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Leveraging Parallelism with CUDA and OpenCL

S. Park, D. Shires, J. Ross, D. Richie
U. S. Army Research Laboratory, APG, MD
The 2011 International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA’11), 2011

@article{park2011leveraging,

   title={Leveraging Parallelism with CUDA and OpenCL},

   author={Park, S. and Shires, D. and Ross, J. and Richie, D.},

   year={2011}

}

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Graphics processing units (GPUs), originally designed for computing and manipulating pixels, have become general-purpose processors capable of executing in excess of trillion calculations per second. Taking advantage of GPU’s compute power and commodity popularity, the field of computing systems is exhibiting a trend toward heterogeneous platforms consisting of a central processor integrated with graphics hardware. To leverage parallelism within graphics processors, programming approaches employing CUDA and more recent OpenCL framework are evaluated in the context of implementing a ballistic threat field calculation.
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