Abstract
This paper presents a technique to fully automatically generate efficient and readable code for parallel processors. We base our approach on skeleton-based compilation and ‘algorithmic species’, an algorithm classification of program code. We use a tool to automatically annotate C code with species information where possible. The annotated program code is subsequently fed into the skeleton-based source-to-source compiler ‘Bones’, which generates OpenMP, OpenCL or CUDA code and optimises host-accelerator transfers. This results in a unique approach, integrating a skeleton-based compiler for the first time into an automated flow. We demonstrate the benefits of our approach on the PolyBench suite by showing average speed-ups of 1.4x and 1.6x for GPU code compared to ppcg and Par4All, two state-of-the-art compilers.
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Nugteren, C., Custers, P., Corporaal, H. (2013). Automatic Skeleton-Based Compilation through Integration with an Algorithm Classification. In: Wu, C., Cohen, A. (eds) Advanced Parallel Processing Technologies. APPT 2013. Lecture Notes in Computer Science, vol 8299. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45293-2_14
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DOI: https://doi.org/10.1007/978-3-642-45293-2_14
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