MLPerf: An industry standard benchmark suite for machine learning performance

Citation:

Mattson Peter, Vijay Reddi, Christine Cheng, Cody Coleman, Greg Diamos, David Kanter, Paulius Micikevicius, David Patterson, Guenther Schmuelling, Hanlin Tang, Gu-Yeon Wei, and Carole-Jean Wu. 3/1/2020. “MLPerf: An industry standard benchmark suite for machine learning performance.” IEEE Micro, 40, 2, Pp. 8–16. Publisher's Version

Abstract:

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.
Last updated on 04/29/2022