Jaeho Kim 103461f119
[mlir][spirv] Fix lookup logic spirv.target_env for gpu.module (#147262)
The `gpu.module` operation can contain `spirv.target_env` attributes
within an array attribute named `"targets"`. So it accounts for that
case by iterating over the `"targets"` attribute, if present, and
looking up `spirv.target_env`.

---------

Co-authored-by: Jakub Kuderski <kubakuderski@gmail.com>
2025-08-01 06:54:04 -04:00

854 lines
35 KiB
C++

//===- GPUToSPIRV.cpp - GPU to SPIR-V Patterns ----------------------------===//
//
// 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 patterns to convert GPU dialect to SPIR-V dialect.
//
//===----------------------------------------------------------------------===//
#include "mlir/Conversion/GPUToSPIRV/GPUToSPIRV.h"
#include "mlir/Dialect/GPU/IR/GPUDialect.h"
#include "mlir/Dialect/SPIRV/IR/SPIRVAttributes.h"
#include "mlir/Dialect/SPIRV/IR/SPIRVEnums.h"
#include "mlir/Dialect/SPIRV/IR/SPIRVOps.h"
#include "mlir/Dialect/SPIRV/IR/SPIRVTypes.h"
#include "mlir/Dialect/SPIRV/IR/TargetAndABI.h"
#include "mlir/Dialect/SPIRV/Transforms/SPIRVConversion.h"
#include "mlir/IR/Matchers.h"
#include "mlir/Transforms/DialectConversion.h"
#include <optional>
using namespace mlir;
static constexpr const char kSPIRVModule[] = "__spv__";
namespace {
/// Pattern lowering GPU block/thread size/id to loading SPIR-V invocation
/// builtin variables.
template <typename SourceOp, spirv::BuiltIn builtin>
class LaunchConfigConversion : public OpConversionPattern<SourceOp> {
public:
using OpConversionPattern<SourceOp>::OpConversionPattern;
LogicalResult
matchAndRewrite(SourceOp op, typename SourceOp::Adaptor adaptor,
ConversionPatternRewriter &rewriter) const override;
};
/// Pattern lowering subgroup size/id to loading SPIR-V invocation
/// builtin variables.
template <typename SourceOp, spirv::BuiltIn builtin>
class SingleDimLaunchConfigConversion : public OpConversionPattern<SourceOp> {
public:
using OpConversionPattern<SourceOp>::OpConversionPattern;
LogicalResult
matchAndRewrite(SourceOp op, typename SourceOp::Adaptor adaptor,
ConversionPatternRewriter &rewriter) const override;
};
/// This is separate because in Vulkan workgroup size is exposed to shaders via
/// a constant with WorkgroupSize decoration. So here we cannot generate a
/// builtin variable; instead the information in the `spirv.entry_point_abi`
/// attribute on the surrounding FuncOp is used to replace the gpu::BlockDimOp.
class WorkGroupSizeConversion : public OpConversionPattern<gpu::BlockDimOp> {
public:
WorkGroupSizeConversion(const TypeConverter &typeConverter,
MLIRContext *context)
: OpConversionPattern(typeConverter, context, /*benefit*/ 10) {}
LogicalResult
matchAndRewrite(gpu::BlockDimOp op, OpAdaptor adaptor,
ConversionPatternRewriter &rewriter) const override;
};
/// Pattern to convert a kernel function in GPU dialect within a spirv.module.
class GPUFuncOpConversion final : public OpConversionPattern<gpu::GPUFuncOp> {
public:
using OpConversionPattern<gpu::GPUFuncOp>::OpConversionPattern;
LogicalResult
matchAndRewrite(gpu::GPUFuncOp funcOp, OpAdaptor adaptor,
ConversionPatternRewriter &rewriter) const override;
private:
SmallVector<int32_t, 3> workGroupSizeAsInt32;
};
/// Pattern to convert a gpu.module to a spirv.module.
class GPUModuleConversion final : public OpConversionPattern<gpu::GPUModuleOp> {
public:
using OpConversionPattern<gpu::GPUModuleOp>::OpConversionPattern;
LogicalResult
matchAndRewrite(gpu::GPUModuleOp moduleOp, OpAdaptor adaptor,
ConversionPatternRewriter &rewriter) const override;
};
/// Pattern to convert a gpu.return into a SPIR-V return.
