Oak ridge OpenSHMEM benchmark suite

Thomas Naughton; Ferrol Aderholdt; Matt Baker; Swaroop Pophale; Manjunath Gorentla Venkata; Neena Imam

doi:10.1007/978-3-030-04918-8_13

Oak ridge OpenSHMEM benchmark suite

Thomas Naughton, Ferrol Aderholdt, Matt Baker, Swaroop Pophale, Manjunath Gorentla Venkata, Neena Imam

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

The assessment of application performance is a fundamental task in high-performance computing (HPC). The OpenSHMEM Benchmark (OSB) suite is a collection of micro-benchmarks and mini-applications/compute kernels that have been ported to use OpenSHMEM. Some, like the NPB OpenSHMEM benchmarks, have been published before while most others have been used for evaluations but never formally introduced or discussed. This suite puts them together and is useful for assessing the performance of different use cases of OpenSHMEM. This offers system implementers a useful means of measuring performance and assessing the effects of new features as well as implementation strategies. The suite is also useful for application developers to assess the performance of the growing number of OpenSHMEM implementations that are emerging. In this paper, we describe the current set of codes available within the OSB suite, how they are intended to be used, and, where possible, a snapshot of their behavior on one of the OpenSHMEM implementations available to us. We also include detailed descriptions of every benchmark and kernel, focusing on how OpenSHMEM was used. This includes details on the enhancements we made to the benchmarks to support multithreaded variants. We encourage the OpenSHMEM community to use, review, and provide feedback on the benchmarks.

Original language	English
Title of host publication	OpenSHMEM and Related Technologies. OpenSHMEM in the Era of Extreme Heterogeneity - 5th Workshop, OpenSHMEM 2018, Revised Selected Papers
Editors	Swaroop Pophale, Neena Imam, Ferrol Aderholdt, Manjunath Gorentla Venkata
Publisher	Springer Verlag
Pages	202-216
Number of pages	15
ISBN (Print)	9783030049171
DOIs	https://doi.org/10.1007/978-3-030-04918-8_13
State	Published - 2019
Event	5th Workshop on OpenSHMEM and Related Technologies, 2018 - Baltimore, United States Duration: Aug 21 2018 → Aug 23 2018

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11283 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	5th Workshop on OpenSHMEM and Related Technologies, 2018
Country/Territory	United States
City	Baltimore
Period	08/21/18 → 08/23/18

Funding

Acknowledgements. This research was supported by the United States Department of Defense (DoD) and Computational Research and Development Programs at Oak Ridge National Laboratory. This work was sponsored by the U.S. Department of Energy’s Office of Advanced Scientific Computing Research. This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. This work was sponsored by the U.S. Department of Energy’s Office of Advanced Scientific Computing Research. This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/ downloads/doe-public-access-plan). This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. This work was sponsored by the U.S. Department of Energy’s Office of Advanced Scientific Computing Research. This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow‏ oth‏ers ‏to do so, fo‏r United States Gove‏rn‏ment purposes.‏ T‏he Departm‏ent of Energ‏y will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://‏ener‏gy.g‏ov‏/ downloads/doe-public-access-plan). This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.This research was supported by the United States Department of Defense (DoD) and Computational Research and Development Programs at Oak Ridge National Laboratory. This work was sponsored by the U.S. Department of Energy’s Office of Advanced Scientific Computing Research. This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.

Funders	Funder number
U.S. Department of Defense
U.S. Department of Energy	DE-AC05-00OR22725
Office of Science
Advanced Scientific Computing Research
Oak Ridge National Laboratory

Access to Document

10.1007/978-3-030-04918-8_13

Cite this

Naughton, T., Aderholdt, F., Baker, M., Pophale, S., Gorentla Venkata, M., & Imam, N. (2019). Oak ridge OpenSHMEM benchmark suite. In S. Pophale, N. Imam, F. Aderholdt, & M. Gorentla Venkata (Eds.), OpenSHMEM and Related Technologies. OpenSHMEM in the Era of Extreme Heterogeneity - 5th Workshop, OpenSHMEM 2018, Revised Selected Papers (pp. 202-216). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11283 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-04918-8_13

