Files
clang-p2996/mlir/lib/Conversion/SPIRVToLLVM/ConvertLaunchFuncToLLVMCalls.cpp
Tres Popp 5550c82189 [mlir] Move casting calls from methods to function calls
The MLIR classes Type/Attribute/Operation/Op/Value support
cast/dyn_cast/isa/dyn_cast_or_null functionality through llvm's doCast
functionality in addition to defining methods with the same name.
This change begins the migration of uses of the method to the
corresponding function call as has been decided as more consistent.

Note that there still exist classes that only define methods directly,
such as AffineExpr, and this does not include work currently to support
a functional cast/isa call.

Caveats include:
- This clang-tidy script probably has more problems.
- This only touches C++ code, so nothing that is being generated.

Context:
- https://mlir.llvm.org/deprecation/ at "Use the free function variants
  for dyn_cast/cast/isa/…"
- Original discussion at https://discourse.llvm.org/t/preferred-casting-style-going-forward/68443

Implementation:
This first patch was created with the following steps. The intention is
to only do automated changes at first, so I waste less time if it's
reverted, and so the first mass change is more clear as an example to
other teams that will need to follow similar steps.

Steps are described per line, as comments are removed by git:
0. Retrieve the change from the following to build clang-tidy with an
   additional check:
   https://github.com/llvm/llvm-project/compare/main...tpopp:llvm-project:tidy-cast-check
1. Build clang-tidy
2. Run clang-tidy over your entire codebase while disabling all checks
   and enabling the one relevant one. Run on all header files also.
3. Delete .inc files that were also modified, so the next build rebuilds
   them to a pure state.
4. Some changes have been deleted for the following reasons:
   - Some files had a variable also named cast
   - Some files had not included a header file that defines the cast
     functions
   - Some files are definitions of the classes that have the casting
     methods, so the code still refers to the method instead of the
     function without adding a prefix or removing the method declaration
     at the same time.

```
ninja -C $BUILD_DIR clang-tidy

run-clang-tidy -clang-tidy-binary=$BUILD_DIR/bin/clang-tidy -checks='-*,misc-cast-functions'\
               -header-filter=mlir/ mlir/* -fix

rm -rf $BUILD_DIR/tools/mlir/**/*.inc

git restore mlir/lib/IR mlir/lib/Dialect/DLTI/DLTI.cpp\
            mlir/lib/Dialect/Complex/IR/ComplexDialect.cpp\
            mlir/lib/**/IR/\
            mlir/lib/Dialect/SparseTensor/Transforms/SparseVectorization.cpp\
            mlir/lib/Dialect/Vector/Transforms/LowerVectorMultiReduction.cpp\
            mlir/test/lib/Dialect/Test/TestTypes.cpp\
            mlir/test/lib/Dialect/Transform/TestTransformDialectExtension.cpp\
            mlir/test/lib/Dialect/Test/TestAttributes.cpp\
            mlir/unittests/TableGen/EnumsGenTest.cpp\
            mlir/test/python/lib/PythonTestCAPI.cpp\
            mlir/include/mlir/IR/
```

Differential Revision: https://reviews.llvm.org/D150123
2023-05-12 11:21:25 +02:00

