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Apple Silicon Performance in Scientific Computing

Distributed, Parallel, and Cluster Computing 2022-11-03 v1 Computational Physics

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.

Keywords

Cite

@article{arxiv.2211.00720,
  title  = {Apple Silicon Performance in Scientific Computing},
  author = {Connor Kenyon and Collin Capano},
  journal= {arXiv preprint arXiv:2211.00720},
  year   = {2022}
}

Comments

10 pages, 3 figures, IEEE HPEC

R2 v1 2026-06-28T04:57:53.490Z