@Scale 2018: MLPerf: A suite of benchmarks for machine learning

The MLPerf effort aims to build a common set of benchmarks that enables the machine learning field to measure system performance for both training and inference from mobile devices to cloud services. In this presentation, Cliff Young, Software Engineer at Google, discusses how a widely accepted benchmark suite will benefit the entire community, including researchers, developers, builders of machine learning frameworks, cloud service providers, hardware manufacturers, application providers, and end users.