algorithm for compressed sensing developed using a Basis Pursuit Algorithm shows over 8X speedup when run on an NVIDIA GPU.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Fat/Water Reconstruction for Medical Images | Case Western Reserve University</strong>\"]\r\n\r\n<strong>Authors:</strong> D. H. Johnson, S. Narayan, C. A. Flask, and D. L. Wilson, Case Western Reserve University\r\n<strong>Speedup:</strong> 11.6X\r\n\r\nCase Western Reserve University researchers turned to GPUs running ArrayFire software to develop a fast and robust version of the \"Iterative Decomposition of water and fat with an Echo Asymmetry and Least-squares\" (IDEAL) reconstruction algorithm. This algorithm uses a lot of Image Processing algorithms for reconstruction, and was shown to achieve very high speedups.\r\n[/accordion_item]\r\n\r\n[/accordion]\r\n<h5>Finance</h5>\r\n[accordion][accordion_item title=\"<strong>Option Pricing | Koch Supply and Trading</strong>\"]\r\n\r\n<strong>Authors:</strong> Koch Supply &amp; Trading\r\n<strong>Speedup:</strong> 51.8X\r\n\r\nAndrew Shin, Market Risk Manager of Koch Supply &amp; Trading, achieves significant performance increases on option pricing algorithms using ArrayFire software to accelerate his code with GPUs. Andrew says, \"My buddy and I are, at best, novice programmers and we couldn\'t imagine having to figure out how to code all this in CUDA.\" But he found ArrayFire software to be straight-forward. With these results, he says he can see ArrayFire software and GPUs populating Koch\'s mark-to-futures cube, which contains its assets, simulations, and simulated asset prices.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>GPU Computing in Automated Trader | Automated Trader</strong>\"]\r\n\r\n<strong>Authors:</strong> Automated Trader\r\n<strong>Speedup:</strong> 37.5X\r\n\r\nThe Q1 2012 issue of Automated Trader contains an excellent Mashup piece reviewing software for algorithmic trading. The article provides a wonderful glimpse into the 1-2 month adventure of Andy Webb, Automated Trader.s Founder, and Wrecking Crew building a fast trading platform from several technologies. The full trading platform they built was quite extensive. The part that caught our eye was the core computational component of the pipeline. That component involved permuting 1,000 potential pairs with cointegration tests for 350 time windows on each potential pair.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>GPUs in Quantitative Analytics and Finance | Private Bank</strong>\"]\r\n\r\nThe world of Quantitative finance is all about getting accurate results really, really fast. ArrayFire is working with one of the largest banks in Spain to maximize their output using GPUs. Click the link below for an overview of the uses of GPU computing in finance.[/accordion_item][/accordion]\r\n<h5>Government</h5>\r\n[accordion][accordion_item title=\"<strong>Powering Mars Research | NASA and UAA in Anchorage</strong>\" ]\r\n\r\n<strong>Authors:</strong> NASA and UAA in Anchorage\r\n<strong>Speedup:</strong> 5X\r\n\r\nThe main thrust of this research is improving mars rover image compression via GPUs and genetic algorithms. With ArrayFire software and GPUs, the researchers were able to achieve 5X speedups on the larger data sizes. The algorithm works by pairing neighboring pixels with a random one and then adjusting the random pixel based on whether it incrementally improves the original image. Babb described the algorithm as an embarrassingly parallel process, ideally suited to GPU acceleration. He estimates he has been able to achieve a 20 to 30 percent error reduction in subjects like fingerprints and satellite imagery.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Radar Image Formation | System Planning Corporation</strong>\"]\r\n\r\n<strong>Authors:</strong> Gary Rubin and Earl Sager - System Planning Corporation\r\n<strong>Speedup:</strong> ~45X\r\n\r\nRadar imaging is computationally intensive. As a result, many imaging algorithms apply FFT-based approximations. While efficient, these algorithms sacrifice data fidelity for speed. Other algorithms better preserve information, but are often too slow for many applications. At System Planning Corporation (SPC) , we have implemented a SAR/ISAR imaging routine based on the Backprojection algorithm. Using ArrayFire software, we have demonstrated speedups of roughly 45x for large datasets.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Radar Clutter Reduction | System Planning Corporation</strong>\"]\r\n\r\n<strong>Authors:</strong> David Berger and Gary Rubin - System Planning Corporation\r\n<strong>Speedup:</strong> 5-10X\r\n\r\nSystem Planning Corporation (SPC) uses ArrayFire software to accelerate radar processing algorithms. The system processes raw data from marine navigation radars using a variety of thresholding techniques to extract real targets from clutter. This involves highly data-parallel processing in which each radar pulse is subjected to the same computations; very few operations occur across multiple pulses. Using ArrayFire software, SPC has achieved 10x speed improvements relative to a Core i7-920 CPU and 5x improvements relative to a realtime DSP implementation.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Novel Algorithms for Linear Algebra | SAIC</strong>\" ]\r\n\r\n<strong>Authors:</strong> Nolan Davis and Daniel Redig, SAIC\r\n<strong>Speedup:</strong> 3.5X\r\n\r\nNolan Davis and Daniel Redig at SAIC recently presented work on Hybrid GPU/Multicore Solutions for Large Linear Algebra Problems where they developed a novel algorithm for LU decomposition, one of the most important routines in linear algebra. They presented a Hybrid CPU/GPU computing approach, where problems too large to fit in GPU memory can also be solved faster than using only the CPU.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Geolocation | BAE Systems</strong>\"]\r\n\r\n<strong>Authors:</strong> BAE Systems\r\n<strong>Speedup:</strong> 17X\r\n\r\nGeolocation is the identification of the real-world geographic location of a target of interest. In this application, the system receives the signal with an array of several antennas and computes the direction of arrival of the radio energy by measuring the time difference of arrival (or the phase difference) at the different antennas.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Tsunami Modeling | University of Minnesota, Boise State, Saint Scholastica, and NCAR</strong>\"]\r\n\r\n<strong>Authors:</strong> University of Minnesota, Boise State, Saint Scholastica, and NCAR\r\n<strong>Speedup:</strong> 3-5X\r\n\r\nNatural catastrophic disasters like tsunamis commonly strike with little warning. For most people, tsunamis are underrated as major hazards. People sometimes wrongly believe that they occur infrequently and only along distant coasts. Tsunamis are usually caused by earthquakes. Seismic signals can give some margin of warning since the speed of tsunami waves travels at 1/30 the speed of seismic waves. Still there is little time between the creation of the tsunami and its impact making fast processing critical to producing effective warning systems. ArrayFire software was used to run an RBF simulation on the GPU with a time to solution not available by other alternatives.\r\n[/accordion_item][/accordion]\r\n<h5>Life Sciences</h5>\r\n[accordion][accordion_item title=\"<strong>Parallelized Gene Predictors | University of Quebec</strong>\" ]\r\n\r\n<strong>Authors:</strong> University of Quebec\r\n<strong>Speedup:</strong> 43X\r\n\r\nComputerized approaches to studying the human genome are challenged by the exploding amount of data, which doubles roughly every 6 months. In order to deal with this burgeoning datasets, demands for faster processing power continue to arise. This work focuses on predicting genes using frequency analysis with FFTs and with an equivalent technique known as Goertzel\'s algorithm. In these applications, the emphasis of this paper is to propose tools to geneticists and molecular biologists for the prediction or identification of new genes using existing complementary strategies. The criteria for these tools are speed, reliability, accuracy and ease of use, thus requiring little training.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Pathology Advances with GPUs | Northeastern University</strong>\" ]\r\n\r\n<strong>Authors:</strong> Laboratory for Spectral Diagnosis at Northeastern University\r\n<strong>Speedup:</strong> 100X+\r\n\r\nOne element of the hyperspectral image analysis workflow that requires more than a traditional desktop workstation or personal computer is Hierarchical Cluster analysis (HCA). HCA requires a large amount of data space and substantial computation time (~11 hours) for typical datasets using a single processor personal computer. Rather than following the traditional approach of moving to a lower level programming language like C or C++ and complex parallel programming paradigms such as OpenMP or the Massage Passing Interface (MPI), the lab utilized graphics processing units, or GPUs, and the ArrayFire software platform. The solution allowed the lab to dramatically increase the performance of the analysis while substantially decreasing the amount of calendar time to reach the desired results.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Hepatitis C Virus - Mutation Modeling | Centers for Disease Control and Prevention</strong>\" ]\r\n\r\n<strong>Authors:</strong> CDC Research and Development Team\r\n<strong>Speedup:</strong> ~20X\r\n\r\nThis case study provides a look at biological research regarding coordinated mutations of the Hepatitis C Virus (HCV). ArrayFire provided collaborative R&amp;D resources and greatly improved the speed of this HCV research with the use of parallelization, reducing the computing time from 40 days to less than 1 day. Most importantly, the conclusion of the case study illustrates the the relative price-performance of personal supercomputers that leverage GPUs and ArrayFire software provides a compelling solution versus other architectures and approaches.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Accelerating the SPM Package for Neuroimaging | Georgia Institute of Technology</strong>\" ]\r\n\r\n<strong>Authors:</strong> Georgia Institute of Technology\r\n<strong>Speedup:</strong> 3.5X\r\n\r\nThe Georgia Tech team explores the value of ArrayFire software and GPUs for fMRI workflows within the popular SPM - Statistical Parametric Mapping software widely used in neuroscience research.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Medical Image Compression | Indian Institute of Technology, Roorkee, India</strong>\" ]\r\n\r\n<strong>Authors:</strong> Jaideep Singh, Ipseeta Aruni, R. Balasubramanian - IIT - Roorkee, India\r\n<strong>Speedup:</strong> 38X\r\n\r\nThis study presents the acceleration of Haar wavelet-based image compression algorithm for medical imaging on the Graphics Processing Unit (GPU) using ArrayFire software. Due to bandwidth and image size constraints of medical imaging systems, image compression plays a vital role in reducing the bit rate of transmission or storage. Wavelet-based image compression provides the most promising approach for high quality image compression.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Brain Displacement | Spencer Technologies</strong>\"]\r\n\r\n<strong>Authors:</strong> Spencer Technologies\r\n<strong>Speedup:</strong> 12X\r\n\r\nSpencer describes how ArrayFire software facilitates the development of fast algorithms enabling observation of brain displacement across depth with sampling density that far surpasses previous benchmarks.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Multidimensional Scaling for Genomics | Leibniz Institute of Plant Genetics and Crop Plant Research</strong>\" ]\r\n\r\n<strong>Authors:</strong> Leibniz Institute of Plant Genetics and Crop Plant Research\r\n<strong>Speedup:</strong> 20-35X\r\n\r\nMultidimensional scaling (MDS) is a general computing technique to turn a distance matrix into a set of reconstructed points with pair-wise relationships approximating the original distances by points located in a usually low-dimensional space. ArrayFire software is used to enhance execution of the HiT-MDS procedure and delivers considerable performance improvement.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Drug Delivery Model | Georgia Institute of Technology</strong>\"]\r\n\r\n<strong>Authors:</strong> Georgia Institute of Technology\r\n<strong>Speedup:</strong> 70X\r\n\r\nIn this work, the researchers simulate the delivery of a novel nanoparticle chemotherapy drug to cancerous tissue. Simulation allows scientists to predict experimental outcomes and thus reduce the cost of development and time to clinical relevance. The simulation model includes blood vessels, tumor cells, and healthy cells and an engine to calculate the spatial distributions of both drug and oxygen. ArrayFire software is used to speed up the diffusion calculations for the drug and oxygen within the tissue.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Biomedical Infrared Spectroscopy | University of Manchester and Nofima Mat, Norway</strong>\" ]\r\n\r\n<strong>Authors:</strong> University of Manchester and Nofima Mat, Norway\r\n<strong>Speedup:</strong> Hours of runtime reduction\r\n\r\nThe authors present an iterative algorithm that applies full Mie scattering theory and avoids noise accumulation in their iterative algorithm by integrating a curve-fitting step. ArrayFire software along with NVIDIA GPUs are leveraged to reduce the time added by the curve-fitting step.\r\n[/accordion_item][/accordion]\r\n<h5>Manufacturing</h5>\r\n[accordion][accordion_item title=\"<strong>Feature Learning on Images | Stanford</strong>\" ]\r\n\r\n<strong>Authors:</strong> Andrew Ng, Stanford University\r\n<strong>Speedup:</strong> Ability to process many images in parallel\r\n\r\nStanford researchers in Andrew Ng\'s group used GPUs and ArrayFire software to speed up their work on Feature Learning Architectures. They decided to use ArrayFire software for this study because of the need to quickly evaluate many architectures on thousands of images. ArrayFire software taps into the immense computing power of GPUs and speeds up research utilizing many images.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Tomography of Vegetation - Filtered Back-Projection and Non-Uniform FFTs | Universita di Napoli Federico II</strong>\" ]\r\n\r\n<strong>Authors:</strong> Drs. Capozzoli, Curcio, di Vico, and Liseno, Universita di Napoli Federico II\r\n<strong>Speedup:</strong> 10X\r\n\r\nIn order to investigate changes of forest biomass, scientists use microwave tomography to image the vegetation. At the smallest scale, individual plants can be imaged to investigate branching and growth, but even synthetic aperture radar can reveal large-scale changes in regional ecology. To the right, you can see the experimental setup to image an individual plant.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Action Recognition with Independent Subspace Analysis | Stanford University</strong>\" ]\r\n\r\n<strong>Authors:</strong> Quoc Le, Will Zou, Serena Yeung, Andrew Ng, Stanford University\r\n<strong>Speedup:</strong> 4.4X\r\n\r\nIn a paper at this year\'s CVPR 2011, entitled \"Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis\", the authors explain how their unsupervised feature learning algorithm competes with other algorithms that are hand crafted or use learned features. For their training purposes, they used a multi-layered stacked convolutional ISA (Independent subspace analysis) network. An ISA is used for learning features from image patches without supervision.\r\n[/accordion_item][/accordion]\r\n<h5>Media and Computer Vision</h5>\r\n[accordion][accordion_item title=\"<strong>Fast Computer Vision with OpenCV and ArrayFire | OpenCV Blogger</strong>\" ]\r\n\r\n<strong>Authors:</strong> OpenCV Blogger\r\n<strong>Speedup:</strong> ~10X\r\n\r\nThe OpenCV library is the defacto standard for doing computer vision and image processing research projects. OpenCV includes several hundreds of computer vision algorithms, aimed for use in realtime vision applications. This case study shows how to use both libraries together. There is a simple example application that demonstrates using OpenCV for webcam access and ArrayFire for some basic processing routines and displaying results.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Video Processing | Google</strong>\" ]\r\n\r\n<strong>Authors:</strong> Google and Stanford\r\n<strong>Speedup:</strong> 10-20X\r\n\r\nVideo content analysis is the basis for categorizing videos and enabling search by content. Growing interest in using sparse-coding methods to extract motion features in video in support of video content analysis led to the application of ArrayFire software to improve performance by substantially accelerating the solution of the L1-regularized least-squares optimization problem.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Action Recognition with Independent Subspace Analysis | Stanford University</strong>\"]\r\n\r\n<strong>Authors:</strong> Quoc Le, Will Zou, Serena Yeung, Andrew Ng, Stanford University\r\n<strong>Speedup:</strong> 4.4X\r\n\r\nIn a paper at this year\'s CVPR 2011, entitled \"Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis\", the authors explain how their unsupervised feature learning algorithm competes with other algorithms that are hand crafted or use learned features. For their training purposes, they used a multi-layered stacked convolutional ISA (Independent subspace analysis) network. An ISA is used for learning features from image patches without supervision.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Music Beat Analysis | Georgia Tech</strong>\"]\r\n\r\n<strong>Authors:</strong> Vidhur Vohra - Georgia Tech\r\n<strong>Speedup:</strong> 15X\r\n\r\nDid you ever wonder how the music visualizer in your media player works? Watching it pulsate in synchrony with the beats of the song is almost as entertaining as listening to the song itself! Researchers have been attempting to detect beats in audio signals for many years, and there are many techniques available, from the simplest (and least accurate) to more complicated algorithms that are highly accurate. All algorithms, though, perform some form of signal processing and frequency analysis, applications highly suited to GPU Computing.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Optimization Methods for Deep Learning | Stanford Artificial Intelligence Laboratory</strong>\" ]\r\n\r\n<strong>Authors:</strong> Stanford Artificial Intelligence Laboratory\r\n<strong>Speedup:</strong> Improved accuracy\r\n\r\nResearchers at SAIL (Stanford Artificial Intelligence Laboratory), have done it again. They have successfully used ArrayFire software to speed up the training part of Deep Learning algorithms. In their paper titled .On Optimization Methods for Deep Learning., they experiment with some of the well known training algorithms and demostrate their scalability across parallel architectures (GPUs as well as multi-machine networks). The algorithms include SGDs (Stochastic Gradient Descent) L-BFGS (Limited BFGS used for solving non-linear problems), CG (Conjugate Gradient).\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Feature Learning on Images | Stanford University</strong>\" ]\r\n\r\n<strong>Authors:</strong> Andrew Ng, Stanford University\r\n<strong>Speedup:</strong> Ability to process many images in parallel\r\n\r\nStanford researchers in Andrew Ng’s group used ArrayFire software to speed up their work on Feature Learning Architectures. They decided to use ArrayFire software for this study because of the need to quickly evaluate many architectures on thousands of images. ArrayFire software taps into the immense computing power of GPUs and speeds up research utilizing many images.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Digital Holography for Imaging | National University of Ireland, Maynooth</strong>\" ]\r\n\r\n<strong>Authors:</strong> Nitesh Pandey, Damien Kelly, Bryan Hennelly and Thomas Naughton from the National University of Ireland, Maynooth\r\n<strong>Speedup:</strong> 17X\r\n\r\nDigital holography is a powerful imaging technique with many new applications like true 3D display. It allows the capture of both amplitude and phase information of the light reflected off the surface of 3D objects. Researchers at the National University of Ireland, Maynooth are developing techniques based on digital holography for 3D display applications.\r\nReconstruction of large digital holograms can be computationally intensive to generate on CPUs, but GPUs running ArrayFire software offer amazing possibilities.\r\n[/accordion_item][/accordion]\r\n<h5>Oil and Gas</h5>\r\n[accordion][accordion_item title=\"<strong>3D Mantle Convection - Geodynamics | Boise State, University of Colorado, University of Minnesota</strong>\" ]\r\n\r\n<strong>Authors:</strong> Boise State, University of Colorado, University of Minnesota\r\n<strong>Speedup:</strong> 2.5-4.5X\r\n\r\nThe authors introduce a GPU implementation of a three-dimensional mantle convection modeling at a high Rayleigh number to the solid earth geophysics community. They outline code development time, compare performance of CPUs versus GPUs, and deliver powerful visualizations.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Ground Water Simulations | Louisiana State University</strong>\" ]\r\n\r\n<strong>Authors:</strong> Kevin R. Tubbs and Frank T-C. Tsai at Louisiana State University\r\n<strong>Speedup:</strong> &gt;20X\r\n\r\nA lattice Boltzmann method for solving the shallow water equations and the advection-dispersion equation is developed and implemented on graphics processing unit (GPU)-based architectures. The proposed LBM is implemented to an NVIDIA Computing Processor in a single GPU workstation. GPU computing is performed using ArrayFire software. Mass transport with velocity-dependent dispersion in shallow water flow is simulated by combining the MRT-LBM model and the TRT-LBM model. The GPU parallel performance increases as the grid size increases. The results indicate the promise of the GPU-accelerated LBM for modeling mass transport phenomena in shallow water flows.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Shallow Water Fluid Flow | Louisiana State University</strong>\" ]\r\n\r\n<strong>Authors:</strong> Louisiana State University\r\n<strong>Speedup:</strong> &gt;10X\r\n\r\nA lattice Boltzmann method (LBM) on high performance computing (HPC) environments for three-dimensional shallow water flow fields coupled to mass transport is developed. LBM is an attractive method for solving the multilayered shallow water equations because the extension to multilayer is straight forward with all of the simplicities and advantages of the LBM in mass transport in shallow water flows and the LBM performance on central processing unit (CPU)-based and graphics processing unit (GPU)-based HPC environments.\r\n[/accordion_item][/accordion]\r\n<div id=\"consulting\"></div>\r\n[/content_band]\r\n<div id=\"services\"></div>\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"][column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"]Hire our acceleration gang[/custom_headline]\r\n\r\nHire us to accelerate your code. Or to train your pros. Or even to write new code for your organization!\r\n\r\nWe’ve already helped thousands of organizations speedup their code. We’ve accelerated algorithms, data sets, and challenging problems of all types in the past, and we’re confident that we can accelerate your code too.\r\n\r\n[gap size=\"10%\"][button  type=\"flat\" shape=\"rounded\" href=\"http://meetme.so/arrayfire\" size=\"x-large\" ]Schedule a consultation[/button][/column][column type=\"one-half\" last=\"true\" class=\"center-text\"][gap size=\"5%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Bat-signal-e1391790016951.png\"][/column] [gap size=\"7%\"]\r\n\r\n[column type=\"one-third\" class=\"center-text\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/04/LFG-B-HORZ_202_K-e1396448935778.jpg\"][line]Lincoln Financial Group ported their CPU code (C/C++) to CUDA, and this enabled them to speed up the necessary financial calculations. Their primary objective was to reduce the time taken to run this code. Before porting to CUDA, they required 10-12 hours to run the entire code. After porting to CUDA, they were able to do the same work in about 30 minutes.[/column][column type=\"one-third\" class=\"center-text\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/reveal_logo-e1396449044651.jpg\"][line]Reveal Imaging, an SAIC company, uses ArrayFire in developing threat-detection products for transportation systems—such as cargo and baggage screening in airports—and in securing facilities and public events.[/column][column type=\"one-third\" last=\"true\" class=\"center-text\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/04/1800contactlogo.png\"][line]The Glasses.com app relies on computer vision to recognize the features of a user’s face. The application then generates an accurate, high-fidelity, three-dimensional model of that face, and virtually places selected frames on the image.[/column]\r\n<div id=\"starterpackage\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n\r\n[column type=\"one-half\" last=\"false\" fade=\"true\" fade_animation=\"in-from-left\" ][gap size=\"10%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/comingatyou.png\"][/column][column type=\"one-half\" last=\"true\"] [custom_headline type=\"left\" level=\"h3\"]Starter Package ($500)* [/custom_headline] Hire us for 1-day. We set you up with one engineer dedicated for a full day, as well as support from senior and test engineers throughout the day. Here\'s how it works:\r\n\r\n[icon_list] [icon_list_item type=\"angle-double-right\"]Initial phone call[/icon_list_item] [icon_list_item type=\"angle-double-right\"]You send us your code or algorithm [/icon_list_item] [icon_list_item type=\"angle-double-right\"]We analyze your code for potential GPU benefit[/icon_list_item][icon_list_item type=\"angle-double-right\"]We accelerate as much of the code as is possible within the 1-day effort, applying our extensive GPU software libraries[/icon_list_item][icon_list_item type=\"angle-double-right\"]We produce a final report, along with code[/icon_list_item] [/icon_list] The final report outlines the best approach to follow for full GPU-acceleration of your code.\r\n\r\n&nbsp;\r\n\r\n[button type=\"flat\" shape=\"rounded\" size=\"regular\" href=\"http://sandbox.arrayfire.com/product/consulting-starter-package/\" title=\"Starter Package\"]Buy the Starter Package[/button]\r\n\r\n&nbsp;\r\n\r\n*Limit one (1) per customer.\r\n\r\n[/column]\r\n<div id=\"customcode\"></div>\r\n[/content_band] [content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n\r\n[column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\" ]Coding Work (Custom)[/custom_headline]\r\n\r\n[custom_headline type=\"left\" level=\"h6\" ]Why Choose Us?