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157 lines
6.2 KiB
C++
157 lines
6.2 KiB
C++
//===- KernelOutlining.cpp - Implementation of GPU kernel outling ---------===//
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//
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// Copyright 2019 The MLIR Authors.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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// =============================================================================
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//
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// This file implements the GPU dialect kernel outlining pass.
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//
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//===----------------------------------------------------------------------===//
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#include "mlir/Dialect/GPU/GPUDialect.h"
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#include "mlir/Dialect/GPU/Passes.h"
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#include "mlir/Dialect/StandardOps/Ops.h"
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#include "mlir/IR/BlockAndValueMapping.h"
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#include "mlir/IR/Builders.h"
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#include "mlir/Pass/Pass.h"
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using namespace mlir;
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template <typename OpTy>
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static void createForAllDimensions(OpBuilder &builder, Location loc,
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SmallVectorImpl<Value *> &values) {
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for (StringRef dim : {"x", "y", "z"}) {
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Value *v = builder.create<OpTy>(loc, builder.getIndexType(),
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builder.getStringAttr(dim));
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values.push_back(v);
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}
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}
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// Add operations generating block/thread ids and gird/block dimensions at the
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// beginning of `kernelFunc` and replace uses of the respective function args.
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static void injectGpuIndexOperations(Location loc, FuncOp kernelFunc) {
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OpBuilder OpBuilder(kernelFunc.getBody());
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SmallVector<Value *, 12> indexOps;
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createForAllDimensions<gpu::BlockId>(OpBuilder, loc, indexOps);
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createForAllDimensions<gpu::ThreadId>(OpBuilder, loc, indexOps);
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createForAllDimensions<gpu::GridDim>(OpBuilder, loc, indexOps);
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createForAllDimensions<gpu::BlockDim>(OpBuilder, loc, indexOps);
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// Replace the leading 12 function args with the respective thread/block index
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// operations. Iterate backwards since args are erased and indices change.
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for (int i = 11; i >= 0; --i) {
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auto &firstBlock = kernelFunc.front();
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firstBlock.getArgument(i)->replaceAllUsesWith(indexOps[i]);
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firstBlock.eraseArgument(i);
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}
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}
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// Move all constant arguments of the given kernel function into the function,
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// thereby reducing the number of kernel arguments.
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static gpu::LaunchFuncOp inlineConstants(FuncOp kernelFunc,
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gpu::LaunchFuncOp launch) {
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OpBuilder kernelBuilder(kernelFunc.getBody());
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auto &firstBlock = kernelFunc.getBody().front();
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llvm::SmallVector<Value *, 8> newLaunchArgs;
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for (int i = launch.getNumKernelOperands() - 1; i >= 0; --i) {
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auto operandOp = launch.getKernelOperand(i)->getDefiningOp();
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auto constant = dyn_cast_or_null<ConstantOp>(operandOp);
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if (!constant) {
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newLaunchArgs.push_back(launch.getKernelOperand(i));
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continue;
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}
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auto newConstant = kernelBuilder.clone(*operandOp);
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firstBlock.getArgument(i)->replaceAllUsesWith(newConstant->getResult(0));
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firstBlock.eraseArgument(i);
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}
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if (newLaunchArgs.size() == launch.getNumKernelOperands())
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return launch;
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std::reverse(newLaunchArgs.begin(), newLaunchArgs.end());
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OpBuilder LaunchBuilder(launch);
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SmallVector<Type, 8> newArgumentTypes;
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newArgumentTypes.reserve(firstBlock.getNumArguments());
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for (auto value : firstBlock.getArguments()) {
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newArgumentTypes.push_back(value->getType());
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}
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kernelFunc.setType(LaunchBuilder.getFunctionType(newArgumentTypes, {}));
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auto newLaunch = LaunchBuilder.create<gpu::LaunchFuncOp>(
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launch.getLoc(), kernelFunc, launch.getGridSizeOperandValues(),
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launch.getBlockSizeOperandValues(), newLaunchArgs);
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launch.erase();
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return newLaunch;
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}
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// Outline the `gpu.launch` operation body into a kernel function. Replace
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// `gpu.return` operations by `std.return` in the generated functions.
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static FuncOp outlineKernelFunc(gpu::LaunchOp launchOp) {
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Location loc = launchOp.getLoc();
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SmallVector<Type, 4> kernelOperandTypes(launchOp.getKernelOperandTypes());
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FunctionType type =
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FunctionType::get(kernelOperandTypes, {}, launchOp.getContext());
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std::string kernelFuncName =
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Twine(launchOp.getParentOfType<FuncOp>().getName(), "_kernel").str();
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FuncOp outlinedFunc = FuncOp::create(loc, kernelFuncName, type);
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outlinedFunc.getBody().takeBody(launchOp.getBody());
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Builder builder(launchOp.getContext());
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outlinedFunc.setAttr(gpu::GPUDialect::getKernelFuncAttrName(),
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builder.getUnitAttr());
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injectGpuIndexOperations(loc, outlinedFunc);
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outlinedFunc.walk([](mlir::gpu::Return op) {
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OpBuilder replacer(op);
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replacer.create<ReturnOp>(op.getLoc());
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op.erase();
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});
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return outlinedFunc;
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}
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// Replace `gpu.launch` operations with an `gpu.launch_func` operation launching
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// `kernelFunc`. The kernel func contains the body of the `gpu.launch` with
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// constant region arguments inlined.
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static void convertToLaunchFuncOp(gpu::LaunchOp &launchOp, FuncOp kernelFunc) {
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OpBuilder builder(launchOp);
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SmallVector<Value *, 4> kernelOperandValues(
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launchOp.getKernelOperandValues());
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auto launchFuncOp = builder.create<gpu::LaunchFuncOp>(
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launchOp.getLoc(), kernelFunc, launchOp.getGridSizeOperandValues(),
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launchOp.getBlockSizeOperandValues(), kernelOperandValues);
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inlineConstants(kernelFunc, launchFuncOp);
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launchOp.erase();
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}
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namespace {
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class GpuKernelOutliningPass : public ModulePass<GpuKernelOutliningPass> {
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public:
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void runOnModule() override {
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ModuleManager moduleManager(getModule());
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for (auto func : getModule().getOps<FuncOp>()) {
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func.walk([&](mlir::gpu::LaunchOp op) {
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FuncOp outlinedFunc = outlineKernelFunc(op);
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moduleManager.insert(outlinedFunc);
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convertToLaunchFuncOp(op, outlinedFunc);
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});
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}
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}
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};
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} // namespace
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std::unique_ptr<OpPassBase<ModuleOp>> mlir::createGpuKernelOutliningPass() {
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return std::make_unique<GpuKernelOutliningPass>();
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}
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static PassRegistration<GpuKernelOutliningPass>
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pass("gpu-kernel-outlining",
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"Outline gpu.launch bodies to kernel functions.");
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