336 lines
14 KiB
C++

//===- ConvertLaunchFuncToLLVMCalls.cpp - MLIR GPU launch to LLVM pass ----===//
//
// 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 passes to convert `gpu.launch_func` op into a sequence
// of LLVM calls that emulate the host and device sides.
//
//===----------------------------------------------------------------------===//
#include "mlir/Conversion/SPIRVToLLVM/SPIRVToLLVMPass.h"
#include "mlir/Conversion/ArithToLLVM/ArithToLLVM.h"
#include "mlir/Conversion/FuncToLLVM/ConvertFuncToLLVM.h"
#include "mlir/Conversion/LLVMCommon/LoweringOptions.h"
#include "mlir/Conversion/LLVMCommon/Pattern.h"
#include "mlir/Conversion/LLVMCommon/TypeConverter.h"
#include "mlir/Conversion/MemRefToLLVM/MemRefToLLVM.h"
#include "mlir/Conversion/SPIRVToLLVM/SPIRVToLLVM.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"
#include "mlir/Dialect/GPU/IR/GPUDialect.h"
#include "mlir/Dialect/LLVMIR/LLVMDialect.h"
#include "mlir/Dialect/SPIRV/IR/SPIRVOps.h"
#include "mlir/IR/BuiltinOps.h"
#include "mlir/IR/SymbolTable.h"
#include "mlir/Pass/Pass.h"
#include "mlir/Transforms/DialectConversion.h"
#include "llvm/ADT/DenseMap.h"
#include "llvm/ADT/StringExtras.h"
#include "llvm/Support/FormatVariadic.h"
namespace mlir {
#define GEN_PASS_DEF_LOWERHOSTCODETOLLVMPASS
#include "mlir/Conversion/Passes.h.inc"
} // namespace mlir
using namespace mlir;
static constexpr const char kSPIRVModule[] = "__spv__";
//===----------------------------------------------------------------------===//
// Utility functions
//===----------------------------------------------------------------------===//
/// Returns the string name of the `DescriptorSet` decoration.
static std::string descriptorSetName() {
return llvm::convertToSnakeFromCamelCase(
stringifyDecoration(spirv::Decoration::DescriptorSet));
}
/// Returns the string name of the `Binding` decoration.
static std::string bindingName() {
return llvm::convertToSnakeFromCamelCase(
stringifyDecoration(spirv::Decoration::Binding));
}
/// Calculates the index of the kernel's operand that is represented by the
/// given global variable with the `bind` attribute. We assume that the index of
/// each kernel's operand is mapped to (descriptorSet, binding) by the map:
/// i -> (0, i)
/// which is implemented under `LowerABIAttributesPass`.
static unsigned calculateGlobalIndex(spirv::GlobalVariableOp op) {
IntegerAttr binding = op->getAttrOfType<IntegerAttr>(bindingName());
return binding.getInt();
}
/// Copies the given number of bytes from src to dst pointers.
static void copy(Location loc, Value dst, Value src, Value size,
OpBuilder &builder) {
MLIRContext *context = builder.getContext();
auto llvmI1Type = IntegerType::get(context, 1);
Value isVolatile = builder.create<LLVM::ConstantOp>(
loc, llvmI1Type, builder.getBoolAttr(false));
builder.create<LLVM::MemcpyOp>(loc, dst, src, size, isVolatile);
}
/// Encodes the binding and descriptor set numbers into a new symbolic name.
/// The name is specified by
/// {kernel_module_name}_{variable_name}_descriptor_set{ds}_binding{b}
/// to avoid symbolic conflicts, where 'ds' and 'b' are descriptor set and
/// binding numbers.
static std::string
createGlobalVariableWithBindName(spirv::GlobalVariableOp op,
StringRef kernelModuleName) {
IntegerAttr descriptorSet =
op->getAttrOfType<IntegerAttr>(descriptorSetName());
IntegerAttr binding = op->getAttrOfType<IntegerAttr>(bindingName());
return llvm::formatv("{0}_{1}_descriptor_set{2}_binding{3}",
kernelModuleName.str(), op.getSymName().str(),
std::to_string(descriptorSet.getInt()),
std::to_string(binding.getInt()));
}
/// Returns true if the given global variable has both a descriptor set number
/// and a binding number.
static bool hasDescriptorSetAndBinding(spirv::GlobalVariableOp op) {
IntegerAttr descriptorSet =
op->getAttrOfType<IntegerAttr>(descriptorSetName());
IntegerAttr binding = op->getAttrOfType<IntegerAttr>(bindingName());
return descriptorSet && binding;
}
/// Fills `globalVariableMap` with SPIR-V global variables that represent kernel
/// arguments from the given SPIR-V module. We assume that the module contains a
/// single entry point function. Hence, all `spirv.GlobalVariable`s with a bind
