Cornell Collaboration Tests MATLAB with GPUs

July 20, 2011

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The Cornell University Center for Advanced Computing, together with Nvidia, Dell, and MathWorks, are working together to test the performance of GPUs with MATLAB. The collaboration is specifically focused on the use of multiple GPUs on the desktop via the MathWorks Parallel Computing Toolbox and a GPU cluster via MATLAB Distributed Computing Server.

Researchers at the Weill Cornell Medical Center, University of Michigan Health System, and the Rutgers Laboratory for Computational Imaging and Bioinformatics are currently utilizing GPUs and MATLAB to ramp up the diagnosis of cancer cells with template matching. Using GPUs, they were able to speed up the code processing time from 86.9 to 5.9 seconds. Trying to exploit GPUs in this manner would be particularly useful for pathologists looking to process many large scale images per day.

The GP-you Group, which develops high-level software tools to access GPUs from different platforms, has already released a freeware library named GPUmat that allows MATLAB users to exploit GPUs.

The basic foundation for exploiting GPUs in MATLAB is Jacket, a numerical computing platform built around the M (or MATLAB) language. Click here for a series of lectures on Jacket courtesy of Torban Larsen at Aalborg University.

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