//===- ObjectHandler.cpp - Implements base ObjectManager attributes -------===// // // 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 the `OffloadingLLVMTranslationAttrInterface` for the // `SelectObject` attribute. // //===----------------------------------------------------------------------===// #include "mlir/Dialect/GPU/IR/GPUDialect.h" #include "mlir/Target/LLVMIR/Dialect/GPU/GPUToLLVMIRTranslation.h" #include "mlir/Target/LLVMIR/Export.h" #include "mlir/Target/LLVMIR/ModuleTranslation.h" #include "llvm/IR/Constants.h" #include "llvm/IR/IRBuilder.h" #include "llvm/IR/LLVMContext.h" #include "llvm/IR/Module.h" #include "llvm/Support/FormatVariadic.h" using namespace mlir; namespace { // Implementation of the `OffloadingLLVMTranslationAttrInterface` model. class SelectObjectAttrImpl : public gpu::OffloadingLLVMTranslationAttrInterface::FallbackModel< SelectObjectAttrImpl> { public: // Translates a `gpu.binary`, embedding the binary into a host LLVM module as // global binary string. LogicalResult embedBinary(Attribute attribute, Operation *operation, llvm::IRBuilderBase &builder, LLVM::ModuleTranslation &moduleTranslation) const; // Translates a `gpu.launch_func` to a sequence of LLVM instructions resulting // in a kernel launch call. LogicalResult launchKernel(Attribute attribute, Operation *launchFuncOperation, Operation *binaryOperation, llvm::IRBuilderBase &builder, LLVM::ModuleTranslation &moduleTranslation) const; // Returns the selected object for embedding. gpu::ObjectAttr getSelectedObject(gpu::BinaryOp op) const; }; // Returns an identifier for the global string holding the binary. std::string getBinaryIdentifier(StringRef binaryName) { return binaryName.str() + "_bin_cst"; } } // namespace void mlir::gpu::registerOffloadingLLVMTranslationInterfaceExternalModels( DialectRegistry ®istry) { registry.addExtension(+[](MLIRContext *ctx, gpu::GPUDialect *dialect) { SelectObjectAttr::attachInterface(*ctx); }); } gpu::ObjectAttr SelectObjectAttrImpl::getSelectedObject(gpu::BinaryOp op) const { ArrayRef objects = op.getObjectsAttr().getValue(); // Obtain the index of the object to select. int64_t index = -1; if (Attribute target = cast(op.getOffloadingHandlerAttr()) .getTarget()) { // If the target attribute is a number it is the index. Otherwise compare // the attribute to every target inside the object array to find the index. if (auto indexAttr = mlir::dyn_cast(target)) { index = indexAttr.getInt(); } else { for (auto [i, attr] : llvm::enumerate(objects)) { auto obj = mlir::dyn_cast(attr); if (obj.getTarget() == target) { index = i; } } } } else { // If the target attribute is null then it's selecting the first object in // the object array. index = 0; } if (index < 0 || index >= static_cast(objects.size())) { op->emitError("the requested target object couldn't be found"); return nullptr; } return mlir::dyn_cast(objects[index]); } LogicalResult SelectObjectAttrImpl::embedBinary( Attribute attribute, Operation *operation, llvm::IRBuilderBase &builder, LLVM::ModuleTranslation &moduleTranslation) const { assert(operation && "The binary operation must be non null."); if (!operation) return failure(); auto op = mlir::dyn_cast(operation); if (!op) { operation->emitError("operation must be a GPU binary"); return failure(); } gpu::ObjectAttr object = getSelectedObject(op); if (!object) return failure(); llvm::Module *module = moduleTranslation.getLLVMModule(); // Embed