commit | 3659ccf168725bcc33e2db8c101e222c0a903c35 | [log] [tgz] |
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author | MaheshRavishankar <1663364+MaheshRavishankar@users.noreply.github.com> | Tue Sep 28 09:28:49 2021 -0700 |
committer | GitHub <noreply@github.com> | Tue Sep 28 09:28:49 2021 -0700 |
tree | 48bb593079bc5509d70b043a5a687d224e738687 | |
parent | 5c4478401fbed50f1256a59d4c7eb3f71b6230f5 [diff] |
Revisit CPU lowering configuration settings. (#7157) The current configurations on CPU backends (and all backends) rely on looking at operations within the dispatch region to pick a default. This makes it hard to set a good default to ensure good tile distribute of operations. For every op a configuration method is needed. Instead one can just look at the loops and get an idea of the problem size. These loops are created by tile + distribute at the flow level using parametric tile sizes. The bounds of the loop are already determined from the problem sizes. Ideally we would have a loop representation that does not immediately materialize the distributed loop, but rather maintains the loop in undistributed form, with additional operands that specify the id/count/size to use when materializing the distributed loop (defering the materialization to a later convenient point). In absense of this, in this PR, the tiled loop as generated today is recognized by "lifting" it back to the untiled version based on the know distribution pattern used at the flow level. From this the original problem size is known as well and used for default distribution without having to look at the code within the dispatch region.
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.