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<td style="color: #000000; font-size: 12pt; background-color: #ffffff; font-family: arial;" width="650"><span style="font-size: 12pt;"><span style="font-weight: bold;">Annou</span></span><span style="font-size: 12pt;"><span style="font-weight: bold;"><span>ncements</span></span></span>
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	<li><a href="http://wiki.accelereyes.com/wiki/index.php/Release_Notes#Version_1.8" target="_blank">Jacket v1.8</a> for MATLAB<span style="font-size: 12pt;">®</span> now available</li>
	<li><a href="http://www.accelereyes.com/wiki/libjacket/release_notes.htm" target="_blank">LibJacket v1.1</a> for C/C++/Python/Fortran now available</li>
	<li><span style="font-size: 12pt;">Request a <a href="mailto:support@accelereyes.com?subject=FREE%20GPU%20Computing%20Consultation&amp;body=I%20would%20like%20to%20request%20a%20FREE%20GPU%20computing%20consultation%20session%20with%20one%20of%20your%20GPU%20experts.%20%20I%20am%20available%20for%20a%20phone%20call%20during%20the%20following%20times%3A%0A%0A%3Clist%20available%20times%3E%0A" target="_blank">FREE GPU computing consultation</a></span></li>
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<td style="color: #000000; font-size: 12pt; background-color: #ffffff; font-family: arial;" width="650"><span style="font-size: 12pt;"><span style="font-weight: bold;">Introduction </span></span>Enhance<span style="font-size: 12pt;"> your code with the fastest, most comprehensive library for GPU computing:</span>
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	<li><span style="font-size: 12pt;"><strong>Jacket</strong> - the best GPU computing in MATLAB®.  <a href="http://accelereyes.com/jacket_tour" target="_blank">Take a tour</a> and <a href="http://accelereyes.com/compare" target="_blank">compare</a>!</span></li>
	<li><span style="font-size: 12pt;"><strong>LibJacket</strong> - the best way to kick start your CUDA development.  <a href="http://accelereyes.com/libjacket_tour" target="_blank">Take a tour</a>!</span></li>
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<span style="font-size: 12pt;">Both products enable:</span>
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	<li><span style="font-size: 12pt;">Manipulating vectors, matrices, and ND arrays</span></li>
	<li><span style="font-size: 12pt;">Support for single- and double-precision, boolean, real, and complex numbers</span></li>
	<li><span style="font-size: 12pt;">Hundreds of routines for arithmetic, linear algebra, statistics, imaging, signal processing, and more (full list: <a href="http://wiki.accelereyes.com/wiki/index.php/Function_List" target="_blank">Jacket</a>, <a href="http://wiki.accelereyes.com/wiki/libjacket/modules.htm" target="_blank">LibJacket</a>)</span></li>
	<li><span style="font-size: 12pt;">Thousands of lines of optimized code for any CUDA-capable GPU</span></li>
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<td style="color: #000000; font-size: 12pt; background-color: #ffffff; font-family: arial;" width="50%"><span style="font-size: 12pt;"><span style="font-weight: bold;">New Product Features</span></span>
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	<li><span style="font-size: 12pt;">Expanded support for the Signal Processing, Image Processing, and Statistics Libraries included with both Jacket and LibJacket</span></li>
	<li><span style="font-size: 12pt;">Faster linear algebra for special systems (e.g. symmetric, positive definite, triangular, etc.)</span></li>
	<li><span style="font-size: 12pt;">Enhanced visualizations</span></li>
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	<li><img style="width: 75px; height: 102px;" title="jacket_logo" src="https://03cd632607-custmedia.vresp.com/114431ae68/jacket_logo.jpg" alt="jacket_logo" width="75" height="102" align="right" border="0" hspace="0" vspace="0" /><span style="font-size: 12pt;">New and updated examples: FDTD, Mandelbrot fractals, maximum-likelihood neural segmentation, MDS for genomics</span></li>
	<li><span style="font-size: 12pt;">Built with CUDA 4.0 for peak performance</span></li>
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<td style="color: #000000; font-size: 12pt; background-color: #ffffff; font-family: arial;" width="50%"><span style="font-size: 12pt;"><span style="font-weight: bold;">Examples &amp; Benchmarks</span></span>
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	<li><span style="font-size: 10pt;">Recent case studies: video feature learning (<a href="../2011/04/09/feature_learning_architectures/" target="_blank">Stanford</a>), digital holography (<a href="../2011/04/30/digital-holograms-faster-than-ever/" target="_blank">REAL3d</a>), hybrid LU decomposition (<a href="../2011/02/18/hybrid_gpu_multicore_matlab_lu_decompositions/" target="_blank">SAIC</a>), GPU Computing seminar (<a href="../2011/06/27/jacket-lectures-learn-and-teach-gpu-computing/" target="_blank">U Aalborg</a>), and more</span></li>
	<li><span style="font-size: 10pt;"><a href="../2011/01/31/stanford_gpu_benchmarks/" target="_blank"><span style="text-decoration: underline;">Stanford benchmarks</span></a> show Jacket outperforms the Parallel Computing Toolbox.</span></li>
	<li><span style="font-size: 10pt;"><a href="http://www.accelereyes.com/products/benchmarks_libjacket" target="_blank">Benchmarks</a> showing how LibJacket outperforms <a href="http://software.intel.com/en-us/articles/intel-mkl/" target="_blank">MKL</a>, <a href="http://software.intel.com/en-us/articles/intel-ipp/" target="_blank">IPP</a>, and other CPU libraries.</span></li>
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<td style="color: #000000; font-size: 12pt; background-color: #ffffff; font-family: arial;" width="50%"><span style="font-size: 12pt;"><span style="font-weight: bold;">Quick links</span></span>
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	<li><span style="font-size: 10pt;"> <a href="http://www.accelereyes.com/resources/whitepapers" target="_blank">Technical Whitepapers</a> to learn how Jacket works</span></li>
	<li><span style="font-size: 10pt;">Documentation for <a href="http://wiki.accelereyes.com/" target="_blank"><span style="text-decoration: underline;">Jacket</span></a> and <a href="http://accelereyes.com/wiki/libjacket" target="_blank">LibJacket</a></span></li>
	<li><span style="font-size: 10pt;"><a href="http://www.accelereyes.com/support" target="_blank">Online help</a> for getting started and optimizing the performance of your code</span></li>
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<td style="color: #000000; font-size: 12pt; background-color: #ffffff; font-family: arial;" colspan="2" width="50%"><span style="font-size: 8pt;">* MATLAB® is a registered trademark of The MathWorks, as if you didn't know that already :)</span></td>
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