[/custom_headline] [icon_list] [icon_list_item type=\"angle-double-right\"]Deep experience, already servicing thousands of customers[/icon_list_item] [icon_list_item type=\"angle-double-right\"]Quality work, with leading GPU software [/icon_list_item] [icon_list_item type=\"angle-double-right\"]Efficient delivery, with ArrayFire\'s code base we can deliver results fast[/icon_list_item][icon_list_item type=\"angle-double-right\"]Proven, we make customers happy through faster code[/icon_list_item][/icon_list] [custom_headline type=\"left\" level=\"h6\" ]Our Strengths[/custom_headline] [icon_list] [icon_list_item type=\"angle-double-right\"]Excellence in GPU code[/icon_list_item] [icon_list_item type=\"angle-double-right\"]Well-written, efficient C, C++, Fortran, Java, or .NET [/icon_list_item] [icon_list_item type=\"angle-double-right\"]Application porting and integration[/icon_list_item][icon_list_item type=\"angle-double-right\"]Tuning software to peak hardware performance[/icon_list_item][icon_list_item type=\"angle-double-right\"]Scalability of algorithms to handle enterprise-level programs[/icon_list_item] [/icon_list][button type=\"flat\" shape=\"rounded\" size=\"regular\" href=\"http://meetme.so/arrayfire\" title=\"Tech Consultation\"]Schedule a consultation[/button] [/column][column type=\"one-half\"  fade=\"true\" fade_animation=\"in-from-right\" last=\"true\" ][gap size=\"25%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/Holoham.png\"][/column]\r\n<div id=\"training\"></div>\r\n[/content_band] [content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n\r\n[column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\" ]Training[/custom_headline] Attendees will receive the latest industry knowledge and techniques for GPU computing in CUDA and OpenCL.\r\n\r\nArrayFire offers up to four days of specialized GPU training in CUDA and OpenCL programming. Register for a general course, or schedule a course dedicated for your organization. We can travel to you, or you can travel to our Atlanta office.\r\n\r\nWe recommend that attendees have a working knowledge of C/C++ in order to gain the most from the training courses.\r\n\r\n[/column]\r\n\r\n[column type=\"one-half\" last=\"true\"][gap size=\"8%\"]\r\n<h5><strong>Fee includes:</strong></h5>\r\n[icon_list] [icon_list_item type=\"angle-double-right\"]Instruction by an excellent and interesting expert, with hands-on exercises[/icon_list_item] [icon_list_item type=\"angle-double-right\"]Use of a laptop with CUDA and OpenCL capable GPUs and CPUs [/icon_list_item] [icon_list_item type=\"angle-double-right\"]Choice of Linux or Windows operating system[/icon_list_item][icon_list_item type=\"angle-double-right\"]Printed manual of lecture material[/icon_list_item][icon_list_item type=\"angle-double-right\"]Electronic copy of programming exercises[/icon_list_item][/icon_list]\r\n\r\n[button type=\"flat\" shape=\"rounded\" size=\"regular\" href=\"http://sandbox.arrayfire.com/product-category/training/\" title=\"Register\"]Register for Training[/button][/column]\r\n\r\n[column type=\"one-half\" fade=\"true\" fade_animation=\"in-from-left\" class=\"center-text\" ][gap size=\"30%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/Professor-AF_Exported-e1395436350363.png\" ][/column][column type=\"one-half\" last=\"true\"][gap size=\"20%\"][custom_headline type=\"left\" level=\"h3\" looks_like=\"h3\"]Upcoming Courses[/custom_headline]\r\n<table>\r\n<tbody>\r\n<tr>\r\n<th>CUDA</th>\r\n<th>OpenCL</th>\r\n</tr>\r\n<tr>\r\n<td> Atlanta, GA</td>\r\n<td> Atlanta, GA</td>\r\n</tr>\r\n<tr>\r\n<td> Boston, MA</td>\r\n<td> Boston, MA</td>\r\n</tr>\r\n<tr>\r\n<td> New York City, NY</td>\r\n<td> New York City, NY</td>\r\n</tr>\r\n<tr>\r\n<td> Houston, TX</td>\r\n<td> Houston, TX</td>\r\n</tr>\r\n<tr>\r\n<td> San Jose, CA</td>\r\n<td> San Jose, CA</td>\r\n</tr>\r\n<tr>\r\n<td> Albuquerque, NM</td>\r\n<td> Albuquerque, NM</td>\r\n</tr>\r\n<tr>\r\n<td> Baltimore/Washington DC</td>\r\n<td> Baltimore/Washington DC</td>\r\n</tr>\r\n<tr>\r\n<td> San Diego, CA</td>\r\n<td> San Diego, CA</td>\r\n</tr>\r\n</tbody>\r\n</table>\r\n[/column][gap size=\"10%\"]\r\n\r\n[custom_headline type=\"left\" level=\"h3\"]Training Course Syllabus[/custom_headline] [column type=\"one-half\"] [custom_headline type=\"left\" level=\"h5\"  accent=\"false\"]Day 1, Introduction[/custom_headline] <strong>Lectures:</strong>\r\nGPU Computing Overview\r\nThe Programming Model\r\nBasic Dataset Mapping Techniques\r\nLibraries, ArrayFire\r\nProfiling Tools\r\n\r\n<strong>Practice:</strong>\r\nA Simple Kernel\r\nEquivalent ArrayFire Example\r\nUsing Libraries\r\nMonte Carlo Pi Estimation\r\nTiming and ArrayFire\r\nDebugging Code\r\n\r\n[custom_headline type=\"left\" level=\"h5\" accent=\"false\"]Day 3, Multi-GPU[/custom_headline] <strong>Lectures:</strong>\r\nMulti-GPU Use Cases\r\nMulti-GPUs: Contexts\r\nExisting Libraries\r\nScaling Across Multiple GPUs\r\n\r\n<strong>Practice:</strong>\r\nOut of Core Problems: Matrix Multiply\r\nTask Level Parallelism: Optimization\r\nArrayFire Multi-GPU[/column]\r\n\r\n[column type=\"one-half\" last=\"true\"] [custom_headline type=\"left\" level=\"h5\" accent=\"false\"]Day 2, Optimization[/custom_headline] <strong>Lectures:</strong>\r\nArchitecture: Grids, Blocks, and Threads\r\nMemory Model: Global, Shared, and Constant Memory\r\nAdvanced Mapping Techniques\r\nStreams: Asynchronos Launches and Concurrent Execution\r\nArrayFire: Lazy Evaluation and Code Vectorization\r\n\r\n<strong>Practice:</strong>\r\nMatrix Transpose\r\nOptimization Using Shared Memory\r\nMedian Filter\r\nOptimization Using Constant Memory\r\nStream Example\r\nArrayFire Example: Nearest Neighbor Algorithm\r\n\r\n[custom_headline type=\"left\" level=\"h5\" accent=\"false\"]Day 4, Algorithm Problems[/custom_headline]\r\n\r\n<strong>Lectures and Practice:</strong>\r\nReductions\r\nScan Algorithms\r\nSort\r\nConvolution\r\nCustomer-Specific Problem [/column][/content_band]','Home','','inherit','open','closed','','245-revision-v1','','','2014-04-07 15:02:37','2014-04-07 15:02:37','',245,'http://sandbox.arrayfire.com/245-revision-v1/',0,'revision','',0),(5412,7,'2014-04-07 15:28:05','2014-04-07 15:28:05','','Products','','publish','open','closed','','products','','','2014-04-07 15:28:05','2014-04-07 15:28:05','',0,'http://sandbox.arrayfire.com/?p=5412',1,'nav_menu_item','',0),(5413,7,'2014-04-07 15:28:05','2014-04-07 15:28:05','','Services','','publish','open','closed','','services','','','2014-04-07 15:28:05','2014-04-07 15:28:05','',0,'http://sandbox.arrayfire.com/?p=5413',2,'nav_menu_item','',0),(5415,7,'2014-04-07 15:42:35','2014-04-07 15:42:35','','Products','','publish','open','closed','','products-3','','','2014-04-07 21:14:48','2014-04-07 21:14:48','',0,'http://sandbox.arrayfire.com/?p=5415',1,'nav_menu_item','',0),(5417,1,'2014-04-08 17:33:55','2014-04-08 17:33:55','[theme-my-login]','Logout','','inherit','open','closed','','12-revision-v1','','','2014-04-08 17:33:55','2014-04-08 17:33:55','',12,'http://sandbox.arrayfire.com/12-revision-v1/',0,'revision','',0),(5418,1,'2014-04-08 17:37:34','2014-04-08 17:37:34','<script type=\"text/javascript\">// <![CDATA[\nwindow.location=\"http://www.sandbox.arrayfire.com/my-account/customer-logout\";\n// ]]></script>','Logout','','inherit','open','closed','','12-autosave-v1','','','2014-04-08 17:37:34','2014-04-08 17:37:34','',12,'http://sandbox.arrayfire.com/12-autosave-v1/',0,'revision','',0),(5419,1,'2014-04-08 17:36:32','2014-04-08 17:36:32','<script type=\"text/javascript\">\r\n<!--\r\nwindow.location=\"http://www.sandbox.arrayfire.com/my-account/customer-logout\";\r\n//--></script>','Logout','','inherit','open','closed','','12-revision-v1','','','2014-04-08 17:36:32','2014-04-08 17:36:32','',12,'http://sandbox.arrayfire.com/12-revision-v1/',0,'revision','',0),(5420,1,'2014-04-08 17:37:39','2014-04-08 17:37:39','Logging you out...\r\n\r\n<script type=\"text/javascript\">// <![CDATA[\r\nwindow.location=\"http://www.sandbox.arrayfire.com/my-account/customer-logout\";\r\n// ]]></script>','Logout','','inherit','open','closed','','12-revision-v1','','','2014-04-08 17:37:39','2014-04-08 17:37:39','',12,'http://sandbox.arrayfire.com/12-revision-v1/',0,'revision','',0),(5421,7,'2014-04-09 20:46:57','2014-04-09 20:46:57','','53863A_AMD_E_Wh_RGB','','inherit','open','closed','','53863a_amd_e_wh_rgb','','','2014-04-09 20:46:57','2014-04-09 20:46:57','',187,'http://sandbox.arrayfire.com/wp-content/uploads/2014/01/53863A_AMD_E_Wh_RGB.png',0,'attachment','image/png',0),(5422,7,'2014-04-09 20:47:08','2014-04-09 20:47:08','','53863A_AMD_E_Blk_RGB','','inherit','open','closed','','53863a_amd_e_blk_rgb','','','2014-04-09 20:47:08','2014-04-09 20:47:08','',187,'http://sandbox.arrayfire.com/wp-content/uploads/2014/01/53863A_AMD_E_Blk_RGB.jpg',0,'attachment','image/jpeg',0),(5423,7,'2014-04-09 20:48:45','2014-04-09 20:48:45','[content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\"][column type=\"one-half\"]\r\n\r\n[custom_headline type=\"left\" level=\"h3\"]Partner Program[/custom_headline]\r\n\r\nThe Partner Program is designed to promote the development and sale of products and services to maximize the productivity of scientists, analysts, and engineers working on technical computing problems that can leverage GPU technology. As our Partner, you benefit from a tight working relationship with ArrayFire staff and our other partners, while your customers benefit from the integration of your products and solutions with ArrayFire.\r\n\r\nThe ArrayFire Partner Program is built upon the belief that the purpose of a viable partnership includes a market opportunity, a joint product or service which matches that opportunity, and a strategy to market, sell, and support the joint offering. Therefore, ArrayFire includes programs and activities centered around technical and go-to-market resources that allow the partnership to work hand in hand to develop the solution and properly communicate the solution value into the market while providing the highest level of customer satisfaction.[/column][column type=\"one-half\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\"][gap size=\"20%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/car.png\"][/column][/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"bottom\" padding_top=\"40px\" padding_bottom=\"40px\"][column type=\"two-fifths\" fade=\"true\" fade_animation=\"in-from left\"][gap size=\"20%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/hq-vehicles.png\"][/column][column type=\"three-fifths\" last=\"true\"]\r\n\r\n[custom_headline type=\"left\" level=\"h3\"]Partner Categories[/custom_headline]\r\n\r\nArrayFire resources dedicated to our partner program fall into two broad categories:\r\n\r\n[icon_list] [icon_list_item type=\"angle-double-right\"]<strong>Technical</strong>\r\nDistribution and Integration partners have access to development and evaluation licenses to accomplish business objectives. Porting and optimization support resources are available to maximize value to customers and revenue to both parties. Engineering resources are made available to ensure ArrayFire meets and exceeds partner and customer goals. On-going support resources are available to support integration partners in delivering solutions to the market and to customers of distribution partners as contracted by those customers.[/icon_list_item] [icon_list_item type=\"angle-double-right\"]<strong>Go-to-Market</strong>\r\nAll ArrayFire partners have access to a broad array of Go-to-Market resources, including but not limited to: go-to-market campaigns, sales and marketing training, collateral, press, trade show participation, lead generation, partner portal access, partner relationship Management system access, joint selling, and more. In addition to technical and go-to-market resources, ArrayFire provides competitive margins to our distribution and integration partners based on market reach, vertical focus, volume of ArrayFire product distributed on an annual basis, and overall commitment to ArrayFire and the company\'s product.[/icon_list_item] [/icon_list][/column]\r\n\r\n[/content_band][content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n\r\n[custom_headline type=\"center\" level=\"h3\" ]Current Partners[/custom_headline]\r\n\r\n&nbsp;\r\n\r\n[tab_nav type=\"three-up\"] [tab_nav_item title=\"Hardware Partners\" active=\"true\"] [tab_nav_item title=\"OEM Partners\"][tab_nav_item title=\"VAR Partners\"] [/tab_nav] [tabs] [tab active=\"true\"]\r\n<p style=\"text-align: left;\">[column type=\"one-fifth\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/53863A_AMD_E_Blk_RGB.jpg\" alt=\"Alt Text\" type=\"rounded\"][/column][column type=\"four-fifths\" last=\"true\"]<a href=\"http://developer.amd.com/\">AMD</a> makes OpenCL-capable devices. It serves the high performance computing market with its Opteron™ CPUs &amp; APUs as well as its Radeon™ FirePro™ GPUs.[/column]</p>\r\n[column type=\"one-fifth\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/em-photonics-logo-small34.png\" alt=\"Alt Text\" type=\"rounded\"][/column][column type=\"four-fifths\" last=\"true\"]<a href=\"http://www.culatools.com/\">EM Photonics</a> develops CULA, a LAPACK libraries for NVIDIA CUDA-capable GPUs. ArrayFire (the CUDA version) includes CULA technology as part of some linear algebra functions.[/column]\r\n\r\n[column type=\"one-fifth\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Intel_Logo_Capture.png\" alt=\"Alt Text\" type=\"rounded\"][/column][column type=\"four-fifths\" last=\"true\"]<a href=\"http://www.intel.com/content/www/us/en/high-performance-computing/high-performance-xeon-phi-coprocessor-brief.html\">Intel</a> makes OpenCL-capable devices. It serves the high performance computing market with its Intel® Xeon™ CPUs (and integrated GPUs) and Intel® Xeon Phi™ coprocessor.[/column]\r\n\r\n[column type=\"one-fifth\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/nvidia-horizontal.png\" alt=\"Alt Text\" type=\"rounded\"][/column][column type=\"four-fifths\" last=\"true\"]<a href=\"http://www.nvidia.com/object/cuda_home.html\">NVIDIA</a> makes CUDA-capable GPUs. It serves the high performance computing market with its Tesla™ GPUs.[/column]\r\n\r\n[/tab] [tab]\r\n\r\nOEM Partners represent ArrayFire on a global basis. Our OEM partners package and bundle ArrayFire with state of the art hardware systems that consist of single GPU systems to large scale GPU clusters.\r\n\r\n[column type=\"one-fifth\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/ColfaxLogo-w150.gif\" alt=\"Alt Text\" type=\"rounded\"][/column][column type=\"four-fifths\" last=\"true\"]<a href=\"http://www.colfax-intl.com/ms_tesla.asp?M=1\" target=\"_blank\">Colfax</a> - Buy it from a trusted expert. Colfax provides the most comprehensive range of innovative, cutting-edge and highly customized GPU solutions. Colfax has been first-to-market with a 4GPU PSC and the revolutionary CXT8000 - the world\'s first 8GPU server. Leading universities, labs and companies are accelerating their research and business outcomes with optimally configured, ready-to-go Colfax GPU solutions.[/column]\r\n\r\n[column type=\"one-fifth\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/microway-logo.png\" alt=\"Alt Text\" type=\"rounded\"][/column][column type=\"four-fifths\" last=\"true\"]<a href=\"http://www.microway.com/accelereyes\" target=\"_blank\">Microway</a> - an NVIDIA Tesla Preferred Provider. Different GPU applications require specific hardware configurations. Microway supports them all. Widely credited with introducing numeric coprocessors to the general market, Microway became the primary source and recognized industry leader for numeric coprocessors and supporting software. Today Microway\'s reputation is based on excellence in designing and manufacturing high density Linux and UNIX workstations and clusters.[/column]\r\n\r\n[column type=\"one-fifth\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/silicon_mechanics_logo.gif\" alt=\"Alt Text\" type=\"rounded\"][/column][column type=\"four-fifths\" last=\"true\"]<a href=\"http://www.siliconmechanics.com/\" target=\"_blank\">Silicon Mechanics, Inc.</a> - can integrate Tesla GPU technology as needed to address your HPC requirements; the company offers the Nvidia® Tesla&amp;trade C2050 cGPU, the NVIDIA Tesla C1060 GPGPU, the NVIDIA Tesla S1070 GPU Computing System (1.296 GHz), and the NVIDIA Tesla S1070 GPU Computing System (1.44 GHz).[/column]\r\n\r\n[column type=\"one-fifth\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/EXXACT_Logo_Final.jpg\" alt=\"Alt Text\" type=\"rounded\"][/column][column type=\"four-fifths\" last=\"true\"]<a href=\"http://www.exxactcorp.com/nvidiatesla.html\" target=\"_blank\">Exxact Corporation</a> - Founded in 1992, Exxact Corporation is a manufacturer of high performance workstations, servers and clusters for visualization, compute-intensive and other specialized applications such as space exploration, medical imaging, financial modeling, film production, broadcasting and industrial design. Exxact is also a value-added distributor of graphics cards, motherboards and peripherals for professional workstations.[/column]\r\n\r\n<strong>Australia</strong>\r\n\r\n[column type=\"one-fifth\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/xenon_logo.gif\" alt=\"Alt Text\" type=\"rounded\"][/column][column type=\"four-fifths\" last=\"true\"]<a href=\"http://www.xenon.com.au/\" target=\"_blank\">Xenon</a> - an NVIDIA Tesla Preferred Provider. XENON provides seamless end-to-end solutions that integrate hardware, software, consulting, and support services for customers with high performance computing (HPC) requirements. XENON\'s customised HPC solutions enable organisations to process, transfer and manage huge data sets using the latest industry technologies. Scientific research, education, defence, manufacturing &amp; film are some of the demanding industries where XENON\'s HPC solutions have been successfully implemented. XENON\'s core advantage lies in its innovative approach to providing cutting edge solutions to complex problems and that all its resources, including pre and post sales are based in Australia.[/column]\r\n\r\n<strong>China</strong>\r\n\r\n[column type=\"one-fifth\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/GPUS-LOGO.jpg\" alt=\"Alt Text\" type=\"rounded\"][/column][column type=\"four-fifths\" last=\"true\"]<a href=\"http://www.gpusolution.com/_d270298476.htm\" target=\"_blank\">GPUSolution Technologies</a> - is focused on providing GPU-based solutions in China. The company offers GPU hardware systems, GPU software, GPU technical training, GPU optimization, GPU system integration and related technical support.[/column]\r\n\r\n<strong>India</strong>\r\n\r\n[column type=\"one-fifth\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/connoisseur_logo_sm.png\" alt=\"Alt Text\" type=\"rounded\"][/column][column type=\"four-fifths\" last=\"true\"]<a href=\"http://www.connoiseur.com/\" target=\"_blank\">Connoiseur</a> - an NVIDIA Tesla Preferred Provider. Connoiseur Electronics Pvt. Ltd. is one of India\'s leading computer manufacturing company and is ISO 9001:2000 (TUV) certified. We design, build and customize products and offer services to satisfy a range of customer requirements, from desktops, workstations and entry level servers to high end mission critical servers and we also provide premier services to leading global corporations.[/column]\r\n\r\n<strong>South Korea</strong>\r\n\r\n[column type=\"one-fifth\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/miruware_logo.jpg\" alt=\"Alt Text\" type=\"rounded\"][/column][column type=\"four-fifths\" last=\"true\"]<a href=\"http://www.miruware.com/\" target=\"_blank\">Miruware</a> - an NVIDIA Tesla Preferred Provider providing HPC solutions in South Korea.[/column]\r\n\r\n[/tab][tab]\r\n\r\nReseller (VAR) partners represent ArrayFire on a geographical and/or vertical market basis. Our VARs are the heart of the ArrayFire distribution strategy and have the ability to bundle ArrayFire with a wide variety of complimentary hardware, software, and service offerings to meet our customer needs.\r\n\r\n<strong>Europe</strong>\r\n\r\n[column type=\"one-fifth\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/footer_smb.jpg\" alt=\"Alt Text\" type=\"rounded\"][/column][column type=\"four-fifths\" last=\"true\"]<a href=\"http://www.developers-source.de/\" target=\"_blank\">SMB GmbH</a> - is a european reseller for high-performance computing compilers and tools. SMB provides ArrayFire to customers in <b>Germany, Austria, and the Netherlands</b>. SMB is offering a portfolio of GPU Computing tools and services to government, education, scientific research and manufacturing customers to develop their own GPU Solutions on different platforms. SMB provides customers with workshops, local language support and training.[/column]\r\n\r\n[column type=\"one-fifth\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/sciworks_logo.jpg\" alt=\"Alt Text\" type=\"rounded\"][/column][column type=\"four-fifths\" last=\"true\"]<a href=\"http://www.sciworkstech.com/logiciels/jacket.html\" target=\"_blank\">SciWorks Technologies</a> - is a high technology company that is primarily aimed at users and developers of scientific computing solutions. SciWorks provides ArrayFire to customers in <b>France</b>. SciWorks relies on collaboration between its people and scientists who are in need of technology, consultancy, training, development and research. SciWorks offers expertise in various fields of applied mathematics and system control and signal processing, among others.[/column]\r\n\r\n[column type=\"one-fifth\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/sprinx_logo.png\" alt=\"Alt Text\" type=\"rounded\"][/column][column type=\"four-fifths\" last=\"true\"]<a href=\"http://hpc.sprinx.cz/sw/jacket-2.aspx\" target=\"_blank\">Sprinx</a> - an NVIDIA Tesla Preferred Provider in the <b>Czech Republic</b> and <b>Slovakia</b>. Sprinx\'s HPC mission is to provide solutions that enable customers and partners to receive the greatest value from their IT investments by leveraging HPC (high performance computing) technologies. We provide high quality professional services in two areas: Software Services and System Services. These services can be provided onsite at the customer\'s location or at Sprinx\'s HPC.[/column]\r\n\r\n<strong>Australia</strong>\r\n\r\n[column type=\"one-fifth\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/xenon_logo.gif\" alt=\"Alt Text\" type=\"rounded\"][/column][column type=\"four-fifths\" last=\"true\"]<a href=\"http://www.xenon.com.au/\" target=\"_blank\">Xenon</a> - an NVIDIA Tesla Preferred Provider in <b>Australia</b>. XENON provides seamless end-to-end solutions that integrate hardware, software, consulting, and support services for customers with high performance computing (HPC) requirements. XENON\'s customised HPC solutions enable organisations to process, transfer and manage huge data sets using the latest industry technologies.[/column]\r\n\r\n<strong>China</strong>\r\n\r\n[column type=\"one-fifth\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/hirain_logo.gif\" alt=\"Alt Text\" type=\"rounded\"][/column][column type=\"four-fifths\" last=\"true\"]<a href=\"http://www.hirain.com/Product/product_intro1.asp?menucolr=3&amp;ID=1224\" target=\"_blank\">HiRain Technologies</a> - HiRain Technologies, founded in 1998 and headquartered in Beijing with offices in Hongkong, Shanghai, Chengdu, Changchun and Wuhan, is a high-tech service company. Offering system-level solutions that span software, hardware, engineering services and systems, HiRain has earned a reputation for serving customers across diverse industry segments including aero/defense, automotive, telecommunications, electronics, education, research, etc. Hirain\'s depth of product solutions including MATLAB from The Mathworks makes them a solid partner for ArrayFire in China.[/column]\r\n\r\n[column type=\"one-fifth\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/netop_logo.jpg\" alt=\"Alt Text\" type=\"rounded\"][/column][column type=\"four-fifths\" last=\"true\"]<a href=\"http://www.netopcomputing.com/\" target=\"_blank\">NetOp Computing</a> - is a high-performance computing and visualization industry experts, focusing on government, education and scientific research and manufacturing customers with innovative high-performance computing and visualization solutions and professional consultation services in China.[/column]\r\n\r\n<strong>Japan</strong>\r\n\r\n[column type=\"one-fifth\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/concurrent_logo.gif\" alt=\"Alt Text\" type=\"rounded\"][/column][column type=\"four-fifths\" last=\"true\"]<a href=\"http://www.concurrent.co.jp/products/jacket/index.html\" target=\"_blank\">Concurrent Systems</a> - has been providing the best HPC solutions in Japan since 1987.[/column]\r\n\r\n[column type=\"one-fifth\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/HPCTECH_logo01.jpg\" alt=\"Alt Text\" type=\"rounded\"][/column][column type=\"four-fifths\" last=\"true\"]<a href=\"http://www.hpctech.co.jp/\" target=\"_blank\">HPC Tech</a> - We have been forcusing on HPC (High Performance Computing) and advanced IT technology which support for the new technology and new service.[/column]\r\n\r\n<strong>Mexico</strong>\r\n\r\n[column type=\"one-fifth\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/logo_global.jpg\" alt=\"Alt Text\" type=\"rounded\"][/column][column type=\"four-fifths\" last=\"true\"]<a href=\"http://www.globalcomputing.com.mx/index.html\" target=\"_blank\">Global Computing</a> - founded in 1998 to support academic institutions and research centers in Mexico to quickly and efficiently develop technical applications for engineering and scientific disciplines. Global Computing helps its clients to increase productivity, reduce costs and accelerate efforts in development.[/column]\r\n\r\n<strong>India</strong>\r\n\r\n[column type=\"one-fifth\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/netwebindia.jpg\" alt=\"Alt Text\" type=\"rounded\"][/column][column type=\"four-fifths\" last=\"true\"]<a href=\"http://www.netwebindia.com/gpgpu/jackethpc.html\" target=\"_blank\">Netweb</a> offers solutions based on NVIDIA® Tesla C1060 and S1070. These solutions enable every computational researcher and technical professional to have a dedicated computing resource. Netweb Technologies offers the latest technology solutions to increase the return on investments.[/column]\r\n\r\n[column type=\"one-fifth\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/connoisseur_logo_sm.png\" alt=\"Alt Text\" type=\"rounded\"][/column][column type=\"four-fifths\" last=\"true\"]<a href=\"http://www.connoiseur.com/\" target=\"_blank\">Connoiseur</a> - an NVIDIA Tesla Preferred Provider. Connoiseur Electronics Pvt. Ltd. is one of India\'s leading computer manufacturing company and is ISO 9001:2000 (TUV) certified. We design, build and customize products and offer services to satisfy a range of customer requirements, from desktops, workstations and entry level servers to high end mission critical servers and we also provide premier services to leading global corporations.[/column]\r\n\r\n<strong>Singapore &amp; Malaysia - ASEAN</strong>\r\n\r\n[column type=\"one-fifth\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/taknet_logo.jpg\" alt=\"Alt Text\" type=\"rounded\"][/column][column type=\"four-fifths\" last=\"true\"]<a href=\"http://www.taknet.com.sg/GPU_Workstations.html\" target=\"_blank\">Taknet</a> - provides solutions in the ASEAN region to meet and exceed a wide variety of needs. GPU Computing solutions from Taknet include the option of the ArrayFire. The latest NVIDIA GPUs are integrated with these solutions.