Abstract
OpenMP tasking supports parallelization of irregular algorithms. Recent OpenMP specifications extended tasking to increase functionality and to support optimizations, for instance with the taskloop construct. However, task scheduling remains opaque, which leads to inconsistent performance on NUMA architectures. We assess design issues for task affinity and explore several approaches to enable it. We evaluate these proposals with implementations in the Nanos++ and LLVM OpenMP runtimes that improve performance up to 40 % and significantly reduce execution time variation.
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Notes
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Future versions of OpenMP may support explicit memory affinity and thereby inhance the definition of a location.
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Further information about the STREAM benchmark suite available at: http://www.cs.virginia.edu/stream/ref.html.
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Acknowledgement
Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energys National Nuclear Security Administration under contract DE-AC04-94AL85000.
This work has been developed with the support of the grant SEV-2011-00067 of the Severo Ochoa Program, awarded by the Spanish Government, by the Spanish Ministry of Science and Innovation (TIN2015-65316-P, Computacion de Altas Prestaciones VII) and by the Intel-BSC Exascale Lab collaboration project.
Some of the experiments were performed with computing resources granted by JARA-HPC from RWTH Aachen University under project jara0001. Parts of this work were funded by the German Federal Ministry of Research and Education (BMBF) under grant numbers 01IH13008A(ELP).
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Terboven, C. et al. (2016). Approaches for Task Affinity in OpenMP. In: Maruyama, N., de Supinski, B., Wahib, M. (eds) OpenMP: Memory, Devices, and Tasks. IWOMP 2016. Lecture Notes in Computer Science(), vol 9903. Springer, Cham. https://doi.org/10.1007/978-3-319-45550-1_8
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