commit | 954cb36d8201638823a08d0c65eb35325758c730 | [log] [tgz] |
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author | MaheshRavishankar <1663364+MaheshRavishankar@users.noreply.github.com> | Fri Apr 12 14:00:49 2024 -0700 |
committer | GitHub <noreply@github.com> | Fri Apr 12 14:00:49 2024 -0700 |
tree | d8c4316b8c547a371b217c25c15fc54a42d5854b | |
parent | 699d244b7b82e26cb41e33bbb45a4237f3918a84 [diff] |
Move Codegen pass pipelines to nest on `FunctionOpInterface`. (#16665) This PR modifies the codegen backends to have the lowering pass pipelines nest on `FunctionOpInterface`. This allows running different pass pipelines on functions within the dispatch. This would allow you to have things like ``` func.func @foo_pipeline(...) { } func.func @bar_pipeline(...) { } func.func @entry_point() { if (<condnn for foo pipeline based lowering>) { foo_pipeline() } else { bar_pipeline() } } ``` To connect everything the following things are done 1) The `iree_codegen.translation_info` attribute that was set on entry point operations are now set on the surrounding function. This allows implementing a lowering strategy on a function. 2) The GPU backends set the `workgroup_size` and `subgroup_size` on the `hal.executable.export` operation. To unwind this, the `translation_info` has fields for `workgroup_size` and `subgroup_size`. This allows GPU backends to set the expected `workgroup_size` and `subgroup_size` on the `translation_info` itself (which is now on the surrounding function). 3) A pass is added after lower strategies to `ReconcileTranslationInfo`. The intent of this pass is to take the `translation_info` on each function and set the values for `workgroup_size` and `subgroup_size` on the `hal.executable.export`. Eventually this would also be a place where the number of workgroups is populated on the `hal.executable.export` (instead of doing it on `TileAndDistributeToWorkgroups` as it is done today). 4) All backends `*SelectLoweringStrategy` work as Module pass. These need to be Module passes since transform dialect tends to inject the transform script within the module. 5) The `*LowerExecutableStrategy` works at `FunctionOpInterface` now. 6) The transform dialect interpreter has to run on `Module` granularity, so a new pass `LowerExecutableUsingTransformDialect` is added. This runs the transform interpreter before `*SelectLoweringStrategy`. After this pass is run, the `translation_info` is expected to have the pipeline be set to `None` to skip subsequent lowering pipelines. 7) Most tests are now moved to remove the boiler plates surrounding `hal.executable` and `hal.executable.variant`. This does most of the heavy lifting for running lowering strategies per function-like op. The biggest missing piece are 1) The `TileAndDistributeOnWorkgroups` ops still cannot really be run on a dispatch with multiple functions since it updates the `hal.executable.export`. To address this, the pass will have to move to use `scf.forall`. 2) Some optimizations expect static workgroup count. Those currently go upto the `hal.executable.export` op to get these values (that were populated by `TileAndDistributeToWorkgroups`). When moving to `scf.forall` this will be available withint the function. ci-extra: build_test_all_arm64, build_test_all_windows, build_test_all_maxos_arm64, build_test_all_macos_x86_64, test_nvidia_a100
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.