Files
clang-p2996/mlir/lib/Conversion/AVX512ToLLVM/ConvertAVX512ToLLVM.cpp
River Riddle 8d67d187ba [mlir][DialectConversion] Refactor how block argument types get converted
This revision removes the TypeConverter parameter passed to the apply* methods, and instead moves the responsibility of region type conversion to patterns. The types of a region can be converted using the 'convertRegionTypes' method, which acts similarly to the existing 'applySignatureConversion'. This method ensures that all blocks within, and including those moved into, a region will have the block argument types converted using the provided converter.

This has the benefit of making more of the legalization logic controlled by patterns, instead of being handled explicitly by the driver. It also opens up the possibility to support multiple type conversions at some point in the future.

This revision also adds a new utility class `FailureOr<T>` that provides a LogicalResult friendly facility for returning a failure or a valid result value.

Differential Revision: https://reviews.llvm.org/D81681
2020-06-18 15:59:22 -07:00

190 lines
7.6 KiB
C++

//===- ConvertAVX512ToLLVM.cpp - Convert AVX512 to the LLVM dialect -------===//
//
// 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
//
//===----------------------------------------------------------------------===//
#include "mlir/Conversion/AVX512ToLLVM/ConvertAVX512ToLLVM.h"
#include "../PassDetail.h"
#include "mlir/Conversion/StandardToLLVM/ConvertStandardToLLVM.h"
#include "mlir/Conversion/StandardToLLVM/ConvertStandardToLLVMPass.h"
#include "mlir/Conversion/VectorToLLVM/ConvertVectorToLLVM.h"
#include "mlir/Dialect/AVX512/AVX512Dialect.h"
#include "mlir/Dialect/LLVMIR/LLVMAVX512Dialect.h"
#include "mlir/Dialect/LLVMIR/LLVMDialect.h"
#include "mlir/Dialect/StandardOps/IR/Ops.h"
#include "mlir/Dialect/Vector/VectorOps.h"
#include "mlir/IR/Module.h"
#include "mlir/IR/PatternMatch.h"
#include "mlir/Pass/Pass.h"
using namespace mlir;
using namespace mlir::vector;
using namespace mlir::avx512;
template <typename OpTy>
static Type getSrcVectorElementType(OpTy op) {
return op.src().getType().template cast<VectorType>().getElementType();
}
// TODO(ntv, zinenko): Code is currently copy-pasted and adapted from the code
// 1-1 LLVM conversion. It would better if it were properly exposed in core and
// reusable.
/// Basic lowering implementation for one-to-one rewriting from AVX512 Ops to
/// LLVM Dialect Ops. Convert the type of the result to an LLVM type, pass
/// operands as is, preserve attributes.
template <typename SourceOp, typename TargetOp>
static LogicalResult
matchAndRewriteOneToOne(const ConvertToLLVMPattern &lowering,
LLVMTypeConverter &typeConverter, Operation *op,
ArrayRef<Value> operands,
ConversionPatternRewriter &rewriter) {
unsigned numResults = op->getNumResults();
Type packedType;
if (numResults != 0) {
packedType = typeConverter.packFunctionResults(op->getResultTypes());
if (!packedType)
return failure();
}
auto newOp = rewriter.create<TargetOp>(op->getLoc(), packedType, operands,
op->getAttrs());
// If the operation produced 0 or 1 result, return them immediately.
if (numResults == 0)
return rewriter.eraseOp(op), success();
if (numResults == 1)
return rewriter.replaceOp(op, newOp.getOperation()->getResult(0)),
success();
// Otherwise, it had been converted to an operation producing a structure.
// Extract individual results from the structure and return them as list.
SmallVector<Value, 4> results;
results.reserve(numResults);
for (unsigned i = 0; i < numResults; ++i) {
auto type = typeConverter.convertType(op->getResult(i).getType());
results.push_back(rewriter.create<LLVM::ExtractValueOp>(
op->getLoc(), type, newOp.getOperation()->getResult(0),
rewriter.getI64ArrayAttr(i)));
}
rewriter.replaceOp(op, results);
return success();
}
namespace {
// TODO(ntv): Patterns are too verbose due to the fact that we have 1 op (e.g.