[/column]\r\n\r\n<strong>South Korea</strong>\r\n\r\n[column type=\"one-fifth\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/miruware_logo.jpg\" alt=\"Alt Text\" type=\"rounded\"][/column][column type=\"four-fifths\" last=\"true\"]<a href=\"http://www.miruware.com/\" target=\"_blank\">Miruware</a> - an NVIDIA Tesla Preferred Provider providing HPC solutions in South Korea.[/column]\r\n\r\n<strong>Russia</strong>\r\n\r\n[column type=\"one-fifth\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/softkey_logo.jpg\" alt=\"Alt Text\" type=\"rounded\"][/column][column type=\"four-fifths\" last=\"true\"]<a href=\"http://www.softkey.ru/\" target=\"_blank\">Softkey JSC</a> - SoftKey is the leading Internet software-distributing company in Russia. Its catalogue includes over 12 thousands software positions. SoftKey offers its customers wide assortment; diversity of payment methods; prompt (frequently, immediate) order processing; process of order execution tracing in personal section; various discounts from the store and the software manufacturers. The company has its offices in 10 countries, among them the Ukraine, Kazakhstan, Belarus, Bulgaria, Israel, Poland, the Baltic countries, Moldova.[/column]\r\n\r\n[/tab] [/tabs][/content_band]','Partner Program','','inherit','open','closed','','187-revision-v1','','','2014-04-09 20:48:45','2014-04-09 20:48:45','',187,'http://sandbox.arrayfire.com/187-revision-v1/',0,'revision','',0),(5425,7,'2014-04-09 20:55:14','2014-04-09 20:55:14','[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\"][column type=\"two-fifths\"]\r\n\r\n[custom_headline type=\"left\" level=\"h3\"]If you want faster code, you\'ve come to the right place.[/custom_headline][gap size=\"15%\"][button  type=\"flat\" shape=\"rounded\" href=\"http://www.accelereyes.com/arrayfire/c/installation.htm\" size=\"x-large\" block=\"true\"]Download ArrayFire[/button]\r\n\r\n[gap size=\"10%\"]\r\n\r\n[button  type=\"flat\" block=\"true\" shape=\"rounded\" href=\"http://www.meetme.so/arrayfire\" size=\"x-large\" ]Schedule a consultation[/button]\r\n\r\n[/column][column type=\"three-fifths\" last=\"true\"][gap size=\"7%\"]\r\n<div class=\"wistia_embed\" id=\"wistia_rj2bar3xxp\" style=\"width: 640px; height: 388px;\"></div>\r\n<script charset=\"ISO-8859-1\" type=\"text/javascript\" src=\"//fast.wistia.com/assets/external/E-v1.js\"></script><script type=\"text/javascript\">// <![CDATA[\r\nwistiaEmbed = Wistia.embed(\"rj2bar3xxp\");\r\n// ]]></script>[/column]\r\n<div id=\"arrayfire\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"][column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"]Faster code[/custom_headline]\r\n\r\nArrayFire is a fast, hardware-neutral software library for GPU computing with an easy-to-use API. Its array-based function set makes GPU programming simple. A few lines of code in ArrayFire can replace dozens of lines of raw GPU code, saving you valuable time and lowering development costs.\r\n\r\n[gap size=\"10%\"][button  type=\"flat\" shape=\"rounded\" href=\"http://www.accelereyes.com/arrayfire/c/installation.htm\" size=\"x-large\" ]Download ArrayFire[/button][/column][column type=\"one-half\" last=\"true\" class=\"center-text\"][gap size=\"5%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Triumvirate_Exported.png\"][/column] [gap size=\"5%\"]\r\n\r\n[column type=\"one-third\" class=\"center-text\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/04/Googlelogo-e1396387097279.png\"][line]Video content analysis is the basis for categorizing videos and enabling search by content. Google used ArrayFire to extract motion features in video, improving performance by substantially accelerating the solution of the L1-regularized least-squares optimization problem.[/column][column type=\"one-third\" class=\"center-text\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/04/Koch-Industries-e1396387359637.jpg\"][line]Andrew Shin, Market Risk Manager of Koch Supply &amp; Trading, achieves significant performance increases on option pricing algorithms using ArrayFire software, \"My buddy and I are, at best, novice programmers and we couldn\'t imagine having to figure out how to code all this in CUDA.\"[/column][column type=\"one-third\" last=\"true\" class=\"center-text\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/04/nasa-e1396387230473.png\"][line]The main thrust of this research was improving Mars rover image compression via GPUs and genetic algorithms. With ArrayFire software and GPUs, the researchers were able to achieve 5X speedups on the larger data sizes.[/column]\r\n<div id=\"hardware\"></div>\r\n[/content_band]\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n\r\n[column type=\"one-half\"][gap size=\"15%\"]\r\n<p style=\"text-align: center;\"><img class=\"aligncenter\" alt=\"CUDA logo\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/CUDA-logo.jpg\" width=\"231\" height=\"140\" /></p>\r\n<img class=\"aligncenter\" alt=\"OpenCL\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/OpenCLLogo_678x452.png\" width=\"326\" height=\"217\" />\r\n\r\n[/column][column type=\"one-half\" last=\"true\"][gap size=\"10%\"]\r\n\r\n[custom_headline type=\"left\" level=\"h3\"] ArrayFire for CUDA and OpenCL[/custom_headline]\r\n\r\nArrayFire supports CUDA-capable NVIDIA GPUs and most OpenCL devices, including AMD GPUs/APUs and Intel Xeon Phi co-processors. It also supports mobile OpenCL devices from ARM, Qualcomm, and others.\r\n\r\n<span style=\"line-height: 1.5em;\">ArrayFire is a high-performance software library designed for maximum productivity and speed without the hassle of writing difficult low-level device code. Each of ArrayFire\'s functions has been hand-tuned by our CUDA and OpenCL experts.</span>\r\n\r\n[/column]\r\n<div id=\"mobile\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n[column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"  ]Mobile GPU Computing[/custom_headline]\r\n\r\nMobile GPUs offer accelerated performance. If you would like to use ArrayFire in a mobile application or if you would like to hire our mobile acceleration services, email us at <a href=\"mailto:sales@arrayfire.com\" target=\"_blank\">sales@arrayfire.com</a> and include a description of your application.\r\n\r\nOur clients have achieved between 5X to 30X speed boosts for convolutions and other compute functions on mobile devices. It enables:[icon_list][icon_list_item type=\"angle-double-right\"]Real-time video processing[/icon_list_item][icon_list_item type=\"angle-double-right\"]Better augmented reality [/icon_list_item][icon_list_item type=\"angle-double-right\"]Better computational photograph[/icon_list_item][icon_list_item type=\"angle-double-right\"]Faster data processing[/icon_list_item][/icon_list]\r\n\r\nAll mobile devices have a GPU which can deliver greater compute throughput than the CPU. Why not use the GPU to make your app faster?[/column][column type=\"one-half\" fade=\"true\" last=\"true\" fade_animation=\"in-from-right\" class=\"center-text\"][gap size=\"10%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/mobile_Exported1-e1395437261846.png\"][/column]\r\n<div id=\"documentation\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"][column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"]Documentation[/custom_headline]\r\n\r\n<strong>ArrayFire for C, C++, and Fortran\r\n</strong>Open the hood—take a look at the beautiful nitty-gritty.\r\n\r\n<strong></strong>[icon type=\"angle-double-right\"] <a href=\"http://www.accelereyes.com/arrayfire/c\" target=\"_blank\">CUDA &amp; OpenCL C/C++\r\n</a>[icon type=\"angle-double-right\"] <a href=\"http://www.accelereyes.com/arrayfire/fortran\" target=\"_blank\">CUDA &amp; OpenCL Fortran</a>\r\n\r\n<strong>Functions\r\n</strong>Hundreds of functions, hand-tuned and optimized by our engineers.\r\n\r\n[icon type=\"angle-double-right\"] <a title=\"ArrayFire Functions\" href=\"http://www.accelereyes.com/arrayfire/c/modules.htm\">ArrayFire Functions</a>\r\n\r\n<strong>User Forums</strong>\r\nEvery post gets a response from ArrayFire engineers.\r\n\r\n[icon type=\"angle-double-right\"] <a href=\"http://forums.accelereyes.com/\" target=\"_blank\">User Forums</a>\r\n\r\n[/column][column class=\"center-text\" type=\"one-half\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][gap size=\"5%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/gears1.png\"][/column]\r\n<div id=\"benchmarks\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n[column type=\"one-half\" fade=\"true\" fade_animation=\"in-from-left\" ][gap size=\"5%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/Benchmark-guy-torso-opposite-e1392155948298.png\"][/column]\r\n\r\n[column type=\"one-half\" last=\"true\"][custom_headline type=\"left\" level=\"h3\" ]Benchmarks[/custom_headline]\r\n\r\nAll benchmarks were performed on a NVIDIA Tesla C2050 with an Intel i7-950 processor. The benchmarks compare ArrayFire with several popular CPU-based acceleration libraries, including <a href=\"http://software.intel.com/en-us/articles/intel-mkl/\" target=\"_new\">Intel Math Kernel Library</a>, <a href=\"http://software.intel.com/en-us/articles/intel-ipp/\" target=\"_new\">Intel Integrated Performance Primitives</a>, <a href=\"http://eigen.tuxfamily.org/index.php?title=Main_Page\" target=\"_new\">Eigen</a>, and <a href=\"http://arma.sourceforge.net/\" target=\"_new\">Armadillo</a>.[/column]\r\n<p style=\"text-align: center;\">[column type=\"one-fifth\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"three-fifths\"][tab_nav type=\"four-up\"][tab_nav_item title=\"Base\" active=\"true\"][tab_nav_item title=\"Linear Algebra\" active=\"\"][tab_nav_item title=\"Convolution\" active=\"\"][tab_nav_item title=\"Utility\" active=\"\"][/tab_nav][tabs][tab active=\"true\"]<img class=\"aligncenter  wp-image-351\" alt=\"Matrix Multiply\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/matrix_multiply-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-352\" alt=\"Matrix Transpose\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/matrix_transpose-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-349\" alt=\"FFT\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/fft-1024x730.png\" width=\"491\" height=\"350\" />[/tab][tab]<img class=\"aligncenter  wp-image-350\" alt=\"LU\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/lu-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-357\" alt=\"SVD\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/svd-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-354\" alt=\"Solve\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/solve-1024x730.png\" width=\"491\" height=\"350\" />[/tab][tab]<img class=\"aligncenter  wp-image-348\" alt=\"Convs\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/convs-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-347\" alt=\"Conv\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/conv-1024x730.png\" width=\"491\" height=\"350\" />[/tab][tab]<img class=\"aligncenter  wp-image-356\" alt=\"sum\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/sum-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-355\" alt=\"sort\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/sort-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-353\" alt=\"scan\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/scan-1024x730.png\" width=\"491\" height=\"350\" />[/tab][/tabs][/column][column type=\"one-fifth\" last=\"true\"]<span style=\"color: #ffffff;\">.</span>[/column]</p>\r\n\r\n<div id=\"free\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n\r\n[column type=\"one-half\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"one-fourth\"]<span style=\"color: #ffffff;\">.</span>[custom_headline type=\"center\"  level=\"h3\" class=\"mtn\"]ArrayFire Free[/custom_headline][/column][column type=\"one-fourth\" last=\"true\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"one-fourth\"  fade=\"true\" fade_animation=\"in-from-left\" ][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/right-leaning-e1391788779101.png\"][/column][column type=\"one-fourth\"]\r\n<table>\r\n<tbody>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Functions[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Basic Operations</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Arithmetic</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Signal Processing</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Image Processing</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Statistics</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Visualization</td>\r\n</tr>\r\n</tbody>\r\n</table>\r\n[gap size=\"17%\"][button type=\"flat\" block=\"true\" shape=\"rounded\" size=\"large\"  href=\"http://www.accelereyes.com/arrayfire/c/installation.htm\"]Download ArrayFire[/button] [/column][column type=\"one-fourth\"]\r\n<table>\r\n<tbody>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Hardware[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] CUDA</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] OpenCL</td>\r\n</tr>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Languages[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] C/C++</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Fortran</td>\r\n</tr>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Advanced[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td> [icon type=\"check-circle\" style=\"color: #8cc540;\"] GFOR Loop</td>\r\n</tr>\r\n</tbody>\r\n</table>\r\n[/column][column type=\"one-fourth\" last=\"true\"]\r\n<table>\r\n<tbody>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Platforms[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Windows</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Linux</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Mac</td>\r\n</tr>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Data Types[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] All types</td>\r\n</tr>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Support[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td> [icon type=\"check-circle\" style=\"color: #8cc540;\"] Forums</td>\r\n</tr>\r\n</tbody>\r\n</table>\r\n<div id=\"licensing\"></div>\r\n[/column][gap size=\"8%\"]\r\n\r\n[pricing_table id=\"pricing\" columns=\"3\"][pricing_table_column  featured=\"false\" title=\"ArrayFire Developer\" currency=\"$\" price=\"499 / year\" interval=\"$149 / year (Academic)\"] [icon_list] [icon_list_item type=\"star\" ]Dedicated license [/icon_list_item] [icon_list_item  type=\"times-circle\"] Starts at 2 GPUs or devices [/icon_list_item] [icon_list_item type=\"times-circle\"] Linear algebra [/icon_list_item] [icon_list_item type=\"times-circle\"] Sparse matrices [/icon_list_item][icon_list_item type=\"times-circle\"] Phone support [/icon_list_item][icon_list_item type=\"times-circle\"] Premium support &amp; consulting [/icon_list_item][/icon_list] [button href=\"http://sandbox.arrayfire.com/shop\"] Purchase [/button] [/pricing_table_column] [pricing_table_column featured=\"true\" featured_sub=\"Most Popular\" title=\"ArrayFire Pro\" currency=\"$\" price=\"1,499 / year\" interval=\"$525 / year (Academic)\"] [icon_list] [icon_list_item type=\"star\"] Dedicated license [/icon_list_item] [icon_list_item type=\"star\"] Starts at 2 GPUs or devices [/icon_list_item] [icon_list_item type=\"star\"] Linear algebra [/icon_list_item][icon_list_item type=\"star\"] Sparse matrices [/icon_list_item][icon_list_item type=\"times-circle\"] Phone support [/icon_list_item][icon_list_item type=\"times-circle\"] Premium support &amp; consulting [/icon_list_item] [/icon_list] [button href=\"http://sandbox.arrayfire.com/shop\"]Purchase [/button] [/pricing_table_column] [pricing_table_column featured=\"false\" title=\"ArrayFire Enterprise\" currency=\"$\" price=\"2,999 / year\" interval=\"$1,049 / year (Academic)\"] [icon_list] [icon_list_item type=\"star\"] Dedicated license [/icon_list_item] [icon_list_item type=\"star\"] Starts at 2 GPUs or devices [/icon_list_item] [icon_list_item type=\"star\"] Linear algebra [/icon_list_item][icon_list_item type=\"star\"]Sparse matrices [/icon_list_item][icon_list_item type=\"star\"] Phone support[/icon_list_item][icon_list_item type=\"star\"]Premium support &amp; consulting [/icon_list_item][/icon_list] [button href=\"http://sandbox.arrayfire.com/shop\"] Purchase [/button] [/pricing_table_column] [/pricing_table]\r\n<div id=\"whitepapers\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n\r\n[column type=\"one-half\"][gap size=\"20%\"][image type=\"thumbnail\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/wp2.jpg\"][button href=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/03/arrayfire_matrix_computations_chrzeszczyk.pdf\" shape=\"rounded\" size=\"regular\" block=\"true\"]Download <em>Matrix Computations on the GPU with ArrayFire for C/C++</em>[/button][/column][column type=\"one-half\" last=\"true\"]\r\n\r\n[custom_headline type=\"left\" level=\"h3\" ]Whitepapers[/custom_headline]\r\n\r\n<img alt=\"Whitepaper 1\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/Whitepaper-1.png\" width=\"466\" height=\"374\" />\r\n\r\n&nbsp;\r\n\r\n[/column][gap size=\"10%\"]\r\n\r\n[column type=\"one-half\"]<img alt=\"Whitepaper 2\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/Whitepaper-2.png\" width=\"442\" height=\"304\" />[/column][column type=\"one-half\" last=\"true\"][image type=\"thumbnail\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/wp1.jpg\"][button href=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/03/arrayfire_whitepaper.pdf\" shape=\"rounded\" size=\"regular\"  block=\"true\" float=\"right\"]Download <em>High-level GPU Computing in C, C++, and Fortran</em>[/button][/column]\r\n<div id=\"casestudies\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n\r\n[column type=\"one-half\"][gap size=\"12%\"][custom_headline type=\"left\" level=\"h3\" ]Case Studies[/custom_headline]\r\n\r\nLearn how ArrayFire has worked in real code, including applications in academia, finance, government, life sciences, manufacturing, media, and oil &amp; gas.[/column][column type=\"one-half\" last=\"true\" fade=\"true\" fade_animation=\"in-from right\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/model-A.png\"][/column][custom_headline type=\"left\" level=\"h5\"]Academia [/custom_headline][accordion][accordion_item title=\"<strong>Accelerating LTE Simulation | Tsinghua University</strong>\"]\r\n\r\n<strong>Authors:</strong> Yuan Gao, Yin Sun, Chun Hui Zhou, Xin Su, Xi Bin Xu, Shi Dong Zhou, Tsinghua University\r\n<strong>Speedup:</strong> 3X\r\n\r\nFast simulations are a driving force in several research projects. However, the accompanying long simulation times can tend to be a drag in many of these projects. In this article, we shall bring up the example of the work on 3GPP LTE System Simulation by Yuan Gao et al (from Tsinghua University, Beijing) and demonstrate how the use of ArrayFire software can significantly improve the simulator performance and lead to faster validation times in simulation projects.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>High Performance Compressive Sensing | Rice University</strong>\"]\r\n\r\n<strong>Authors:</strong> Nabor Reyna and Wotao Yin from Rice University\r\n<strong>Speedup:</strong> 5X\r\n\r\nThis work deals with reconstruction of signals using partial Fourier matrices (RecPF). The major computational components of the algorithm involve shrinkage and FFTs. ArrayFire software is employed to accelerate this compute-heavy code.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Power System Simulations | Indian Institute of Technology, Roorkee, India</strong>\"]\r\n<strong>Authors:</strong> Indian Institute of Technology, Roorkee\r\n<strong>Speedup:</strong> 35X\r\n\r\nPower flow studies are one of the most important aspects of power system planning and operation. The power flow reveals the sinusoidal steady state characteristics of the entire system - voltages, real and reactive power generated, and absorbed and line losses- elucidating the voltage magnitudes and angles at each bus, the generation of each generating unit, and real and reactive power losses in the system. All this is necessary to ensure the security, economy, and control of electrical energy distribution. Learn how ArrayFire software can deliver magnitudes of performance improvement over CPU-based solutions.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Antenna Array Simulations | University of Naples Federico II</strong>\"]\r\n\r\n<strong>Authors:</strong> A. Capozzoli, C. Cucio, A. Liseno at University of Naples Federico II\r\n<strong>Speedup:</strong> 24X\r\n\r\nAntenna array design involves repeated simulation to tune the many parameters involved, and waiting around for simulations to finish is no fun. Offloading the optimization problem onto the GPU cuts that time down significantly. In their recent paper, Capozzoli, Curcio, and Liseno of University of Naples Federico II demonstrated how a simple modification to their echo generator array simulation took advantage of the GPU to bring immediate speedups.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Laplace Transform Inversion | Acunum Algorithms and Simulations</strong>\"]\r\n\r\n<strong>Authors:</strong> Patrick Kano and Moysey Brio at Acunum Algorithms and Simulations\r\n<strong>Speedup:</strong> 3.8X\r\n\r\nThe numerical inversion of the Laplace transform is a long standing problem due its implicit ill-posedness. Patrick Kano and Moysey Brio of Acunum Algorithms and Simulations, with their experience in computational methods and algorithm development, found a solution that not only works, but is very fast.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Compressed Sensing for Image Reconstruction | College of Engineering, Roorkee, India</strong>\"]\r\n\r\n<strong>Authors:</strong> Kuldeep Yadav, Ankush Mittal, M. A. Ansar, and Avi Srivastava, College of Engineering, Roorkee, India\r\n<strong>Speedup:</strong> 8X\r\n\r\nCompressed sensing is very critical in the areas of medical image reconstruction, image acquisition or sensor networks. An algorithm for compressed sensing developed using a Basis Pursuit Algorithm shows over 8X speedup when run on an NVIDIA GPU.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Fat/Water Reconstruction for Medical Images | Case Western Reserve University</strong>\"]\r\n\r\n<strong>Authors:</strong> D. H. Johnson, S. Narayan, C. A. Flask, and D. L. Wilson, Case Western Reserve University\r\n<strong>Speedup:</strong> 11.6X\r\n\r\nCase Western Reserve University researchers turned to GPUs running ArrayFire software to develop a fast and robust version of the \"Iterative Decomposition of water and fat with an Echo Asymmetry and Least-squares\" (IDEAL) reconstruction algorithm. This algorithm uses a lot of Image Processing algorithms for reconstruction, and was shown to achieve very high speedups.\r\n[/accordion_item]\r\n\r\n[/accordion]\r\n<h5>Finance</h5>\r\n[accordion][accordion_item title=\"<strong>Option Pricing | Koch Supply and Trading</strong>\"]\r\n\r\n<strong>Authors:</strong> Koch Supply &amp; Trading\r\n<strong>Speedup:</strong> 51.8X\r\n\r\nAndrew Shin, Market Risk Manager of Koch Supply &amp; Trading, achieves significant performance increases on option pricing algorithms using ArrayFire software to accelerate his code with GPUs. Andrew says, \"My buddy and I are, at best, novice programmers and we couldn\'t imagine having to figure out how to code all this in CUDA.\" But he found ArrayFire software to be straight-forward. With these results, he says he can see ArrayFire software and GPUs populating Koch\'s mark-to-futures cube, which contains its assets, simulations, and simulated asset prices.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>GPU Computing in Automated Trader | Automated Trader</strong>\"]\r\n\r\n<strong>Authors:</strong> Automated Trader\r\n<strong>Speedup:</strong> 37.5X\r\n\r\nThe Q1 2012 issue of Automated Trader contains an excellent Mashup piece reviewing software for algorithmic trading. The article provides a wonderful glimpse into the 1-2 month adventure of Andy Webb, Automated Trader.s Founder, and Wrecking Crew building a fast trading platform from several technologies. The full trading platform they built was quite extensive. The part that caught our eye was the core computational component of the pipeline. That component involved permuting 1,000 potential pairs with cointegration tests for 350 time windows on each potential pair.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>GPUs in Quantitative Analytics and Finance | Private Bank</strong>\"]\r\n\r\nThe world of Quantitative finance is all about getting accurate results really, really fast. ArrayFire is working with one of the largest banks in Spain to maximize their output using GPUs. Click the link below for an overview of the uses of GPU computing in finance.[/accordion_item][/accordion]\r\n<h5>Government</h5>\r\n[accordion][accordion_item title=\"<strong>Powering Mars Research | NASA and UAA in Anchorage</strong>\" ]\r\n\r\n<strong>Authors:</strong> NASA and UAA in Anchorage\r\n<strong>Speedup:</strong> 5X\r\n\r\nThe main thrust of this research is improving mars rover image compression via GPUs and genetic algorithms. With ArrayFire software and GPUs, the researchers were able to achieve 5X speedups on the larger data sizes. The algorithm works by pairing neighboring pixels with a random one and then adjusting the random pixel based on whether it incrementally improves the original image. Babb described the algorithm as an embarrassingly parallel process, ideally suited to GPU acceleration. He estimates he has been able to achieve a 20 to 30 percent error reduction in subjects like fingerprints and satellite imagery.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Radar Image Formation | System Planning Corporation</strong>\"]\r\n\r\n<strong>Authors:</strong> Gary Rubin and Earl Sager - System Planning Corporation\r\n<strong>Speedup:</strong> ~45X\r\n\r\nRadar imaging is computationally intensive. As a result, many imaging algorithms apply FFT-based approximations. While efficient, these algorithms sacrifice data fidelity for speed. Other algorithms better preserve information, but are often too slow for many applications. At System Planning Corporation (SPC) , we have implemented a SAR/ISAR imaging routine based on the Backprojection algorithm. Using ArrayFire software, we have demonstrated speedups of roughly 45x for large datasets.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Radar Clutter Reduction | System Planning Corporation</strong>\"]\r\n\r\n<strong>Authors:</strong> David Berger and Gary Rubin - System Planning Corporation\r\n<strong>Speedup:</strong> 5-10X\r\n\r\nSystem Planning Corporation (SPC) uses ArrayFire software to accelerate radar processing algorithms. The system processes raw data from marine navigation radars using a variety of thresholding techniques to extract real targets from clutter. This involves highly data-parallel processing in which each radar pulse is subjected to the same computations; very few operations occur across multiple pulses. Using ArrayFire software, SPC has achieved 10x speed improvements relative to a Core i7-920 CPU and 5x improvements relative to a realtime DSP implementation.