the object as a global string. llvm::Constant *binary = llvm::ConstantDataArray::getString( builder.getContext(), object.getObject().getValue(), false); llvm::GlobalVariable *serializedObj = new llvm::GlobalVariable(*module, binary->getType(), true, llvm::GlobalValue::LinkageTypes::InternalLinkage, binary, getBinaryIdentifier(op.getName())); serializedObj->setLinkage(llvm::GlobalValue::LinkageTypes::InternalLinkage); serializedObj->setAlignment(llvm::MaybeAlign(8)); serializedObj->setUnnamedAddr(llvm::GlobalValue::UnnamedAddr::None); return success(); } namespace llvm { namespace { class LaunchKernel { public: LaunchKernel(Module &module, IRBuilderBase &builder, mlir::LLVM::ModuleTranslation &moduleTranslation); // Get the kernel launch callee. FunctionCallee getKernelLaunchFn(); // Get the kernel launch callee. FunctionCallee getClusterKernelLaunchFn(); // Get the module function callee. FunctionCallee getModuleFunctionFn(); // Get the module load callee. FunctionCallee getModuleLoadFn(); // Get the module load JIT callee. FunctionCallee getModuleLoadJITFn(); // Get the module unload callee. FunctionCallee getModuleUnloadFn(); // Get the stream create callee. FunctionCallee getStreamCreateFn(); // Get the stream destroy callee. FunctionCallee getStreamDestroyFn(); // Get the stream sync callee. FunctionCallee getStreamSyncFn(); // Ger or create the function name global string. Value *getOrCreateFunctionName(StringRef moduleName, StringRef kernelName); // Create the void* kernel array for passing the arguments. Value *createKernelArgArray(mlir::gpu::LaunchFuncOp op); // Create the full kernel launch. mlir::LogicalResult createKernelLaunch(mlir::gpu::LaunchFuncOp op, mlir::gpu::ObjectAttr object); private: Module &module; IRBuilderBase &builder; mlir::LLVM::ModuleTranslation &moduleTranslation; Type *i32Ty{}; Type *i64Ty{}; Type *voidTy{}; Type *intPtrTy{}; PointerType *ptrTy{}; }; } // namespace } // namespace llvm LogicalResult SelectObjectAttrImpl::launchKernel( Attribute attribute, Operation *launchFuncOperation, Operation *binaryOperation, llvm::IRBuilderBase &builder, LLVM::ModuleTranslation &moduleTranslation) const { assert(launchFuncOperation && "The launch func operation must be non null."); if (!launchFuncOperation) return failure(); auto launchFuncOp = mlir::dyn_cast(launchFuncOperation); if (!launchFuncOp) { launchFuncOperation->emitError("operation must be a GPU launch func Op."); return failure(); } auto binOp = mlir::dyn_cast(binaryOperation); if (!binOp) { binaryOperation->emitError("operation must be a GPU binary."); return failure(); } gpu::ObjectAttr object = getSelectedObject(binOp); if (!object) return failure(); return llvm::LaunchKernel(*moduleTranslation.getLLVMModule(), builder, moduleTranslation) .createKernelLaunch(launchFuncOp, object); } llvm::LaunchKernel::LaunchKernel( Module &module, IRBuilderBase &builder, mlir::LLVM::ModuleTranslation &moduleTranslation) : module(module), builder(builder), moduleTranslation(moduleTranslation) { i32Ty = builder.getInt32Ty(); i64Ty = builder.getInt64Ty(); ptrTy = builder.getPtrTy(0); voidTy = builder.getVoidTy(); intPtrTy = builder.getIntPtrTy(module.getDataLayout()); } llvm::FunctionCallee llvm::LaunchKernel::getKernelLaunchFn() { return module.getOrInsertFunction( "mgpuLaunchKernel", FunctionType::get(voidTy, ArrayRef({ptrTy, intPtrTy, intPtrTy, intPtrTy, intPtrTy, intPtrTy, intPtrTy, i32Ty, ptrTy, ptrTy, ptrTy, i64Ty}), false)); } llvm::FunctionCallee