cbfa265e98
Adds the `#llvm.target<triple = $TRIPLE, chip = $CHIP, features = $FEATURES>` attribute and along with a `-llvm-target-to-data-layout` pass to derive a MLIR data layout from the LLVM data layout string (using the existing `DataLayoutImporter`). The attribute implements the relevant DLTI-interfaces, to expose the `triple`, `chip` (AKA `cpu`) and `features` on `#llvm.target` and the full `DataLayoutSpecInterface`. The pass combines the generated `#dlti.dl_spec` with an existing `dl_spec` in case one is already present, e.g. a `dl_spec` which is there to specify size of the `index` type. Adds a `TargetAttrInterface` which can be implemented by all attributes representing LLVM targets. Similar to the Draft PR https://github.com/llvm/llvm-project/pull/78073. RFC on which this PR is based: https://discourse.llvm.org/t/mandatory-data-layout-in-the-llvm-dialect/85875
102 lines
3.9 KiB
C++
102 lines
3.9 KiB
C++
//===- RegisterAllPasses.cpp - MLIR Registration ----------------*- C++ -*-===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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//
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// This file defines a helper to trigger the registration of all passes to the
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// system.
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//
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//===----------------------------------------------------------------------===//
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#include "mlir/InitAllPasses.h"
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#include "mlir/Conversion/Passes.h"
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#include "mlir/Dialect/AMDGPU/Transforms/Passes.h"
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#include "mlir/Dialect/Affine/Passes.h"
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#include "mlir/Dialect/Arith/Transforms/Passes.h"
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#include "mlir/Dialect/ArmSME/Transforms/Passes.h"
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#include "mlir/Dialect/ArmSVE/Transforms/Passes.h"
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#include "mlir/Dialect/Async/Passes.h"
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#include "mlir/Dialect/Bufferization/Pipelines/Passes.h"
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#include "mlir/Dialect/Bufferization/Transforms/Passes.h"
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#include "mlir/Dialect/EmitC/Transforms/Passes.h"
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#include "mlir/Dialect/Func/Transforms/Passes.h"
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#include "mlir/Dialect/GPU/Pipelines/Passes.h"
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#include "mlir/Dialect/GPU/Transforms/Passes.h"
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#include "mlir/Dialect/LLVMIR/Transforms/Passes.h"
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#include "mlir/Dialect/Linalg/Passes.h"
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#include "mlir/Dialect/MLProgram/Transforms/Passes.h"
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#include "mlir/Dialect/Math/Transforms/Passes.h"
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#include "mlir/Dialect/MemRef/Transforms/Passes.h"
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#include "mlir/Dialect/NVGPU/Transforms/Passes.h"
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#include "mlir/Dialect/OpenACC/Transforms/Passes.h"
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#include "mlir/Dialect/Quant/Transforms/Passes.h"
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#include "mlir/Dialect/SCF/Transforms/Passes.h"
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#include "mlir/Dialect/SPIRV/Transforms/Passes.h"
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#include "mlir/Dialect/Shape/Transforms/Passes.h"
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#include "mlir/Dialect/Shard/Transforms/Passes.h"
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#include "mlir/Dialect/SparseTensor/Pipelines/Passes.h"
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#include "mlir/Dialect/SparseTensor/Transforms/Passes.h"
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#include "mlir/Dialect/Tensor/Transforms/Passes.h"
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#include "mlir/Dialect/Tosa/Transforms/Passes.h"
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#include "mlir/Dialect/Transform/Transforms/Passes.h"
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#include "mlir/Dialect/Vector/Transforms/Passes.h"
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#include "mlir/Dialect/XeGPU/Transforms/Passes.h"
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#include "mlir/Target/LLVMIR/Transforms/Passes.h"
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#include "mlir/Transforms/Passes.h"
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// This function may be called to register the MLIR passes with the
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// global registry.
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// If you're building a compiler, you likely don't need this: you would build a
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// pipeline programmatically without the need to register with the global
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// registry, since it would already be calling the creation routine of the
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// individual passes.
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// The global registry is interesting to interact with the command-line tools.
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void mlir::registerAllPasses() {
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// General passes
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registerTransformsPasses();
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// Conversion passes
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registerConversionPasses();
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// Dialect passes
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acc::registerOpenACCPasses();
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affine::registerAffinePasses();
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amdgpu::registerAMDGPUPasses();
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registerAsyncPasses();
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arith::registerArithPasses();
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bufferization::registerBufferizationPasses();
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func::registerFuncPasses();
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registerGPUPasses();
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registerLinalgPasses();
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registerNVGPUPasses();
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registerSparseTensorPasses();
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LLVM::registerLLVMPasses();
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LLVM::registerTargetLLVMIRTransformsPasses();
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math::registerMathPasses();
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memref::registerMemRefPasses();
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shard::registerShardPasses();
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ml_program::registerMLProgramPasses();
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quant::registerQuantPasses();
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registerSCFPasses();
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registerShapePasses();
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spirv::registerSPIRVPasses();
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tensor::registerTensorPasses();
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tosa::registerTosaOptPasses();
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transform::registerTransformPasses();
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vector::registerVectorPasses();
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arm_sme::registerArmSMEPasses();
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arm_sve::registerArmSVEPasses();
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emitc::registerEmitCPasses();
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xegpu::registerXeGPUPasses();
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// Dialect pipelines
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bufferization::registerBufferizationPipelines();
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sparse_tensor::registerSparseTensorPipelines();
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tosa::registerTosaToLinalgPipelines();
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gpu::registerGPUToNVVMPipeline();
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}
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