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Novel Algorithms for Linear Algebra | SAIC</strong>\" ]\r\n\r\n<strong>Authors:</strong> Nolan Davis and Daniel Redig, SAIC\r\n<strong>Speedup:</strong> 3.5X\r\n\r\nNolan Davis and Daniel Redig at SAIC recently presented work on Hybrid GPU/Multicore Solutions for Large Linear Algebra Problems where they developed a novel algorithm for LU decomposition, one of the most important routines in linear algebra. They presented a Hybrid CPU/GPU computing approach, where problems too large to fit in GPU memory can also be solved faster than using only the CPU.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Geolocation | BAE Systems</strong>\"]\r\n\r\n<strong>Authors:</strong> BAE Systems\r\n<strong>Speedup:</strong> 17X\r\n\r\nGeolocation is the identification of the real-world geographic location of a target of interest. In this application, the system receives the signal with an array of several antennas and computes the direction of arrival of the radio energy by measuring the time difference of arrival (or the phase difference) at the different antennas.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Tsunami Modeling | University of Minnesota, Boise State, Saint Scholastica, and NCAR</strong>\"]\r\n\r\n<strong>Authors:</strong> University of Minnesota, Boise State, Saint Scholastica, and NCAR\r\n<strong>Speedup:</strong> 3-5X\r\n\r\nNatural catastrophic disasters like tsunamis commonly strike with little warning. For most people, tsunamis are underrated as major hazards. People sometimes wrongly believe that they occur infrequently and only along distant coasts. Tsunamis are usually caused by earthquakes. Seismic signals can give some margin of warning since the speed of tsunami waves travels at 1/30 the speed of seismic waves. Still there is little time between the creation of the tsunami and its impact making fast processing critical to producing effective warning systems. ArrayFire software was used to run an RBF simulation on the GPU with a time to solution not available by other alternatives.\r\n[/accordion_item][/accordion]\r\n<h5>Life Sciences</h5>\r\n[accordion][accordion_item title=\"<strong>Parallelized Gene Predictors | University of Quebec</strong>\" ]\r\n\r\n<strong>Authors:</strong> University of Quebec\r\n<strong>Speedup:</strong> 43X\r\n\r\nComputerized approaches to studying the human genome are challenged by the exploding amount of data, which doubles roughly every 6 months. In order to deal with this burgeoning datasets, demands for faster processing power continue to arise. This work focuses on predicting genes using frequency analysis with FFTs and with an equivalent technique known as Goertzel\'s algorithm. In these applications, the emphasis of this paper is to propose tools to geneticists and molecular biologists for the prediction or identification of new genes using existing complementary strategies. The criteria for these tools are speed, reliability, accuracy and ease of use, thus requiring little training.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Pathology Advances with GPUs | Northeastern University</strong>\" ]\r\n\r\n<strong>Authors:</strong> Laboratory for Spectral Diagnosis at Northeastern University\r\n<strong>Speedup:</strong> 100X+\r\n\r\nOne element of the hyperspectral image analysis workflow that requires more than a traditional desktop workstation or personal computer is Hierarchical Cluster analysis (HCA). HCA requires a large amount of data space and substantial computation time (~11 hours) for typical datasets using a single processor personal computer. Rather than following the traditional approach of moving to a lower level programming language like C or C++ and complex parallel programming paradigms such as OpenMP or the Massage Passing Interface (MPI), the lab utilized graphics processing units, or GPUs, and the ArrayFire software platform. The solution allowed the lab to dramatically increase the performance of the analysis while substantially decreasing the amount of calendar time to reach the desired results.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Hepatitis C Virus - Mutation Modeling | Centers for Disease Control and Prevention</strong>\" ]\r\n\r\n<strong>Authors:</strong> CDC Research and Development Team\r\n<strong>Speedup:</strong> ~20X\r\n\r\nThis case study provides a look at biological research regarding coordinated mutations of the Hepatitis C Virus (HCV). ArrayFire provided collaborative R&amp;D resources and greatly improved the speed of this HCV research with the use of parallelization, reducing the computing time from 40 days to less than 1 day. Most importantly, the conclusion of the case study illustrates the the relative price-performance of personal supercomputers that leverage GPUs and ArrayFire software provides a compelling solution versus other architectures and approaches.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Accelerating the SPM Package for Neuroimaging | Georgia Institute of Technology</strong>\" ]\r\n\r\n<strong>Authors:</strong> Georgia Institute of Technology\r\n<strong>Speedup:</strong> 3.5X\r\n\r\nThe Georgia Tech team explores the value of ArrayFire software and GPUs for fMRI workflows within the popular SPM - Statistical Parametric Mapping software widely used in neuroscience research.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Medical Image Compression | Indian Institute of Technology, Roorkee, India</strong>\" ]\r\n\r\n<strong>Authors:</strong> Jaideep Singh, Ipseeta Aruni, R. Balasubramanian - IIT - Roorkee, India\r\n<strong>Speedup:</strong> 38X\r\n\r\nThis study presents the acceleration of Haar wavelet-based image compression algorithm for medical imaging on the Graphics Processing Unit (GPU) using ArrayFire software. Due to bandwidth and image size constraints of medical imaging systems, image compression plays a vital role in reducing the bit rate of transmission or storage. Wavelet-based image compression provides the most promising approach for high quality image compression.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Brain Displacement | Spencer Technologies</strong>\"]\r\n\r\n<strong>Authors:</strong> Spencer Technologies\r\n<strong>Speedup:</strong> 12X\r\n\r\nSpencer describes how ArrayFire software facilitates the development of fast algorithms enabling observation of brain displacement across depth with sampling density that far surpasses previous benchmarks.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Multidimensional Scaling for Genomics | Leibniz Institute of Plant Genetics and Crop Plant Research</strong>\" ]\r\n\r\n<strong>Authors:</strong> Leibniz Institute of Plant Genetics and Crop Plant Research\r\n<strong>Speedup:</strong> 20-35X\r\n\r\nMultidimensional scaling (MDS) is a general computing technique to turn a distance matrix into a set of reconstructed points with pair-wise relationships approximating the original distances by points located in a usually low-dimensional space. ArrayFire software is used to enhance execution of the HiT-MDS procedure and delivers considerable performance improvement.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Drug Delivery Model | Georgia Institute of Technology</strong>\"]\r\n\r\n<strong>Authors:</strong> Georgia Institute of Technology\r\n<strong>Speedup:</strong> 70X\r\n\r\nIn this work, the researchers simulate the delivery of a novel nanoparticle chemotherapy drug to cancerous tissue. Simulation allows scientists to predict experimental outcomes and thus reduce the cost of development and time to clinical relevance. The simulation model includes blood vessels, tumor cells, and healthy cells and an engine to calculate the spatial distributions of both drug and oxygen. ArrayFire software is used to speed up the diffusion calculations for the drug and oxygen within the tissue.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Biomedical Infrared Spectroscopy | University of Manchester and Nofima Mat, Norway</strong>\" ]\r\n\r\n<strong>Authors:</strong> University of Manchester and Nofima Mat, Norway\r\n<strong>Speedup:</strong> Hours of runtime reduction\r\n\r\nThe authors present an iterative algorithm that applies full Mie scattering theory and avoids noise accumulation in their iterative algorithm by integrating a curve-fitting step. ArrayFire software along with NVIDIA GPUs are leveraged to reduce the time added by the curve-fitting step.\r\n[/accordion_item][/accordion]\r\n<h5>Manufacturing</h5>\r\n[accordion][accordion_item title=\"<strong>Feature Learning on Images | Stanford</strong>\" ]\r\n\r\n<strong>Authors:</strong> Andrew Ng, Stanford University\r\n<strong>Speedup:</strong> Ability to process many images in parallel\r\n\r\nStanford researchers in Andrew Ng\'s group used GPUs and ArrayFire software to speed up their work on Feature Learning Architectures. They decided to use ArrayFire software for this study because of the need to quickly evaluate many architectures on thousands of images. ArrayFire software taps into the immense computing power of GPUs and speeds up research utilizing many images.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Tomography of Vegetation - Filtered Back-Projection and Non-Uniform FFTs | Universita di Napoli Federico II</strong>\" ]\r\n\r\n<strong>Authors:</strong> Drs. Capozzoli, Curcio, di Vico, and Liseno, Universita di Napoli Federico II\r\n<strong>Speedup:</strong> 10X\r\n\r\nIn order to investigate changes of forest biomass, scientists use microwave tomography to image the vegetation. At the smallest scale, individual plants can be imaged to investigate branching and growth, but even synthetic aperture radar can reveal large-scale changes in regional ecology. To the right, you can see the experimental setup to image an individual plant.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Action Recognition with Independent Subspace Analysis | Stanford University</strong>\" ]\r\n\r\n<strong>Authors:</strong> Quoc Le, Will Zou, Serena Yeung, Andrew Ng, Stanford University\r\n<strong>Speedup:</strong> 4.4X\r\n\r\nIn a paper at this year\'s CVPR 2011, entitled \"Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis\", the authors explain how their unsupervised feature learning algorithm competes with other algorithms that are hand crafted or use learned features. For their training purposes, they used a multi-layered stacked convolutional ISA (Independent subspace analysis) network. An ISA is used for learning features from image patches without supervision.\r\n[/accordion_item][/accordion]\r\n<h5>Media and Computer Vision</h5>\r\n[accordion][accordion_item title=\"<strong>Fast Computer Vision with OpenCV and ArrayFire | OpenCV Blogger</strong>\" ]\r\n\r\n<strong>Authors:</strong> OpenCV Blogger\r\n<strong>Speedup:</strong> ~10X\r\n\r\nThe OpenCV library is the defacto standard for doing computer vision and image processing research projects. OpenCV includes several hundreds of computer vision algorithms, aimed for use in realtime vision applications. This case study shows how to use both libraries together. There is a simple example application that demonstrates using OpenCV for webcam access and ArrayFire for some basic processing routines and displaying results.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Video Processing | Google</strong>\" ]\r\n\r\n<strong>Authors:</strong> Google and Stanford\r\n<strong>Speedup:</strong> 10-20X\r\n\r\nVideo content analysis is the basis for categorizing videos and enabling search by content. Growing interest in using sparse-coding methods to extract motion features in video in support of video content analysis led to the application of ArrayFire software to improve performance by substantially accelerating the solution of the L1-regularized least-squares optimization problem.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Action Recognition with Independent Subspace Analysis | Stanford University</strong>\"]\r\n\r\n<strong>Authors:</strong> Quoc Le, Will Zou, Serena Yeung, Andrew Ng, Stanford University\r\n<strong>Speedup:</strong> 4.4X\r\n\r\nIn a paper at this year\'s CVPR 2011, entitled \"Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis\", the authors explain how their unsupervised feature learning algorithm competes with other algorithms that are hand crafted or use learned features. For their training purposes, they used a multi-layered stacked convolutional ISA (Independent subspace analysis) network. An ISA is used for learning features from image patches without supervision.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Music Beat Analysis | Georgia Tech</strong>\"]\r\n\r\n<strong>Authors:</strong> Vidhur Vohra - Georgia Tech\r\n<strong>Speedup:</strong> 15X\r\n\r\nDid you ever wonder how the music visualizer in your media player works? Watching it pulsate in synchrony with the beats of the song is almost as entertaining as listening to the song itself! Researchers have been attempting to detect beats in audio signals for many years, and there are many techniques available, from the simplest (and least accurate) to more complicated algorithms that are highly accurate. All algorithms, though, perform some form of signal processing and frequency analysis, applications highly suited to GPU Computing.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Optimization Methods for Deep Learning | Stanford Artificial Intelligence Laboratory</strong>\" ]\r\n\r\n<strong>Authors:</strong> Stanford Artificial Intelligence Laboratory\r\n<strong>Speedup:</strong> Improved accuracy\r\n\r\nResearchers at SAIL (Stanford Artificial Intelligence Laboratory), have done it again. They have successfully used ArrayFire software to speed up the training part of Deep Learning algorithms. In their paper titled .On Optimization Methods for Deep Learning., they experiment with some of the well known training algorithms and demostrate their scalability across parallel architectures (GPUs as well as multi-machine networks). The algorithms include SGDs (Stochastic Gradient Descent) L-BFGS (Limited BFGS used for solving non-linear problems), CG (Conjugate Gradient).\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Feature Learning on Images | Stanford University</strong>\" ]\r\n\r\n<strong>Authors:</strong> Andrew Ng, Stanford University\r\n<strong>Speedup:</strong> Ability to process many images in parallel\r\n\r\nStanford researchers in Andrew Ng’s group used ArrayFire software to speed up their work on Feature Learning Architectures. They decided to use ArrayFire software for this study because of the need to quickly evaluate many architectures on thousands of images. ArrayFire software taps into the immense computing power of GPUs and speeds up research utilizing many images.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Digital Holography for Imaging | National University of Ireland, Maynooth</strong>\" ]\r\n\r\n<strong>Authors:</strong> Nitesh Pandey, Damien Kelly, Bryan Hennelly and Thomas Naughton from the National University of Ireland, Maynooth\r\n<strong>Speedup:</strong> 17X\r\n\r\nDigital holography is a powerful imaging technique with many new applications like true 3D display. It allows the capture of both amplitude and phase information of the light reflected off the surface of 3D objects. Researchers at the National University of Ireland, Maynooth are developing techniques based on digital holography for 3D display applications.\r\nReconstruction of large digital holograms can be computationally intensive to generate on CPUs, but GPUs running ArrayFire software offer amazing possibilities.\r\n[/accordion_item][/accordion]\r\n<h5>Oil and Gas</h5>\r\n[accordion][accordion_item title=\"<strong>3D Mantle Convection - Geodynamics | Boise State, University of Colorado, University of Minnesota</strong>\" ]\r\n\r\n<strong>Authors:</strong> Boise State, University of Colorado, University of Minnesota\r\n<strong>Speedup:</strong> 2.5-4.5X\r\n\r\nThe authors introduce a GPU implementation of a three-dimensional mantle convection modeling at a high Rayleigh number to the solid earth geophysics community. They outline code development time, compare performance of CPUs versus GPUs, and deliver powerful visualizations.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Ground Water Simulations | Louisiana State University</strong>\" ]\r\n\r\n<strong>Authors:</strong> Kevin R. Tubbs and Frank T-C. Tsai at Louisiana State University\r\n<strong>Speedup:</strong> &gt;20X\r\n\r\nA lattice Boltzmann method for solving the shallow water equations and the advection-dispersion equation is developed and implemented on graphics processing unit (GPU)-based architectures. The proposed LBM is implemented to an NVIDIA Computing Processor in a single GPU workstation. GPU computing is performed using ArrayFire software. Mass transport with velocity-dependent dispersion in shallow water flow is simulated by combining the MRT-LBM model and the TRT-LBM model. The GPU parallel performance increases as the grid size increases. The results indicate the promise of the GPU-accelerated LBM for modeling mass transport phenomena in shallow water flows.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Shallow Water Fluid Flow | Louisiana State University</strong>\" ]\r\n\r\n<strong>Authors:</strong> Louisiana State University\r\n<strong>Speedup:</strong> &gt;10X\r\n\r\nA lattice Boltzmann method (LBM) on high performance computing (HPC) environments for three-dimensional shallow water flow fields coupled to mass transport is developed. LBM is an attractive method for solving the multilayered shallow water equations because the extension to multilayer is straight forward with all of the simplicities and advantages of the LBM in mass transport in shallow water flows and the LBM performance on central processing unit (CPU)-based and graphics processing unit (GPU)-based HPC environments.\r\n[/accordion_item][/accordion]\r\n<div id=\"consulting\"></div>\r\n[/content_band]\r\n<div id=\"services\"></div>\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"][column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"]Hire our acceleration gang[/custom_headline]\r\n\r\nHire us to accelerate your code. Or to train your pros. Or even to write new code for your organization!\r\n\r\nWe’ve already helped thousands of organizations speedup their code. We’ve accelerated algorithms, data sets, and challenging problems of all types in the past, and we’re confident that we can accelerate your code too.\r\n\r\n[gap size=\"10%\"][button  type=\"flat\" shape=\"rounded\" href=\"http://meetme.so/arrayfire\" size=\"x-large\" ]Schedule a consultation[/button][/column][column type=\"one-half\" last=\"true\" class=\"center-text\"][gap size=\"5%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Bat-signal-e1391790016951.png\"][/column] [gap size=\"7%\"]\r\n\r\n[column type=\"one-third\" class=\"center-text\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/04/LFG-B-HORZ_202_K-e1396448935778.jpg\"][line]Lincoln Financial Group ported their CPU code (C/C++) to CUDA, and this enabled them to speed up the necessary financial calculations. Their primary objective was to reduce the time taken to run this code. Before porting to CUDA, they required 10-12 hours to run the entire code. After porting to CUDA, they were able to do the same work in about 30 minutes.[/column][column type=\"one-third\" class=\"center-text\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/reveal_logo-e1396449044651.jpg\"][line]Reveal Imaging, an SAIC company, uses ArrayFire in developing threat-detection products for transportation systems—such as cargo and baggage screening in airports—and in securing facilities and public events.[/column][column type=\"one-third\" last=\"true\" class=\"center-text\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/04/1800contactlogo.png\"][line]The Glasses.com app relies on computer vision to recognize the features of a user’s face. The application then generates an accurate, high-fidelity, three-dimensional model of that face, and virtually places selected frames on the image.[/column]\r\n<div id=\"starterpackage\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n\r\n[column type=\"one-half\" last=\"false\" fade=\"true\" fade_animation=\"in-from-left\" ][gap size=\"10%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/comingatyou.png\"][/column][column type=\"one-half\" last=\"true\"] [custom_headline type=\"left\" level=\"h3\"]Starter Package ($500)* [/custom_headline] Hire us for 1-day. We set you up with one engineer dedicated for a full day, as well as support from senior and test engineers throughout the day. Here\'s how it works:\r\n\r\n[icon_list] [icon_list_item type=\"angle-double-right\"]Initial phone call[/icon_list_item] [icon_list_item type=\"angle-double-right\"]You send us your code or algorithm [/icon_list_item] [icon_list_item type=\"angle-double-right\"]We analyze your code for potential GPU benefit[/icon_list_item][icon_list_item type=\"angle-double-right\"]We accelerate as much of the code as is possible within the 1-day effort, applying our extensive GPU software libraries[/icon_list_item][icon_list_item type=\"angle-double-right\"]We produce a final report, along with code[/icon_list_item] [/icon_list] The final report outlines the best approach to follow for full GPU-acceleration of your code.\r\n\r\n&nbsp;\r\n\r\n[button type=\"flat\" shape=\"rounded\" size=\"regular\" href=\"http://sandbox.arrayfire.com/product/consulting-starter-package/\" title=\"Starter Package\"]Buy the Starter Package[/button]\r\n\r\n&nbsp;\r\n\r\n*Limit one (1) per customer.\r\n\r\n[/column]\r\n<div id=\"customcode\"></div>\r\n[/content_band] [content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n\r\n[column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\" ]Coding Work (Custom)[/custom_headline]\r\n\r\n[custom_headline type=\"left\" level=\"h6\" ]Why Choose Us?[/custom_headline] [icon_list] [icon_list_item type=\"angle-double-right\"]Deep experience, already servicing thousands of customers[/icon_list_item] [icon_list_item type=\"angle-double-right\"]Quality work, with leading GPU software [/icon_list_item] [icon_list_item type=\"angle-double-right\"]Efficient delivery, with ArrayFire\'s code base we can deliver results fast[/icon_list_item][icon_list_item type=\"angle-double-right\"]Proven, we make customers happy through faster code[/icon_list_item][/icon_list] [custom_headline type=\"left\" level=\"h6\" ]Our Strengths[/custom_headline] [icon_list] [icon_list_item type=\"angle-double-right\"]Excellence in GPU code[/icon_list_item] [icon_list_item type=\"angle-double-right\"]Well-written, efficient C, C++, Fortran, Java, or .NET [/icon_list_item] [icon_list_item type=\"angle-double-right\"]Application porting and integration[/icon_list_item][icon_list_item type=\"angle-double-right\"]Tuning software to peak hardware performance[/icon_list_item][icon_list_item type=\"angle-double-right\"]Scalability of algorithms to handle enterprise-level programs[/icon_list_item] [/icon_list][button type=\"flat\" shape=\"rounded\" size=\"regular\" href=\"http://meetme.so/arrayfire\" title=\"Tech Consultation\"]Schedule a consultation[/button] [/column][column type=\"one-half\"  fade=\"true\" fade_animation=\"in-from-right\" last=\"true\" ][gap size=\"25%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/Holoham.png\"][/column]\r\n<div id=\"training\"></div>\r\n[/content_band] [content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n\r\n[column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\" ]Training[/custom_headline] Attendees will receive the latest industry knowledge and techniques for GPU computing in CUDA and OpenCL.\r\n\r\nArrayFire offers up to four days of specialized GPU training in CUDA and OpenCL programming. Register for a general course, or schedule a course dedicated for your organization. We can travel to you, or you can travel to our Atlanta office.\r\n\r\nWe recommend that attendees have a working knowledge of C/C++ in order to gain the most from the training courses.\r\n\r\n[/column]\r\n\r\n[column type=\"one-half\" last=\"true\"][gap size=\"8%\"]\r\n<h5><strong>Fee includes:</strong></h5>\r\n[icon_list] [icon_list_item type=\"angle-double-right\"]Instruction by an excellent and interesting expert, with hands-on exercises[/icon_list_item] [icon_list_item type=\"angle-double-right\"]Use of a laptop with CUDA and OpenCL capable GPUs and CPUs [/icon_list_item] [icon_list_item type=\"angle-double-right\"]Choice of Linux or Windows operating system[/icon_list_item][icon_list_item type=\"angle-double-right\"]Printed manual of lecture material[/icon_list_item][icon_list_item type=\"angle-double-right\"]Electronic copy of programming exercises[/icon_list_item][/icon_list]\r\n\r\n[button type=\"flat\" shape=\"rounded\" size=\"regular\" href=\"http://sandbox.arrayfire.com/product-category/training/\" title=\"Register\"]Register for Training[/button][/column]\r\n\r\n[column type=\"one-half\" fade=\"true\" fade_animation=\"in-from-left\" class=\"center-text\" ][gap size=\"30%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/Professor-AF_Exported-e1395436350363.png\" ][/column][column type=\"one-half\" last=\"true\"][gap size=\"20%\"][custom_headline type=\"left\" level=\"h3\" looks_like=\"h3\"]Upcoming Courses[/custom_headline]\r\n<table>\r\n<tbody>\r\n<tr>\r\n<th>CUDA</th>\r\n<th>OpenCL</th>\r\n</tr>\r\n<tr>\r\n<td> Atlanta, GA</td>\r\n<td> Atlanta, GA</td>\r\n</tr>\r\n<tr>\r\n<td> Boston, MA</td>\r\n<td> Boston, MA</td>\r\n</tr>\r\n<tr>\r\n<td> New York City, NY</td>\r\n<td> New York City, NY</td>\r\n</tr>\r\n<tr>\r\n<td> Houston, TX</td>\r\n<td> Houston, TX</td>\r\n</tr>\r\n<tr>\r\n<td> San Jose, CA</td>\r\n<td> San Jose, CA</td>\r\n</tr>\r\n<tr>\r\n<td> Albuquerque, NM</td>\r\n<td> Albuquerque, NM</td>\r\n</tr>\r\n<tr>\r\n<td> Baltimore/Washington DC</td>\r\n<td> Baltimore/Washington DC</td>\r\n</tr>\r\n<tr>\r\n<td> San Diego, CA</td>\r\n<td> San Diego, CA</td>\r\n</tr>\r\n</tbody>\r\n</table>\r\n[/column][gap size=\"10%\"]\r\n\r\n[custom_headline type=\"left\" level=\"h3\"]Training Course Syllabus[/custom_headline] [column type=\"one-half\"] [custom_headline type=\"left\" level=\"h5\"  accent=\"false\"]Day 1, Introduction[/custom_headline] <strong>Lectures:</strong>\r\nGPU Computing Overview\r\nThe Programming Model\r\nBasic Dataset Mapping Techniques\r\nLibraries, ArrayFire\r\nProfiling Tools\r\n\r\n<strong>Practice:</strong>\r\nA Simple Kernel\r\nEquivalent ArrayFire Example\r\nUsing Libraries\r\nMonte Carlo Pi Estimation\r\nTiming and ArrayFire\r\nDebugging Code\r\n\r\n[custom_headline type=\"left\" level=\"h5\" accent=\"false\"]Day 3, Multi-GPU[/custom_headline] <strong>Lectures:</strong>\r\nMulti-GPU Use Cases\r\nMulti-GPUs: Contexts\r\nExisting Libraries\r\nScaling Across Multiple GPUs\r\n\r\n<strong>Practice:</strong>\r\nOut of Core Problems: Matrix Multiply\r\nTask Level Parallelism: Optimization\r\nArrayFire Multi-GPU[/column]\r\n\r\n[column type=\"one-half\" last=\"true\"] [custom_headline type=\"left\" level=\"h5\" accent=\"false\"]Day 2, Optimization[/custom_headline] <strong>Lectures:</strong>\r\nArchitecture: Grids, Blocks, and Threads\r\nMemory Model: Global, Shared, and Constant Memory\r\nAdvanced Mapping Techniques\r\nStreams: Asynchronos Launches and Concurrent Execution\r\nArrayFire: Lazy Evaluation and Code Vectorization\r\n\r\n<strong>Practice:</strong>\r\nMatrix Transpose\r\nOptimization Using Shared Memory\r\nMedian Filter\r\nOptimization Using Constant Memory\r\nStream Example\r\nArrayFire Example: Nearest Neighbor Algorithm\r\n\r\n[custom_headline type=\"left\" level=\"h5\" accent=\"false\"]Day 4, Algorithm Problems[/custom_headline]\r\n\r\n<strong>Lectures and Practice:</strong>\r\nReductions\r\nScan Algorithms\r\nSort\r\nConvolution\r\nCustomer-Specific Problem [/column][/content_band]','Home','','inherit','open','closed','','245-revision-v1','','','2014-04-09 20:55:14','2014-04-09 20:55:14','',245,'http://sandbox.arrayfire.com/245-revision-v1/',0,'revision','',0),(5435,7,'2014-04-29 19:28:28','2014-04-29 19:28:28','[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\"][column type=\"two-fifths\"]\r\n\r\n[custom_headline type=\"left\" level=\"h3\"]If you want faster code, you\'ve come to the right place.