// MaskRndScaleOp) and different possible target ops. It would be better to take
// a Functor so that all these conversions become 1-liners.
struct MaskRndScaleOpPS512Conversion : public ConvertToLLVMPattern {
explicit MaskRndScaleOpPS512Conversion(MLIRContext *context,
LLVMTypeConverter &typeConverter)
: ConvertToLLVMPattern(MaskRndScaleOp::getOperationName(), context,
typeConverter) {}
LogicalResult
matchAndRewrite(Operation *op, ArrayRef<Value> operands,
ConversionPatternRewriter &rewriter) const override {
if (!getSrcVectorElementType(cast<MaskRndScaleOp>(op)).isF32())
return failure();
return matchAndRewriteOneToOne<MaskRndScaleOp,
LLVM::x86_avx512_mask_rndscale_ps_512>(
*this, this->typeConverter, op, operands, rewriter);
}
};
struct MaskRndScaleOpPD512Conversion : public ConvertToLLVMPattern {
explicit MaskRndScaleOpPD512Conversion(MLIRContext *context,
LLVMTypeConverter &typeConverter)
: ConvertToLLVMPattern(MaskRndScaleOp::getOperationName(), context,
typeConverter) {}
LogicalResult
matchAndRewrite(Operation *op, ArrayRef<Value> operands,
ConversionPatternRewriter &rewriter) const override {
if (!getSrcVectorElementType(cast<MaskRndScaleOp>(op)).isF64())
return failure();
return matchAndRewriteOneToOne<MaskRndScaleOp,
LLVM::x86_avx512_mask_rndscale_pd_512>(
*this, this->typeConverter, op, operands, rewriter);
}
};
struct ScaleFOpPS512Conversion : public ConvertToLLVMPattern {
explicit ScaleFOpPS512Conversion(MLIRContext *context,
LLVMTypeConverter &typeConverter)
: ConvertToLLVMPattern(MaskScaleFOp::getOperationName(), context,
typeConverter) {}
LogicalResult
matchAndRewrite(Operation *op, ArrayRef<Value> operands,
ConversionPatternRewriter &rewriter) const override {
if (!getSrcVectorElementType(cast<MaskScaleFOp>(op)).isF32())
return failure();
return matchAndRewriteOneToOne<MaskScaleFOp,
LLVM::x86_avx512_mask_scalef_ps_512>(
*this, this->typeConverter, op, operands, rewriter);
}
};
struct ScaleFOpPD512Conversion : public ConvertToLLVMPattern {
explicit ScaleFOpPD512Conversion(MLIRContext *context,
LLVMTypeConverter &typeConverter)
: ConvertToLLVMPattern(MaskScaleFOp::getOperationName(), context,
typeConverter) {}
LogicalResult
matchAndRewrite(Operation *op, ArrayRef<Value> operands,
ConversionPatternRewriter &rewriter) const override {
if (!getSrcVectorElementType(cast<MaskScaleFOp>(op)).isF64())
return failure();
return matchAndRewriteOneToOne<MaskScaleFOp,
LLVM::x86_avx512_mask_scalef_pd_512>(
*this, this->typeConverter, op, operands, rewriter);
}
};
} // namespace
/// Populate the given list with patterns that convert from AVX512 to LLVM.
void mlir::populateAVX512ToLLVMConversionPatterns(
LLVMTypeConverter &converter, OwningRewritePatternList &patterns) {
MLIRContext *ctx = converter.getDialect()->getContext();
// clang-format off
patterns.insert<MaskRndScaleOpPS512Conversion,
MaskRndScaleOpPD512Conversion,
ScaleFOpPS512Conversion,
ScaleFOpPD512Conversion>(ctx, converter);
// clang-format on
}
namespace {
struct ConvertAVX512ToLLVMPass
: public ConvertAVX512ToLLVMBase<ConvertAVX512ToLLVMPass> {
void runOnOperation() override;
};
} // namespace
void ConvertAVX512ToLLVMPass::runOnOperation() {
// Convert to the LLVM IR dialect.
OwningRewritePatternList patterns;
LLVMTypeConverter converter(&getContext());
populateAVX512ToLLVMConversionPatterns(converter, patterns);
populateVectorToLLVMConversionPatterns(converter, patterns);
populateStdToLLVMConversionPatterns(converter, patterns);
ConversionTarget target(getContext());
target.addLegalDialect<LLVM::LLVMDialect>();
target.addLegalDialect<LLVM::LLVMAVX512Dialect>();
target.addIllegalDialect<avx512::AVX512Dialect>();
if (failed(applyPartialConversion(getOperation(), target, patterns))) {
signalPassFailure();
}
}
std::unique_ptr<OperationPass<ModuleOp>> mlir::createConvertAVX512ToLLVMPass() {
return std::make_unique<ConvertAVX512ToLLVMPass>();
}