df852599f3
Currently, the VectorToLLVM patterns are built into a library along with the corresponding pass, which also pulls in all the platform-specific vector dialects (like AMXDialect) to apply all the vector to LLVM conversions. This causes dependency bloat when writing libraries - for example the GPU to LLVM passes, which use the vector to LLVM patterns, don't need the X86Vector dialect to be present at all. This commit partitions the library into VectorToLLVM and VectorToLLVMPass, where the latter pulls in all the other vector transformations. Reviewed By: nicolasvasilache, mehdi_amini Differential Revision: https://reviews.llvm.org/D158287
124 lines
5.1 KiB
C++
124 lines
5.1 KiB
C++
//===- mlir-vulkan-runner.cpp - MLIR Vulkan Execution Driver --------------===//
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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 is a command line utility that executes an MLIR file on the Vulkan by
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// translating MLIR GPU module to SPIR-V and host part to LLVM IR before
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// JIT-compiling and executing the latter.
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//
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//===----------------------------------------------------------------------===//
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#include "mlir/Conversion/FuncToLLVM/ConvertFuncToLLVMPass.h"
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#include "mlir/Conversion/GPUToSPIRV/GPUToSPIRVPass.h"
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#include "mlir/Conversion/GPUToVulkan/ConvertGPUToVulkanPass.h"
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#include "mlir/Conversion/LLVMCommon/LoweringOptions.h"
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#include "mlir/Conversion/MemRefToLLVM/MemRefToLLVM.h"
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#include "mlir/Conversion/ReconcileUnrealizedCasts/ReconcileUnrealizedCasts.h"
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#include "mlir/Conversion/VectorToLLVM/ConvertVectorToLLVMPass.h"
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#include "mlir/Dialect/Arith/IR/Arith.h"
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#include "mlir/Dialect/Func/IR/FuncOps.h"
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#include "mlir/Dialect/GPU/IR/GPUDialect.h"
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#include "mlir/Dialect/GPU/Transforms/Passes.h"
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#include "mlir/Dialect/LLVMIR/LLVMDialect.h"
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#include "mlir/Dialect/LLVMIR/Transforms/RequestCWrappers.h"
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#include "mlir/Dialect/MemRef/IR/MemRef.h"
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#include "mlir/Dialect/MemRef/Transforms/Passes.h"
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#include "mlir/Dialect/SPIRV/IR/SPIRVDialect.h"
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#include "mlir/Dialect/SPIRV/IR/SPIRVOps.h"
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#include "mlir/Dialect/SPIRV/Transforms/Passes.h"
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#include "mlir/Dialect/Vector/IR/VectorOps.h"
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#include "mlir/ExecutionEngine/JitRunner.h"
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#include "mlir/Pass/Pass.h"
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#include "mlir/Pass/PassManager.h"
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#include "mlir/Target/LLVMIR/Dialect/Builtin/BuiltinToLLVMIRTranslation.h"
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#include "mlir/Target/LLVMIR/Dialect/LLVMIR/LLVMToLLVMIRTranslation.h"
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#include "llvm/Support/InitLLVM.h"
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#include "llvm/Support/TargetSelect.h"
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using namespace mlir;
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namespace {
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struct VulkanRunnerOptions {
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llvm::cl::OptionCategory category{"mlir-vulkan-runner options"};
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llvm::cl::opt<bool> spirvWebGPUPrepare{
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"vulkan-runner-spirv-webgpu-prepare",
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llvm::cl::desc("Run MLIR transforms used when targetting WebGPU"),
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llvm::cl::cat(category)};
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};
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} // namespace
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static LogicalResult runMLIRPasses(Operation *op,
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VulkanRunnerOptions &options) {
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auto module = dyn_cast<ModuleOp>(op);
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if (!module)
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return op->emitOpError("expected a 'builtin.module' op");
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PassManager passManager(module.getContext());
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if (failed(applyPassManagerCLOptions(passManager)))
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return failure();
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passManager.addPass(createGpuKernelOutliningPass());
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passManager.addPass(memref::createFoldMemRefAliasOpsPass());
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passManager.addPass(createConvertGPUToSPIRVPass(/*mapMemorySpace=*/true));
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OpPassManager &modulePM = passManager.nest<spirv::ModuleOp>();
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modulePM.addPass(spirv::createSPIRVLowerABIAttributesPass());
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modulePM.addPass(spirv::createSPIRVUpdateVCEPass());
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if (options.spirvWebGPUPrepare)
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modulePM.addPass(spirv::createSPIRVWebGPUPreparePass());
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auto enableOpaquePointers = [](auto passOption) {
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passOption.useOpaquePointers = true;
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return passOption;
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};
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passManager.addPass(createConvertGpuLaunchFuncToVulkanLaunchFuncPass());
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passManager.addPass(createFinalizeMemRefToLLVMConversionPass(
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enableOpaquePointers(FinalizeMemRefToLLVMConversionPassOptions{})));
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passManager.addPass(createConvertVectorToLLVMPass(
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enableOpaquePointers(ConvertVectorToLLVMPassOptions{})));
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passManager.nest<func::FuncOp>().addPass(LLVM::createRequestCWrappersPass());
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ConvertFuncToLLVMPassOptions funcToLLVMOptions{};
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funcToLLVMOptions.indexBitwidth =
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DataLayout(module).getTypeSizeInBits(IndexType::get(module.getContext()));
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passManager.addPass(
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createConvertFuncToLLVMPass(enableOpaquePointers(funcToLLVMOptions)));
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passManager.addPass(createReconcileUnrealizedCastsPass());
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passManager.addPass(createConvertVulkanLaunchFuncToVulkanCallsPass(
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enableOpaquePointers(ConvertVulkanLaunchFuncToVulkanCallsPassOptions{})));
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return passManager.run(module);
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}
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int main(int argc, char **argv) {
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llvm::llvm_shutdown_obj x;
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registerPassManagerCLOptions();
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llvm::InitLLVM y(argc, argv);
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llvm::InitializeNativeTarget();
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llvm::InitializeNativeTargetAsmPrinter();
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// Initialize runner-specific CLI options. These will be parsed and
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// initialzied in `JitRunnerMain`.
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VulkanRunnerOptions options;
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auto runPassesWithOptions = [&options](Operation *op, JitRunnerOptions &) {
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return runMLIRPasses(op, options);
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};
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mlir::JitRunnerConfig jitRunnerConfig;
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jitRunnerConfig.mlirTransformer = runPassesWithOptions;
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mlir::DialectRegistry registry;
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registry.insert<mlir::arith::ArithDialect, mlir::LLVM::LLVMDialect,
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mlir::gpu::GPUDialect, mlir::spirv::SPIRVDialect,
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mlir::func::FuncDialect, mlir::memref::MemRefDialect,
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mlir::vector::VectorDialect>();
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mlir::registerBuiltinDialectTranslation(registry);
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mlir::registerLLVMDialectTranslation(registry);
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return mlir::JitRunnerMain(argc, argv, registry, jitRunnerConfig);
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}
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