2024 LLVM Developers' Meeting ------ Extending MLIR Dialects for Deep Learning Compilers Speaker: Charitha Saumya, Jianhui Li ------ Slides: ----- This talk discusses the design of XeTile, a dialect developed for expressing and compilation of deep learning kernels. XeTile demonstrates that with a few critical extensions, MLIR dialects can be used as building blocks to support deep learning compiler development for high-performant code generation. With the "Tile" data type and a few operations, XeTile dialect greatly simplifies the lowering of dense operations. Any tile-based GEMM-like algorithms can easily be expressed in a few lines of code, including advanced optimizations like cooperative load/prefetch, K-slicing, and software pipelining. ----- Videos Edited by Bash Films: