Files
clang-p2996/mlir/lib/Conversion/GPUCommon/GPUOpsLowering.cpp
Dumitru Potop 9a0ea5994b [mlir] Support alignment in LLVM dialect GlobalOp
First step in adding alignment as an attribute to MLIR global definitions. Alignment can be specified for global objects in LLVM IR. It can also be specified as a named attribute in the LLVMIR dialect of MLIR. However, this attribute has no standing and is discarded during translation from MLIR to LLVM IR. This patch does two things: First, it adds the attribute to the syntax of the llvm.mlir.global operation, and by doing this it also adds accessors and verifications. The syntax is "align=XX" (with XX being an integer), placed right after the value of the operation. Second, it allows transforming this operation to and from LLVM IR. It is checked whether the value is an integer power of 2.

Reviewed By: ftynse, mehdi_amini

Differential Revision: https://reviews.llvm.org/D101492
2021-05-12 09:07:20 +02:00

149 lines
6.8 KiB
C++

//===- GPUOpsLowering.cpp - GPU FuncOp / ReturnOp lowering ----------------===//
//
// 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 "GPUOpsLowering.h"
#include "mlir/Dialect/StandardOps/IR/Ops.h"
#include "mlir/IR/Builders.h"
#include "llvm/Support/FormatVariadic.h"
using namespace mlir;
LogicalResult
GPUFuncOpLowering::matchAndRewrite(gpu::GPUFuncOp gpuFuncOp,
ArrayRef<Value> operands,
ConversionPatternRewriter &rewriter) const {
assert(operands.empty() && "func op is not expected to have operands");
Location loc = gpuFuncOp.getLoc();
SmallVector<LLVM::GlobalOp, 3> workgroupBuffers;
workgroupBuffers.reserve(gpuFuncOp.getNumWorkgroupAttributions());
for (auto en : llvm::enumerate(gpuFuncOp.getWorkgroupAttributions())) {
Value attribution = en.value();
auto type = attribution.getType().dyn_cast<MemRefType>();
assert(type && type.hasStaticShape() && "unexpected type in attribution");
uint64_t numElements = type.getNumElements();
auto elementType =
typeConverter->convertType(type.getElementType()).template cast<Type>();
auto arrayType = LLVM::LLVMArrayType::get(elementType, numElements);
std::string name = std::string(
llvm::formatv("__wg_{0}_{1}", gpuFuncOp.getName(), en.index()));
auto globalOp = rewriter.create<LLVM::GlobalOp>(
gpuFuncOp.getLoc(), arrayType, /*isConstant=*/false,
LLVM::Linkage::Internal, name, /*value=*/Attribute(),
/*alignment=*/0, gpu::GPUDialect::getWorkgroupAddressSpace());
workgroupBuffers.push_back(globalOp);
}
// Rewrite the original GPU function to an LLVM function.
auto funcType = typeConverter->convertType(gpuFuncOp.getType())
.template cast<LLVM::LLVMPointerType>()
.getElementType();
// Remap proper input types.
TypeConverter::SignatureConversion signatureConversion(
gpuFuncOp.front().getNumArguments());
getTypeConverter()->convertFunctionSignature(
gpuFuncOp.getType(), /*isVariadic=*/false, signatureConversion);
// Create the new function operation. Only copy those attributes that are
// not specific to function modeling.
SmallVector<NamedAttribute, 4> attributes;
for (const auto &attr : gpuFuncOp->getAttrs()) {
if (attr.first == SymbolTable::getSymbolAttrName() ||
attr.first == function_like_impl::getTypeAttrName() ||
attr.first == gpu::GPUFuncOp::getNumWorkgroupAttributionsAttrName())
continue;
attributes.push_back(attr);
}
// Add a dialect specific kernel attribute in addition to GPU kernel
// attribute. The former is necessary for further translation while the
// latter is expected by gpu.launch_func.
