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Converting Data-Parallelism to Task-Parallelism by Rewrites: Purely Functional Programs Across Multiple GPUs

Bo Joel Svensson, Michael Vollmer, Eric Holk, Trevor L. McDonell, Ryan R. Newton
Indiana University
The 20th ACM SIGPLAN International Conference on Functional Programming (ICFP), 2015

@article{svensson2015converting,

   title={Converting Data-Parallelism to Task-Parallelism by Rewrites},

   author={Svensson, Bo Joel and Vollmer, Michael and Holk, Eric and McDonell, Trevor L and Newton, Ryan R},

   year={2015}

}

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High-level domain-specific languages for array processing on the GPU are increasingly common, but they typically only run on a single GPU. As computational power is distributed across more devices, languages must target multiple devices simultaneously. To this end, we present a compositional translation that fissions data-parallel programs in the Accelerate language, allowing subsequent compiler and runtime stages to map computations onto multiple devices for improved performance-even programs that begin as a single data-parallel kernel.
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