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

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Provided by: Indiana University
Topic: Hardware
Format: PDF
High-level domain-specific-languages for array processing on the GPU are increasingly common, but to date they run only on a single GPU. The authors argue that languages will need to target multiple devices, even simultaneous combinations of GPU/GPU and CPU/GPU. Increased flexibility may be key to making these languages more easily deployable and thus widespread. To this end, they present a compositional translation that fissions data-parallel programs in the accelerate language, allowing subsequent compiler stages to map computations on multiple devices via different code-generation backends.
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