William Moses
William (Billy) Moses is an Assistant Professor at the University of Illinois in the Computer Science and Electrical and Computer Engineering departments. He received a Ph.D. in Computer Science from MIT, where he also received his M.Eng in electrical engineering and computer science (EECS) and B.S. in EECS and physics. William's research involves creating compilers and program representations that enable performance and use-case portability, thus enabling non-experts to leverage the latest in high-performance computing and ML. He is known as the lead developer of Enzyme, a tool for LLVM/MLIR capable of differentiating code in a variety of languages; Polygeist, a polyhedral compiler and C++ frontend for MLIR; and Reactant, a tool for enabling existing scientific code to run on distributed ML accelerators. He has also worked on the Tensor Comprehensions framework for synthesizing high-performance GPU kernels of ML code, the Tapir compiler for parallel programs, and compilers that use machine learning to better optimize. He is a recipient of the 2026 SIAM Supercomputing Early Career Prize, the 2024 SIGHPC Doctoral Dissertation Award, a DOE Computational Science Graduate Fellowship and the Karl Taylor Compton Prize, MIT's highest student award.
Session
We present an approach for building a Reactant backend for ParallelStencil, a Julia package for high-performance stencil computations. The approach includes the generation of kernel code and data structures that are pre-optimized to serve as optimal input for Reactant to generate efficient and correct GPU, TPU, and CPU code. We report performance of representative stencil mini-apps on recent hardware platforms, including NVIDIA H100 GPUs, evaluate it in absolute terms, and compare it with performance obtained with straightforward implementations using CUDA.jl, KernelAbstractions.jl, and other Julia packages that enable explicit GPU kernel programming.