Uploaded December 2021 | Updated September 2026, 3 weeks ago
Tutorial 1, Part 1, Hot Chips 33 (2021), Sunday, August 22, 2021.
Organizers: Natalia Vassilieva, Cerebras, David Kanter, Real World Insights, and Vartika Singh, NVIDIA
Machine learning is a rich, varied, and rapidly evolving field. This tutorial explores the applications, performance characteristics, and key challenges of many different unique workloads across training and inference. In particular, it focuses on hardware/software co-optimization for the industry-standard MLPerf™ benchmarks and selected applications and considerations at prominent cloud players.
---------------------------
In Part 1 of the tutorial, Paulius Micikevicius describes the hurdles associated with ML performance in a general manner, and Peter Mattson explains the MLPerf benchmarks that many are now using to drive further performance improvements.
Modern Neural Networks and their Computational Characteristics
Paulius Micikevicius, NVIDIA
MLPerf™ Training and Inference
Peter Mattson, Google
Tutorial 1, Part 1, Hot Chips 33 (2021), Sunday, August 22, 2021.
Organizers: Natalia Vassilieva, Cerebras, David Kanter, Real World Insights, and Vartika Singh, NVIDIA
Machine learning is a rich, varied, and rapidly evolving field. This tutorial explores the applications, performance characteristics, and key challenges of many different unique workloads across training and inference. In particular, it focuses on hardware/software co-optimization for the industry-standard MLPerf™ benchmarks and selected applications and considerations at prominent cloud players.
---------------------------
In Part 1 of the tutorial, Paulius Micikevicius describes the hurdles associated with ML performance in a general manner, and Peter Mattson explains the MLPerf benchmarks that many are now using to drive further performance improvements.
Modern Neural Networks and their Computational Characteristics
Paulius Micikevicius, NVIDIA
MLPerf™ Training and Inference
Peter Mattson, Google
