Simple CPU runner
This implements a simple CPU runner based on LLVM Orc JIT. The base
functionality is provided by the ExecutionEngine class that compiles and links
the module, and provides an interface for obtaining function pointers to the
JIT-compiled MLIR functions and for invoking those functions directly. Since
function pointers need to be casted to the correct pointer type, the
ExecutionEngine wraps LLVM IR functions obtained from MLIR into a helper
function with the common signature `void (void **)` where the single argument
is interpreted as a list of pointers to the actual arguments passed to the
function, eventually followed by a pointer to the result of the function.
Additionally, the ExecutionEngine is set up to resolve library functions to
those available in the current process, enabling support for, e.g., simple C
library calls.
For integration purposes, this also provides a simplistic runtime for memref
descriptors as expected by the LLVM IR code produced by MLIR translation. In
particular, memrefs are transformed into LLVM structs (can be mapped to C
structs) with a pointer to the data, followed by dynamic sizes. This
implementation only supports statically-shaped memrefs of type float, but can
be extened if necessary.
Provide a binary for the runner and a test that exercises it.
PiperOrigin-RevId: 230876363
2019-01-25 19:16:06 +08:00
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//===- ExecutionEngine.cpp - MLIR Execution engine and utils --------------===//
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//
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// Copyright 2019 The MLIR Authors.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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// =============================================================================
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//
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// This file implements the execution engine for MLIR modules based on LLVM Orc
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// JIT engine.
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//
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//===----------------------------------------------------------------------===//
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#include "mlir/ExecutionEngine/ExecutionEngine.h"
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#include "mlir/IR/Function.h"
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#include "mlir/IR/Module.h"
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#include "mlir/Pass.h"
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#include "mlir/Target/LLVMIR.h"
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#include "mlir/Transforms/Passes.h"
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#include "llvm/ExecutionEngine/Orc/CompileUtils.h"
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#include "llvm/ExecutionEngine/Orc/ExecutionUtils.h"
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#include "llvm/ExecutionEngine/Orc/IRCompileLayer.h"
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#include "llvm/ExecutionEngine/Orc/JITTargetMachineBuilder.h"
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#include "llvm/ExecutionEngine/Orc/RTDyldObjectLinkingLayer.h"
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#include "llvm/ExecutionEngine/SectionMemoryManager.h"
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#include "llvm/IR/IRBuilder.h"
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#include "llvm/Support/Error.h"
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#include "llvm/Support/TargetRegistry.h"
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using namespace mlir;
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using llvm::Error;
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using llvm::Expected;
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namespace {
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// Memory manager for the JIT's objectLayer. Its main goal is to fallback to
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// resolving functions in the current process if they cannot be resolved in the
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// JIT-compiled modules.
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class MemoryManager : public llvm::SectionMemoryManager {
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public:
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MemoryManager(llvm::orc::ExecutionSession &execSession)
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: session(execSession) {}
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// Resolve the named symbol. First, try looking it up in the main library of
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// the execution session. If there is no such symbol, try looking it up in
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// the current process (for example, if it is a standard library function).
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// Return `nullptr` if lookup fails.
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llvm::JITSymbol findSymbol(const std::string &name) override {
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auto mainLibSymbol = session.lookup({&session.getMainJITDylib()}, name);
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if (mainLibSymbol)
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return mainLibSymbol.get();
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auto address = llvm::RTDyldMemoryManager::getSymbolAddressInProcess(name);
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if (!address) {
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llvm::errs() << "Could not look up: " << name << '\n';
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return nullptr;
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}
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return llvm::JITSymbol(address, llvm::JITSymbolFlags::Exported);
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}
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private:
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llvm::orc::ExecutionSession &session;
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};
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} // end anonymous namespace
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namespace mlir {
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namespace impl {
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// Simple layered Orc JIT compilation engine.
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class OrcJIT {
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public:
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// Construct a JIT engine for the target host defined by `machineBuilder`,
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// using the data layout provided as `dataLayout`.
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// Setup the object layer to use our custom memory manager in order to resolve
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// calls to library functions present in the process.
