Abstract
Accelerator-based heterogeneous computing is gaining momentum in High Performance Computing arena. However, the increased complexity of the accelerator architectures demands more generic, high-level programming models. OpenACC is one such attempt to tackle the problem. While the abstraction endowed by OpenACC offers productivity, it raises questions on its portability. This paper evaluates the performance portability obtained by OpenACC on twelve OpenACC programs on NVIDIA CUDA, AMD GCN, and Intel MIC architectures. We study the effects of various compiler optimizations and OpenACC program settings on these architectures to provide insights into the achieved performance portability.
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Acknowledgements
The paper has been authored by Oak Ridge National Laboratory, which is managed by UT-Battelle, LLC under Contract #DE-AC05-00OR22725 to the U.S. Government. Accordingly, the U.S. Government retains a non-exclusive, royalty-free license to publish or reproduce the published form of this contribution, or allow others to do so, for U.S. Government purposes. This research is sponsored by the Office of Advanced Scientific Computing Research in the U.S. Department of Energy. This research is sponsored by the Office of Advanced Scientific Computing Research in the U.S. Department of Energy.
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Sabne, A., Sakdhnagool, P., Lee, S., Vetter, J.S. (2015). Evaluating Performance Portability of OpenACC. In: Brodman, J., Tu, P. (eds) Languages and Compilers for Parallel Computing. LCPC 2014. Lecture Notes in Computer Science(), vol 8967. Springer, Cham. https://doi.org/10.1007/978-3-319-17473-0_4
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DOI: https://doi.org/10.1007/978-3-319-17473-0_4
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