High-density high-speed linear I/O for AI clusters

The performance of compute clusters for machine learning and artificial intelligence (AI) is severely limited by available interface (I/O) bandwidths within the cluster. We review bandwidth and reach bottlenecks and discuss important characteristics of I/O solutions for AI clusters, such as I/O density, power, latency, fan-out, and the need to efficiently interface to standardized high-speed networking protocols.

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Publication Details

Published
2025-03-19
DOI
https://doi.org/10.1117/12.3045631
Primary Topic
Iterative Learning Control Systems
Type
article
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article

High-density high-speed linear I/O for AI clusters

Peter J. Winzer, Daniel J. Harding
Iterative Learning Control Systems
article

High-density high-speed linear I/O for AI clusters

Peter J. Winzer, Daniel J. Harding
article en

Abstract

The performance of compute clusters for machine learning and artificial intelligence (AI) is severely limited by available interface (I/O) bandwidths within the cluster. We review bandwidth and reach bottlenecks and discuss important characteristics of I/O solutions for AI clusters, such as I/O density, power, latency, fan-out, and the need to efficiently interface to standardized high-speed networking protocols.

L-3 Communications (United States) (US)
Affordable and clean energy
Openalex Percentile: Top 95%
Iterative Learning Control Systems
DOISourceOpenAlex
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High-density high-speed linear I/O for AI clusters — Peter J. Winzer, Daniel J. Harding · (2025) | TGRS Research Map | TGRS