RISC-V Summit

This deep dive will explain an end to end software stack solution to RISC-V based AI chips, including an innovation way to write AI kernels with new programming languages such as Triton (and Mojo later), using MLIR/LLVM based AI compiler infra to lower Triton kernels and neural networks from frameworks such as Pytorch, ONNX, Tensorflow and JAX into a range of high/middle/low level of MLIR dialects to do coarse grained high level optimizations such as loop tiling, kernel fusion, auto-vectorization etc. This paves the way of sharing common open source Triton kernels libraries provided in PyTorch and other frameworks, and greatly reduces the adoption time for AI software stack to RISC-V based AI chip. This talk will also explore the limitation of Triton language, and how can we extend the Triton language, and also the MLIR conversion and optimization passes to better support non GPU architecture target such as RISC-V.