commit | 4d7683ec4888d8a50565277d2403a6554dd3dbb8 | [log] [tgz] |
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author | Nicolas Vasilache <nicolasvasilache@users.noreply.github.com> | Tue Mar 29 12:08:38 2022 +0200 |
committer | GitHub <noreply@github.com> | Tue Mar 29 03:08:38 2022 -0700 |
tree | 3238228e7418a7b82a94b8df6a4a3f8eaa578d62 | |
parent | 1daeb12e03c36cefae17ac78d19089d12b244ec2 [diff] |
Add support for calling tile_to_in_parallel from IREE. (#8627) * Add support for calling tile_to_in_parallel form IREE. This revision updates the linalg_transform test to use tiling to the LinalgExt parallel abstractions. These abstractions will be later connected to the proper workgroup concepts. In the process, the PrintOp gains an optional argument to more easily print the handles resulting from transformations. `tile_to_iree_linalg_ext_tile_op` is extended to return 2 values: the tiled operation and the linalg_ext.tile_op. * clang-format
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.