
AbstractWe analyze the performance portability of the skeleton-based, single-source multi-backend high-level programming framework SkePU across multiple different CPU–GPU heterogeneous systems. Thereby, we provide a systematic application efficiency characterization of SkePU-generated code in comparison to equivalent hand-written code in more low-level parallel programming models such as OpenMP and CUDA. For this purpose, we contribute ports of the STREAM benchmark suite and of a part of the NAS Parallel Benchmark suite to SkePU. We show that for STREAM and the EP benchmark, SkePU regularly scores efficiency values above 80% and in particular for CPU systems, SkePU can outperform hand-written code.
Algorithmic skeletons; Parallel efficiency; Performance portability; Heterogeneous parallel computing; High-level parallel programming, Inbäddad systemteknik, Embedded Systems
Algorithmic skeletons; Parallel efficiency; Performance portability; Heterogeneous parallel computing; High-level parallel programming, Inbäddad systemteknik, Embedded Systems
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