Automated Discovery of Machine Learning Optimizations
Zhihao Jia is a Ph.D. candidate in the Computer Science department at Stanford University working with Alex Aiken and Matei
Zaharia. His research interests lie in the intersection of computer systems and machine learning, with a focus on building
efficient, scalable, and high-performance systems for ML computation.
As an increasingly important workload, machine learning (ML) applications require different performance optimization
techniques from traditional runtimes and compilers. In particular, to accelerate ML applications, it is generally necessary to
perform ML computations on heterogeneous hardware and parallelize computations using multiple data dimensions, neither of
which is even expressible in traditional compilers and runtimes. In this talk, Zhihao will describe their work on automated
discovery of performance optimizations to accelerate ML computations.
Zhihao will also outline future research directions for further automating ML systems, such as codesigning ML models, software
systems, and hardware backends for end-to-end ML deployment.