Naughton, Thomas ; Aderholdt, Ferrol ; Baker, Matt et al. / Oak ridge OpenSHMEM benchmark suite. OpenSHMEM and Related Technologies. OpenSHMEM in the Era of Extreme Heterogeneity - 5th Workshop, OpenSHMEM 2018, Revised Selected Papers. editor / Swaroop Pophale ; Neena Imam ; Ferrol Aderholdt ; Manjunath Gorentla Venkata. Springer Verlag, 2019. pp. 202-216 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{b109e91691704febb39a880183277d24,

title = "Oak ridge OpenSHMEM benchmark suite",

abstract = "The assessment of application performance is a fundamental task in high-performance computing (HPC). The OpenSHMEM Benchmark (OSB) suite is a collection of micro-benchmarks and mini-applications/compute kernels that have been ported to use OpenSHMEM. Some, like the NPB OpenSHMEM benchmarks, have been published before while most others have been used for evaluations but never formally introduced or discussed. This suite puts them together and is useful for assessing the performance of different use cases of OpenSHMEM. This offers system implementers a useful means of measuring performance and assessing the effects of new features as well as implementation strategies. The suite is also useful for application developers to assess the performance of the growing number of OpenSHMEM implementations that are emerging. In this paper, we describe the current set of codes available within the OSB suite, how they are intended to be used, and, where possible, a snapshot of their behavior on one of the OpenSHMEM implementations available to us. We also include detailed descriptions of every benchmark and kernel, focusing on how OpenSHMEM was used. This includes details on the enhancements we made to the benchmarks to support multithreaded variants. We encourage the OpenSHMEM community to use, review, and provide feedback on the benchmarks.",

author = "Thomas Naughton and Ferrol Aderholdt and Matt Baker and Swaroop Pophale and {Gorentla Venkata}, Manjunath and Neena Imam",

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doi = "10.1007/978-3-030-04918-8_13",

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Naughton, T, Aderholdt, F, Baker, M, Pophale, S, Gorentla Venkata, M & Imam, N 2019, Oak ridge OpenSHMEM benchmark suite. in S Pophale, N Imam, F Aderholdt & M Gorentla Venkata (eds), OpenSHMEM and Related Technologies. OpenSHMEM in the Era of Extreme Heterogeneity - 5th Workshop, OpenSHMEM 2018, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11283 LNCS, Springer Verlag, pp. 202-216, 5th Workshop on OpenSHMEM and Related Technologies, 2018, Baltimore, United States, 08/21/18. https://doi.org/10.1007/978-3-030-04918-8_13

Oak ridge OpenSHMEM benchmark suite. / Naughton, Thomas; Aderholdt, Ferrol; Baker, Matt et al.
OpenSHMEM and Related Technologies. OpenSHMEM in the Era of Extreme Heterogeneity - 5th Workshop, OpenSHMEM 2018, Revised Selected Papers. ed. / Swaroop Pophale; Neena Imam; Ferrol Aderholdt; Manjunath Gorentla Venkata. Springer Verlag, 2019. p. 202-216 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11283 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - The assessment of application performance is a fundamental task in high-performance computing (HPC). The OpenSHMEM Benchmark (OSB) suite is a collection of micro-benchmarks and mini-applications/compute kernels that have been ported to use OpenSHMEM. Some, like the NPB OpenSHMEM benchmarks, have been published before while most others have been used for evaluations but never formally introduced or discussed. This suite puts them together and is useful for assessing the performance of different use cases of OpenSHMEM. This offers system implementers a useful means of measuring performance and assessing the effects of new features as well as implementation strategies. The suite is also useful for application developers to assess the performance of the growing number of OpenSHMEM implementations that are emerging. In this paper, we describe the current set of codes available within the OSB suite, how they are intended to be used, and, where possible, a snapshot of their behavior on one of the OpenSHMEM implementations available to us. We also include detailed descriptions of every benchmark and kernel, focusing on how OpenSHMEM was used. This includes details on the enhancements we made to the benchmarks to support multithreaded variants. We encourage the OpenSHMEM community to use, review, and provide feedback on the benchmarks.

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Naughton T, Aderholdt F, Baker M, Pophale S, Gorentla Venkata M, Imam N. Oak ridge OpenSHMEM benchmark suite. In Pophale S, Imam N, Aderholdt F, Gorentla Venkata M, editors, OpenSHMEM and Related Technologies. OpenSHMEM in the Era of Extreme Heterogeneity - 5th Workshop, OpenSHMEM 2018, Revised Selected Papers. Springer Verlag. 2019. p. 202-216. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-04918-8_13

Oak ridge OpenSHMEM benchmark suite

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