Before revision:   Driven by more than URLanizations as well as more than 200 ML engineers and practitioners, MLPerf implements a set of rules and  practices to ensure comparability across systems with wildly differing architectures.
After revision:  In this paper, we present our benchmarking method for evaluating ML inference systems. Driven by more than URLanizations as well as more than 200 ML engineers and practitioners, MLPerf implements a set of rules and practices to ensure comparability across systems with wildly differing architectures.