[/custom_headline][gap size=\"15%\"][button  type=\"flat\" shape=\"rounded\" href=\"http://www.sandbox.arrayfire.com/docs/installation.htm\" size=\"x-large\" block=\"true\"]Download ArrayFire[/button]\r\n\r\n[gap size=\"10%\"]\r\n\r\n[button  type=\"flat\" block=\"true\" shape=\"rounded\" href=\"http://www.meetme.so/arrayfire\" size=\"x-large\" ]Schedule a consultation[/button]\r\n\r\n[/column][column type=\"three-fifths\" last=\"true\"][gap size=\"7%\"]\r\n<div class=\"wistia_embed\" id=\"wistia_rj2bar3xxp\" style=\"width: 640px; height: 388px;\"></div>\r\n<script charset=\"ISO-8859-1\" type=\"text/javascript\" src=\"//fast.wistia.com/assets/external/E-v1.js\"></script><script type=\"text/javascript\">// <![CDATA[\r\nwistiaEmbed = Wistia.embed(\"rj2bar3xxp\");\r\n// ]]></script>[/column]\r\n<div id=\"arrayfire\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"][column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"]Faster code[/custom_headline]\r\n\r\nArrayFire is a fast, hardware-neutral software library for GPU computing with an easy-to-use API. Its array-based function set makes GPU programming simple. A few lines of code in ArrayFire can replace dozens of lines of raw GPU code, saving you valuable time and lowering development costs.\r\n\r\n[gap size=\"10%\"][button  type=\"flat\" shape=\"rounded\" href=\"http://www.sandbox.arrayfire.com/docs/installation.htm\" size=\"x-large\" ]Download ArrayFire[/button][/column][column type=\"one-half\" last=\"true\" class=\"center-text\"][gap size=\"5%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Triumvirate_Exported.png\"][/column] [gap size=\"5%\"]\r\n\r\n[column type=\"one-third\" class=\"center-text\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/04/Googlelogo-e1396387097279.png\"][line]Video content analysis is the basis for categorizing videos and enabling search by content. Google used ArrayFire to extract motion features in video, improving performance by substantially accelerating the solution of the L1-regularized least-squares optimization problem.[/column][column type=\"one-third\" class=\"center-text\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/04/Koch-Industries-e1396387359637.jpg\"][line]Andrew Shin, Market Risk Manager of Koch Supply &amp; Trading, achieves significant performance increases on option pricing algorithms using ArrayFire software, \"My buddy and I are, at best, novice programmers and we couldn\'t imagine having to figure out how to code all this in CUDA.\"[/column][column type=\"one-third\" last=\"true\" class=\"center-text\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/04/nasa-e1396387230473.png\"][line]The main thrust of this research was improving Mars rover image compression via GPUs and genetic algorithms. With ArrayFire software and GPUs, the researchers were able to achieve 5X speedups on the larger data sizes.[/column]\r\n<div id=\"hardware\"></div>\r\n[/content_band]\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n\r\n[column type=\"one-half\"][gap size=\"15%\"]\r\n<p style=\"text-align: center;\"><img class=\"aligncenter\" alt=\"CUDA logo\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/CUDA-logo.jpg\" width=\"231\" height=\"140\" /></p>\r\n<img class=\"aligncenter\" alt=\"OpenCL\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/OpenCLLogo_678x452.png\" width=\"326\" height=\"217\" />\r\n\r\n[/column][column type=\"one-half\" last=\"true\"][gap size=\"10%\"]\r\n\r\n[custom_headline type=\"left\" level=\"h3\"] ArrayFire for CUDA and OpenCL[/custom_headline]\r\n\r\nArrayFire supports CUDA-capable NVIDIA GPUs and most OpenCL devices, including AMD GPUs/APUs and Intel Xeon Phi co-processors. It also supports mobile OpenCL devices from ARM, Qualcomm, and others.\r\n\r\n<span style=\"line-height: 1.5em;\">ArrayFire is a high-performance software library designed for maximum productivity and speed without the hassle of writing difficult low-level device code. Each of ArrayFire\'s functions has been hand-tuned by our CUDA and OpenCL experts.</span>\r\n\r\n[/column]\r\n<div id=\"mobile\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n[column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"  ]Mobile GPU Computing[/custom_headline]\r\n\r\nMobile GPUs offer accelerated performance. If you would like to use ArrayFire in a mobile application or if you would like to hire our mobile acceleration services, email us at <a href=\"mailto:sales@arrayfire.com\" target=\"_blank\">sales@arrayfire.com</a> and include a description of your application.\r\n\r\nOur clients have achieved between 5X to 30X speed boosts for convolutions and other compute functions on mobile devices. It enables:[icon_list][icon_list_item type=\"angle-double-right\"]Real-time video processing[/icon_list_item][icon_list_item type=\"angle-double-right\"]Better augmented reality [/icon_list_item][icon_list_item type=\"angle-double-right\"]Better computational photograph[/icon_list_item][icon_list_item type=\"angle-double-right\"]Faster data processing[/icon_list_item][/icon_list]\r\n\r\nAll mobile devices have a GPU which can deliver greater compute throughput than the CPU. Why not use the GPU to make your app faster?[/column][column type=\"one-half\" fade=\"true\" last=\"true\" fade_animation=\"in-from-right\" class=\"center-text\"][gap size=\"10%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/mobile_Exported1-e1395437261846.png\"][/column]\r\n<div id=\"documentation\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"][column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"]Documentation[/custom_headline]\r\n\r\n<strong>ArrayFire for C, C++, and Fortran\r\n</strong>Open the hood—take a look at the beautiful nitty-gritty.\r\n\r\n<strong></strong>[icon type=\"angle-double-right\"] <a href=\"http://www.accelereyes.com/arrayfire/c\" target=\"_blank\">CUDA &amp; OpenCL C/C++\r\n</a>[icon type=\"angle-double-right\"] <a href=\"http://www.accelereyes.com/arrayfire/fortran\" target=\"_blank\">CUDA &amp; OpenCL Fortran</a>\r\n\r\n<strong>Functions\r\n</strong>Hundreds of functions, hand-tuned and optimized by our engineers.\r\n\r\n[icon type=\"angle-double-right\"] <a title=\"ArrayFire Functions\" href=\"http://www.accelereyes.com/arrayfire/c/modules.htm\">ArrayFire Functions</a>\r\n\r\n<strong>User Forums</strong>\r\nEvery post gets a response from ArrayFire engineers.\r\n\r\n[icon type=\"angle-double-right\"] <a href=\"http://forums.accelereyes.com/\" target=\"_blank\">User Forums</a>\r\n\r\n[/column][column class=\"center-text\" type=\"one-half\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][gap size=\"5%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/gears1.png\"][/column]\r\n<div id=\"benchmarks\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n[column type=\"one-half\" fade=\"true\" fade_animation=\"in-from-left\" ][gap size=\"5%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/Benchmark-guy-torso-opposite-e1392155948298.png\"][/column]\r\n\r\n[column type=\"one-half\" last=\"true\"][custom_headline type=\"left\" level=\"h3\" ]Benchmarks[/custom_headline]\r\n\r\nAll benchmarks were performed on a NVIDIA Tesla C2050 with an Intel i7-950 processor. The benchmarks compare ArrayFire with several popular CPU-based acceleration libraries, including <a href=\"http://software.intel.com/en-us/articles/intel-mkl/\" target=\"_new\">Intel Math Kernel Library</a>, <a href=\"http://software.intel.com/en-us/articles/intel-ipp/\" target=\"_new\">Intel Integrated Performance Primitives</a>, <a href=\"http://eigen.tuxfamily.org/index.php?title=Main_Page\" target=\"_new\">Eigen</a>, and <a href=\"http://arma.sourceforge.net/\" target=\"_new\">Armadillo</a>.[/column]\r\n<p style=\"text-align: center;\">[column type=\"one-fifth\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"three-fifths\"][tab_nav type=\"four-up\"][tab_nav_item title=\"Base\" active=\"true\"][tab_nav_item title=\"Linear Algebra\" active=\"\"][tab_nav_item title=\"Convolution\" active=\"\"][tab_nav_item title=\"Utility\" active=\"\"][/tab_nav][tabs][tab active=\"true\"]<img class=\"aligncenter  wp-image-351\" alt=\"Matrix Multiply\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/matrix_multiply-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-352\" alt=\"Matrix Transpose\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/matrix_transpose-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-349\" alt=\"FFT\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/fft-1024x730.png\" width=\"491\" height=\"350\" />[/tab][tab]<img class=\"aligncenter  wp-image-350\" alt=\"LU\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/lu-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-357\" alt=\"SVD\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/svd-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-354\" alt=\"Solve\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/solve-1024x730.png\" width=\"491\" height=\"350\" />[/tab][tab]<img class=\"aligncenter  wp-image-348\" alt=\"Convs\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/convs-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-347\" alt=\"Conv\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/conv-1024x730.png\" width=\"491\" height=\"350\" />[/tab][tab]<img class=\"aligncenter  wp-image-356\" alt=\"sum\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/sum-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-355\" alt=\"sort\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/sort-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-353\" alt=\"scan\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/scan-1024x730.png\" width=\"491\" height=\"350\" />[/tab][/tabs][/column][column type=\"one-fifth\" last=\"true\"]<span style=\"color: #ffffff;\">.</span>[/column]</p>\r\n\r\n<div id=\"free\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n\r\n[column type=\"one-half\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"one-fourth\"]<span style=\"color: #ffffff;\">.</span>[custom_headline type=\"center\"  level=\"h3\" class=\"mtn\"]ArrayFire Free[/custom_headline][/column][column type=\"one-fourth\" last=\"true\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"one-fourth\"  fade=\"true\" fade_animation=\"in-from-left\" ][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/right-leaning-e1391788779101.png\"][/column][column type=\"one-fourth\"]\r\n<table>\r\n<tbody>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Functions[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Basic Operations</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Arithmetic</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Signal Processing</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Image Processing</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Statistics</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Visualization</td>\r\n</tr>\r\n</tbody>\r\n</table>\r\n[gap size=\"17%\"][button type=\"flat\" block=\"true\" shape=\"rounded\" size=\"large\"  href=\"http://www.sandbox.arrayfire.com/docs/installation.htm\"]Download ArrayFire[/button] [/column][column type=\"one-fourth\"]\r\n<table>\r\n<tbody>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Hardware[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] CUDA</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] OpenCL</td>\r\n</tr>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Languages[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] C/C++</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Fortran</td>\r\n</tr>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Advanced[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td> [icon type=\"check-circle\" style=\"color: #8cc540;\"] GFOR Loop</td>\r\n</tr>\r\n</tbody>\r\n</table>\r\n[/column][column type=\"one-fourth\" last=\"true\"]\r\n<table>\r\n<tbody>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Platforms[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Windows</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Linux</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Mac</td>\r\n</tr>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Data Types[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] All types</td>\r\n</tr>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Support[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td> [icon type=\"check-circle\" style=\"color: #8cc540;\"] Forums</td>\r\n</tr>\r\n</tbody>\r\n</table>\r\n<div id=\"licensing\"></div>\r\n[/column][gap size=\"8%\"]\r\n\r\n[pricing_table id=\"pricing\" columns=\"3\"][pricing_table_column  featured=\"false\" title=\"ArrayFire Developer\" currency=\"$\" price=\"499 / year\" interval=\"$149 / year (Academic)\"] [icon_list] [icon_list_item type=\"star\" ]Dedicated license [/icon_list_item] [icon_list_item  type=\"times-circle\"] Starts at 2 GPUs or devices [/icon_list_item] [icon_list_item type=\"times-circle\"] Linear algebra [/icon_list_item] [icon_list_item type=\"times-circle\"] Sparse matrices [/icon_list_item][icon_list_item type=\"times-circle\"] Phone support [/icon_list_item][icon_list_item type=\"times-circle\"] Premium support &amp; consulting [/icon_list_item][/icon_list] [button href=\"http://sandbox.arrayfire.com/shop\"] Purchase [/button] [/pricing_table_column] [pricing_table_column featured=\"true\" featured_sub=\"Most Popular\" title=\"ArrayFire Pro\" currency=\"$\" price=\"1,499 / year\" interval=\"$525 / year (Academic)\"] [icon_list] [icon_list_item type=\"star\"] Dedicated license [/icon_list_item] [icon_list_item type=\"star\"] Starts at 2 GPUs or devices [/icon_list_item] [icon_list_item type=\"star\"] Linear algebra [/icon_list_item][icon_list_item type=\"star\"] Sparse matrices [/icon_list_item][icon_list_item type=\"times-circle\"] Phone support [/icon_list_item][icon_list_item type=\"times-circle\"] Premium support &amp; consulting [/icon_list_item] [/icon_list] [button href=\"http://sandbox.arrayfire.com/shop\"]Purchase [/button] [/pricing_table_column] [pricing_table_column featured=\"false\" title=\"ArrayFire Enterprise\" currency=\"$\" price=\"2,999 / year\" interval=\"$1,049 / year (Academic)\"] [icon_list] [icon_list_item type=\"star\"] Dedicated license [/icon_list_item] [icon_list_item type=\"star\"] Starts at 2 GPUs or devices [/icon_list_item] [icon_list_item type=\"star\"] Linear algebra [/icon_list_item][icon_list_item type=\"star\"]Sparse matrices [/icon_list_item][icon_list_item type=\"star\"] Phone support[/icon_list_item][icon_list_item type=\"star\"]Premium support &amp; consulting [/icon_list_item][/icon_list] [button href=\"http://sandbox.arrayfire.com/shop\"] Purchase [/button] [/pricing_table_column] [/pricing_table]\r\n<div id=\"whitepapers\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n\r\n[column type=\"one-half\"][gap size=\"20%\"][image type=\"thumbnail\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/wp2.jpg\"][button href=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/03/arrayfire_matrix_computations_chrzeszczyk.pdf\" shape=\"rounded\" size=\"regular\" block=\"true\"]Download <em>Matrix Computations on the GPU with ArrayFire for C/C++</em>[/button][/column][column type=\"one-half\" last=\"true\"]\r\n\r\n[custom_headline type=\"left\" level=\"h3\" ]Whitepapers[/custom_headline]\r\n\r\n<img alt=\"Whitepaper 1\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/Whitepaper-1.png\" width=\"466\" height=\"374\" />\r\n\r\n&nbsp;\r\n\r\n[/column][gap size=\"10%\"]\r\n\r\n[column type=\"one-half\"]<img alt=\"Whitepaper 2\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/Whitepaper-2.png\" width=\"442\" height=\"304\" />[/column][column type=\"one-half\" last=\"true\"][image type=\"thumbnail\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/wp1.jpg\"][button href=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/03/arrayfire_whitepaper.pdf\" shape=\"rounded\" size=\"regular\"  block=\"true\" float=\"right\"]Download <em>High-level GPU Computing in C, C++, and Fortran</em>[/button][/column]\r\n<div id=\"casestudies\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n\r\n[column type=\"one-half\"][gap size=\"12%\"][custom_headline type=\"left\" level=\"h3\" ]Case Studies[/custom_headline]\r\n\r\nLearn how ArrayFire has worked in real code, including applications in academia, finance, government, life sciences, manufacturing, media, and oil &amp; gas.[/column][column type=\"one-half\" last=\"true\" fade=\"true\" fade_animation=\"in-from right\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/model-A.png\"][/column][custom_headline type=\"left\" level=\"h5\"]Academia [/custom_headline][accordion][accordion_item title=\"<strong>Accelerating LTE Simulation | Tsinghua University</strong>\"]\r\n\r\n<strong>Authors:</strong> Yuan Gao, Yin Sun, Chun Hui Zhou, Xin Su, Xi Bin Xu, Shi Dong Zhou, Tsinghua University\r\n<strong>Speedup:</strong> 3X\r\n\r\nFast simulations are a driving force in several research projects. However, the accompanying long simulation times can tend to be a drag in many of these projects. In this article, we shall bring up the example of the work on 3GPP LTE System Simulation by Yuan Gao et al (from Tsinghua University, Beijing) and demonstrate how the use of ArrayFire software can significantly improve the simulator performance and lead to faster validation times in simulation projects.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>High Performance Compressive Sensing | Rice University</strong>\"]\r\n\r\n<strong>Authors:</strong> Nabor Reyna and Wotao Yin from Rice University\r\n<strong>Speedup:</strong> 5X\r\n\r\nThis work deals with reconstruction of signals using partial Fourier matrices (RecPF). The major computational components of the algorithm involve shrinkage and FFTs. ArrayFire software is employed to accelerate this compute-heavy code.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Power System Simulations | Indian Institute of Technology, Roorkee, India</strong>\"]\r\n<strong>Authors:</strong> Indian Institute of Technology, Roorkee\r\n<strong>Speedup:</strong> 35X\r\n\r\nPower flow studies are one of the most important aspects of power system planning and operation. The power flow reveals the sinusoidal steady state characteristics of the entire system - voltages, real and reactive power generated, and absorbed and line losses- elucidating the voltage magnitudes and angles at each bus, the generation of each generating unit, and real and reactive power losses in the system. All this is necessary to ensure the security, economy, and control of electrical energy distribution. Learn how ArrayFire software can deliver magnitudes of performance improvement over CPU-based solutions.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Antenna Array Simulations | University of Naples Federico II</strong>\"]\r\n\r\n<strong>Authors:</strong> A. Capozzoli, C. Cucio, A. Liseno at University of Naples Federico II\r\n<strong>Speedup:</strong> 24X\r\n\r\nAntenna array design involves repeated simulation to tune the many parameters involved, and waiting around for simulations to finish is no fun. Offloading the optimization problem onto the GPU cuts that time down significantly. In their recent paper, Capozzoli, Curcio, and Liseno of University of Naples Federico II demonstrated how a simple modification to their echo generator array simulation took advantage of the GPU to bring immediate speedups.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Laplace Transform Inversion | Acunum Algorithms and Simulations</strong>\"]\r\n\r\n<strong>Authors:</strong> Patrick Kano and Moysey Brio at Acunum Algorithms and Simulations\r\n<strong>Speedup:</strong> 3.8X\r\n\r\nThe numerical inversion of the Laplace transform is a long standing problem due its implicit ill-posedness. Patrick Kano and Moysey Brio of Acunum Algorithms and Simulations, with their experience in computational methods and algorithm development, found a solution that not only works, but is very fast.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Compressed Sensing for Image Reconstruction | College of Engineering, Roorkee, India</strong>\"]\r\n\r\n<strong>Authors:</strong> Kuldeep Yadav, Ankush Mittal, M. A. Ansar, and Avi Srivastava, College of Engineering, Roorkee, India\r\n<strong>Speedup:</strong> 8X\r\n\r\nCompressed sensing is very critical in the areas of medical image reconstruction, image acquisition or sensor networks. An algorithm for compressed sensing developed using a Basis Pursuit Algorithm shows over 8X speedup when run on an NVIDIA GPU.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Fat/Water Reconstruction for Medical Images | Case Western Reserve University</strong>\"]\r\n\r\n<strong>Authors:</strong> D. H. Johnson, S. Narayan, C. A. Flask, and D. L. Wilson, Case Western Reserve University\r\n<strong>Speedup:</strong> 11.6X\r\n\r\nCase Western Reserve University researchers turned to GPUs running ArrayFire software to develop a fast and robust version of the \"Iterative Decomposition of water and fat with an Echo Asymmetry and Least-squares\" (IDEAL) reconstruction algorithm. This algorithm uses a lot of Image Processing algorithms for reconstruction, and was shown to achieve very high speedups.\r\n[/accordion_item]\r\n\r\n[/accordion]\r\n<h5>Finance</h5>\r\n[accordion][accordion_item title=\"<strong>Option Pricing | Koch Supply and Trading</strong>\"]\r\n\r\n<strong>Authors:</strong> Koch Supply &amp; Trading\r\n<strong>Speedup:</strong> 51.8X\r\n\r\nAndrew Shin, Market Risk Manager of Koch Supply &amp; Trading, achieves significant performance increases on option pricing algorithms using ArrayFire software to accelerate his code with GPUs. Andrew says, \"My buddy and I are, at best, novice programmers and we couldn\'t imagine having to figure out how to code all this in CUDA.\" But he found ArrayFire software to be straight-forward. With these results, he says he can see ArrayFire software and GPUs populating Koch\'s mark-to-futures cube, which contains its assets, simulations, and simulated asset prices.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>GPU Computing in Automated Trader | Automated Trader</strong>\"]\r\n\r\n<strong>Authors:</strong> Automated Trader\r\n<strong>Speedup:</strong> 37.5X\r\n\r\nThe Q1 2012 issue of Automated Trader contains an excellent Mashup piece reviewing software for algorithmic trading. The article provides a wonderful glimpse into the 1-2 month adventure of Andy Webb, Automated Trader.s Founder, and Wrecking Crew building a fast trading platform from several technologies. The full trading platform they built was quite extensive. The part that caught our eye was the core computational component of the pipeline. That component involved permuting 1,000 potential pairs with cointegration tests for 350 time windows on each potential pair.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>GPUs in Quantitative Analytics and Finance | Private Bank</strong>\"]\r\n\r\nThe world of Quantitative finance is all about getting accurate results really, really fast. ArrayFire is working with one of the largest banks in Spain to maximize their output using GPUs. Click the link below for an overview of the uses of GPU computing in finance.[/accordion_item][/accordion]\r\n<h5>Government</h5>\r\n[accordion][accordion_item title=\"<strong>Powering Mars Research | NASA and UAA in Anchorage</strong>\" ]\r\n\r\n<strong>Authors:</strong> NASA and UAA in Anchorage\r\n<strong>Speedup:</strong> 5X\r\n\r\nThe main thrust of this research is improving mars rover image compression via GPUs and genetic algorithms. With ArrayFire software and GPUs, the researchers were able to achieve 5X speedups on the larger data sizes. The algorithm works by pairing neighboring pixels with a random one and then adjusting the random pixel based on whether it incrementally improves the original image. Babb described the algorithm as an embarrassingly parallel process, ideally suited to GPU acceleration. He estimates he has been able to achieve a 20 to 30 percent error reduction in subjects like fingerprints and satellite imagery.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Radar Image Formation | System Planning Corporation</strong>\"]\r\n\r\n<strong>Authors:</strong> Gary Rubin and Earl Sager - System Planning Corporation\r\n<strong>Speedup:</strong> ~45X\r\n\r\nRadar imaging is computationally intensive. As a result, many imaging algorithms apply FFT-based approximations. While efficient, these algorithms sacrifice data fidelity for speed. Other algorithms better preserve information, but are often too slow for many applications. At System Planning Corporation (SPC) , we have implemented a SAR/ISAR imaging routine based on the Backprojection algorithm. Using ArrayFire software, we have demonstrated speedups of roughly 45x for large datasets.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Radar Clutter Reduction | System Planning Corporation</strong>\"]\r\n\r\n<strong>Authors:</strong> David Berger and Gary Rubin - System Planning Corporation\r\n<strong>Speedup:</strong> 5-10X\r\n\r\nSystem Planning Corporation (SPC) uses ArrayFire software to accelerate radar processing algorithms. The system processes raw data from marine navigation radars using a variety of thresholding techniques to extract real targets from clutter. This involves highly data-parallel processing in which each radar pulse is subjected to the same computations; very few operations occur across multiple pulses. Using ArrayFire software, SPC has achieved 10x speed improvements relative to a Core i7-920 CPU and 5x improvements relative to a realtime DSP implementation.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Novel Algorithms for Linear Algebra | SAIC</strong>\" ]\r\n\r\n<strong>Authors:</strong> Nolan Davis and Daniel Redig, SAIC\r\n<strong>Speedup:</strong> 3.5X\r\n\r\nNolan Davis and Daniel Redig at SAIC recently presented work on Hybrid GPU/Multicore Solutions for Large Linear Algebra Problems where they developed a novel algorithm for LU decomposition, one of the most important routines in linear algebra. They presented a Hybrid CPU/GPU computing approach, where problems too large to fit in GPU memory can also be solved faster than using only the CPU.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Geolocation | BAE Systems</strong>\"]\r\n\r\n<strong>Authors:</strong> BAE Systems\r\n<strong>Speedup:</strong> 17X\r\n\r\nGeolocation is the identification of the real-world geographic location of a target of interest. In this application, the system receives the signal with an array of several antennas and computes the direction of arrival of the radio energy by measuring the time difference of arrival (or the phase difference) at the different antennas.