llvm::LaunchKernel::getClusterKernelLaunchFn() { return module.getOrInsertFunction( "mgpuLaunchClusterKernel", FunctionType::get( voidTy, ArrayRef({ptrTy, intPtrTy, intPtrTy, intPtrTy, intPtrTy, intPtrTy, intPtrTy, intPtrTy, intPtrTy, intPtrTy, i32Ty, ptrTy, ptrTy, ptrTy}), false)); } llvm::FunctionCallee llvm::LaunchKernel::getModuleFunctionFn() { return module.getOrInsertFunction( "mgpuModuleGetFunction", FunctionType::get(ptrTy, ArrayRef({ptrTy, ptrTy}), false)); } llvm::FunctionCallee llvm::LaunchKernel::getModuleLoadFn() { return module.getOrInsertFunction( "mgpuModuleLoad", FunctionType::get(ptrTy, ArrayRef({ptrTy, i64Ty}), false)); } llvm::FunctionCallee llvm::LaunchKernel::getModuleLoadJITFn() { return module.getOrInsertFunction( "mgpuModuleLoadJIT", FunctionType::get(ptrTy, ArrayRef({ptrTy, i32Ty}), false)); } llvm::FunctionCallee llvm::LaunchKernel::getModuleUnloadFn() { return module.getOrInsertFunction( "mgpuModuleUnload", FunctionType::get(voidTy, ArrayRef({ptrTy}), false)); } llvm::FunctionCallee llvm::LaunchKernel::getStreamCreateFn() { return module.getOrInsertFunction("mgpuStreamCreate", FunctionType::get(ptrTy, false)); } llvm::FunctionCallee llvm::LaunchKernel::getStreamDestroyFn() { return module.getOrInsertFunction( "mgpuStreamDestroy", FunctionType::get(voidTy, ArrayRef({ptrTy}), false)); } llvm::FunctionCallee llvm::LaunchKernel::getStreamSyncFn() { return module.getOrInsertFunction( "mgpuStreamSynchronize", FunctionType::get(voidTy, ArrayRef({ptrTy}), false)); } // 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. llvm::Value *llvm::LaunchKernel::getOrCreateFunctionName(StringRef moduleName, StringRef kernelName) { std::string globalName = std::string(formatv("{0}_{1}_kernel_name", moduleName, kernelName)); if (GlobalVariable *gv = module.getGlobalVariable(globalName)) return gv; return builder.CreateGlobalString(kernelName, globalName); } // 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 llvm::Value * llvm::LaunchKernel::createKernelArgArray(mlir::gpu::LaunchFuncOp op) { SmallVector args = moduleTranslation.lookupValues(op.getKernelOperands()); SmallVector structTypes(args.size(), nullptr); for (auto [i, arg] : llvm::enumerate(args)) structTypes[i] = arg->getType(); Type *structTy = StructType::create(module.getContext(), structTypes); Value *argStruct = builder.CreateAlloca(structTy, 0u); Value *argArray = builder.CreateAlloca( ptrTy, ConstantInt::get(intPtrTy, structTypes.size())); for (auto [i, arg] : enumerate(args)) { Value *structMember = builder.CreateStructGEP(structTy, argStruct, i); builder.CreateStore(arg, structMember); Value *arrayMember = builder.CreateConstGEP1_32(ptrTy, argArray, i); builder.CreateStore(structMember, arrayMember); } return argArray; } // Emits LLVM IR to launch a kernel function: // %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) // call %streamDestroy(%4) // call %moduleUnload(%1) mlir::LogicalResult llvm::LaunchKernel::createKernelLaunch(mlir::gpu::LaunchFuncOp op, mlir::gpu::ObjectAttr object) { auto llvmValue = [&](mlir::Value value) -> Value * { Value *v = moduleTranslation.lookupValue(value); assert(v && "Value has not been translated."); return v; }; // Get grid dimensions. mlir::gpu::KernelDim3 grid = op.getGridSizeOperandValues(); Value *gx = llvmValue(grid.x), *gy = llvmValue(grid.y), *gz = llvmValue(grid.z); // Get block