MLPerf: An Industry Standard Benchmark Suite for Machine Learning Performance

In this article, we describe the design choices behind MLPerf, a machine learning performance benchmark that has become an industry standard. The first two rounds of the MLPerf Training benchmark helped drive improvements to software-stack performance and scalability, showing a 1.3× speedup in the t...

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Veröffentlicht in:IEEE MICRO 2020-03, Vol.40 (2), p.8-16
Hauptverfasser: Mattson, Peter, Reddi, Vijay Janapa, Cheng, Christine, Coleman, Cody, Diamos, Greg, Kanter, David, Micikevicius, Paulius, Patterson, David, Schmuelling, Guenther, Tang, Hanlin, Wei, Gu-Yeon, Wu, Carole-Jean
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Sprache:eng
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Zusammenfassung:In this article, we describe the design choices behind MLPerf, a machine learning performance benchmark that has become an industry standard. The first two rounds of the MLPerf Training benchmark helped drive improvements to software-stack performance and scalability, showing a 1.3× speedup in the top 16-chip results despite higher quality targets and a 5.5× increase in system scale. The first round of MLPerf Inference received over 500 benchmark results from 14 different organizations, showing growing adoption.
ISSN:0272-1732
1937-4143
DOI:10.1109/MM.2020.2974843