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Tsunami Modeling | University of Minnesota, Boise State, Saint Scholastica, and NCAR</strong>\"]\r\n\r\n<strong>Authors:</strong> University of Minnesota, Boise State, Saint Scholastica, and NCAR\r\n<strong>Speedup:</strong> 3-5X\r\n\r\nNatural catastrophic disasters like tsunamis commonly strike with little warning. For most people, tsunamis are underrated as major hazards. People sometimes wrongly believe that they occur infrequently and only along distant coasts. Tsunamis are usually caused by earthquakes. Seismic signals can give some margin of warning since the speed of tsunami waves travels at 1/30 the speed of seismic waves. Still there is little time between the creation of the tsunami and its impact making fast processing critical to producing effective warning systems. ArrayFire software was used to run an RBF simulation on the GPU with a time to solution not available by other alternatives.\r\n[/accordion_item][/accordion]\r\n<h5>Life Sciences</h5>\r\n[accordion][accordion_item title=\"<strong>Parallelized Gene Predictors | University of Quebec</strong>\" ]\r\n\r\n<strong>Authors:</strong> University of Quebec\r\n<strong>Speedup:</strong> 43X\r\n\r\nComputerized approaches to studying the human genome are challenged by the exploding amount of data, which doubles roughly every 6 months. In order to deal with this burgeoning datasets, demands for faster processing power continue to arise. This work focuses on predicting genes using frequency analysis with FFTs and with an equivalent technique known as Goertzel\'s algorithm. In these applications, the emphasis of this paper is to propose tools to geneticists and molecular biologists for the prediction or identification of new genes using existing complementary strategies. The criteria for these tools are speed, reliability, accuracy and ease of use, thus requiring little training.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Pathology Advances with GPUs | Northeastern University</strong>\" ]\r\n\r\n<strong>Authors:</strong> Laboratory for Spectral Diagnosis at Northeastern University\r\n<strong>Speedup:</strong> 100X+\r\n\r\nOne element of the hyperspectral image analysis workflow that requires more than a traditional desktop workstation or personal computer is Hierarchical Cluster analysis (HCA). HCA requires a large amount of data space and substantial computation time (~11 hours) for typical datasets using a single processor personal computer. Rather than following the traditional approach of moving to a lower level programming language like C or C++ and complex parallel programming paradigms such as OpenMP or the Massage Passing Interface (MPI), the lab utilized graphics processing units, or GPUs, and the ArrayFire software platform. The solution allowed the lab to dramatically increase the performance of the analysis while substantially decreasing the amount of calendar time to reach the desired results.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Hepatitis C Virus - Mutation Modeling | Centers for Disease Control and Prevention</strong>\" ]\r\n\r\n<strong>Authors:</strong> CDC Research and Development Team\r\n<strong>Speedup:</strong> ~20X\r\n\r\nThis case study provides a look at biological research regarding coordinated mutations of the Hepatitis C Virus (HCV). ArrayFire provided collaborative R&amp;D resources and greatly improved the speed of this HCV research with the use of parallelization, reducing the computing time from 40 days to less than 1 day. Most importantly, the conclusion of the case study illustrates the the relative price-performance of personal supercomputers that leverage GPUs and ArrayFire software provides a compelling solution versus other architectures and approaches.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Accelerating the SPM Package for Neuroimaging | Georgia Institute of Technology</strong>\" ]\r\n\r\n<strong>Authors:</strong> Georgia Institute of Technology\r\n<strong>Speedup:</strong> 3.5X\r\n\r\nThe Georgia Tech team explores the value of ArrayFire software and GPUs for fMRI workflows within the popular SPM - Statistical Parametric Mapping software widely used in neuroscience research.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Medical Image Compression | Indian Institute of Technology, Roorkee, India</strong>\" ]\r\n\r\n<strong>Authors:</strong> Jaideep Singh, Ipseeta Aruni, R. Balasubramanian - IIT - Roorkee, India\r\n<strong>Speedup:</strong> 38X\r\n\r\nThis study presents the acceleration of Haar wavelet-based image compression algorithm for medical imaging on the Graphics Processing Unit (GPU) using ArrayFire software. Due to bandwidth and image size constraints of medical imaging systems, image compression plays a vital role in reducing the bit rate of transmission or storage. Wavelet-based image compression provides the most promising approach for high quality image compression.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Brain Displacement | Spencer Technologies</strong>\"]\r\n\r\n<strong>Authors:</strong> Spencer Technologies\r\n<strong>Speedup:</strong> 12X\r\n\r\nSpencer describes how ArrayFire software facilitates the development of fast algorithms enabling observation of brain displacement across depth with sampling density that far surpasses previous benchmarks.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Multidimensional Scaling for Genomics | Leibniz Institute of Plant Genetics and Crop Plant Research</strong>\" ]\r\n\r\n<strong>Authors:</strong> Leibniz Institute of Plant Genetics and Crop Plant Research\r\n<strong>Speedup:</strong> 20-35X\r\n\r\nMultidimensional scaling (MDS) is a general computing technique to turn a distance matrix into a set of reconstructed points with pair-wise relationships approximating the original distances by points located in a usually low-dimensional space. ArrayFire software is used to enhance execution of the HiT-MDS procedure and delivers considerable performance improvement.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Drug Delivery Model | Georgia Institute of Technology</strong>\"]\r\n\r\n<strong>Authors:</strong> Georgia Institute of Technology\r\n<strong>Speedup:</strong> 70X\r\n\r\nIn this work, the researchers simulate the delivery of a novel nanoparticle chemotherapy drug to cancerous tissue. Simulation allows scientists to predict experimental outcomes and thus reduce the cost of development and time to clinical relevance. The simulation model includes blood vessels, tumor cells, and healthy cells and an engine to calculate the spatial distributions of both drug and oxygen. ArrayFire software is used to speed up the diffusion calculations for the drug and oxygen within the tissue.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Biomedical Infrared Spectroscopy | University of Manchester and Nofima Mat, Norway</strong>\" ]\r\n\r\n<strong>Authors:</strong> University of Manchester and Nofima Mat, Norway\r\n<strong>Speedup:</strong> Hours of runtime reduction\r\n\r\nThe authors present an iterative algorithm that applies full Mie scattering theory and avoids noise accumulation in their iterative algorithm by integrating a curve-fitting step. ArrayFire software along with NVIDIA GPUs are leveraged to reduce the time added by the curve-fitting step.\r\n[/accordion_item][/accordion]\r\n<h5>Manufacturing</h5>\r\n[accordion][accordion_item title=\"<strong>Feature Learning on Images | Stanford</strong>\" ]\r\n\r\n<strong>Authors:</strong> Andrew Ng, Stanford University\r\n<strong>Speedup:</strong> Ability to process many images in parallel\r\n\r\nStanford researchers in Andrew Ng\'s group used GPUs and ArrayFire software to speed up their work on Feature Learning Architectures. They decided to use ArrayFire software for this study because of the need to quickly evaluate many architectures on thousands of images. ArrayFire software taps into the immense computing power of GPUs and speeds up research utilizing many images.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Tomography of Vegetation - Filtered Back-Projection and Non-Uniform FFTs | Universita di Napoli Federico II</strong>\" ]\r\n\r\n<strong>Authors:</strong> Drs. Capozzoli, Curcio, di Vico, and Liseno, Universita di Napoli Federico II\r\n<strong>Speedup:</strong> 10X\r\n\r\nIn order to investigate changes of forest biomass, scientists use microwave tomography to image the vegetation. At the smallest scale, individual plants can be imaged to investigate branching and growth, but even synthetic aperture radar can reveal large-scale changes in regional ecology. To the right, you can see the experimental setup to image an individual plant.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Action Recognition with Independent Subspace Analysis | Stanford University</strong>\" ]\r\n\r\n<strong>Authors:</strong> Quoc Le, Will Zou, Serena Yeung, Andrew Ng, Stanford University\r\n<strong>Speedup:</strong> 4.4X\r\n\r\nIn a paper at this year\'s CVPR 2011, entitled \"Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis\", the authors explain how their unsupervised feature learning algorithm competes with other algorithms that are hand crafted or use learned features. For their training purposes, they used a multi-layered stacked convolutional ISA (Independent subspace analysis) network. An ISA is used for learning features from image patches without supervision.\r\n[/accordion_item][/accordion]\r\n<h5>Media and Computer Vision</h5>\r\n[accordion][accordion_item title=\"<strong>Fast Computer Vision with OpenCV and ArrayFire | OpenCV Blogger</strong>\" ]\r\n\r\n<strong>Authors:</strong> OpenCV Blogger\r\n<strong>Speedup:</strong> ~10X\r\n\r\nThe OpenCV library is the defacto standard for doing computer vision and image processing research projects. OpenCV includes several hundreds of computer vision algorithms, aimed for use in realtime vision applications. This case study shows how to use both libraries together. There is a simple example application that demonstrates using OpenCV for webcam access and ArrayFire for some basic processing routines and displaying results.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Video Processing | Google</strong>\" ]\r\n\r\n<strong>Authors:</strong> Google and Stanford\r\n<strong>Speedup:</strong> 10-20X\r\n\r\nVideo content analysis is the basis for categorizing videos and enabling search by content. Growing interest in using sparse-coding methods to extract motion features in video in support of video content analysis led to the application of ArrayFire software to improve performance by substantially accelerating the solution of the L1-regularized least-squares optimization problem.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Action Recognition with Independent Subspace Analysis | Stanford University</strong>\"]\r\n\r\n<strong>Authors:</strong> Quoc Le, Will Zou, Serena Yeung, Andrew Ng, Stanford University\r\n<strong>Speedup:</strong> 4.4X\r\n\r\nIn a paper at this year\'s CVPR 2011, entitled \"Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis\", the authors explain how their unsupervised feature learning algorithm competes with other algorithms that are hand crafted or use learned features. For their training purposes, they used a multi-layered stacked convolutional ISA (Independent subspace analysis) network. An ISA is used for learning features from image patches without supervision.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Music Beat Analysis | Georgia Tech</strong>\"]\r\n\r\n<strong>Authors:</strong> Vidhur Vohra - Georgia Tech\r\n<strong>Speedup:</strong> 15X\r\n\r\nDid you ever wonder how the music visualizer in your media player works? Watching it pulsate in synchrony with the beats of the song is almost as entertaining as listening to the song itself! Researchers have been attempting to detect beats in audio signals for many years, and there are many techniques available, from the simplest (and least accurate) to more complicated algorithms that are highly accurate. All algorithms, though, perform some form of signal processing and frequency analysis, applications highly suited to GPU Computing.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Optimization Methods for Deep Learning | Stanford Artificial Intelligence Laboratory</strong>\" ]\r\n\r\n<strong>Authors:</strong> Stanford Artificial Intelligence Laboratory\r\n<strong>Speedup:</strong> Improved accuracy\r\n\r\nResearchers at SAIL (Stanford Artificial Intelligence Laboratory), have done it again. They have successfully used ArrayFire software to speed up the training part of Deep Learning algorithms. In their paper titled .On Optimization Methods for Deep Learning., they experiment with some of the well known training algorithms and demostrate their scalability across parallel architectures (GPUs as well as multi-machine networks). The algorithms include SGDs (Stochastic Gradient Descent) L-BFGS (Limited BFGS used for solving non-linear problems), CG (Conjugate Gradient).\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Feature Learning on Images | Stanford University</strong>\" ]\r\n\r\n<strong>Authors:</strong> Andrew Ng, Stanford University\r\n<strong>Speedup:</strong> Ability to process many images in parallel\r\n\r\nStanford researchers in Andrew Ng’s group used ArrayFire software to speed up their work on Feature Learning Architectures. They decided to use ArrayFire software for this study because of the need to quickly evaluate many architectures on thousands of images. ArrayFire software taps into the immense computing power of GPUs and speeds up research utilizing many images.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Digital Holography for Imaging | National University of Ireland, Maynooth</strong>\" ]\r\n\r\n<strong>Authors:</strong> Nitesh Pandey, Damien Kelly, Bryan Hennelly and Thomas Naughton from the National University of Ireland, Maynooth\r\n<strong>Speedup:</strong> 17X\r\n\r\nDigital holography is a powerful imaging technique with many new applications like true 3D display. It allows the capture of both amplitude and phase information of the light reflected off the surface of 3D objects. Researchers at the National University of Ireland, Maynooth are developing techniques based on digital holography for 3D display applications.\r\nReconstruction of large digital holograms can be computationally intensive to generate on CPUs, but GPUs running ArrayFire software offer amazing possibilities.\r\n[/accordion_item][/accordion]\r\n<h5>Oil and Gas</h5>\r\n[accordion][accordion_item title=\"<strong>3D Mantle Convection - Geodynamics | Boise State, University of Colorado, University of Minnesota</strong>\" ]\r\n\r\n<strong>Authors:</strong> Boise State, University of Colorado, University of Minnesota\r\n<strong>Speedup:</strong> 2.5-4.5X\r\n\r\nThe authors introduce a GPU implementation of a three-dimensional mantle convection modeling at a high Rayleigh number to the solid earth geophysics community. They outline code development time, compare performance of CPUs versus GPUs, and deliver powerful visualizations.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Ground Water Simulations | Louisiana State University</strong>\" ]\r\n\r\n<strong>Authors:</strong> Kevin R. Tubbs and Frank T-C. Tsai at Louisiana State University\r\n<strong>Speedup:</strong> &gt;20X\r\n\r\nA lattice Boltzmann method for solving the shallow water equations and the advection-dispersion equation is developed and implemented on graphics processing unit (GPU)-based architectures. The proposed LBM is implemented to an NVIDIA Computing Processor in a single GPU workstation. GPU computing is performed using ArrayFire software. Mass transport with velocity-dependent dispersion in shallow water flow is simulated by combining the MRT-LBM model and the TRT-LBM model. The GPU parallel performance increases as the grid size increases. The results indicate the promise of the GPU-accelerated LBM for modeling mass transport phenomena in shallow water flows.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Shallow Water Fluid Flow | Louisiana State University</strong>\" ]\r\n\r\n<strong>Authors:</strong> Louisiana State University\r\n<strong>Speedup:</strong> &gt;10X\r\n\r\nA lattice Boltzmann method (LBM) on high performance computing (HPC) environments for three-dimensional shallow water flow fields coupled to mass transport is developed. LBM is an attractive method for solving the multilayered shallow water equations because the extension to multilayer is straight forward with all of the simplicities and advantages of the LBM in mass transport in shallow water flows and the LBM performance on central processing unit (CPU)-based and graphics processing unit (GPU)-based HPC environments.\r\n[/accordion_item][/accordion]\r\n<div id=\"consulting\"></div>\r\n[/content_band]\r\n<div id=\"services\"></div>\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"][column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"]Hire our acceleration gang[/custom_headline]\r\n\r\nHire us to accelerate your code. Or to train your pros. Or even to write new code for your organization!\r\n\r\nWe’ve already helped thousands of organizations speedup their code. We’ve accelerated algorithms, data sets, and challenging problems of all types in the past, and we’re confident that we can accelerate your code too.\r\n\r\n[gap size=\"10%\"][button  type=\"flat\" shape=\"rounded\" href=\"http://meetme.so/arrayfire\" size=\"x-large\" ]Schedule a consultation[/button][/column][column type=\"one-half\" last=\"true\" class=\"center-text\"][gap size=\"5%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Bat-signal-e1391790016951.png\"][/column] [gap size=\"7%\"]\r\n\r\n[column type=\"one-third\" class=\"center-text\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/04/LFG-B-HORZ_202_K-e1396448935778.jpg\"][line]Lincoln Financial Group ported their CPU code (C/C++) to CUDA, and this enabled them to speed up the necessary financial calculations. Their primary objective was to reduce the time taken to run this code. Before porting to CUDA, they required 10-12 hours to run the entire code. After porting to CUDA, they were able to do the same work in about 30 minutes.[/column][column type=\"one-third\" class=\"center-text\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/reveal_logo-e1396449044651.jpg\"][line]Reveal Imaging, an SAIC company, uses ArrayFire in developing threat-detection products for transportation systems—such as cargo and baggage screening in airports—and in securing facilities and public events.[/column][column type=\"one-third\" last=\"true\" class=\"center-text\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/04/1800contactlogo.png\"][line]The Glasses.com app relies on computer vision to recognize the features of a user’s face. The application then generates an accurate, high-fidelity, three-dimensional model of that face, and virtually places selected frames on the image.[/column]\r\n<div id=\"starterpackage\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n\r\n[column type=\"one-half\" last=\"false\" fade=\"true\" fade_animation=\"in-from-left\" ][gap size=\"10%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/comingatyou.png\"][/column][column type=\"one-half\" last=\"true\"] [custom_headline type=\"left\" level=\"h3\"]Starter Package ($500)* [/custom_headline] Hire us for 1-day. We set you up with one engineer dedicated for a full day, as well as support from senior and test engineers throughout the day. Here\'s how it works:\r\n\r\n[icon_list] [icon_list_item type=\"angle-double-right\"]Initial phone call[/icon_list_item] [icon_list_item type=\"angle-double-right\"]You send us your code or algorithm [/icon_list_item] [icon_list_item type=\"angle-double-right\"]We analyze your code for potential GPU benefit[/icon_list_item][icon_list_item type=\"angle-double-right\"]We accelerate as much of the code as is possible within the 1-day effort, applying our extensive GPU software libraries[/icon_list_item][icon_list_item type=\"angle-double-right\"]We produce a final report, along with code[/icon_list_item] [/icon_list] The final report outlines the best approach to follow for full GPU-acceleration of your code.\r\n\r\n&nbsp;\r\n\r\n[button type=\"flat\" shape=\"rounded\" size=\"regular\" href=\"http://sandbox.arrayfire.com/product/consulting-starter-package/\" title=\"Starter Package\"]Buy the Starter Package[/button]\r\n\r\n&nbsp;\r\n\r\n*Limit one (1) per customer.\r\n\r\n[/column]\r\n<div id=\"customcode\"></div>\r\n[/content_band] [content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n\r\n[column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\" ]Coding Work (Custom)[/custom_headline]\r\n\r\n[custom_headline type=\"left\" level=\"h6\" ]Why Choose Us?[/custom_headline] [icon_list] [icon_list_item type=\"angle-double-right\"]Deep experience, already servicing thousands of customers[/icon_list_item] [icon_list_item type=\"angle-double-right\"]Quality work, with leading GPU software [/icon_list_item] [icon_list_item type=\"angle-double-right\"]Efficient delivery, with ArrayFire\'s code base we can deliver results fast[/icon_list_item][icon_list_item type=\"angle-double-right\"]Proven, we make customers happy through faster code[/icon_list_item][/icon_list] [custom_headline type=\"left\" level=\"h6\" ]Our Strengths[/custom_headline] [icon_list] [icon_list_item type=\"angle-double-right\"]Excellence in GPU code[/icon_list_item] [icon_list_item type=\"angle-double-right\"]Well-written, efficient C, C++, Fortran, Java, or .NET [/icon_list_item] [icon_list_item type=\"angle-double-right\"]Application porting and integration[/icon_list_item][icon_list_item type=\"angle-double-right\"]Tuning software to peak hardware performance[/icon_list_item][icon_list_item type=\"angle-double-right\"]Scalability of algorithms to handle enterprise-level programs[/icon_list_item] [/icon_list][button type=\"flat\" shape=\"rounded\" size=\"regular\" href=\"http://meetme.so/arrayfire\" title=\"Tech Consultation\"]Schedule a consultation[/button] [/column][column type=\"one-half\"  fade=\"true\" fade_animation=\"in-from-right\" last=\"true\" ][gap size=\"25%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/Holoham.png\"][/column]\r\n<div id=\"training\"></div>\r\n[/content_band] [content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n\r\n[column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\" ]Training[/custom_headline] Attendees will receive the latest industry knowledge and techniques for GPU computing in CUDA and OpenCL.\r\n\r\nArrayFire offers up to four days of specialized GPU training in CUDA and OpenCL programming. Register for a general course, or schedule a course dedicated for your organization. We can travel to you, or you can travel to our Atlanta office.\r\n\r\nWe recommend that attendees have a working knowledge of C/C++ in order to gain the most from the training courses.\r\n\r\n[/column]\r\n\r\n[column type=\"one-half\" last=\"true\"][gap size=\"8%\"]\r\n<h5><strong>Fee includes:</strong></h5>\r\n[icon_list] [icon_list_item type=\"angle-double-right\"]Instruction by an excellent and interesting expert, with hands-on exercises[/icon_list_item] [icon_list_item type=\"angle-double-right\"]Use of a laptop with CUDA and OpenCL capable GPUs and CPUs [/icon_list_item] [icon_list_item type=\"angle-double-right\"]Choice of Linux or Windows operating system[/icon_list_item][icon_list_item type=\"angle-double-right\"]Printed manual of lecture material[/icon_list_item][icon_list_item type=\"angle-double-right\"]Electronic copy of programming exercises[/icon_list_item][/icon_list]\r\n\r\n[button type=\"flat\" shape=\"rounded\" size=\"regular\" href=\"http://sandbox.arrayfire.com/product-category/training/\" title=\"Register\"]Register for Training[/button][/column]\r\n\r\n[column type=\"one-half\" fade=\"true\" fade_animation=\"in-from-left\" class=\"center-text\" ][gap size=\"30%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/Professor-AF_Exported-e1395436350363.png\" ][/column][column type=\"one-half\" last=\"true\"][gap size=\"20%\"][custom_headline type=\"left\" level=\"h3\" looks_like=\"h3\"]Upcoming Courses[/custom_headline]\r\n<table>\r\n<tbody>\r\n<tr>\r\n<th>CUDA</th>\r\n<th>OpenCL</th>\r\n</tr>\r\n<tr>\r\n<td> Atlanta, GA</td>\r\n<td> Atlanta, GA</td>\r\n</tr>\r\n<tr>\r\n<td> Boston, MA</td>\r\n<td> Boston, MA</td>\r\n</tr>\r\n<tr>\r\n<td> New York City, NY</td>\r\n<td> New York City, NY</td>\r\n</tr>\r\n<tr>\r\n<td> Houston, TX</td>\r\n<td> Houston, TX</td>\r\n</tr>\r\n<tr>\r\n<td> San Jose, CA</td>\r\n<td> San Jose, CA</td>\r\n</tr>\r\n<tr>\r\n<td> Albuquerque, NM</td>\r\n<td> Albuquerque, NM</td>\r\n</tr>\r\n<tr>\r\n<td> Baltimore/Washington DC</td>\r\n<td> Baltimore/Washington DC</td>\r\n</tr>\r\n<tr>\r\n<td> San Diego, CA</td>\r\n<td> San Diego, CA</td>\r\n</tr>\r\n</tbody>\r\n</table>\r\n[/column][gap size=\"10%\"]\r\n\r\n[custom_headline type=\"left\" level=\"h3\"]Training Course Syllabus[/custom_headline] [column type=\"one-half\"] [custom_headline type=\"left\" level=\"h5\"  accent=\"false\"]Day 1, Introduction[/custom_headline] <strong>Lectures:</strong>\r\nGPU Computing Overview\r\nThe Programming Model\r\nBasic Dataset Mapping Techniques\r\nLibraries, ArrayFire\r\nProfiling Tools\r\n\r\n<strong>Practice:</strong>\r\nA Simple Kernel\r\nEquivalent ArrayFire Example\r\nUsing Libraries\r\nMonte Carlo Pi Estimation\r\nTiming and ArrayFire\r\nDebugging Code\r\n\r\n[custom_headline type=\"left\" level=\"h5\" accent=\"false\"]Day 3, Multi-GPU[/custom_headline] <strong>Lectures:</strong>\r\nMulti-GPU Use Cases\r\nMulti-GPUs: Contexts\r\nExisting Libraries\r\nScaling Across Multiple GPUs\r\n\r\n<strong>Practice:</strong>\r\nOut of Core Problems: Matrix Multiply\r\nTask Level Parallelism: Optimization\r\nArrayFire Multi-GPU[/column]\r\n\r\n[column type=\"one-half\" last=\"true\"] [custom_headline type=\"left\" level=\"h5\" accent=\"false\"]Day 2, Optimization[/custom_headline] <strong>Lectures:</strong>\r\nArchitecture: Grids, Blocks, and Threads\r\nMemory Model: Global, Shared, and Constant Memory\r\nAdvanced Mapping Techniques\r\nStreams: Asynchronos Launches and Concurrent Execution\r\nArrayFire: Lazy Evaluation and Code Vectorization\r\n\r\n<strong>Practice:</strong>\r\nMatrix Transpose\r\nOptimization Using Shared Memory\r\nMedian Filter\r\nOptimization Using Constant Memory\r\nStream Example\r\nArrayFire Example: Nearest Neighbor Algorithm\r\n\r\n[custom_headline type=\"left\" level=\"h5\" accent=\"false\"]Day 4, Algorithm Problems[/custom_headline]\r\n\r\n<strong>Lectures and Practice:</strong>\r\nReductions\r\nScan Algorithms\r\nSort\r\nConvolution\r\nCustomer-Specific Problem [/column][/content_band]','Home','','inherit','open','closed','','245-revision-v1','','','2014-04-29 19:28:28','2014-04-29 19:28:28','',245,'http://sandbox.arrayfire.com/245-revision-v1/',0,'revision','',0),(5436,7,'2014-04-29 19:53:00','2014-04-29 19:53:00','[content_band inner_container=\"true\" no_margin=\"true\" border=\"none\" padding_top=\"40px\" padding_bottom=\"40px\"][column type=\"two-fifths\"]\r\n\r\n[custom_headline type=\"left\" level=\"h3\"]If you want faster code, you\'ve come to the right place.