// TODO: This can go to DRR when GPU return has operands.
class GPUReturnOpConversion final : public OpConversionPattern<gpu::ReturnOp> {
public:
using OpConversionPattern<gpu::ReturnOp>::OpConversionPattern;
LogicalResult
matchAndRewrite(gpu::ReturnOp returnOp, OpAdaptor adaptor,
ConversionPatternRewriter &rewriter) const override;
};
/// Pattern to convert a gpu.barrier op into a spirv.ControlBarrier op.
class GPUBarrierConversion final : public OpConversionPattern<gpu::BarrierOp> {
public:
using OpConversionPattern::OpConversionPattern;
LogicalResult
matchAndRewrite(gpu::BarrierOp barrierOp, OpAdaptor adaptor,
ConversionPatternRewriter &rewriter) const override;
};
/// Pattern to convert a gpu.shuffle op into a spirv.GroupNonUniformShuffle op.
class GPUShuffleConversion final : public OpConversionPattern<gpu::ShuffleOp> {
public:
using OpConversionPattern::OpConversionPattern;
LogicalResult
matchAndRewrite(gpu::ShuffleOp shuffleOp, OpAdaptor adaptor,
ConversionPatternRewriter &rewriter) const override;
};
/// Pattern to convert a gpu.rotate op into a spirv.GroupNonUniformRotateKHROp.
class GPURotateConversion final : public OpConversionPattern<gpu::RotateOp> {
public:
using OpConversionPattern::OpConversionPattern;
LogicalResult
matchAndRewrite(gpu::RotateOp rotateOp, OpAdaptor adaptor,
ConversionPatternRewriter &rewriter) const override;
};
class GPUPrintfConversion final : public OpConversionPattern<gpu::PrintfOp> {
public:
using OpConversionPattern::OpConversionPattern;
LogicalResult
matchAndRewrite(gpu::PrintfOp gpuPrintfOp, OpAdaptor adaptor,
ConversionPatternRewriter &rewriter) const override;
};
} // namespace
//===----------------------------------------------------------------------===//
// Builtins.
//===----------------------------------------------------------------------===//
template <typename SourceOp, spirv::BuiltIn builtin>
LogicalResult LaunchConfigConversion<SourceOp, builtin>::matchAndRewrite(
SourceOp op, typename SourceOp::Adaptor adaptor,
ConversionPatternRewriter &rewriter) const {
auto *typeConverter = this->template getTypeConverter<SPIRVTypeConverter>();
Type indexType = typeConverter->getIndexType();
// For Vulkan, these SPIR-V builtin variables are required to be a vector of
// type <3xi32> by the spec:
// https://registry.khronos.org/vulkan/specs/1.3-extensions/man/html/NumWorkgroups.html
// https://registry.khronos.org/vulkan/specs/1.3-extensions/man/html/WorkgroupId.html
// https://registry.khronos.org/vulkan/specs/1.3-extensions/man/html/WorkgroupSize.html
// https://registry.khronos.org/vulkan/specs/1.3-extensions/man/html/LocalInvocationId.html
// https://registry.khronos.org/vulkan/specs/1.3-extensions/man/html/LocalInvocationId.html
// https://registry.khronos.org/vulkan/specs/1.3-extensions/man/html/GlobalInvocationId.html
//
// For OpenCL, it depends on the Physical32/Physical64 addressing model:
// https://registry.khronos.org/OpenCL/specs/3.0-unified/html/OpenCL_Env.html#_built_in_variables
bool forShader =
typeConverter->getTargetEnv().allows(spirv::Capability::Shader);
Type builtinType = forShader ? rewriter.getIntegerType(32) : indexType;
Value vector =
spirv::getBuiltinVariableValue(op, builtin, builtinType, rewriter);
Value dim = spirv::CompositeExtractOp::create(
rewriter, op.getLoc(), builtinType, vector,
rewriter.getI32ArrayAttr({static_cast<int32_t>(op.getDimension())}));
if (forShader && builtinType != indexType)
dim = spirv::UConvertOp::create(rewriter, op.getLoc(), indexType, dim);
rewriter.replaceOp(op, dim);
return success();
}
template <typename SourceOp, spirv::BuiltIn builtin>
LogicalResult