/// attribute are kernel arguments.
static LogicalResult getKernelGlobalVariables(
spirv::ModuleOp module,
DenseMap<uint32_t, spirv::GlobalVariableOp> &globalVariableMap) {
auto entryPoints = module.getOps<spirv::EntryPointOp>();
if (!llvm::hasSingleElement(entryPoints)) {
return module.emitError(
"The module must contain exactly one entry point function");
}
auto globalVariables = module.getOps<spirv::GlobalVariableOp>();
for (auto globalOp : globalVariables) {
if (hasDescriptorSetAndBinding(globalOp))
globalVariableMap[calculateGlobalIndex(globalOp)] = globalOp;
}
return success();
}
/// Encodes the SPIR-V module's symbolic name into the name of the entry point
/// function.
static LogicalResult encodeKernelName(spirv::ModuleOp module) {
StringRef spvModuleName = module.getSymName().value_or(kSPIRVModule);
// We already know that the module contains exactly one entry point function
// based on `getKernelGlobalVariables()` call. Update this function's name
// to:
// {spv_module_name}_{function_name}
auto entryPoints = module.getOps<spirv::EntryPointOp>();
if (!llvm::hasSingleElement(entryPoints)) {
return module.emitError(
"The module must contain exactly one entry point function");
}
spirv::EntryPointOp entryPoint = *entryPoints.begin();
StringRef funcName = entryPoint.getFn();
auto funcOp = module.lookupSymbol<spirv::FuncOp>(entryPoint.getFnAttr());
StringAttr newFuncName =
StringAttr::get(module->getContext(), spvModuleName + "_" + funcName);
if (failed(SymbolTable::replaceAllSymbolUses(funcOp, newFuncName, module)))
return failure();
SymbolTable::setSymbolName(funcOp, newFuncName);
return success();
}
//===----------------------------------------------------------------------===//
// Conversion patterns
//===----------------------------------------------------------------------===//
namespace {
/// Structure to group information about the variables being copied.
struct CopyInfo {
Value dst;
Value src;
Value size;
};
/// This pattern emulates a call to the kernel in LLVM dialect. For that, we
/// copy the data to the global variable (emulating device side), call the
/// kernel as a normal void LLVM function, and copy the data back (emulating the
/// host side).
class GPULaunchLowering : public ConvertOpToLLVMPattern<gpu::LaunchFuncOp> {
using ConvertOpToLLVMPattern<gpu::LaunchFuncOp>::ConvertOpToLLVMPattern;
LogicalResult
matchAndRewrite(gpu::LaunchFuncOp launchOp, OpAdaptor adaptor,
ConversionPatternRewriter &rewriter) const override {
auto *op = launchOp.getOperation();
MLIRContext *context = rewriter.getContext();
auto module = launchOp->getParentOfType<ModuleOp>();
// Get the SPIR-V module that represents the gpu kernel module. The module
// is named:
// __spv__{kernel_module_name}
// based on GPU to SPIR-V conversion.
StringRef kernelModuleName = launchOp.getKernelModuleName().getValue();
std::string spvModuleName = kSPIRVModule + kernelModuleName.str();
auto spvModule = module.lookupSymbol<spirv::ModuleOp>(
StringAttr::get(context, spvModuleName));
if (!spvModule) {
return launchOp.emitOpError("SPIR-V kernel module '")
<< spvModuleName << "' is not found";
}
// Declare kernel function in the main module so that it later can be linked
// with its definition from the kernel module. We know that the kernel
// function would have no arguments and the data is passed via global
// variables. The name of the kernel will be
// {spv_module_name}_{kernel_function_name}
// to avoid symbolic name conflicts.
StringRef kernelFuncName = launchOp.getKernelName().getValue();
std::string newKernelFuncName = spvModuleName + "_" + kernelFuncName.str();
auto kernelFunc = module.lookupSymbol<LLVM::LLVMFuncOp>(
StringAttr::get(context, newKernelFuncName));
if (!kernelFunc) {
OpBuilder::InsertionGuard guard(rewriter);
rewriter.setInsertionPointToStart(module.getBody());
kernelFunc = rewriter.create<LLVM::LLVMFuncOp>(
rewriter.getUnknownLoc(), newKernelFuncName,
LLVM::LLVMFunctionType::get(LLVM::LLVMVoidType::get(context),
ArrayRef<Type>()));
rewriter.setInsertionPoint(launchOp);
}
// Get all global variables associated with the kernel operands.
DenseMap<uint32_t, spirv::GlobalVariableOp> globalVariableMap;
if (failed(getKernelGlobalVariables(spvModule, globalVariableMap)))
