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cs.LG2019★ 171 cited
MLPerf Training Benchmark
Peter Mattson, Christine Cheng, Cody Coleman +34
Machine learning (ML) needs industry-standard performance benchmarks to support design and competitive evaluation of the many emerging software and hardware solutions for ML. But M…
cs.DB2019
Willump: A Statistically-Aware End-to-end Optimizer for Machine Learning Inference
Peter Kraft, Daniel Kang, Deepak Narayanan +3
Systems for ML inference are widely deployed today, but they typically optimize ML inference workloads using techniques designed for conventional data serving workloads and miss cr…