SingleDimLaunchConfigConversion<SourceOp, builtin>::matchAndRewrite(
SourceOp op, typename SourceOp::Adaptor adaptor,
ConversionPatternRewriter &rewriter) const {
auto *typeConverter = this->template getTypeConverter<SPIRVTypeConverter>();
Type indexType = typeConverter->getIndexType();
Type i32Type = rewriter.getIntegerType(32);
// For Vulkan, these SPIR-V builtin variables are required to be a vector of
// type i32 by the spec:
// https://registry.khronos.org/vulkan/specs/1.3-extensions/man/html/NumSubgroups.html
// https://registry.khronos.org/vulkan/specs/1.3-extensions/man/html/SubgroupId.html
// https://registry.khronos.org/vulkan/specs/1.3-extensions/man/html/SubgroupSize.html
//
// For OpenCL, they are also required to be i32:
// https://registry.khronos.org/OpenCL/specs/3.0-unified/html/OpenCL_Env.html#_built_in_variables
Value builtinValue =
spirv::getBuiltinVariableValue(op, builtin, i32Type, rewriter);
if (i32Type != indexType)
builtinValue = spirv::UConvertOp::create(rewriter, op.getLoc(), indexType,
builtinValue);
rewriter.replaceOp(op, builtinValue);
return success();
}
LogicalResult WorkGroupSizeConversion::matchAndRewrite(
gpu::BlockDimOp op, OpAdaptor adaptor,
ConversionPatternRewriter &rewriter) const {
DenseI32ArrayAttr workGroupSizeAttr = spirv::lookupLocalWorkGroupSize(op);
if (!workGroupSizeAttr)
return failure();
int val =
workGroupSizeAttr.asArrayRef()[static_cast<int32_t>(op.getDimension())];
auto convertedType =
getTypeConverter()->convertType(op.getResult().getType());
if (!convertedType)
return failure();
rewriter.replaceOpWithNewOp<spirv::ConstantOp>(
op, convertedType, IntegerAttr::get(convertedType, val));
return success();
}
//===----------------------------------------------------------------------===//
// GPUFuncOp
//===----------------------------------------------------------------------===//
// Legalizes a GPU function as an entry SPIR-V function.
static spirv::FuncOp
lowerAsEntryFunction(gpu::GPUFuncOp funcOp, const TypeConverter &typeConverter,
ConversionPatternRewriter &rewriter,
spirv::EntryPointABIAttr entryPointInfo,
ArrayRef<spirv::InterfaceVarABIAttr> argABIInfo) {
auto fnType = funcOp.getFunctionType();
if (fnType.getNumResults()) {
funcOp.emitError("SPIR-V lowering only supports entry functions"
"with no return values right now");
return nullptr;
}
if (!argABIInfo.empty() && fnType.getNumInputs() != argABIInfo.size()) {
funcOp.emitError(
"lowering as entry functions requires ABI info for all arguments "
"or none of them");
return nullptr;
}
// Update the signature to valid SPIR-V types and add the ABI
// attributes. These will be "materialized" by using the
// LowerABIAttributesPass.
TypeConverter::SignatureConversion signatureConverter(fnType.getNumInputs());
{
for (const auto &argType :
enumerate(funcOp.getFunctionType().getInputs())) {
auto convertedType = typeConverter.convertType(argType.value());
if (!convertedType)
return nullptr;
signatureConverter.addInputs(argType.index(), convertedType);
}
}
auto newFuncOp = spirv::FuncOp::create(
rewriter, funcOp.getLoc(), funcOp.getName(),
rewriter.getFunctionType(signatureConverter.getConvertedTypes(), {}));
for (const auto &namedAttr : funcOp->getAttrs()) {
if (namedAttr.getName() == funcOp.getFunctionTypeAttrName() ||
namedAttr.getName() == SymbolTable::getSymbolAttrName())
continue;
newFuncOp->setAttr(namedAttr.getName(), namedAttr.getValue());
}
rewriter.inlineRegionBefore(funcOp.getBody(), newFuncOp.getBody(),
newFuncOp.end());
if (failed(rewriter.convertRegionTypes(&newFuncOp.getBody(), typeConverter,
&signatureConverter)))
return nullptr;
rewriter.eraseOp(funcOp);
// Set the attributes for argument and the function.