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OrcJIT(llvm::orc::JITTargetMachineBuilder machineBuilder,
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llvm::DataLayout layout)
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: objectLayer(
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session,
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[this]() { return llvm::make_unique<MemoryManager>(session); }),
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compileLayer(
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session, objectLayer,
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llvm::orc::ConcurrentIRCompiler(std::move(machineBuilder))),
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dataLayout(layout), mangler(session, this->dataLayout),
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threadSafeCtx(llvm::make_unique<llvm::LLVMContext>()) {
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session.getMainJITDylib().setGenerator(
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cantFail(llvm::orc::DynamicLibrarySearchGenerator::GetForCurrentProcess(
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layout)));
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}
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// Create a JIT engine for the current host.
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static Expected<std::unique_ptr<OrcJIT>> createDefault() {
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auto machineBuilder = llvm::orc::JITTargetMachineBuilder::detectHost();
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if (!machineBuilder)
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return machineBuilder.takeError();
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auto dataLayout = machineBuilder->getDefaultDataLayoutForTarget();
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if (!dataLayout)
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return dataLayout.takeError();
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return llvm::make_unique<OrcJIT>(std::move(*machineBuilder),
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std::move(*dataLayout));
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}
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// Add an LLVM module to the main library managed by the JIT engine.
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Error addModule(std::unique_ptr<llvm::Module> M) {
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return compileLayer.add(
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session.getMainJITDylib(),
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llvm::orc::ThreadSafeModule(std::move(M), threadSafeCtx));
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}
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// Lookup a symbol in the main library managed by the JIT engine.
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Expected<llvm::JITEvaluatedSymbol> lookup(StringRef Name) {
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return session.lookup({&session.getMainJITDylib()}, mangler(Name.str()));
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}
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private:
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llvm::orc::ExecutionSession session;
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llvm::orc::RTDyldObjectLinkingLayer objectLayer;
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llvm::orc::IRCompileLayer compileLayer;
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llvm::DataLayout dataLayout;
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llvm::orc::MangleAndInterner mangler;
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llvm::orc::ThreadSafeContext threadSafeCtx;
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};
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} // end namespace impl
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} // namespace mlir
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// Wrap a string into an llvm::StringError.
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static inline Error make_string_error(const llvm::Twine &message) {
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return llvm::make_error<llvm::StringError>(message.str(),
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llvm::inconvertibleErrorCode());
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}
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// Given a list of PassInfo coming from a higher level, creates the passes to
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// run as an owning vector and appends the extra required passes to lower to
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// LLVMIR. Currently, these extra passes are:
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// - constant folding
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// - CSE
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// - canonicalization
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// - affine lowering
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static std::vector<std::unique_ptr<mlir::Pass>>
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getDefaultPasses(const std::vector<const mlir::PassInfo *> &mlirPassInfoList) {
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std::vector<std::unique_ptr<mlir::Pass>> passList;
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passList.reserve(mlirPassInfoList.size() + 4);
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// Run each of the passes that were selected.
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for (const auto *passInfo : mlirPassInfoList) {
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passList.emplace_back(passInfo->createPass());
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}
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// Append the extra passes for lowering to MLIR.
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passList.emplace_back(mlir::createConstantFoldPass());
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passList.emplace_back(mlir::createCSEPass());
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passList.emplace_back(mlir::createCanonicalizerPass());
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passList.emplace_back(mlir::createLowerAffinePass());
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return passList;
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}
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// Run the passes sequentially on the given module.
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// Return `nullptr` immediately if any of the passes fails.
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static bool runPasses(const std::vector<std::unique_ptr<mlir::Pass>> &passes,
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Module *module) {
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for (const auto &pass : passes) {
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mlir::PassResult result = pass->runOnModule(module);
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if (result == mlir::PassResult::Failure || module->verify()) {
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llvm::errs() << "Pass failed\n";
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return true;
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}
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}
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return false;
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}
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// Setup LLVM target triple from the current machine.
