English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Conference Paper

Apple Silicon Performance in Scientific Computing

MPS-Authors
/persons/resource/persons192149

Capano,  Collin
Observational Relativity and Cosmology, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society;

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)

2211.00720.pdf
(Preprint), 227KB

Supplementary Material (public)
There is no public supplementary material available
Citation

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


Cite as: https://hdl.handle.net/21.11116/0000-000C-345A-5
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.