dimensions. mlir::gpu::KernelDim3 block = op.getBlockSizeOperandValues(); Value *bx = llvmValue(block.x), *by = llvmValue(block.y), *bz = llvmValue(block.z); // Get dynamic shared memory size. Value *dynamicMemorySize = nullptr; if (mlir::Value dynSz = op.getDynamicSharedMemorySize()) dynamicMemorySize = llvmValue(dynSz); else dynamicMemorySize = ConstantInt::get(i32Ty, 0); // Create the argument array. Value *argArray = createKernelArgArray(op); // Default JIT optimization level. llvm::Constant *optV = llvm::ConstantInt::get(i32Ty, 0); // Check if there's an optimization level embedded in the object. DictionaryAttr objectProps = object.getProperties(); mlir::Attribute optAttr; if (objectProps && (optAttr = objectProps.get("O"))) { auto optLevel = dyn_cast(optAttr); if (!optLevel) return op.emitError("the optimization level must be an integer"); optV = llvm::ConstantInt::get(i32Ty, optLevel.getValue()); } // Load the kernel module. StringRef moduleName = op.getKernelModuleName().getValue(); std::string binaryIdentifier = getBinaryIdentifier(moduleName); Value *binary = module.getGlobalVariable(binaryIdentifier, true); if (!binary) return op.emitError() << "Couldn't find the binary: " << binaryIdentifier; auto binaryVar = dyn_cast(binary); if (!binaryVar) return op.emitError() << "Binary is not a global variable: " << binaryIdentifier; llvm::Constant *binaryInit = binaryVar->getInitializer(); auto binaryDataSeq = dyn_cast_if_present(binaryInit); if (!binaryDataSeq) return op.emitError() << "Couldn't find binary data array: " << binaryIdentifier; llvm::Constant *binarySize = llvm::ConstantInt::get(i64Ty, binaryDataSeq->getNumElements() * binaryDataSeq->getElementByteSize()); Value *moduleObject = object.getFormat() == gpu::CompilationTarget::Assembly ? builder.CreateCall(getModuleLoadJITFn(), {binary, optV}) : builder.CreateCall(getModuleLoadFn(), {binary, binarySize}); // Load the kernel function. Value *moduleFunction = builder.CreateCall( getModuleFunctionFn(), {moduleObject, getOrCreateFunctionName(moduleName, op.getKernelName().getValue())}); // Get the stream to use for execution. If there's no async object then create // a stream to make a synchronous kernel launch. Value *stream = nullptr; bool handleStream = false; if (mlir::Value asyncObject = op.getAsyncObject()) { stream = llvmValue(asyncObject); } else { handleStream = true; stream = builder.CreateCall(getStreamCreateFn(), {}); } llvm::Constant *paramsCount = llvm::ConstantInt::get(i64Ty, op.getNumKernelOperands()); // Create the launch call. Value *nullPtr = ConstantPointerNull::get(ptrTy); // Launch kernel with clusters if cluster size is specified. if (op.hasClusterSize()) { mlir::gpu::KernelDim3 cluster = op.getClusterSizeOperandValues(); Value *cx = llvmValue(cluster.x), *cy = llvmValue(cluster.y), *cz = llvmValue(cluster.z); builder.CreateCall( getClusterKernelLaunchFn(), ArrayRef({moduleFunction, cx, cy, cz, gx, gy, gz, bx, by, bz, dynamicMemorySize, stream, argArray, nullPtr})); } else { builder.CreateCall(getKernelLaunchFn(), ArrayRef({moduleFunction, gx, gy, gz, bx, by, bz, dynamicMemorySize, stream, argArray, nullPtr, paramsCount})); } // Sync & destroy the stream, for synchronous launches. if (handleStream) { builder.CreateCall(getStreamSyncFn(), {stream}); builder.CreateCall(getStreamDestroyFn(), {stream}); } // Unload the kernel module. builder.CreateCall(getModuleUnloadFn(), {moduleObject}); return success(); }