//===- ConvertLaunchFuncToGpuRuntimeCalls.cpp - MLIR GPU lowering passes --===// // // Part of the LLVM 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 a pass to convert gpu.launch_func op into a sequence of // GPU runtime calls. As most of GPU runtimes does not have a stable published // ABI, this pass uses a slim runtime layer that builds on top of the public // API from GPU runtime headers. // //===----------------------------------------------------------------------===// #include "mlir/Conversion/GPUCommon/GPUCommonPass.h" #include "../PassDetail.h" #include "mlir/Conversion/StandardToLLVM/ConvertStandardToLLVM.h" #include "mlir/Dialect/GPU/GPUDialect.h" #include "mlir/Dialect/LLVMIR/LLVMDialect.h" #include "mlir/IR/Attributes.h" #include "mlir/IR/Builders.h" #include "mlir/IR/Function.h" #include "mlir/IR/Module.h" #include "mlir/IR/StandardTypes.h" #include "llvm/ADT/STLExtras.h" #include "llvm/IR/DataLayout.h" #include "llvm/IR/DerivedTypes.h" #include "llvm/IR/Module.h" #include "llvm/IR/Type.h" #include "llvm/Support/Error.h" #include "llvm/Support/FormatVariadic.h" using namespace mlir; static constexpr const char *kGpuBinaryStorageSuffix = "_gpubin_cst"; namespace { class GpuToLLVMConversionPass : public GpuToLLVMConversionPassBase { public: GpuToLLVMConversionPass(StringRef gpuBinaryAnnotation) { if (!gpuBinaryAnnotation.empty()) this->gpuBinaryAnnotation = gpuBinaryAnnotation.str(); } // Run the dialect converter on the module. void runOnOperation() override; }; class FunctionCallBuilder { public: FunctionCallBuilder(StringRef functionName, LLVM::LLVMType returnType, ArrayRef argumentTypes) : functionName(functionName), functionType(LLVM::LLVMType::getFunctionTy(returnType, argumentTypes, /*isVarArg=*/false)) {} LLVM::CallOp create(Location loc, OpBuilder &builder, ArrayRef arguments) const; private: StringRef functionName; LLVM::LLVMType functionType; }; template class ConvertOpToGpuRuntimeCallPattern : public ConvertOpToLLVMPattern { public: explicit ConvertOpToGpuRuntimeCallPattern(LLVMTypeConverter &typeConverter) : ConvertOpToLLVMPattern(typeConverter) {} protected: MLIRContext *context = &this->typeConverter.getContext(); LLVM::LLVMType llvmVoidType = LLVM::LLVMType::getVoidTy(context); LLVM::LLVMType llvmPointerType = LLVM::LLVMType::getInt8PtrTy(context); LLVM::LLVMType llvmPointerPointerType = llvmPointerType.getPointerTo(); LLVM::LLVMType llvmInt8Type = LLVM::LLVMType::getInt8Ty(context); LLVM::LLVMType llvmInt32Type = LLVM::LLVMType::getInt32Ty(context); LLVM::LLVMType llvmInt64Type = LLVM::LLVMType::getInt64Ty(context); LLVM::LLVMType llvmIntPtrType = LLVM::LLVMType::getIntNTy( context, this->typeConverter.getPointerBitwidth(0)); FunctionCallBuilder moduleLoadCallBuilder = { "mgpuModuleLoad", llvmPointerType /* void *module */, {llvmPointerType /* void *cubin */}}; FunctionCallBuilder moduleGetFunctionCallBuilder = { "mgpuModuleGetFunction", llvmPointerType /* void *function */, { llvmPointerType, /* void *module */ llvmPointerType /* char *name */ }}; FunctionCallBuilder launchKernelCallBuilder = { "mgpuLaunchKernel", llvmVoidType, { llvmPointerType, /* void* f */ llvmIntPtrType, /* intptr_t gridXDim */ llvmIntPtrType, /* intptr_t gridyDim */ llvmIntPtrType, /* intptr_t gridZDim */ llvmIntPtrType, /* intptr_t blockXDim */ llvmIntPtrType, /* intptr_t blockYDim */ llvmIntPtrType, /* intptr_t blockZDim */ llvmInt32Type, /* unsigned int sharedMemBytes */ llvmPointerType, /* void *hstream */ llvmPointerPointerType, /* void **kernelParams */ llvmPointerPointerType /* void **extra */ }}; FunctionCallBuilder streamCreateCallBuilder = { "mgpuStreamCreate", llvmPointerType /* void *stream */, {}}; FunctionCallBuilder streamSynchronizeCallBuilder = { "mgpuStreamSynchronize", llvmVoidType, {llvmPointerType /* void *stream */}}; FunctionCallBuilder hostRegisterCallBuilder = { "mgpuMemHostRegisterMemRef", llvmVoidType, {llvmIntPtrType /* intptr_t rank */, llvmPointerType /* void *memrefDesc */, llvmIntPtrType /* intptr_t elementSizeBytes */}}; }; /// A rewrite patter to convert gpu.host_register operations into a GPU runtime /// call. Currently it supports CUDA and ROCm (HIP). class ConvertHostRegisterOpToGpuRuntimeCallPattern : public ConvertOpToGpuRuntimeCallPattern { public: ConvertHostRegisterOpToGpuRuntimeCallPattern(LLVMTypeConverter &typeConverter) : ConvertOpToGpuRuntimeCallPattern(typeConverter) {} private: LogicalResult matchAndRewrite(Operation *op, ArrayRef operands, ConversionPatternRewriter &rewriter) const override; }; /// A rewrite patter to convert gpu.launch_func operations into a sequence of /// GPU runtime calls. Currently it supports CUDA and ROCm (HIP). /// /// In essence, a gpu.launch_func operations gets compiled into the following /// sequence of runtime calls: /// /// * moduleLoad -- loads the module given the cubin / hsaco data /// * moduleGetFunction -- gets a handle to the actual kernel function /// * getStreamHelper -- initializes a new compute stream on GPU /// * launchKernel -- launches the kernel on a stream /// * streamSynchronize -- waits for operations on the stream to finish /// /// Intermediate data structures are allocated on the stack. class ConvertLaunchFuncOpToGpuRuntimeCallPattern : public ConvertOpToGpuRuntimeCallPattern { public: ConvertLaunchFuncOpToGpuRuntimeCallPattern(LLVMTypeConverter &typeConverter, StringRef gpuBinaryAnnotation) : ConvertOpToGpuRuntimeCallPattern(typeConverter), gpuBinaryAnnotation(gpuBinaryAnnotation) {} private: Value generateParamsArray(gpu::LaunchFuncOp launchOp, ArrayRef operands, OpBuilder &builder) const; Value generateKernelNameConstant(StringRef moduleName, StringRef name, Location loc, OpBuilder &builder) const; LogicalResult matchAndRewrite(Operation *op, ArrayRef operands, ConversionPatternRewriter &rewriter) const override; llvm::SmallString<32> gpuBinaryAnnotation; }; class EraseGpuModuleOpPattern : public OpRewritePattern { using OpRewritePattern::OpRewritePattern; LogicalResult matchAndRewrite(gpu::GPUModuleOp op, PatternRewriter &rewriter) const override { // GPU kernel modules are no longer necessary since we have a global // constant with the CUBIN, or HSACO data. rewriter.eraseOp(op); return success(); } }; } // namespace void GpuToLLVMConversionPass::runOnOperation() { LLVMTypeConverter converter(&getContext()); OwningRewritePatternList patterns; populateStdToLLVMConversionPatterns(converter, patterns); populateGpuToLLVMConversionPatterns(converter, patterns, gpuBinaryAnnotation); LLVMConversionTarget target(getContext()); if (failed(applyPartialConversion(getOperation(), target, patterns))) signalPassFailure(); } LLVM::CallOp FunctionCallBuilder::create(Location loc, OpBuilder &builder, ArrayRef arguments) const { auto module = builder.getBlock()->getParent()->getParentOfType(); auto function = [&] { if (auto function = module.lookupSymbol(functionName)) return function; return OpBuilder(module.getBody()->getTerminator()) .create(loc, functionName, functionType); }(); return