In January, we <a href="../2010/01/19/torbens_corner/">introduced</a> you to <a href="http://wiki.accelereyes.com/wiki/index.php/Torben%27s_Corner" target="_blank">Torben’s Corner</a> – a resource wiki created and maintained by Jacket programming guru, Torben Larsen at Aalborg University in Denmark.  Many Jacket programmers have gained valuable insights from Torben’s Corner, including GPU performance charts, coding guidelines, special tricks.

Since January, many wonderful additions have been added to Torben’s Corner.  We think you will find value in not only this new information but the entire resource.  Here is a quick summary of the most recent additions with links to the information:
<h3>Benchmarking Update</h3>
Torben’s Corner maintains a long list of benchmarks specifically detailing speedups of Jacket relative to standard MATLAB. This became an enormous task due to the sheer number of functions supported by Jacket and MATLAB.

Therefore, a new benchmarking library has been designed. This library currently consists of 30 benchmarked functions and more will be added over time. These benchmarks measure the speedups of Jacket versus CPU-based MATLAB for matrix/vector and single/double precision. All results are gathered in three automatically generated outputs:
<ol>
	<li>a .mat file with all the measured data,</li>
	<li>a .wki file which is a Wiki table ready to be inserted in a Wiki page, and</li>
	<li>a Latex table with everything needed to produce a beautiful Latex table just by the press of a button.</li>
</ol>
The library is freely available for anyone to use – with the standard requirements for open access software. You can read more and <a href="http://wiki.accelereyes.com/wiki/index.php/Torben%27s_Corner:_Jacket_Benchmark_Tables" target="_blank">download the benchmark</a>. The full set of benchmarks takes 1.5-2 hours to complete.
<h3>Installing on Ubuntu</h3>
A <a href="http://wiki.accelereyes.com/wiki/index.php/Installation_of_Ubuntu/CUDA/MATLAB/Jacket" target="_blank">guide</a> on how to install Jacket on Ubuntu, including installation instructions for Ubuntu, GPU Drivers, MATLAB, Jacket, and Dropbox.
<h3>Running on a plain MATLAB install</h3>
A <a href="http://wiki.accelereyes.com/wiki/index.php/Making_Jacket_Code_Run_On_Plain_MATLAB_Installations" target="_blank">procedure and library of functions</a> enabling Jacket programmers to write GPU code which will run with a plain CPU-only MATLAB installation. This is very important when programmers want to distribute their toolboxes, etc. Of course, without the GPU, the code will run slower, but with this procedure, your code will run without a GPU.
<h3>CPU settings that affect performance</h3>
A <a href="http://wiki.accelereyes.com/wiki/index.php/Influence_of_The_Performance_Setting_Of_The_CPU" target="_blank">small post</a> on how the CPU performance settings affect the floating point performance of the CPU and Jacket.
<h3>Jacket performance study</h3>
A <a href="http://wiki.accelereyes.com/wiki/index.php/Jacket_Floating_Point_Performance_%28GFlops%29" target="_blank">detailed study</a> on the floating point performance of Jacket. This is ongoing work and new results are continually being added.

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Thanks to Torben and his team for these contributions and hope all Jacket programmers can leverage this most recent work and the resource as a whole.