Presenter

Tom St. John is a technical lead in the Compute Platforms Group at Cruise and serves as chair of the MLPerf automotive advisory board. Prior to this role, he led the distributed machine learning performance optimization efforts within Tesla and served as the director of the AI Co-Design Center at Wave Computing. He completed his Ph.D. in the Computer Architecture and Parallel Systems Laboratory at the University of Delaware. His research primarily focuses on the intersection of parallel programming models and computer architecture design, and the impact that this has on large-scale machine learning. Tom has organized a number of workshops/tutorials in the past. These include tutorials on performance analysis of deep learning workloads held at HPCA’21, ASPLOS’21, ISCA’21, and HPCA’22 and a workshop on benchmarking deep learning workloads on emerging hardware at MLSys’20, MLSys’21, and MLSys’22. He has also chaired the MLPerf birds-of-a-feather sessions at SC19, SC20, and SC21.