[/custom_headline][gap size=\"15%\"][button  type=\"flat\" shape=\"rounded\" href=\"http://www.sandbox.arrayfire.com/docs/installation.htm\" size=\"x-large\" block=\"true\"]Download ArrayFire[/button]\r\n\r\n[gap size=\"10%\"]\r\n\r\n[button  type=\"flat\" block=\"true\" shape=\"rounded\" href=\"http://www.meetme.so/arrayfire\" size=\"x-large\" ]Schedule a consultation[/button]\r\n\r\n[/column][column type=\"three-fifths\" last=\"true\"][gap size=\"7%\"]\r\n<div class=\"wistia_embed\" id=\"wistia_rj2bar3xxp\" style=\"width: 640px; height: 388px;\"></div>\r\n<script charset=\"ISO-8859-1\" type=\"text/javascript\" src=\"//fast.wistia.com/assets/external/E-v1.js\"></script><script type=\"text/javascript\">// <![CDATA[\r\nwistiaEmbed = Wistia.embed(\"rj2bar3xxp\");\r\n// ]]></script>[/column]\r\n<div id=\"arrayfire\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"][column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"]Faster code[/custom_headline]\r\n\r\nArrayFire is a fast, hardware-neutral software library for GPU computing with an easy-to-use API. Its array-based function set makes GPU programming simple. A few lines of code in ArrayFire can replace dozens of lines of raw GPU code, saving you valuable time and lowering development costs.\r\n\r\n[gap size=\"10%\"][button  type=\"flat\" shape=\"rounded\" href=\"http://www.sandbox.arrayfire.com/docs/installation.htm\" size=\"x-large\" ]Download ArrayFire[/button][/column][column type=\"one-half\" last=\"true\" class=\"center-text\"][gap size=\"5%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Triumvirate_Exported.png\"][/column] [gap size=\"5%\"]\r\n\r\n[column type=\"one-third\" class=\"center-text\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/04/Googlelogo-e1396387097279.png\"][line]Video content analysis is the basis for categorizing videos and enabling search by content. Google used ArrayFire to extract motion features in video, improving performance by substantially accelerating the solution of the L1-regularized least-squares optimization problem.[/column][column type=\"one-third\" class=\"center-text\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/04/Koch-Industries-e1396387359637.jpg\"][line]Andrew Shin, Market Risk Manager of Koch Supply &amp; Trading, achieves significant performance increases on option pricing algorithms using ArrayFire software, \"My buddy and I are, at best, novice programmers and we couldn\'t imagine having to figure out how to code all this in CUDA.\"[/column][column type=\"one-third\" last=\"true\" class=\"center-text\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/04/nasa-e1396387230473.png\"][line]The main thrust of this research was improving Mars rover image compression via GPUs and genetic algorithms. With ArrayFire software and GPUs, the researchers were able to achieve 5X speedups on the larger data sizes.[/column]\r\n<div id=\"hardware\"></div>\r\n[/content_band]\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n\r\n[column type=\"one-half\"][gap size=\"15%\"]\r\n<p style=\"text-align: center;\"><img class=\"aligncenter\" alt=\"CUDA logo\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/CUDA-logo.jpg\" width=\"231\" height=\"140\" /></p>\r\n<img class=\"aligncenter\" alt=\"OpenCL\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/OpenCLLogo_678x452.png\" width=\"326\" height=\"217\" />\r\n\r\n[/column][column type=\"one-half\" last=\"true\"][gap size=\"10%\"]\r\n\r\n[custom_headline type=\"left\" level=\"h3\"] ArrayFire for CUDA and OpenCL[/custom_headline]\r\n\r\nArrayFire supports CUDA-capable NVIDIA GPUs and most OpenCL devices, including AMD GPUs/APUs and Intel Xeon Phi co-processors. It also supports mobile OpenCL devices from ARM, Qualcomm, and others.\r\n\r\n<span style=\"line-height: 1.5em;\">ArrayFire is a high-performance software library designed for maximum productivity and speed without the hassle of writing difficult low-level device code. Each of ArrayFire\'s functions has been hand-tuned by our CUDA and OpenCL experts.</span>\r\n\r\n[/column]\r\n<div id=\"mobile\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n[column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"  ]Mobile GPU Computing[/custom_headline]\r\n\r\nMobile GPUs offer accelerated performance. If you would like to use ArrayFire in a mobile application or if you would like to hire our mobile acceleration services, email us at <a href=\"mailto:sales@arrayfire.com\" target=\"_blank\">sales@arrayfire.com</a> and include a description of your application.\r\n\r\nOur clients have achieved between 5X to 30X speed boosts for convolutions and other compute functions on mobile devices. It enables:[icon_list][icon_list_item type=\"angle-double-right\"]Real-time video processing[/icon_list_item][icon_list_item type=\"angle-double-right\"]Better augmented reality [/icon_list_item][icon_list_item type=\"angle-double-right\"]Better computational photograph[/icon_list_item][icon_list_item type=\"angle-double-right\"]Faster data processing[/icon_list_item][/icon_list]\r\n\r\nAll mobile devices have a GPU which can deliver greater compute throughput than the CPU. Why not use the GPU to make your app faster?[/column][column type=\"one-half\" fade=\"true\" last=\"true\" fade_animation=\"in-from-right\" class=\"center-text\"][gap size=\"10%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/mobile_Exported1-e1395437261846.png\"][/column]\r\n<div id=\"documentation\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"][column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"]Documentation[/custom_headline]\r\n\r\n<strong>ArrayFire for C, C++, and Fortran\r\n</strong>Open the hood—take a look at the beautiful nitty-gritty.\r\n\r\n<strong></strong>[icon type=\"angle-double-right\"] <a href=\"http://www.sandbox.arrayfire.com/docs/\" target=\"_blank\">CUDA &amp; OpenCL C/C++</a>\r\n\r\n<strong>Functions\r\n</strong>Hundreds of functions, hand-tuned and optimized by our engineers.\r\n\r\n[icon type=\"angle-double-right\"] <a title=\"ArrayFire Functions\" href=\"http://www.sandbox.arrayfire.com/docs/modules.htm\">ArrayFire Functions</a>\r\n\r\n<strong>User Forums</strong>\r\nEvery post gets a response from ArrayFire engineers.\r\n\r\n[icon type=\"angle-double-right\"] <a href=\"http://forums.accelereyes.com/\" target=\"_blank\">User Forums</a>\r\n\r\n[/column][column class=\"center-text\" type=\"one-half\" last=\"true\" fade=\"true\" fade_animation=\"in-from-right\" ][gap size=\"5%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/gears1.png\"][/column]\r\n<div id=\"benchmarks\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n[column type=\"one-half\" fade=\"true\" fade_animation=\"in-from-left\" ][gap size=\"5%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/Benchmark-guy-torso-opposite-e1392155948298.png\"][/column]\r\n\r\n[column type=\"one-half\" last=\"true\"][custom_headline type=\"left\" level=\"h3\" ]Benchmarks[/custom_headline]\r\n\r\nAll benchmarks were performed on a NVIDIA Tesla C2050 with an Intel i7-950 processor. The benchmarks compare ArrayFire with several popular CPU-based acceleration libraries, including <a href=\"http://software.intel.com/en-us/articles/intel-mkl/\" target=\"_new\">Intel Math Kernel Library</a>, <a href=\"http://software.intel.com/en-us/articles/intel-ipp/\" target=\"_new\">Intel Integrated Performance Primitives</a>, <a href=\"http://eigen.tuxfamily.org/index.php?title=Main_Page\" target=\"_new\">Eigen</a>, and <a href=\"http://arma.sourceforge.net/\" target=\"_new\">Armadillo</a>.[/column]\r\n<p style=\"text-align: center;\">[column type=\"one-fifth\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"three-fifths\"][tab_nav type=\"four-up\"][tab_nav_item title=\"Base\" active=\"true\"][tab_nav_item title=\"Linear Algebra\" active=\"\"][tab_nav_item title=\"Convolution\" active=\"\"][tab_nav_item title=\"Utility\" active=\"\"][/tab_nav][tabs][tab active=\"true\"]<img class=\"aligncenter  wp-image-351\" alt=\"Matrix Multiply\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/matrix_multiply-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-352\" alt=\"Matrix Transpose\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/matrix_transpose-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-349\" alt=\"FFT\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/fft-1024x730.png\" width=\"491\" height=\"350\" />[/tab][tab]<img class=\"aligncenter  wp-image-350\" alt=\"LU\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/lu-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-357\" alt=\"SVD\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/svd-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-354\" alt=\"Solve\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/solve-1024x730.png\" width=\"491\" height=\"350\" />[/tab][tab]<img class=\"aligncenter  wp-image-348\" alt=\"Convs\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/convs-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-347\" alt=\"Conv\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/conv-1024x730.png\" width=\"491\" height=\"350\" />[/tab][tab]<img class=\"aligncenter  wp-image-356\" alt=\"sum\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/sum-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-355\" alt=\"sort\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/sort-1024x730.png\" width=\"491\" height=\"350\" />[line]<img class=\"aligncenter  wp-image-353\" alt=\"scan\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/scan-1024x730.png\" width=\"491\" height=\"350\" />[/tab][/tabs][/column][column type=\"one-fifth\" last=\"true\"]<span style=\"color: #ffffff;\">.</span>[/column]</p>\r\n\r\n<div id=\"free\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n\r\n[column type=\"one-half\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"one-fourth\"]<span style=\"color: #ffffff;\">.</span>[custom_headline type=\"center\"  level=\"h3\" class=\"mtn\"]ArrayFire Free[/custom_headline][/column][column type=\"one-fourth\" last=\"true\"]<span style=\"color: #ffffff;\">.</span>[/column][column type=\"one-fourth\"  fade=\"true\" fade_animation=\"in-from-left\" ][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/right-leaning-e1391788779101.png\"][/column][column type=\"one-fourth\"]\r\n<table>\r\n<tbody>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Functions[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Basic Operations</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Arithmetic</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Signal Processing</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Image Processing</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Statistics</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Visualization</td>\r\n</tr>\r\n</tbody>\r\n</table>\r\n[gap size=\"17%\"][button type=\"flat\" block=\"true\" shape=\"rounded\" size=\"large\"  href=\"http://www.sandbox.arrayfire.com/docs/installation.htm\"]Download ArrayFire[/button] [/column][column type=\"one-fourth\"]\r\n<table>\r\n<tbody>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Hardware[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] CUDA</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] OpenCL</td>\r\n</tr>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Languages[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] C/C++</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Fortran</td>\r\n</tr>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Advanced[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td> [icon type=\"check-circle\" style=\"color: #8cc540;\"] GFOR Loop</td>\r\n</tr>\r\n</tbody>\r\n</table>\r\n[/column][column type=\"one-fourth\" last=\"true\"]\r\n<table>\r\n<tbody>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Platforms[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Windows</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Linux</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] Mac</td>\r\n</tr>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Data Types[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td>[icon type=\"check-circle\" style=\"color: #8cc540;\"] All types</td>\r\n</tr>\r\n<tr>\r\n<td>[custom_headline type=\"center\" level=\"h5\"]Support[/custom_headline]</td>\r\n</tr>\r\n<tr>\r\n<td> [icon type=\"check-circle\" style=\"color: #8cc540;\"] Forums</td>\r\n</tr>\r\n</tbody>\r\n</table>\r\n<div id=\"licensing\"></div>\r\n[/column][gap size=\"8%\"]\r\n\r\n[pricing_table id=\"pricing\" columns=\"3\"][pricing_table_column  featured=\"false\" title=\"ArrayFire Developer\" currency=\"$\" price=\"499 / year\" interval=\"$149 / year (Academic)\"] [icon_list] [icon_list_item type=\"star\" ]Dedicated license [/icon_list_item] [icon_list_item  type=\"times-circle\"] Starts at 2 GPUs or devices [/icon_list_item] [icon_list_item type=\"times-circle\"] Linear algebra [/icon_list_item] [icon_list_item type=\"times-circle\"] Sparse matrices [/icon_list_item][icon_list_item type=\"times-circle\"] Phone support [/icon_list_item][icon_list_item type=\"times-circle\"] Premium support &amp; consulting [/icon_list_item][/icon_list] [button href=\"http://sandbox.arrayfire.com/shop\"] Purchase [/button] [/pricing_table_column] [pricing_table_column featured=\"true\" featured_sub=\"Most Popular\" title=\"ArrayFire Pro\" currency=\"$\" price=\"1,499 / year\" interval=\"$525 / year (Academic)\"] [icon_list] [icon_list_item type=\"star\"] Dedicated license [/icon_list_item] [icon_list_item type=\"star\"] Starts at 2 GPUs or devices [/icon_list_item] [icon_list_item type=\"star\"] Linear algebra [/icon_list_item][icon_list_item type=\"star\"] Sparse matrices [/icon_list_item][icon_list_item type=\"times-circle\"] Phone support [/icon_list_item][icon_list_item type=\"times-circle\"] Premium support &amp; consulting [/icon_list_item] [/icon_list] [button href=\"http://sandbox.arrayfire.com/shop\"]Purchase [/button] [/pricing_table_column] [pricing_table_column featured=\"false\" title=\"ArrayFire Enterprise\" currency=\"$\" price=\"2,999 / year\" interval=\"$1,049 / year (Academic)\"] [icon_list] [icon_list_item type=\"star\"] Dedicated license [/icon_list_item] [icon_list_item type=\"star\"] Starts at 2 GPUs or devices [/icon_list_item] [icon_list_item type=\"star\"] Linear algebra [/icon_list_item][icon_list_item type=\"star\"]Sparse matrices [/icon_list_item][icon_list_item type=\"star\"] Phone support[/icon_list_item][icon_list_item type=\"star\"]Premium support &amp; consulting [/icon_list_item][/icon_list] [button href=\"http://sandbox.arrayfire.com/shop\"] Purchase [/button] [/pricing_table_column] [/pricing_table]\r\n<div id=\"whitepapers\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n\r\n[column type=\"one-half\"][gap size=\"20%\"][image type=\"thumbnail\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/wp2.jpg\"][button href=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/03/arrayfire_matrix_computations_chrzeszczyk.pdf\" shape=\"rounded\" size=\"regular\" block=\"true\"]Download <em>Matrix Computations on the GPU with ArrayFire for C/C++</em>[/button][/column][column type=\"one-half\" last=\"true\"]\r\n\r\n[custom_headline type=\"left\" level=\"h3\" ]Whitepapers[/custom_headline]\r\n\r\n<img alt=\"Whitepaper 1\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/Whitepaper-1.png\" width=\"466\" height=\"374\" />\r\n\r\n&nbsp;\r\n\r\n[/column][gap size=\"10%\"]\r\n\r\n[column type=\"one-half\"]<img alt=\"Whitepaper 2\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/Whitepaper-2.png\" width=\"442\" height=\"304\" />[/column][column type=\"one-half\" last=\"true\"][image type=\"thumbnail\" src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/wp1.jpg\"][button href=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/03/arrayfire_whitepaper.pdf\" shape=\"rounded\" size=\"regular\"  block=\"true\" float=\"right\"]Download <em>High-level GPU Computing in C, C++, and Fortran</em>[/button][/column]\r\n<div id=\"casestudies\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n\r\n[column type=\"one-half\"][gap size=\"12%\"][custom_headline type=\"left\" level=\"h3\" ]Case Studies[/custom_headline]\r\n\r\nLearn how ArrayFire has worked in real code, including applications in academia, finance, government, life sciences, manufacturing, media, and oil &amp; gas.[/column][column type=\"one-half\" last=\"true\" fade=\"true\" fade_animation=\"in-from right\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/model-A.png\"][/column][custom_headline type=\"left\" level=\"h5\"]Academia [/custom_headline][accordion][accordion_item title=\"<strong>Accelerating LTE Simulation | Tsinghua University</strong>\"]\r\n\r\n<strong>Authors:</strong> Yuan Gao, Yin Sun, Chun Hui Zhou, Xin Su, Xi Bin Xu, Shi Dong Zhou, Tsinghua University\r\n<strong>Speedup:</strong> 3X\r\n\r\nFast simulations are a driving force in several research projects. However, the accompanying long simulation times can tend to be a drag in many of these projects. In this article, we shall bring up the example of the work on 3GPP LTE System Simulation by Yuan Gao et al (from Tsinghua University, Beijing) and demonstrate how the use of ArrayFire software can significantly improve the simulator performance and lead to faster validation times in simulation projects.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>High Performance Compressive Sensing | Rice University</strong>\"]\r\n\r\n<strong>Authors:</strong> Nabor Reyna and Wotao Yin from Rice University\r\n<strong>Speedup:</strong> 5X\r\n\r\nThis work deals with reconstruction of signals using partial Fourier matrices (RecPF). The major computational components of the algorithm involve shrinkage and FFTs. ArrayFire software is employed to accelerate this compute-heavy code.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Power System Simulations | Indian Institute of Technology, Roorkee, India</strong>\"]\r\n<strong>Authors:</strong> Indian Institute of Technology, Roorkee\r\n<strong>Speedup:</strong> 35X\r\n\r\nPower flow studies are one of the most important aspects of power system planning and operation. The power flow reveals the sinusoidal steady state characteristics of the entire system - voltages, real and reactive power generated, and absorbed and line losses- elucidating the voltage magnitudes and angles at each bus, the generation of each generating unit, and real and reactive power losses in the system. All this is necessary to ensure the security, economy, and control of electrical energy distribution. Learn how ArrayFire software can deliver magnitudes of performance improvement over CPU-based solutions.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Antenna Array Simulations | University of Naples Federico II</strong>\"]\r\n\r\n<strong>Authors:</strong> A. Capozzoli, C. Cucio, A. Liseno at University of Naples Federico II\r\n<strong>Speedup:</strong> 24X\r\n\r\nAntenna array design involves repeated simulation to tune the many parameters involved, and waiting around for simulations to finish is no fun. Offloading the optimization problem onto the GPU cuts that time down significantly. In their recent paper, Capozzoli, Curcio, and Liseno of University of Naples Federico II demonstrated how a simple modification to their echo generator array simulation took advantage of the GPU to bring immediate speedups.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Laplace Transform Inversion | Acunum Algorithms and Simulations</strong>\"]\r\n\r\n<strong>Authors:</strong> Patrick Kano and Moysey Brio at Acunum Algorithms and Simulations\r\n<strong>Speedup:</strong> 3.8X\r\n\r\nThe numerical inversion of the Laplace transform is a long standing problem due its implicit ill-posedness. Patrick Kano and Moysey Brio of Acunum Algorithms and Simulations, with their experience in computational methods and algorithm development, found a solution that not only works, but is very fast.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Compressed Sensing for Image Reconstruction | College of Engineering, Roorkee, India</strong>\"]\r\n\r\n<strong>Authors:</strong> Kuldeep Yadav, Ankush Mittal, M. A. Ansar, and Avi Srivastava, College of Engineering, Roorkee, India\r\n<strong>Speedup:</strong> 8X\r\n\r\nCompressed sensing is very critical in the areas of medical image reconstruction, image acquisition or sensor networks. An algorithm for compressed sensing developed using a Basis Pursuit Algorithm shows over 8X speedup when run on an NVIDIA GPU.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Fat/Water Reconstruction for Medical Images | Case Western Reserve University</strong>\"]\r\n\r\n<strong>Authors:</strong> D. H. Johnson, S. Narayan, C. A. Flask, and D. L. Wilson, Case Western Reserve University\r\n<strong>Speedup:</strong> 11.6X\r\n\r\nCase Western Reserve University researchers turned to GPUs running ArrayFire software to develop a fast and robust version of the \"Iterative Decomposition of water and fat with an Echo Asymmetry and Least-squares\" (IDEAL) reconstruction algorithm. This algorithm uses a lot of Image Processing algorithms for reconstruction, and was shown to achieve very high speedups.\r\n[/accordion_item]\r\n\r\n[/accordion]\r\n<h5>Finance</h5>\r\n[accordion][accordion_item title=\"<strong>Option Pricing | Koch Supply and Trading</strong>\"]\r\n\r\n<strong>Authors:</strong> Koch Supply &amp; Trading\r\n<strong>Speedup:</strong> 51.8X\r\n\r\nAndrew Shin, Market Risk Manager of Koch Supply &amp; Trading, achieves significant performance increases on option pricing algorithms using ArrayFire software to accelerate his code with GPUs. Andrew says, \"My buddy and I are, at best, novice programmers and we couldn\'t imagine having to figure out how to code all this in CUDA.\" But he found ArrayFire software to be straight-forward. With these results, he says he can see ArrayFire software and GPUs populating Koch\'s mark-to-futures cube, which contains its assets, simulations, and simulated asset prices.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>GPU Computing in Automated Trader | Automated Trader</strong>\"]\r\n\r\n<strong>Authors:</strong> Automated Trader\r\n<strong>Speedup:</strong> 37.5X\r\n\r\nThe Q1 2012 issue of Automated Trader contains an excellent Mashup piece reviewing software for algorithmic trading. The article provides a wonderful glimpse into the 1-2 month adventure of Andy Webb, Automated Trader.s Founder, and Wrecking Crew building a fast trading platform from several technologies. The full trading platform they built was quite extensive. The part that caught our eye was the core computational component of the pipeline. That component involved permuting 1,000 potential pairs with cointegration tests for 350 time windows on each potential pair.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>GPUs in Quantitative Analytics and Finance | Private Bank</strong>\"]\r\n\r\nThe world of Quantitative finance is all about getting accurate results really, really fast. ArrayFire is working with one of the largest banks in Spain to maximize their output using GPUs. Click the link below for an overview of the uses of GPU computing in finance.[/accordion_item][/accordion]\r\n<h5>Government</h5>\r\n[accordion][accordion_item title=\"<strong>Powering Mars Research | NASA and UAA in Anchorage</strong>\" ]\r\n\r\n<strong>Authors:</strong> NASA and UAA in Anchorage\r\n<strong>Speedup:</strong> 5X\r\n\r\nThe main thrust of this research is improving mars rover image compression via GPUs and genetic algorithms. With ArrayFire software and GPUs, the researchers were able to achieve 5X speedups on the larger data sizes. The algorithm works by pairing neighboring pixels with a random one and then adjusting the random pixel based on whether it incrementally improves the original image. Babb described the algorithm as an embarrassingly parallel process, ideally suited to GPU acceleration. He estimates he has been able to achieve a 20 to 30 percent error reduction in subjects like fingerprints and satellite imagery.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Radar Image Formation | System Planning Corporation</strong>\"]\r\n\r\n<strong>Authors:</strong> Gary Rubin and Earl Sager - System Planning Corporation\r\n<strong>Speedup:</strong> ~45X\r\n\r\nRadar imaging is computationally intensive. As a result, many imaging algorithms apply FFT-based approximations. While efficient, these algorithms sacrifice data fidelity for speed. Other algorithms better preserve information, but are often too slow for many applications. At System Planning Corporation (SPC) , we have implemented a SAR/ISAR imaging routine based on the Backprojection algorithm. Using ArrayFire software, we have demonstrated speedups of roughly 45x for large datasets.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Radar Clutter Reduction | System Planning Corporation</strong>\"]\r\n\r\n<strong>Authors:</strong> David Berger and Gary Rubin - System Planning Corporation\r\n<strong>Speedup:</strong> 5-10X\r\n\r\nSystem Planning Corporation (SPC) uses ArrayFire software to accelerate radar processing algorithms. The system processes raw data from marine navigation radars using a variety of thresholding techniques to extract real targets from clutter. This involves highly data-parallel processing in which each radar pulse is subjected to the same computations; very few operations occur across multiple pulses. Using ArrayFire software, SPC has achieved 10x speed improvements relative to a Core i7-920 CPU and 5x improvements relative to a realtime DSP implementation.[/accordion_item]\r\n\r\n[accordion_item title=\"<strong>Novel Algorithms for Linear Algebra | SAIC</strong>\" ]\r\n\r\n<strong>Authors:</strong> Nolan Davis and Daniel Redig, SAIC\r\n<strong>Speedup:</strong> 3.5X\r\n\r\nNolan Davis and Daniel Redig at SAIC recently presented work on Hybrid GPU/Multicore Solutions for Large Linear Algebra Problems where they developed a novel algorithm for LU decomposition, one of the most important routines in linear algebra. They presented a Hybrid CPU/GPU computing approach, where problems too large to fit in GPU memory can also be solved faster than using only the CPU.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Geolocation | BAE Systems</strong>\"]\r\n\r\n<strong>Authors:</strong> BAE Systems\r\n<strong>Speedup:</strong> 17X\r\n\r\nGeolocation is the identification of the real-world geographic location of a target of interest. In this application, the system receives the signal with an array of several antennas and computes the direction of arrival of the radio energy by measuring the time difference of arrival (or the phase difference) at the different antennas.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Tsunami Modeling | University of Minnesota, Boise State, Saint Scholastica, and NCAR</strong>\"]\r\n\r\n<strong>Authors:</strong> University of Minnesota, Boise State, Saint Scholastica, and NCAR\r\n<strong>Speedup:</strong> 3-5X\r\n\r\nNatural catastrophic disasters like tsunamis commonly strike with little warning. For most people, tsunamis are underrated as major hazards. People sometimes wrongly believe that they occur infrequently and only along distant coasts. Tsunamis are usually caused by earthquakes. Seismic signals can give some margin of warning since the speed of tsunami waves travels at 1/30 the speed of seismic waves. Still there is little time between the creation of the tsunami and its impact making fast processing critical to producing effective warning systems. ArrayFire software was used to run an RBF simulation on the GPU with a time to solution not available by other alternatives.