commit | f9802f07d951e854cb3d758e9d4b9f2dc5d7b6f9 | [log] [tgz] |
---|---|---|
author | Lei Zhang <antiagainst@google.com> | Sun Feb 05 13:37:44 2023 -0800 |
committer | Lei Zhang <antiagainst@google.com> | Tue Jun 13 21:17:31 2023 -0700 |
tree | 85b6e615625776f96b02dfb1d2fac03f3bcb213b | |
parent | 8a2330fcf4b20322cb09afb972fe446dbfbb985f [diff] |
[metal] Wire up creating devices, allocators, and buffers This commit fills driver APIs for creating devices, and adds a basic device implementation to create allocator and buffers. The rest of device APIs are left as unimplemented. We also start to enable CTS tests since this commit. The first batch includes driver, allocator, and buffer mapping tests.
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.