kth.sePublications KTH
Operational message
There are currently operational disruptions. Troubleshooting is in progress.
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Apple vs. Oranges: Evaluating the Apple Silicon M-Series SoCs for HPC Performance and Efficiency
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science.ORCID iD: 0009-0007-2920-5674
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Computational Science and Technology (CST).ORCID iD: 0009-0009-8783-8335
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Computational Science and Technology (CST).ORCID iD: 0000-0003-4158-3583
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Computational Science and Technology (CST).ORCID iD: 0000-0003-0639-0639
2025 (English)In: Proceedings - 2025 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2025, Institute of Electrical and Electronics Engineers (IEEE) , 2025, p. 45-54Conference paper, Published paper (Refereed)
Abstract [en]

This paper investigates the architectural features and performance potential of the Apple Silicon M-Series SoCs (M1, M2, M3, and M4) for HPC. We provide a detailed review of the CPU and GPU designs, the unified memory architecture, and coprocessors such as Advanced Matrix Extensions (AMX). We design and develop benchmarks in the Metal Shading Language and Objective-C++ to assess FP32 computational and memory performance. We also measure power consumption and efficiency using Apple's powermetrics tool. Our results show that the M-Series chips offer up to 100 GB/s memory bandwidth, and significant generational improvements in computational performance, with up to 2.9 FP32 TFLOPS on the M4. Power consumption varies from a few Watts to 10-20 Watts, with more than 200 GFLOPS per Watt efficiency of GPU and accelerator reached by all four chips. Despite limitations in FP64 support on the GPU, the M-Series chips demonstrate strong potential for energy-efficient HPC applications. While existing HPC solutions such as the Nvidia Grace-Hopper superchip outperform Apple Silicon in both memory bandwidth and computational performance, we see that the M-Series provides a competitive power-efficient alternative to traditional HPC architectures and represents a distinct category altogether - forming an apples-to-oranges comparison.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2025. p. 45-54
Keywords [en]
Apple Silicon M-Series GPU Performance, ARM-based SoC, M1, M2, M3, M4 Architecture
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:kth:diva-370765DOI: 10.1109/IPDPSW66978.2025.00013Scopus ID: 2-s2.0-105015528421OAI: oai:DiVA.org:kth-370765DiVA, id: diva2:2002651
Conference
2025 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2025, Milan, Italy, June 3-7, 2025
Note

Part of ISBN 9798331526436

QC 20251001

Available from: 2025-10-01 Created: 2025-10-01 Last updated: 2025-10-01Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Hübner, PaulHu, AndongPeng, IvyMarkidis, Stefano

Search in DiVA

By author/editor
Hübner, PaulHu, AndongPeng, IvyMarkidis, Stefano
By organisation
Computer ScienceComputational Science and Technology (CST)
Computer Systems

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 89 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf