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  Apple Silicon Performance in Scientific Computing

Kenyon, C., & Capano, C. (2022). Apple Silicon Performance in Scientific Computing. In 2022 IEEE High Performance Extreme Computing Conference, HPEC 2022 (pp. 1-10).

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Item Permalink: https://hdl.handle.net/21.11116/0000-000C-345A-5 Version Permalink: https://hdl.handle.net/21.11116/0000-000C-3E85-9
Genre: Conference Paper

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 Creators:
Kenyon , Connor, Author
Capano, Collin1, Author           
Affiliations:
1Observational Relativity and Cosmology, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society, ou_24011              

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Free keywords: Computer Science, Distributed, Parallel, and Cluster Computing, cs.DC, Physics, Computational Physics, physics.comp-ph
 Abstract: With the release of the Apple Silicon System-on-a-Chip processors, and the
impressive performance shown in general use by both the M1 and M1 Ultra, the
potential use for Apple Silicon processors in scientific computing is explored.
Both the M1 and M1 Ultra are compared to current state-of-the-art data-center
GPUs, including an NVIDIA V100 with PCIe, an NVIDIA V100 with NVLink, and an
NVIDIA A100 with PCIe. The scientific performance is measured using the
Scalable Heterogeneous Computing (SHOC) benchmark suite using OpenCL
benchmarks. We find that both M1 processors outperform the GPUs in all
benchmarks.

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 Dates: 2022-11-012022
 Publication Status: Issued
 Pages: 10 pages, 3 figures, IEEE HPEC
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 Table of Contents: -
 Rev. Type: -
 Identifiers: arXiv: 2211.00720
DOI: 10.1109/HPEC55821.2022.9926315
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Title: IEEE High Performance Extreme Computing Conference, HPEC 2022
Place of Event: Waltham, MA, USA
Start-/End Date: 2022-09-19 - 2022-09-23

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Title: 2022 IEEE High Performance Extreme Computing Conference, HPEC 2022
Source Genre: Proceedings
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Pages: - Volume / Issue: 2022 Sequence Number: 183947 Start / End Page: 1 - 10 Identifier: -