//===- ConvertGPUToSPIRV.cpp - Convert GPU ops to SPIR-V dialect ----------===// // // Part of the MLIR Project, under the Apache License v2.0 with LLVM Exceptions. // See https://llvm.org/LICENSE.txt for license information. // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception // //===----------------------------------------------------------------------===// // // This file implements the conversion patterns from GPU ops to SPIR-V dialect. // //===----------------------------------------------------------------------===// #include "mlir/Conversion/GPUToSPIRV/ConvertGPUToSPIRV.h" #include "mlir/Dialect/GPU/GPUDialect.h" #include "mlir/Dialect/LoopOps/LoopOps.h" #include "mlir/Dialect/SPIRV/SPIRVDialect.h" #include "mlir/Dialect/SPIRV/SPIRVLowering.h" #include "mlir/Dialect/SPIRV/SPIRVOps.h" #include "mlir/IR/Module.h" using namespace mlir; namespace { /// Pattern to convert a loop::ForOp within kernel functions into spirv::LoopOp. class ForOpConversion final : public SPIRVOpLowering { public: using SPIRVOpLowering::SPIRVOpLowering; PatternMatchResult matchAndRewrite(loop::ForOp forOp, ArrayRef operands, ConversionPatternRewriter &rewriter) const override; }; /// Pattern lowering GPU block/thread size/id to loading SPIR-V invocation /// builin variables. template class LaunchConfigConversion : public SPIRVOpLowering { public: using SPIRVOpLowering::SPIRVOpLowering; PatternMatchResult matchAndRewrite(SourceOp op, ArrayRef operands, ConversionPatternRewriter &rewriter) const override; }; /// Pattern to convert a kernel function in GPU dialect within a spv.module. class KernelFnConversion final : public SPIRVOpLowering { public: KernelFnConversion(MLIRContext *context, SPIRVTypeConverter &converter, ArrayRef workGroupSize, PatternBenefit benefit = 1) : SPIRVOpLowering(context, converter, benefit) { auto config = workGroupSize.take_front(3); workGroupSizeAsInt32.assign(config.begin(), config.end()); workGroupSizeAsInt32.resize(3, 1); } PatternMatchResult matchAndRewrite(gpu::GPUFuncOp funcOp, ArrayRef operands, ConversionPatternRewriter &rewriter) const override; private: SmallVector workGroupSizeAsInt32; }; /// Pattern to convert a module with gpu.kernel_module attribute to a /// spv.module. class KernelModuleConversion final : public SPIRVOpLowering { public: using SPIRVOpLowering::SPIRVOpLowering; PatternMatchResult matchAndRewrite(ModuleOp moduleOp, ArrayRef operands, ConversionPatternRewriter &rewriter) const override; }; /// Pattern to convert a module terminator op to a terminator of spv.module op. // TODO: Move this into DRR, but that requires ModuleTerminatorOp to be defined // in ODS. class KernelModuleTerminatorConversion final : public SPIRVOpLowering { public: using SPIRVOpLowering::SPIRVOpLowering; PatternMatchResult matchAndRewrite(ModuleTerminatorOp terminatorOp, ArrayRef operands, ConversionPatternRewriter &rewriter) const override; }; /// Pattern to convert a gpu.return into a SPIR-V return. // TODO: This can go to DRR when GPU return has operands. class GPUReturnOpConversion final : public SPIRVOpLowering { public: using SPIRVOpLowering::SPIRVOpLowering; PatternMatchResult matchAndRewrite(gpu::ReturnOp returnOp, ArrayRef operands, ConversionPatternRewriter &rewriter) const override; }; } // namespace //===----------------------------------------------------------------------===// // loop::ForOp. //===----------------------------------------------------------------------===// PatternMatchResult ForOpConversion::matchAndRewrite(loop::ForOp forOp, ArrayRef operands, ConversionPatternRewriter &rewriter) const { // loop::ForOp can be lowered to the structured control flow represented by // spirv::LoopOp by making the continue block of the spirv::LoopOp the loop // latch and the merge block the exit block. The resulting spirv::LoopOp has a // single back edge from the continue to header block, and a single exit from // header to merge. loop::ForOpOperandAdaptor forOperands(operands); auto loc = forOp.getLoc(); auto loopControl = rewriter.getI32IntegerAttr( static_cast(spirv::LoopControl::None)); auto loopOp = rewriter.create(loc, loopControl); loopOp.addEntryAndMergeBlock(); OpBuilder::InsertionGuard