StringRef argABIAttrName = spirv::getInterfaceVarABIAttrName();
for (auto argIndex : llvm::seq<unsigned>(0, argABIInfo.size())) {
newFuncOp.setArgAttr(argIndex, argABIAttrName, argABIInfo[argIndex]);
}
newFuncOp->setAttr(spirv::getEntryPointABIAttrName(), entryPointInfo);
return newFuncOp;
}
/// Populates `argABI` with spirv.interface_var_abi attributes for lowering
/// gpu.func to spirv.func if no arguments have the attributes set
/// already. Returns failure if any argument has the ABI attribute set already.
static LogicalResult
getDefaultABIAttrs(const spirv::TargetEnv &targetEnv, gpu::GPUFuncOp funcOp,
SmallVectorImpl<spirv::InterfaceVarABIAttr> &argABI) {
if (!spirv::needsInterfaceVarABIAttrs(targetEnv))
return success();
for (auto argIndex : llvm::seq<unsigned>(0, funcOp.getNumArguments())) {
if (funcOp.getArgAttrOfType<spirv::InterfaceVarABIAttr>(
argIndex, spirv::getInterfaceVarABIAttrName()))
return failure();
// Vulkan's interface variable requirements needs scalars to be wrapped in a
// struct. The struct held in storage buffer.
std::optional<spirv::StorageClass> sc;
if (funcOp.getArgument(argIndex).getType().isIntOrIndexOrFloat())
sc = spirv::StorageClass::StorageBuffer;
argABI.push_back(
spirv::getInterfaceVarABIAttr(0, argIndex, sc, funcOp.getContext()));
}
return success();
}
LogicalResult GPUFuncOpConversion::matchAndRewrite(
gpu::GPUFuncOp funcOp, OpAdaptor adaptor,
ConversionPatternRewriter &rewriter) const {
if (!gpu::GPUDialect::isKernel(funcOp))
return failure();
auto *typeConverter = getTypeConverter<SPIRVTypeConverter>();
SmallVector<spirv::InterfaceVarABIAttr, 4> argABI;
if (failed(
getDefaultABIAttrs(typeConverter->getTargetEnv(), funcOp, argABI))) {
argABI.clear();
for (auto argIndex : llvm::seq<unsigned>(0, funcOp.getNumArguments())) {
// If the ABI is already specified, use it.
auto abiAttr = funcOp.getArgAttrOfType<spirv::InterfaceVarABIAttr>(
argIndex, spirv::getInterfaceVarABIAttrName());
if (!abiAttr) {
funcOp.emitRemark(
"match failure: missing 'spirv.interface_var_abi' attribute at "
"argument ")
<< argIndex;
return failure();
}
argABI.push_back(abiAttr);
}
}
auto entryPointAttr = spirv::lookupEntryPointABI(funcOp);
if (!entryPointAttr) {
funcOp.emitRemark(
"match failure: missing 'spirv.entry_point_abi' attribute");
return failure();
}
spirv::FuncOp newFuncOp = lowerAsEntryFunction(
funcOp, *getTypeConverter(), rewriter, entryPointAttr, argABI);
if (!newFuncOp)
return failure();
newFuncOp->removeAttr(
rewriter.getStringAttr(gpu::GPUDialect::getKernelFuncAttrName()));
return success();
}
//===----------------------------------------------------------------------===//
// ModuleOp with gpu.module.
//===----------------------------------------------------------------------===//
LogicalResult GPUModuleConversion::matchAndRewrite(
gpu::GPUModuleOp moduleOp, OpAdaptor adaptor,
ConversionPatternRewriter &rewriter) const {
auto *typeConverter = getTypeConverter<SPIRVTypeConverter>();
const spirv::TargetEnv &targetEnv = typeConverter->getTargetEnv();
spirv::AddressingModel addressingModel = spirv::getAddressingModel(
targetEnv, typeConverter->getOptions().use64bitIndex);
FailureOr<spirv::MemoryModel> memoryModel = spirv::getMemoryModel(targetEnv);
if (failed(memoryModel))
return moduleOp.emitRemark(
"cannot deduce memory model from 'spirv.target_env'");
// Add a keyword to the module name to avoid symbolic conflict.
std::string spvModuleName = (kSPIRVModule + moduleOp.getName()).str();
auto spvModule = spirv::ModuleOp::create(
rewriter, moduleOp.getLoc(), addressingModel, *memoryModel, std::nullopt,
StringRef(spvModuleName));
// Move the region from the module op into the SPIR-V module.
Region &spvModuleRegion = spvModule.getRegion();
rewriter.inlineRegionBefore(moduleOp.getBodyRegion(), spvModuleRegion,
spvModuleRegion.begin());
// The spirv.module build method adds a block. Remove that.
rewriter.eraseBlock(&spvModuleRegion.back());
// Some of the patterns call `lookupTargetEnv` during conversion and they
// will fail if called after GPUModuleConversion and we don't preserve
// `TargetEnv` attribute.
