Implement On Demand Downloading of CUDA Dependencies for non CI Builds (#9425) Adds a new CMake script to `build_tools/third_party/cuda/CMakeLists.txt`. This mirrors the functionality of https://github.com/google/iree/blob/main/build_tools/docker/base/fetch_cuda_deps.sh in CMake by downloading and extracting just the necessary NVIDIA distribution artifacts to setup the build. Artifacts are placed in the build directory under `build_tools/third_party/cuda/` Ex: ```bash # kooljblack @ workstation in /path/to/iree-build/build_tools/third_party/cuda $ ls CMakeFiles cmake_install.cmake include LICENSE nvvm ``` The script is activated during the CUDA configuration phase in the root `CmakeLists.txt` only if CUDA is enabled but an existing install is not found or provided. Note: this change does not enable CUDA by default. Looking for feedback before moving forward with that. Part of #8971
IREE (Intermediate Representation Execution Environment, pronounced as “eerie”) is an MLIR-based end-to-end compiler and runtime that lowers Machine Learning (ML) models to a unified IR that scales up to meet the needs of the datacenter and down to satisfy the constraints and special considerations of mobile and edge deployments.
See our website for project details, user guides, and instructions on building from source.
IREE is still in its early phase. We have settled down on the overarching infrastructure and are actively improving various software components as well as project logistics. It is still quite far from ready for everyday use and is made available without any support at the moment. With that said, we welcome any kind of feedback on any communication channels!
See our website for more information.
IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.