builder.create( loc, const_cast(functionType).getFunctionResultType(), builder.getSymbolRefAttr(function), arguments); } // Returns whether value is of LLVM type. static bool isLLVMType(Value value) { return value.getType().isa(); } LogicalResult ConvertHostRegisterOpToGpuRuntimeCallPattern::matchAndRewrite( Operation *op, ArrayRef operands, ConversionPatternRewriter &rewriter) const { if (!llvm::all_of(operands, isLLVMType)) return rewriter.notifyMatchFailure( op, "Cannot convert if operands aren't of LLVM type."); Location loc = op->getLoc(); auto memRefType = cast(op).value().getType(); auto elementType = memRefType.cast().getElementType(); auto elementSize = getSizeInBytes(loc, elementType, rewriter); auto arguments = typeConverter.promoteOperands(loc, op->getOperands(), operands, rewriter); arguments.push_back(elementSize); hostRegisterCallBuilder.create(loc, rewriter, arguments); rewriter.eraseOp(op); return success(); } // Creates a struct containing all kernel parameters on the stack and returns // an array of type-erased pointers to the fields of the struct. The array can // then be passed to the CUDA / ROCm (HIP) kernel launch calls. // The generated code is essentially as follows: // // %struct = alloca(sizeof(struct { Parameters... })) // %array = alloca(NumParameters * sizeof(void *)) // for (i : [0, NumParameters)) // %fieldPtr = llvm.getelementptr %struct[0, i] // llvm.store parameters[i], %fieldPtr // %elementPtr = llvm.getelementptr %array[i] // llvm.store %fieldPtr, %elementPtr // return %array Value ConvertLaunchFuncOpToGpuRuntimeCallPattern::generateParamsArray( gpu::LaunchFuncOp launchOp, ArrayRef operands, OpBuilder &builder) const { auto loc = launchOp.getLoc(); auto numKernelOperands = launchOp.getNumKernelOperands(); auto arguments = typeConverter.promoteOperands( loc, launchOp.getOperands().take_back(numKernelOperands), operands.take_back(numKernelOperands), builder); auto numArguments = arguments.size(); SmallVector argumentTypes; argumentTypes.reserve(numArguments); for (auto argument : arguments) argumentTypes.push_back(argument.getType().cast()); auto structType = LLVM::LLVMType::createStructTy(argumentTypes, StringRef()); auto one = builder.create(loc, llvmInt32Type, builder.getI32IntegerAttr(1)); auto structPtr = builder.create( loc, structType.getPointerTo(), one, /*alignment=*/0); auto arraySize = builder.create( loc, llvmInt32Type, builder.getI32IntegerAttr(numArguments)); auto arrayPtr = builder.create(loc, llvmPointerPointerType, arraySize, /*alignment=*/0); auto zero = builder.create(loc, llvmInt32Type, builder.getI32IntegerAttr(0)); for (auto en : llvm::enumerate(arguments)) { auto index = builder.create( loc, llvmInt32Type, builder.getI32IntegerAttr(en.index())); auto fieldPtr = builder.create(loc, structType.getPointerTo(), structPtr, ArrayRef{zero, index.getResult()}); builder.create(loc, en.value(), fieldPtr); auto elementPtr = builder.create(loc, llvmPointerPointerType, arrayPtr, index.getResult()); auto casted = builder.create(loc, llvmPointerType, fieldPtr); builder.create(loc, casted, elementPtr); } return arrayPtr; } // Generates an LLVM IR dialect global that contains the name of the given // kernel function as a C string, and returns a pointer to its beginning. // The code is essentially: // // llvm.global constant @kernel_name("function_name\00") // func(...) { // %0 = llvm.addressof @kernel_name // %1 = llvm.constant (0 : index) // %2 = llvm.getelementptr %0[%1, %1] : !llvm<"i8*"> // } Value ConvertLaunchFuncOpToGpuRuntimeCallPattern::generateKernelNameConstant( StringRef