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static bool setupTargetTriple(llvm::Module *llvmModule) {
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// Setup the machine properties from the current architecture.
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auto targetTriple = llvm::sys::getDefaultTargetTriple();
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std::string errorMessage;
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auto target = llvm::TargetRegistry::lookupTarget(targetTriple, errorMessage);
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if (!target) {
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llvm::errs() << "NO target: " << errorMessage << "\n";
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return true;
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}
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auto machine =
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target->createTargetMachine(targetTriple, "generic", "", {}, {});
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llvmModule->setDataLayout(machine->createDataLayout());
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llvmModule->setTargetTriple(targetTriple);
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return false;
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}
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static std::string makePackedFunctionName(StringRef name) {
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return "_mlir_" + name.str();
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}
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// For each function in the LLVM module, define an interface function that wraps
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// all the arguments of the original function and all its results into an i8**
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// pointer to provide a unified invocation interface.
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void packFunctionArguments(llvm::Module *module) {
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auto &ctx = module->getContext();
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llvm::IRBuilder<> builder(ctx);
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llvm::DenseSet<llvm::Function *> interfaceFunctions;
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for (auto &func : module->getFunctionList()) {
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if (func.isDeclaration()) {
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continue;
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}
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if (interfaceFunctions.count(&func)) {
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continue;
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}
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// Given a function `foo(<...>)`, define the interface function
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// `mlir_foo(i8**)`.
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auto newType = llvm::FunctionType::get(
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builder.getVoidTy(), builder.getInt8PtrTy()->getPointerTo(),
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/*isVarArg=*/false);
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auto newName = makePackedFunctionName(func.getName());
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llvm::Constant *funcCst = module->getOrInsertFunction(newName, newType);
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llvm::Function *interfaceFunc = llvm::cast<llvm::Function>(funcCst);
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interfaceFunctions.insert(interfaceFunc);
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// Extract the arguments from the type-erased argument list and cast them to
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// the proper types.
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auto bb = llvm::BasicBlock::Create(ctx);
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bb->insertInto(interfaceFunc);
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builder.SetInsertPoint(bb);
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llvm::Value *argList = interfaceFunc->arg_begin();
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llvm::SmallVector<llvm::Value *, 8> args;
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args.reserve(llvm::size(func.args()));
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for (auto &indexedArg : llvm::enumerate(func.args())) {
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llvm::Value *argIndex = llvm::Constant::getIntegerValue(
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builder.getInt64Ty(), llvm::APInt(64, indexedArg.index()));
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llvm::Value *argPtrPtr = builder.CreateGEP(argList, argIndex);
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llvm::Value *argPtr = builder.CreateLoad(argPtrPtr);
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argPtr = builder.CreateBitCast(
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argPtr, indexedArg.value().getType()->getPointerTo());
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llvm::Value *arg = builder.CreateLoad(argPtr);
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args.push_back(arg);
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}
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// Call the implementation function with the extracted arguments.
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llvm::Value *result = builder.CreateCall(&func, args);
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// Assuming the result is one value, potentially of type `void`.
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if (!result->getType()->isVoidTy()) {
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llvm::Value *retIndex = llvm::Constant::getIntegerValue(
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builder.getInt64Ty(), llvm::APInt(64, llvm::size(func.args())));
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llvm::Value *retPtrPtr = builder.CreateGEP(argList, retIndex);
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llvm::Value *retPtr = builder.CreateLoad(retPtrPtr);
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retPtr = builder.CreateBitCast(retPtr, result->getType()->getPointerTo());
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builder.CreateStore(result, retPtr);
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}
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// The interface function returns void.
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builder.CreateRetVoid();
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}
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}
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2019-01-26 02:51:51 +08:00
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// Out of line for PIMPL unique_ptr.
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ExecutionEngine::~ExecutionEngine() = default;
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Simple CPU runner
This implements a simple CPU runner based on LLVM Orc JIT. The base
functionality is provided by the ExecutionEngine class that compiles and links
the module, and provides an interface for obtaining function pointers to the
JIT-compiled MLIR functions and for invoking those functions directly. Since
function pointers need to be casted to the correct pointer type, the
ExecutionEngine wraps LLVM IR functions obtained from MLIR into a helper
function with the common signature `void (void **)` where the single argument
is interpreted as a list of pointers to the actual arguments passed to the
function, eventually followed by a pointer to the result of the function.
