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Proceedings of the Future Technologies Conference

FTC 2019: Proceedings of the Future Technologies Conference (FTC) 2019 pp 427–446Cite as

Low Power High Performance Computing on Arm System-on-Chip in Astrophysics

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1069))

Abstract

In this paper, we quantitatively evaluate the impact of computation on the energy consumption on Arm MPSoC platforms, exploiting both CPUs and embedded GPUs. Performance and energy measures are made on a direct N-body code, a real scientific application from the astrophysical domain. The time-to-solutions, energy-to-solutions and energy delay product using different software configurations are compared with those obtained on a general purpose x86 desktop and PCIe GPGPU. With this work, we investigate the possibility of using commodity single boards based on Arm MPSoC as an HPC computational resource for real Astrophysical production runs. Our results show to which extent those boards can be used and which modification are necessary to a production code to profit of them. A crucial finding of this work is the effect of the emulated double precision on the GPU performances that allow to use embedded and gaming GPUs as excellent HPC resources.

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Notes

  1. 1.

    https://www.ibm.com/blogs/systems/ibm-nvidia-present-nvlink-server-youve-waiting/.

  2. 2.

    Roofline is a visually intuitive performance model used to bound the performance of various numerical methods and operations running on multicore, manycore, or accelerator processor architectures.

  3. 3.

    https://www.geeks3d.com/20140305/amd-radeon-and-nvidia-geforce-fp32-fp64-gflops-table-computing/.

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Acknowledgments

This work was carried out within the ExaNeSt (FET-HPC) project (Grant no. 671553), the ASTERICS project (Grant no. 653477) and EuroExa (FET-HPC) project (Grant no. 754337) funded by the European Union’s Horizon 2020 research and innovation programme.

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Authors and Affiliations

  1. National Institute of Astrophysics, Astronomical Observatory of Trieste, via G.B. Tiepolo 11, Trieste, Italy

    Giuliano Taffoni, Sara Bertocco, Igor Coretti, David Goz, Antonio Ragagnin & Luca Tornatore

Authors
  1. Giuliano Taffoni
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  2. Sara Bertocco
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  3. Igor Coretti
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  4. David Goz
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  5. Antonio Ragagnin
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  6. Luca Tornatore
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Corresponding author

Correspondence to Sara Bertocco .

Editor information

Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

  2. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Rahul Bhatia

  3. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Supriya Kapoor

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Taffoni, G., Bertocco, S., Coretti, I., Goz, D., Ragagnin, A., Tornatore, L. (2020). Low Power High Performance Computing on Arm System-on-Chip in Astrophysics. In: Arai, K., Bhatia, R., Kapoor, S. (eds) Proceedings of the Future Technologies Conference (FTC) 2019. FTC 2019. Advances in Intelligent Systems and Computing, vol 1069. Springer, Cham. https://doi.org/10.1007/978-3-030-32520-6_33

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