if (gpuFuncOp.isKernel())
attributes.emplace_back(kernelAttributeName, rewriter.getUnitAttr());
auto llvmFuncOp = rewriter.create<LLVM::LLVMFuncOp>(
gpuFuncOp.getLoc(), gpuFuncOp.getName(), funcType,
LLVM::Linkage::External, attributes);
{
// Insert operations that correspond to converted workgroup and private
// memory attributions to the body of the function. This must operate on
// the original function, before the body region is inlined in the new
// function to maintain the relation between block arguments and the
// parent operation that assigns their semantics.
OpBuilder::InsertionGuard guard(rewriter);
// Rewrite workgroup memory attributions to addresses of global buffers.
rewriter.setInsertionPointToStart(&gpuFuncOp.front());
unsigned numProperArguments = gpuFuncOp.getNumArguments();
auto i32Type = IntegerType::get(rewriter.getContext(), 32);
Value zero = nullptr;
if (!workgroupBuffers.empty())
zero = rewriter.create<LLVM::ConstantOp>(loc, i32Type,
rewriter.getI32IntegerAttr(0));
for (auto en : llvm::enumerate(workgroupBuffers)) {
LLVM::GlobalOp global = en.value();
Value address = rewriter.create<LLVM::AddressOfOp>(loc, global);
auto elementType =
global.getType().cast<LLVM::LLVMArrayType>().getElementType();
Value memory = rewriter.create<LLVM::GEPOp>(
loc, LLVM::LLVMPointerType::get(elementType, global.addr_space()),
address, ArrayRef<Value>{zero, zero});
// Build a memref descriptor pointing to the buffer to plug with the
// existing memref infrastructure. This may use more registers than
// otherwise necessary given that memref sizes are fixed, but we can try
// and canonicalize that away later.
Value attribution = gpuFuncOp.getWorkgroupAttributions()[en.index()];
auto type = attribution.getType().cast<MemRefType>();
auto descr = MemRefDescriptor::fromStaticShape(
rewriter, loc, *getTypeConverter(), type, memory);
signatureConversion.remapInput(numProperArguments + en.index(), descr);
}
// Rewrite private memory attributions to alloca'ed buffers.
unsigned numWorkgroupAttributions = gpuFuncOp.getNumWorkgroupAttributions();
auto int64Ty = IntegerType::get(rewriter.getContext(), 64);
for (auto en : llvm::enumerate(gpuFuncOp.getPrivateAttributions())) {
Value attribution = en.value();
auto type = attribution.getType().cast<MemRefType>();
assert(type && type.hasStaticShape() && "unexpected type in attribution");
// Explicitly drop memory space when lowering private memory
// attributions since NVVM models it as `alloca`s in the default
// memory space and does not support `alloca`s with addrspace(5).
auto ptrType = LLVM::LLVMPointerType::get(
typeConverter->convertType(type.getElementType())
.template cast<Type>(),
allocaAddrSpace);
Value numElements = rewriter.create<LLVM::ConstantOp>(
gpuFuncOp.getLoc(), int64Ty,
rewriter.getI64IntegerAttr(type.getNumElements()));
Value allocated = rewriter.create<LLVM::AllocaOp>(
gpuFuncOp.getLoc(), ptrType, numElements, /*alignment=*/0);
auto descr = MemRefDescriptor::fromStaticShape(
rewriter, loc, *getTypeConverter(), type, allocated);
signatureConversion.remapInput(
numProperArguments + numWorkgroupAttributions + en.index(), descr);
}
}
// Move the region to the new function, update the entry block signature.
rewriter.inlineRegionBefore(gpuFuncOp.getBody(), llvmFuncOp.getBody(),
llvmFuncOp.end());
if (failed(rewriter.convertRegionTypes(&llvmFuncOp.getBody(), *typeConverter,
&signatureConversion)))
return failure();
rewriter.eraseOp(gpuFuncOp);
return success();
}