Additionally, the ExecutionEngine is set up to resolve library functions to
those available in the current process, enabling support for, e.g., simple C
library calls.
For integration purposes, this also provides a simplistic runtime for memref
descriptors as expected by the LLVM IR code produced by MLIR translation. In
particular, memrefs are transformed into LLVM structs (can be mapped to C
structs) with a pointer to the data, followed by dynamic sizes. This
implementation only supports statically-shaped memrefs of type float, but can
be extened if necessary.
Provide a binary for the runner and a test that exercises it.
PiperOrigin-RevId: 230876363
2019-01-25 19:16:06 +08:00
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Expected<std::unique_ptr<ExecutionEngine>> ExecutionEngine::create(Module *m) {
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auto engine = llvm::make_unique<ExecutionEngine>();
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auto expectedJIT = impl::OrcJIT::createDefault();
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if (!expectedJIT)
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return expectedJIT.takeError();
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if (runPasses(getDefaultPasses({}), m))
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return make_string_error("passes failed");
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auto llvmModule = convertModuleToLLVMIR(*m, engine->llvmContext);
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if (!llvmModule)
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return make_string_error("could not convert to LLVM IR");
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// FIXME: the triple should be passed to the translation or dialect conversion
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// instead of this. Currently, the LLVM module created above has no triple
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// associated with it.
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setupTargetTriple(llvmModule.get());
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packFunctionArguments(llvmModule.get());
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2019-01-26 02:51:51 +08:00
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engine->jit = std::move(*expectedJIT);
|
Simple CPU runner
This implements a simple CPU runner based on LLVM Orc JIT. The base
functionality is provided by the ExecutionEngine class that compiles and links
the module, and provides an interface for obtaining function pointers to the
JIT-compiled MLIR functions and for invoking those functions directly. Since
function pointers need to be casted to the correct pointer type, the
ExecutionEngine wraps LLVM IR functions obtained from MLIR into a helper
function with the common signature `void (void **)` where the single argument
is interpreted as a list of pointers to the actual arguments passed to the
function, eventually followed by a pointer to the result of the function.
Additionally, the ExecutionEngine is set up to resolve library functions to
those available in the current process, enabling support for, e.g., simple C
library calls.
For integration purposes, this also provides a simplistic runtime for memref
descriptors as expected by the LLVM IR code produced by MLIR translation. In
particular, memrefs are transformed into LLVM structs (can be mapped to C
structs) with a pointer to the data, followed by dynamic sizes. This
implementation only supports statically-shaped memrefs of type float, but can
be extened if necessary.
Provide a binary for the runner and a test that exercises it.
PiperOrigin-RevId: 230876363
2019-01-25 19:16:06 +08:00
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if (auto err = engine->jit->addModule(std::move(llvmModule)))
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return std::move(err);
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return engine;
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}
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Expected<void (*)(void **)> ExecutionEngine::lookup(StringRef name) const {
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auto expectedSymbol = jit->lookup(makePackedFunctionName(name));
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if (!expectedSymbol)
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return expectedSymbol.takeError();
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auto rawFPtr = expectedSymbol->getAddress();
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auto fptr = reinterpret_cast<void (*)(void **)>(rawFPtr);
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if (!fptr)
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return make_string_error("looked up function is null");
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return fptr;
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}
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2019-01-26 06:57:30 +08:00
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llvm::Error ExecutionEngine::invoke(StringRef name,
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MutableArrayRef<void *> args) {
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auto expectedFPtr = lookup(name);
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if (!expectedFPtr)
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return expectedFPtr.takeError();
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auto fptr = *expectedFPtr;
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(*fptr)(args.data());
|
|
|
|
|
|
|
|
return llvm::Error::success();
|
|
|
|
}
|