Luminal - Search-Based Deep Learning Compilers - Joe Fioti
Jun 3, 2025 · 24:35
Joe Fioti presents Luminal, a search-based deep learning compiler that simplifies ML libraries to 12 primitive operations and uses search to automatically discover optimized kernels like flash attention. By representing models as directed acyclic graphs of these simple ops, Luminal keeps its codebase under 5,000 lines yet can run all major models. Its compiler applies 20-25 rewrite rules to search through equivalent GPU kernels, profiling to find the fastest—automatically rediscovering flash attention, an algorithm that took five years for the industry to develop. Data movement accounts for 99% of runtime, so kernel fusion merges many ops into one, dramatically speeding execution. An external auto-grad crate adds training support without altering the core. Future plans include supporting AMD, TPUs, and a serverless cloud that exports optimized graphs for inference.