\r\n[/accordion_item][/accordion]\r\n<h5>Life Sciences</h5>\r\n[accordion][accordion_item title=\"<strong>Parallelized Gene Predictors | University of Quebec</strong>\" ]\r\n\r\n<strong>Authors:</strong> University of Quebec\r\n<strong>Speedup:</strong> 43X\r\n\r\nComputerized approaches to studying the human genome are challenged by the exploding amount of data, which doubles roughly every 6 months. In order to deal with this burgeoning datasets, demands for faster processing power continue to arise. This work focuses on predicting genes using frequency analysis with FFTs and with an equivalent technique known as Goertzel\'s algorithm. In these applications, the emphasis of this paper is to propose tools to geneticists and molecular biologists for the prediction or identification of new genes using existing complementary strategies. The criteria for these tools are speed, reliability, accuracy and ease of use, thus requiring little training.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Pathology Advances with GPUs | Northeastern University</strong>\" ]\r\n\r\n<strong>Authors:</strong> Laboratory for Spectral Diagnosis at Northeastern University\r\n<strong>Speedup:</strong> 100X+\r\n\r\nOne element of the hyperspectral image analysis workflow that requires more than a traditional desktop workstation or personal computer is Hierarchical Cluster analysis (HCA). HCA requires a large amount of data space and substantial computation time (~11 hours) for typical datasets using a single processor personal computer. Rather than following the traditional approach of moving to a lower level programming language like C or C++ and complex parallel programming paradigms such as OpenMP or the Massage Passing Interface (MPI), the lab utilized graphics processing units, or GPUs, and the ArrayFire software platform. The solution allowed the lab to dramatically increase the performance of the analysis while substantially decreasing the amount of calendar time to reach the desired results.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Hepatitis C Virus - Mutation Modeling | Centers for Disease Control and Prevention</strong>\" ]\r\n\r\n<strong>Authors:</strong> CDC Research and Development Team\r\n<strong>Speedup:</strong> ~20X\r\n\r\nThis case study provides a look at biological research regarding coordinated mutations of the Hepatitis C Virus (HCV). ArrayFire provided collaborative R&amp;D resources and greatly improved the speed of this HCV research with the use of parallelization, reducing the computing time from 40 days to less than 1 day. Most importantly, the conclusion of the case study illustrates the the relative price-performance of personal supercomputers that leverage GPUs and ArrayFire software provides a compelling solution versus other architectures and approaches.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Accelerating the SPM Package for Neuroimaging | Georgia Institute of Technology</strong>\" ]\r\n\r\n<strong>Authors:</strong> Georgia Institute of Technology\r\n<strong>Speedup:</strong> 3.5X\r\n\r\nThe Georgia Tech team explores the value of ArrayFire software and GPUs for fMRI workflows within the popular SPM - Statistical Parametric Mapping software widely used in neuroscience research.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Medical Image Compression | Indian Institute of Technology, Roorkee, India</strong>\" ]\r\n\r\n<strong>Authors:</strong> Jaideep Singh, Ipseeta Aruni, R. Balasubramanian - IIT - Roorkee, India\r\n<strong>Speedup:</strong> 38X\r\n\r\nThis study presents the acceleration of Haar wavelet-based image compression algorithm for medical imaging on the Graphics Processing Unit (GPU) using ArrayFire software. Due to bandwidth and image size constraints of medical imaging systems, image compression plays a vital role in reducing the bit rate of transmission or storage. Wavelet-based image compression provides the most promising approach for high quality image compression.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Brain Displacement | Spencer Technologies</strong>\"]\r\n\r\n<strong>Authors:</strong> Spencer Technologies\r\n<strong>Speedup:</strong> 12X\r\n\r\nSpencer describes how ArrayFire software facilitates the development of fast algorithms enabling observation of brain displacement across depth with sampling density that far surpasses previous benchmarks.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Multidimensional Scaling for Genomics | Leibniz Institute of Plant Genetics and Crop Plant Research</strong>\" ]\r\n\r\n<strong>Authors:</strong> Leibniz Institute of Plant Genetics and Crop Plant Research\r\n<strong>Speedup:</strong> 20-35X\r\n\r\nMultidimensional scaling (MDS) is a general computing technique to turn a distance matrix into a set of reconstructed points with pair-wise relationships approximating the original distances by points located in a usually low-dimensional space. ArrayFire software is used to enhance execution of the HiT-MDS procedure and delivers considerable performance improvement.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Drug Delivery Model | Georgia Institute of Technology</strong>\"]\r\n\r\n<strong>Authors:</strong> Georgia Institute of Technology\r\n<strong>Speedup:</strong> 70X\r\n\r\nIn this work, the researchers simulate the delivery of a novel nanoparticle chemotherapy drug to cancerous tissue. Simulation allows scientists to predict experimental outcomes and thus reduce the cost of development and time to clinical relevance. The simulation model includes blood vessels, tumor cells, and healthy cells and an engine to calculate the spatial distributions of both drug and oxygen. ArrayFire software is used to speed up the diffusion calculations for the drug and oxygen within the tissue.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Biomedical Infrared Spectroscopy | University of Manchester and Nofima Mat, Norway</strong>\" ]\r\n\r\n<strong>Authors:</strong> University of Manchester and Nofima Mat, Norway\r\n<strong>Speedup:</strong> Hours of runtime reduction\r\n\r\nThe authors present an iterative algorithm that applies full Mie scattering theory and avoids noise accumulation in their iterative algorithm by integrating a curve-fitting step. ArrayFire software along with NVIDIA GPUs are leveraged to reduce the time added by the curve-fitting step.\r\n[/accordion_item][/accordion]\r\n<h5>Manufacturing</h5>\r\n[accordion][accordion_item title=\"<strong>Feature Learning on Images | Stanford</strong>\" ]\r\n\r\n<strong>Authors:</strong> Andrew Ng, Stanford University\r\n<strong>Speedup:</strong> Ability to process many images in parallel\r\n\r\nStanford researchers in Andrew Ng\'s group used GPUs and ArrayFire software to speed up their work on Feature Learning Architectures. They decided to use ArrayFire software for this study because of the need to quickly evaluate many architectures on thousands of images. ArrayFire software taps into the immense computing power of GPUs and speeds up research utilizing many images.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Tomography of Vegetation - Filtered Back-Projection and Non-Uniform FFTs | Universita di Napoli Federico II</strong>\" ]\r\n\r\n<strong>Authors:</strong> Drs. Capozzoli, Curcio, di Vico, and Liseno, Universita di Napoli Federico II\r\n<strong>Speedup:</strong> 10X\r\n\r\nIn order to investigate changes of forest biomass, scientists use microwave tomography to image the vegetation. At the smallest scale, individual plants can be imaged to investigate branching and growth, but even synthetic aperture radar can reveal large-scale changes in regional ecology. To the right, you can see the experimental setup to image an individual plant.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Action Recognition with Independent Subspace Analysis | Stanford University</strong>\" ]\r\n\r\n<strong>Authors:</strong> Quoc Le, Will Zou, Serena Yeung, Andrew Ng, Stanford University\r\n<strong>Speedup:</strong> 4.4X\r\n\r\nIn a paper at this year\'s CVPR 2011, entitled \"Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis\", the authors explain how their unsupervised feature learning algorithm competes with other algorithms that are hand crafted or use learned features. For their training purposes, they used a multi-layered stacked convolutional ISA (Independent subspace analysis) network. An ISA is used for learning features from image patches without supervision.\r\n[/accordion_item][/accordion]\r\n<h5>Media and Computer Vision</h5>\r\n[accordion][accordion_item title=\"<strong>Fast Computer Vision with OpenCV and ArrayFire | OpenCV Blogger</strong>\" ]\r\n\r\n<strong>Authors:</strong> OpenCV Blogger\r\n<strong>Speedup:</strong> ~10X\r\n\r\nThe OpenCV library is the defacto standard for doing computer vision and image processing research projects. OpenCV includes several hundreds of computer vision algorithms, aimed for use in realtime vision applications. This case study shows how to use both libraries together. There is a simple example application that demonstrates using OpenCV for webcam access and ArrayFire for some basic processing routines and displaying results.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Video Processing | Google</strong>\" ]\r\n\r\n<strong>Authors:</strong> Google and Stanford\r\n<strong>Speedup:</strong> 10-20X\r\n\r\nVideo content analysis is the basis for categorizing videos and enabling search by content. Growing interest in using sparse-coding methods to extract motion features in video in support of video content analysis led to the application of ArrayFire software to improve performance by substantially accelerating the solution of the L1-regularized least-squares optimization problem.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Action Recognition with Independent Subspace Analysis | Stanford University</strong>\"]\r\n\r\n<strong>Authors:</strong> Quoc Le, Will Zou, Serena Yeung, Andrew Ng, Stanford University\r\n<strong>Speedup:</strong> 4.4X\r\n\r\nIn a paper at this year\'s CVPR 2011, entitled \"Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis\", the authors explain how their unsupervised feature learning algorithm competes with other algorithms that are hand crafted or use learned features. For their training purposes, they used a multi-layered stacked convolutional ISA (Independent subspace analysis) network. An ISA is used for learning features from image patches without supervision.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Music Beat Analysis | Georgia Tech</strong>\"]\r\n\r\n<strong>Authors:</strong> Vidhur Vohra - Georgia Tech\r\n<strong>Speedup:</strong> 15X\r\n\r\nDid you ever wonder how the music visualizer in your media player works? Watching it pulsate in synchrony with the beats of the song is almost as entertaining as listening to the song itself! Researchers have been attempting to detect beats in audio signals for many years, and there are many techniques available, from the simplest (and least accurate) to more complicated algorithms that are highly accurate. All algorithms, though, perform some form of signal processing and frequency analysis, applications highly suited to GPU Computing.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Optimization Methods for Deep Learning | Stanford Artificial Intelligence Laboratory</strong>\" ]\r\n\r\n<strong>Authors:</strong> Stanford Artificial Intelligence Laboratory\r\n<strong>Speedup:</strong> Improved accuracy\r\n\r\nResearchers at SAIL (Stanford Artificial Intelligence Laboratory), have done it again. They have successfully used ArrayFire software to speed up the training part of Deep Learning algorithms. In their paper titled .On Optimization Methods for Deep Learning., they experiment with some of the well known training algorithms and demostrate their scalability across parallel architectures (GPUs as well as multi-machine networks). The algorithms include SGDs (Stochastic Gradient Descent) L-BFGS (Limited BFGS used for solving non-linear problems), CG (Conjugate Gradient).\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Feature Learning on Images | Stanford University</strong>\" ]\r\n\r\n<strong>Authors:</strong> Andrew Ng, Stanford University\r\n<strong>Speedup:</strong> Ability to process many images in parallel\r\n\r\nStanford researchers in Andrew Ng’s group used ArrayFire software to speed up their work on Feature Learning Architectures. They decided to use ArrayFire software for this study because of the need to quickly evaluate many architectures on thousands of images. ArrayFire software taps into the immense computing power of GPUs and speeds up research utilizing many images.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Digital Holography for Imaging | National University of Ireland, Maynooth</strong>\" ]\r\n\r\n<strong>Authors:</strong> Nitesh Pandey, Damien Kelly, Bryan Hennelly and Thomas Naughton from the National University of Ireland, Maynooth\r\n<strong>Speedup:</strong> 17X\r\n\r\nDigital holography is a powerful imaging technique with many new applications like true 3D display. It allows the capture of both amplitude and phase information of the light reflected off the surface of 3D objects. Researchers at the National University of Ireland, Maynooth are developing techniques based on digital holography for 3D display applications.\r\nReconstruction of large digital holograms can be computationally intensive to generate on CPUs, but GPUs running ArrayFire software offer amazing possibilities.\r\n[/accordion_item][/accordion]\r\n<h5>Oil and Gas</h5>\r\n[accordion][accordion_item title=\"<strong>3D Mantle Convection - Geodynamics | Boise State, University of Colorado, University of Minnesota</strong>\" ]\r\n\r\n<strong>Authors:</strong> Boise State, University of Colorado, University of Minnesota\r\n<strong>Speedup:</strong> 2.5-4.5X\r\n\r\nThe authors introduce a GPU implementation of a three-dimensional mantle convection modeling at a high Rayleigh number to the solid earth geophysics community. They outline code development time, compare performance of CPUs versus GPUs, and deliver powerful visualizations.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Ground Water Simulations | Louisiana State University</strong>\" ]\r\n\r\n<strong>Authors:</strong> Kevin R. Tubbs and Frank T-C. Tsai at Louisiana State University\r\n<strong>Speedup:</strong> &gt;20X\r\n\r\nA lattice Boltzmann method for solving the shallow water equations and the advection-dispersion equation is developed and implemented on graphics processing unit (GPU)-based architectures. The proposed LBM is implemented to an NVIDIA Computing Processor in a single GPU workstation. GPU computing is performed using ArrayFire software. Mass transport with velocity-dependent dispersion in shallow water flow is simulated by combining the MRT-LBM model and the TRT-LBM model. The GPU parallel performance increases as the grid size increases. The results indicate the promise of the GPU-accelerated LBM for modeling mass transport phenomena in shallow water flows.\r\n[/accordion_item]\r\n[accordion_item title=\"<strong>Shallow Water Fluid Flow | Louisiana State University</strong>\" ]\r\n\r\n<strong>Authors:</strong> Louisiana State University\r\n<strong>Speedup:</strong> &gt;10X\r\n\r\nA lattice Boltzmann method (LBM) on high performance computing (HPC) environments for three-dimensional shallow water flow fields coupled to mass transport is developed. LBM is an attractive method for solving the multilayered shallow water equations because the extension to multilayer is straight forward with all of the simplicities and advantages of the LBM in mass transport in shallow water flows and the LBM performance on central processing unit (CPU)-based and graphics processing unit (GPU)-based HPC environments.\r\n[/accordion_item][/accordion]\r\n<div id=\"consulting\"></div>\r\n[/content_band]\r\n<div id=\"services\"></div>\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"][column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\"]Hire our acceleration gang[/custom_headline]\r\n\r\nHire us to accelerate your code. Or to train your pros. Or even to write new code for your organization!\r\n\r\nWe’ve already helped thousands of organizations speedup their code. We’ve accelerated algorithms, data sets, and challenging problems of all types in the past, and we’re confident that we can accelerate your code too.\r\n\r\n[gap size=\"10%\"][button  type=\"flat\" shape=\"rounded\" href=\"http://meetme.so/arrayfire\" size=\"x-large\" ]Schedule a consultation[/button][/column][column type=\"one-half\" last=\"true\" class=\"center-text\"][gap size=\"5%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/Bat-signal-e1391790016951.png\"][/column] [gap size=\"7%\"]\r\n\r\n[column type=\"one-third\" class=\"center-text\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/04/LFG-B-HORZ_202_K-e1396448935778.jpg\"][line]Lincoln Financial Group ported their CPU code (C/C++) to CUDA, and this enabled them to speed up the necessary financial calculations. Their primary objective was to reduce the time taken to run this code. Before porting to CUDA, they required 10-12 hours to run the entire code. After porting to CUDA, they were able to do the same work in about 30 minutes.[/column][column type=\"one-third\" class=\"center-text\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/reveal_logo-e1396449044651.jpg\"][line]Reveal Imaging, an SAIC company, uses ArrayFire in developing threat-detection products for transportation systems—such as cargo and baggage screening in airports—and in securing facilities and public events.[/column][column type=\"one-third\" last=\"true\" class=\"center-text\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/04/1800contactlogo.png\"][line]The Glasses.com app relies on computer vision to recognize the features of a user’s face. The application then generates an accurate, high-fidelity, three-dimensional model of that face, and virtually places selected frames on the image.[/column]\r\n<div id=\"starterpackage\"></div>\r\n[/content_band]\r\n\r\n[content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\"]\r\n\r\n[column type=\"one-half\" last=\"false\" fade=\"true\" fade_animation=\"in-from-left\" ][gap size=\"10%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/01/comingatyou.png\"][/column][column type=\"one-half\" last=\"true\"] [custom_headline type=\"left\" level=\"h3\"]Starter Package ($500)* [/custom_headline] Hire us for 1-day. We set you up with one engineer dedicated for a full day, as well as support from senior and test engineers throughout the day. Here\'s how it works:\r\n\r\n[icon_list] [icon_list_item type=\"angle-double-right\"]Initial phone call[/icon_list_item] [icon_list_item type=\"angle-double-right\"]You send us your code or algorithm [/icon_list_item] [icon_list_item type=\"angle-double-right\"]We analyze your code for potential GPU benefit[/icon_list_item][icon_list_item type=\"angle-double-right\"]We accelerate as much of the code as is possible within the 1-day effort, applying our extensive GPU software libraries[/icon_list_item][icon_list_item type=\"angle-double-right\"]We produce a final report, along with code[/icon_list_item] [/icon_list] The final report outlines the best approach to follow for full GPU-acceleration of your code.\r\n\r\n&nbsp;\r\n\r\n[button type=\"flat\" shape=\"rounded\" size=\"regular\" href=\"http://sandbox.arrayfire.com/product/consulting-starter-package/\" title=\"Starter Package\"]Buy the Starter Package[/button]\r\n\r\n&nbsp;\r\n\r\n*Limit one (1) per customer.\r\n\r\n[/column]\r\n<div id=\"customcode\"></div>\r\n[/content_band] [content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n\r\n[column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\" ]Coding Work (Custom)[/custom_headline]\r\n\r\n[custom_headline type=\"left\" level=\"h6\" ]Why Choose Us?[/custom_headline] [icon_list] [icon_list_item type=\"angle-double-right\"]Deep experience, already servicing thousands of customers[/icon_list_item] [icon_list_item type=\"angle-double-right\"]Quality work, with leading GPU software [/icon_list_item] [icon_list_item type=\"angle-double-right\"]Efficient delivery, with ArrayFire\'s code base we can deliver results fast[/icon_list_item][icon_list_item type=\"angle-double-right\"]Proven, we make customers happy through faster code[/icon_list_item][/icon_list] [custom_headline type=\"left\" level=\"h6\" ]Our Strengths[/custom_headline] [icon_list] [icon_list_item type=\"angle-double-right\"]Excellence in GPU code[/icon_list_item] [icon_list_item type=\"angle-double-right\"]Well-written, efficient C, C++, Fortran, Java, or .NET [/icon_list_item] [icon_list_item type=\"angle-double-right\"]Application porting and integration[/icon_list_item][icon_list_item type=\"angle-double-right\"]Tuning software to peak hardware performance[/icon_list_item][icon_list_item type=\"angle-double-right\"]Scalability of algorithms to handle enterprise-level programs[/icon_list_item] [/icon_list][button type=\"flat\" shape=\"rounded\" size=\"regular\" href=\"http://meetme.so/arrayfire\" title=\"Tech Consultation\"]Schedule a consultation[/button] [/column][column type=\"one-half\"  fade=\"true\" fade_animation=\"in-from-right\" last=\"true\" ][gap size=\"25%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/Holoham.png\"][/column]\r\n<div id=\"training\"></div>\r\n[/content_band] [content_band inner_container=\"true\" no_margin=\"true\" border=\"top\" padding_top=\"40px\" padding_bottom=\"40px\" ]\r\n\r\n[column type=\"one-half\"][custom_headline type=\"left\" level=\"h3\" ]Training[/custom_headline] Attendees will receive the latest industry knowledge and techniques for GPU computing in CUDA and OpenCL.\r\n\r\nArrayFire offers up to four days of specialized GPU training in CUDA and OpenCL programming. Register for a general course, or schedule a course dedicated for your organization. We can travel to you, or you can travel to our Atlanta office.\r\n\r\nWe recommend that attendees have a working knowledge of C/C++ in order to gain the most from the training courses.\r\n\r\n[/column]\r\n\r\n[column type=\"one-half\" last=\"true\"][gap size=\"8%\"]\r\n<h5><strong>Fee includes:</strong></h5>\r\n[icon_list] [icon_list_item type=\"angle-double-right\"]Instruction by an excellent and interesting expert, with hands-on exercises[/icon_list_item] [icon_list_item type=\"angle-double-right\"]Use of a laptop with CUDA and OpenCL capable GPUs and CPUs [/icon_list_item] [icon_list_item type=\"angle-double-right\"]Choice of Linux or Windows operating system[/icon_list_item][icon_list_item type=\"angle-double-right\"]Printed manual of lecture material[/icon_list_item][icon_list_item type=\"angle-double-right\"]Electronic copy of programming exercises[/icon_list_item][/icon_list]\r\n\r\n[button type=\"flat\" shape=\"rounded\" size=\"regular\" href=\"http://sandbox.arrayfire.com/product-category/training/\" title=\"Register\"]Register for Training[/button][/column]\r\n\r\n[column type=\"one-half\" fade=\"true\" fade_animation=\"in-from-left\" class=\"center-text\" ][gap size=\"30%\"][image src=\"http://sandbox.arrayfire.com/wp-content/uploads/2014/02/Professor-AF_Exported-e1395436350363.png\" ][/column][column type=\"one-half\" last=\"true\"][gap size=\"20%\"][custom_headline type=\"left\" level=\"h3\" looks_like=\"h3\"]Upcoming Courses[/custom_headline]\r\n<table>\r\n<tbody>\r\n<tr>\r\n<th>CUDA</th>\r\n<th>OpenCL</th>\r\n</tr>\r\n<tr>\r\n<td> Atlanta, GA</td>\r\n<td> Atlanta, GA</td>\r\n</tr>\r\n<tr>\r\n<td> Boston, MA</td>\r\n<td> Boston, MA</td>\r\n</tr>\r\n<tr>\r\n<td> New York City, NY</td>\r\n<td> New York City, NY</td>\r\n</tr>\r\n<tr>\r\n<td> Houston, TX</td>\r\n<td> Houston, TX</td>\r\n</tr>\r\n<tr>\r\n<td> San Jose, CA</td>\r\n<td> San Jose, CA</td>\r\n</tr>\r\n<tr>\r\n<td> Albuquerque, NM</td>\r\n<td> Albuquerque, NM</td>\r\n</tr>\r\n<tr>\r\n<td> Baltimore/Washington DC</td>\r\n<td> Baltimore/Washington DC</td>\r\n</tr>\r\n<tr>\r\n<td> San Diego, CA</td>\r\n<td> San Diego, CA</td>\r\n</tr>\r\n</tbody>\r\n</table>\r\n[/column][gap size=\"10%\"]\r\n\r\n[custom_headline type=\"left\" level=\"h3\"]Training Course Syllabus[/custom_headline] [column type=\"one-half\"] [custom_headline type=\"left\" level=\"h5\"  accent=\"false\"]Day 1, Introduction[/custom_headline] <strong>Lectures:</strong>\r\nGPU Computing Overview\r\nThe Programming Model\r\nBasic Dataset Mapping Techniques\r\nLibraries, ArrayFire\r\nProfiling Tools\r\n\r\n<strong>Practice:</strong>\r\nA Simple Kernel\r\nEquivalent ArrayFire Example\r\nUsing Libraries\r\nMonte Carlo Pi Estimation\r\nTiming and ArrayFire\r\nDebugging Code\r\n\r\n[custom_headline type=\"left\" level=\"h5\" accent=\"false\"]Day 3, Multi-GPU[/custom_headline] <strong>Lectures:</strong>\r\nMulti-GPU Use Cases\r\nMulti-GPUs: Contexts\r\nExisting Libraries\r\nScaling Across Multiple GPUs\r\n\r\n<strong>Practice:</strong>\r\nOut of Core Problems: Matrix Multiply\r\nTask Level Parallelism: Optimization\r\nArrayFire Multi-GPU[/column]\r\n\r\n[column type=\"one-half\" last=\"true\"] [custom_headline type=\"left\" level=\"h5\" accent=\"false\"]Day 2, Optimization[/custom_headline] <strong>Lectures:</strong>\r\nArchitecture: Grids, Blocks, and Threads\r\nMemory Model: Global, Shared, and Constant Memory\r\nAdvanced Mapping Techniques\r\nStreams: Asynchronos Launches and Concurrent Execution\r\nArrayFire: Lazy Evaluation and Code Vectorization\r\n\r\n<strong>Practice:</strong>\r\nMatrix Transpose\r\nOptimization Using Shared Memory\r\nMedian Filter\r\nOptimization Using Constant Memory\r\nStream Example\r\nArrayFire Example: Nearest Neighbor Algorithm\r\n\r\n[custom_headline type=\"left\" level=\"h5\" accent=\"false\"]Day 4, Algorithm Problems[/custom_headline]\r\n\r\n<strong>Lectures and Practice:</strong>\r\nReductions\r\nScan Algorithms\r\nSort\r\nConvolution\r\nCustomer-Specific Problem [/column][/content_band]','Home','','inherit','open','closed','','245-revision-v1','','','2014-04-29 19:53:00','2014-04-29 19:53:00','',245,'http://sandbox.arrayfire.com/245-revision-v1/',0,'revision','',0),(5440,17793,'2014-04-30 13:39:47','2014-04-30 13:39:47','We suddenly had the need to generating presentations for talks as quickly as possible with the following restrictions:\r\n\r\n* Universal format - HTML\r\n* Uniform template across all presentations\r\n* Excellent code syntax highlighting / formatting\r\n* Inline Math formatting\r\n\r\n, and, oh yeah, we didn\'t want to point and click. Ever. Ever again.\r\n\r\nOur solution was to hack up our own Emacs mode that compiles markdown to impress.js in realtime while you edit and pushing the output to an open web browser. The result? Realtime presentation authoring from Emacs with a beautiful rendering preview on all our target screen sizes and types (plus projector) at the same time!\r\n\r\n```bash\r\n# Ye old youtube video goes here\r\n```\r\n\r\nWant to try this out yourself?\r\n\r\n* get a new emacs\r\n* grab the files (git clone or download)\r\n* start the mode\r\n* start editing\r\n\r\nTo see how to set this up visually, we put together an instructional video,\r\n\r\n```bash\r\n# Ye old tutorial youtube video goes here\r\n```','Presentations with Emacs and a Browser','','trash','open','closed','','presentations-with-emacs-and-a-browser','','','2014-07-31 17:58:28','2014-07-31 17:58:28','',0,'http://sandbox.arrayfire.com/?p=5440',0,'post','',0),