Merge pull request #7900 from google/benvanik-hal-map-cleanup Metal, WebGPU, and remoting HAL backends map memory in special ways we haven't encountered yet in CUDA/Vulkan/local CPU execution. Many of the tools and samples we have were written assuming that mapping would always succeed, also requiring that the compiler emit buffers that were mappable. This set of changes is designed to make mapping needed less frequently, allow HAL backends to override transfer behavior, and add utilities for users to make it easier to work with data. There's still some places that are doing extremely shady things (like the e2e matmul tests) but most are now in a form that is compatible with unmappable memory.
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.