moduleName, StringRef name, Location loc, OpBuilder &builder) const { // Make sure the trailing zero is included in the constant. std::vector kernelName(name.begin(), name.end()); kernelName.push_back('\0'); std::string globalName = std::string(llvm::formatv("{0}_{1}_kernel_name", moduleName, name)); return LLVM::createGlobalString( loc, builder, globalName, StringRef(kernelName.data(), kernelName.size()), LLVM::Linkage::Internal); } // Emits LLVM IR to launch a kernel function. Expects the module that contains // the compiled kernel function as a cubin in the 'nvvm.cubin' attribute, or a // hsaco in the 'rocdl.hsaco' attribute of the kernel function in the IR. // // %0 = call %binarygetter // %1 = call %moduleLoad(%0) // %2 = // %3 = call %moduleGetFunction(%1, %2) // %4 = call %streamCreate() // %5 = // call %launchKernel(%3, , 0, %4, %5, nullptr) // call %streamSynchronize(%4) LogicalResult ConvertLaunchFuncOpToGpuRuntimeCallPattern::matchAndRewrite( Operation *op, ArrayRef operands, ConversionPatternRewriter &rewriter) const { if (!llvm::all_of(operands, isLLVMType)) return rewriter.notifyMatchFailure( op, "Cannot convert if operands aren't of LLVM type."); auto launchOp = cast(op); Location loc = launchOp.getLoc(); // Create an LLVM global with CUBIN extracted from the kernel annotation and // obtain a pointer to the first byte in it. auto kernelModule = SymbolTable::lookupNearestSymbolFrom( launchOp, launchOp.getKernelModuleName()); assert(kernelModule && "expected a kernel module"); auto binaryAttr = kernelModule.getAttrOfType(gpuBinaryAnnotation); if (!binaryAttr) { kernelModule.emitOpError() << "missing " << gpuBinaryAnnotation << " attribute"; return failure(); } SmallString<128> nameBuffer(kernelModule.getName()); nameBuffer.append(kGpuBinaryStorageSuffix); Value data = LLVM::createGlobalString(loc, rewriter, nameBuffer.str(), binaryAttr.getValue(), LLVM::Linkage::Internal); auto module = moduleLoadCallBuilder.create(loc, rewriter, data); // Get the function from the module. The name corresponds to the name of // the kernel function. auto kernelName = generateKernelNameConstant( launchOp.getKernelModuleName(), launchOp.getKernelName(), loc, rewriter); auto function = moduleGetFunctionCallBuilder.create( loc, rewriter, {module.getResult(0), kernelName}); auto zero = rewriter.create(loc, llvmInt32Type, rewriter.getI32IntegerAttr(0)); // Grab the global stream needed for execution. auto stream = streamCreateCallBuilder.create(loc, rewriter, {}); // Create array of pointers to kernel arguments. auto kernelParams = generateParamsArray(launchOp, operands, rewriter); auto nullpointer = rewriter.create(loc, llvmPointerPointerType); launchKernelCallBuilder.create( loc, rewriter, {function.getResult(0), launchOp.gridSizeX(), launchOp.gridSizeY(), launchOp.gridSizeZ(), launchOp.blockSizeX(), launchOp.blockSizeY(), launchOp.blockSizeZ(), zero, /* sharedMemBytes */ stream.getResult(0), /* stream */ kernelParams, /* kernel params */ nullpointer /* extra */}); streamSynchronizeCallBuilder.create(loc, rewriter, stream.getResult(0)); rewriter.eraseOp(op); return success(); } std::unique_ptr> mlir::createGpuToLLVMConversionPass(StringRef gpuBinaryAnnotation) { return std::make_unique(gpuBinaryAnnotation); } void mlir::populateGpuToLLVMConversionPatterns( LLVMTypeConverter &converter, OwningRewritePatternList &patterns, StringRef gpuBinaryAnnotation) { patterns.insert(converter); patterns.insert( converter, gpuBinaryAnnotation); patterns.insert(&converter.getContext()); }