return failure();
// Traverse kernel operands that were converted to MemRefDescriptors. For
// each operand, create a global variable and copy data from operand to it.
Location loc = launchOp.getLoc();
SmallVector<CopyInfo, 4> copyInfo;
auto numKernelOperands = launchOp.getNumKernelOperands();
auto kernelOperands = adaptor.getOperands().take_back(numKernelOperands);
for (const auto &operand : llvm::enumerate(kernelOperands)) {
// Check if the kernel's operand is a ranked memref.
auto memRefType = dyn_cast<MemRefType>(
launchOp.getKernelOperand(operand.index()).getType());
if (!memRefType)
return failure();
// Calculate the size of the memref and get the pointer to the allocated
// buffer.
SmallVector<Value, 4> sizes;
SmallVector<Value, 4> strides;
Value sizeBytes;
getMemRefDescriptorSizes(loc, memRefType, {}, rewriter, sizes, strides,
sizeBytes);
MemRefDescriptor descriptor(operand.value());
Value src = descriptor.allocatedPtr(rewriter, loc);
// Get the global variable in the SPIR-V module that is associated with
// the kernel operand. Construct its new name and create a corresponding
// LLVM dialect global variable.
spirv::GlobalVariableOp spirvGlobal = globalVariableMap[operand.index()];
auto pointeeType =
cast<spirv::PointerType>(spirvGlobal.getType()).getPointeeType();
auto dstGlobalType = typeConverter->convertType(pointeeType);
if (!dstGlobalType)
return failure();
std::string name =
createGlobalVariableWithBindName(spirvGlobal, spvModuleName);
// Check if this variable has already been created.
auto dstGlobal = module.lookupSymbol<LLVM::GlobalOp>(name);
if (!dstGlobal) {
OpBuilder::InsertionGuard guard(rewriter);
rewriter.setInsertionPointToStart(module.getBody());
dstGlobal = rewriter.create<LLVM::GlobalOp>(
loc, dstGlobalType,
/*isConstant=*/false, LLVM::Linkage::Linkonce, name, Attribute(),
/*alignment=*/0);
rewriter.setInsertionPoint(launchOp);
}
// Copy the data from src operand pointer to dst global variable. Save
// src, dst and size so that we can copy data back after emulating the
// kernel call.
Value dst = rewriter.create<LLVM::AddressOfOp>(
loc, typeConverter->convertType(spirvGlobal.getType()),
dstGlobal.getSymName());
copy(loc, dst, src, sizeBytes, rewriter);
CopyInfo info;
info.dst = dst;
info.src = src;
info.size = sizeBytes;
copyInfo.push_back(info);
}
// Create a call to the kernel and copy the data back.
rewriter.replaceOpWithNewOp<LLVM::CallOp>(op, kernelFunc,
ArrayRef<Value>());
for (CopyInfo info : copyInfo)
copy(loc, info.src, info.dst, info.size, rewriter);
return success();
}
};
class LowerHostCodeToLLVM
: public impl::LowerHostCodeToLLVMPassBase<LowerHostCodeToLLVM> {
public:
using Base::Base;
void runOnOperation() override {
ModuleOp module = getOperation();
// Erase the GPU module.
for (auto gpuModule :
llvm::make_early_inc_range(module.getOps<gpu::GPUModuleOp>()))
gpuModule.erase();
// Request C wrapper emission.
for (auto func : module.getOps<func::FuncOp>()) {
func->setAttr(LLVM::LLVMDialect::getEmitCWrapperAttrName(),
UnitAttr::get(&getContext()));
}
// Specify options to lower to LLVM and pull in the conversion patterns.
LowerToLLVMOptions options(module.getContext());
options.useOpaquePointers = useOpaquePointers;
auto *context = module.getContext();
RewritePatternSet patterns(context);
LLVMTypeConverter typeConverter(context, options);
mlir::arith::populateArithToLLVMConversionPatterns(typeConverter, patterns);
populateFinalizeMemRefToLLVMConversionPatterns(typeConverter, patterns);
populateFuncToLLVMConversionPatterns(typeConverter, patterns);
patterns.add<GPULaunchLowering>(typeConverter);
// Pull in SPIR-V type conversion patterns to convert SPIR-V global
// variable's type to LLVM dialect type.
populateSPIRVToLLVMTypeConversion(typeConverter);
ConversionTarget target(*context);
target.addLegalDialect<LLVM::LLVMDialect>();
if (failed(applyPartialConversion(module, target, std::move(patterns))))
signalPassFailure();
// Finally, modify the kernel function in SPIR-V modules to avoid symbolic
// conflicts.
for (auto spvModule : module.getOps<spirv::ModuleOp>()) {
if (failed(encodeKernelName(spvModule))) {
signalPassFailure();
return;
}
}
}
};
} // namespace