guard(rewriter); // Create the block for the header. auto header = new Block(); // Insert the header. loopOp.body().getBlocks().insert(std::next(loopOp.body().begin(), 1), header); // Create the new induction variable to use. BlockArgument newIndVar = header->addArgument(forOperands.lowerBound().getType()); Block *body = forOp.getBody(); // Apply signature conversion to the body of the forOp. It has a single block, // with argument which is the induction variable. That has to be replaced with // the new induction variable. TypeConverter::SignatureConversion signatureConverter( body->getNumArguments()); signatureConverter.remapInput(0, newIndVar); body = rewriter.applySignatureConversion(&forOp.getLoopBody(), signatureConverter); // Delete the loop terminator. rewriter.eraseOp(body->getTerminator()); // Move the blocks from the forOp into the loopOp. This is the body of the // loopOp. rewriter.inlineRegionBefore(forOp.getOperation()->getRegion(0), loopOp.body(), std::next(loopOp.body().begin(), 2)); // Branch into it from the entry. rewriter.setInsertionPointToEnd(&(loopOp.body().front())); rewriter.create(loc, header, forOperands.lowerBound()); // Generate the rest of the loop header. rewriter.setInsertionPointToEnd(header); auto mergeBlock = loopOp.getMergeBlock(); auto cmpOp = rewriter.create( loc, rewriter.getI1Type(), newIndVar, forOperands.upperBound()); rewriter.create( loc, cmpOp, body, ArrayRef(), mergeBlock, ArrayRef()); // Generate instructions to increment the step of the induction variable and // branch to the header. Block *continueBlock = loopOp.getContinueBlock(); rewriter.setInsertionPointToEnd(continueBlock); // Add the step to the induction variable and branch to the header. Value updatedIndVar = rewriter.create( loc, newIndVar.getType(), newIndVar, forOperands.step()); rewriter.create(loc, header, updatedIndVar); rewriter.eraseOp(forOp); return matchSuccess(); } //===----------------------------------------------------------------------===// // Builtins. //===----------------------------------------------------------------------===// template PatternMatchResult LaunchConfigConversion::matchAndRewrite( SourceOp op, ArrayRef operands, ConversionPatternRewriter &rewriter) const { auto dimAttr = op.getOperation()->template getAttrOfType("dimension"); if (!dimAttr) { return this->matchFailure(); } int32_t index = 0; if (dimAttr.getValue() == "x") { index = 0; } else if (dimAttr.getValue() == "y") { index = 1; } else if (dimAttr.getValue() == "z") { index = 2; } else { return this->matchFailure(); } // SPIR-V invocation builtin variables are a vector of type <3xi32> auto spirvBuiltin = spirv::getBuiltinVariableValue(op, builtin, rewriter); rewriter.replaceOpWithNewOp( op, rewriter.getIntegerType(32), spirvBuiltin, rewriter.getI32ArrayAttr({index})); return this->matchSuccess(); } //===----------------------------------------------------------------------===// // GPUFuncOp //===----------------------------------------------------------------------===// // Legalizes a GPU function as an entry SPIR-V function. static FuncOp lowerAsEntryFunction(gpu::GPUFuncOp funcOp, SPIRVTypeConverter &typeConverter, ConversionPatternRewriter &rewriter, spirv::EntryPointABIAttr entryPointInfo, ArrayRef argABIInfo) { auto fnType = funcOp.getType(); if (fnType.getNumResults()) { funcOp.emitError("SPIR-V lowering only supports entry functions" "with no return values right now"); return nullptr; } if (fnType.getNumInputs() != argABIInfo.size()) { funcOp.emitError( "lowering as entry functions requires ABI info for all arguments"); return nullptr; } // Update the signature to valid SPIR-V types and add the ABI // attributes. These will be "materialized" by using the // LowerABIAttributesPass. TypeConverter::SignatureConversion signatureConverter(fnType.getNumInputs()); { for (auto argType : enumerate(funcOp.getType().getInputs())) { auto convertedType = typeConverter.convertType(argType.value()); signatureConverter.addInputs(argType.index(), convertedType); } } auto newFuncOp = rewriter.create( funcOp.getLoc(), funcOp.getName(), rewriter.getFunctionType(signatureConverter.getConvertedTypes(), llvm::None), ArrayRef()); for (const auto &namedAttr : funcOp.getAttrs()) { if (namedAttr.first.is(impl::getTypeAttrName()) || namedAttr.first.is(SymbolTable::getSymbolAttrName())) continue; newFuncOp.setAttr(namedAttr.first, namedAttr.second); } rewriter.inlineRegionBefore(funcOp.getBody(), newFuncOp.getBody(), newFuncOp.end()); rewriter.applySignatureConversion(&newFuncOp.getBody(), signatureConverter); rewriter.eraseOp(funcOp); spirv::setABIAttrs(newFuncOp, entryPointInfo, argABIInfo); return newFuncOp; } PatternMatchResult KernelFnConversion::matchAndRewrite(gpu::GPUFuncOp funcOp, ArrayRef operands, ConversionPatternRewriter &rewriter) const { if (!gpu::GPUDialect::isKernel(funcOp)) { return matchFailure(); } SmallVector argABI; for (auto argNum : llvm::seq(0, funcOp.getNumArguments())) { argABI.push_back(spirv::getInterfaceVarABIAttr( 0, argNum, spirv::StorageClass::StorageBuffer, rewriter.getContext())); } auto context = rewriter.getContext(); auto entryPointAttr = spirv::getEntryPointABIAttr(workGroupSizeAsInt32, context); FuncOp newFuncOp = lowerAsEntryFunction(funcOp, typeConverter, rewriter, entryPointAttr, argABI); if (!newFuncOp) { return matchFailure(); } newFuncOp.removeAttr(Identifier::get(gpu::GPUDialect::getKernelFuncAttrName(), rewriter.getContext())); return matchSuccess(); } //===----------------------------------------------------------------------===// // ModuleOp with gpu.kernel_module. //===----------------------------------------------------------------------===// PatternMatchResult KernelModuleConversion::matchAndRewrite( ModuleOp moduleOp, ArrayRef operands, ConversionPatternRewriter &rewriter) const { if (!moduleOp.getAttrOfType( gpu::GPUDialect::getKernelModuleAttrName())) { return matchFailure(); } // TODO : Generalize this to account for different extensions, // capabilities, extended_instruction_sets, other addressing models // and memory models. auto spvModule = rewriter.create( moduleOp.getLoc(), spirv::AddressingModel::Logical, spirv::MemoryModel::GLSL450, spirv::Capability::Shader, spirv::Extension::SPV_KHR_storage_buffer_storage_class); // Move the region from the module op into the SPIR-V module. Region &spvModuleRegion = spvModule.getOperation()->getRegion(0); rewriter.inlineRegionBefore(moduleOp.getBodyRegion(), spvModuleRegion, spvModuleRegion.begin()); // The spv.module build method adds a block with a terminator. Remove that // block. The terminator of the module op in the remaining block will be // legalized later. spvModuleRegion.back().erase(); rewriter.eraseOp(moduleOp); return matchSuccess(); } //===----------------------------------------------------------------------===// // ModuleTerminatorOp for gpu.kernel_module. //===----------------------------------------------------------------------===// PatternMatchResult KernelModuleTerminatorConversion::matchAndRewrite( ModuleTerminatorOp terminatorOp, ArrayRef operands, ConversionPatternRewriter &rewriter) const { rewriter.replaceOpWithNewOp(terminatorOp); return matchSuccess(); } //===----------------------------------------------------------------------===// // GPU return inside kernel functions to SPIR-V return. //===----------------------------------------------------------------------===// PatternMatchResult GPUReturnOpConversion::matchAndRewrite( gpu::ReturnOp returnOp, ArrayRef operands, ConversionPatternRewriter &rewriter) const { if (!operands.empty()) return matchFailure(); rewriter.replaceOpWithNewOp(returnOp); return matchSuccess(); } //===----------------------------------------------------------------------===// // GPU To SPIRV Patterns. //===----------------------------------------------------------------------===// void mlir::populateGPUToSPIRVPatterns(MLIRContext *context, SPIRVTypeConverter &typeConverter, OwningRewritePatternList &patterns, ArrayRef workGroupSize) { patterns.insert(context, typeConverter, workGroupSize); patterns.insert< GPUReturnOpConversion, ForOpConversion, KernelModuleConversion, KernelModuleTerminatorConversion, LaunchConfigConversion, LaunchConfigConversion, LaunchConfigConversion, LaunchConfigConversion>(context, typeConverter); }