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High-level GPU computing with jacket for MATLAB and C/C++

Gallagher Pryor, Brett Lucey, Sandeep Maddipatla, Chris McClanahan, John Melonakos, Vishwanath Venugopalakrishnan, Krunal Patel, Pavan Yalamanchili, James Malcolm
AccelerEyes, 75 5th Street NW STE 204, Atlanta, GA 3030, USA
Proc. SPIE 8060, 806005, 2011

@inproceedings{pryor2011high,

   title={High-level GPU computing with jacket for MATLAB and C/C++},

   author={Pryor, G. and Lucey, B. and Maddipatla, S. and McClanahan, C. and Melonakos, J. and Venugopalakrishnan, V. and Patel, K. and Yalamanchili, P. and Malcolm, J.},

   booktitle={Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series},

   volume={8060},

   pages={4},

   year={2011}

}

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We describe a software platform for the rapid development of general purpose GPU (GPGPU) computing applications within the MATLAB computing environment, C, and C++: Jacket. Jacket provides thousands of GPU-tuned function syntaxes within MATLAB, C, and C++, including linear algebra, convolutions, reductions, and FFTs as well as signal, image, statistics, and graphics libraries. Additionally, Jacket includes a compiler that translates MATLAB and C++ code to CUDA PTX assembly and OpenGL shaders on demand at runtime. A facility is also included to compile a domain specific version of the MATLAB language to CUDA assembly at build time. Jacket includes the first parallel GPU FOR-loop construction and the first profiler for comparative analysis of CPU and GPU execution times. Jacket provides full GPU compute capability on CUDA hardware and limited, image processing focused compute on OpenGL/ES (2.0 and up) devices for mobile and embedded applications.
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