//===- LoopsToGPUPass.cpp - Convert a loop nest to a GPU kernel -----------===// // // Copyright 2019 The MLIR Authors. // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. // ============================================================================= #include "mlir/Conversion/LoopsToGPU/LoopsToGPUPass.h" #include "mlir/AffineOps/AffineOps.h" #include "mlir/Conversion/LoopsToGPU/LoopsToGPU.h" #include "mlir/Dialect/LoopOps/LoopOps.h" #include "mlir/Pass/Pass.h" #include "llvm/Support/CommandLine.h" #define PASS_NAME "convert-loops-to-gpu" using namespace mlir; using namespace mlir::loop; static llvm::cl::OptionCategory clOptionsCategory(PASS_NAME " options"); static llvm::cl::opt clNumBlockDims("gpu-block-dims", llvm::cl::desc("Number of GPU block dimensions for mapping"), llvm::cl::cat(clOptionsCategory), llvm::cl::init(1u)); static llvm::cl::opt clNumThreadDims( "gpu-thread-dims", llvm::cl::desc("Number of GPU thread dimensions for mapping"), llvm::cl::cat(clOptionsCategory), llvm::cl::init(1u)); namespace { // A pass that traverses top-level loops in the function and converts them to // GPU launch operations. Nested launches are not allowed, so this does not // walk the function recursively to avoid considering nested loops. struct ForLoopMapper : public FunctionPass { ForLoopMapper(unsigned numBlockDims, unsigned numThreadDims) : numBlockDims(numBlockDims), numThreadDims(numThreadDims) {} void runOnFunction() override { for (Block &block : getFunction()) for (Operation &op : llvm::make_early_inc_range(block)) { if (auto forOp = dyn_cast(&op)) { if (failed(convertAffineLoopNestToGPULaunch(forOp, numBlockDims, numThreadDims))) signalPassFailure(); } else if (auto forOp = dyn_cast(&op)) { if (failed(convertLoopNestToGPULaunch(forOp, numBlockDims, numThreadDims))) signalPassFailure(); } } } unsigned numBlockDims; unsigned numThreadDims; }; } // namespace std::unique_ptr mlir::createSimpleLoopsToGPUPass(unsigned numBlockDims, unsigned numThreadDims) { return llvm::make_unique(numBlockDims, numThreadDims); } static PassRegistration registration(PASS_NAME, "Convert top-level loops to GPU kernels", [] { return llvm::make_unique(clNumBlockDims.getValue(), clNumThreadDims.getValue()); });