// Copy TargetEnvAttr only if it is attached directly to the GPUModuleOp.
if (auto attr = moduleOp->getAttrOfType<spirv::TargetEnvAttr>(
spirv::getTargetEnvAttrName()))
spvModule->setAttr(spirv::getTargetEnvAttrName(), attr);
if (ArrayAttr targets = moduleOp.getTargetsAttr()) {
for (Attribute targetAttr : targets)
if (auto spirvTargetEnvAttr =
dyn_cast<spirv::TargetEnvAttr>(targetAttr)) {
spvModule->setAttr(spirv::getTargetEnvAttrName(), spirvTargetEnvAttr);
break;
}
}
rewriter.eraseOp(moduleOp);
return success();
}
//===----------------------------------------------------------------------===//
// GPU return inside kernel functions to SPIR-V return.
//===----------------------------------------------------------------------===//
LogicalResult GPUReturnOpConversion::matchAndRewrite(
gpu::ReturnOp returnOp, OpAdaptor adaptor,
ConversionPatternRewriter &rewriter) const {
if (!adaptor.getOperands().empty())
return failure();
rewriter.replaceOpWithNewOp<spirv::ReturnOp>(returnOp);
return success();
}
//===----------------------------------------------------------------------===//
// Barrier.
//===----------------------------------------------------------------------===//
LogicalResult GPUBarrierConversion::matchAndRewrite(
gpu::BarrierOp barrierOp, OpAdaptor adaptor,
ConversionPatternRewriter &rewriter) const {
MLIRContext *context = getContext();
// Both execution and memory scope should be workgroup.
auto scope = spirv::ScopeAttr::get(context, spirv::Scope::Workgroup);
// Require acquire and release memory semantics for workgroup memory.
auto memorySemantics = spirv::MemorySemanticsAttr::get(
context, spirv::MemorySemantics::WorkgroupMemory |
spirv::MemorySemantics::AcquireRelease);
rewriter.replaceOpWithNewOp<spirv::ControlBarrierOp>(barrierOp, scope, scope,
memorySemantics);
return success();
}
//===----------------------------------------------------------------------===//
// Shuffle
//===----------------------------------------------------------------------===//
LogicalResult GPUShuffleConversion::matchAndRewrite(
gpu::ShuffleOp shuffleOp, OpAdaptor adaptor,
ConversionPatternRewriter &rewriter) const {
// Require the shuffle width to be the same as the target's subgroup size,
// given that for SPIR-V non-uniform subgroup ops, we cannot select
// participating invocations.
auto targetEnv = getTypeConverter<SPIRVTypeConverter>()->getTargetEnv();
unsigned subgroupSize =
targetEnv.getAttr().getResourceLimits().getSubgroupSize();
IntegerAttr widthAttr;
if (!matchPattern(shuffleOp.getWidth(), m_Constant(&widthAttr)) ||
widthAttr.getValue().getZExtValue() != subgroupSize)
return rewriter.notifyMatchFailure(
shuffleOp, "shuffle width and target subgroup size mismatch");
assert(!adaptor.getOffset().getType().isSignedInteger() &&
"shuffle offset must be a signless/unsigned integer");
Location loc = shuffleOp.getLoc();
auto scope = rewriter.getAttr<spirv::ScopeAttr>(spirv::Scope::Subgroup);
Value result;
Value validVal;
switch (shuffleOp.getMode()) {
case gpu::ShuffleMode::XOR: {
result = spirv::GroupNonUniformShuffleXorOp::create(
rewriter, loc, scope, adaptor.getValue(), adaptor.getOffset());
validVal = spirv::ConstantOp::getOne(rewriter.getI1Type(),
shuffleOp.getLoc(), rewriter);
break;
}
case gpu::ShuffleMode::IDX: {
result = spirv::GroupNonUniformShuffleOp::create(
rewriter, loc, scope, adaptor.getValue(), adaptor.getOffset());
validVal = spirv::ConstantOp::getOne(rewriter.getI1Type(),
shuffleOp.getLoc(), rewriter);
break;
}
case gpu::ShuffleMode::DOWN: {
result = spirv::GroupNonUniformShuffleDownOp::create(
rewriter, loc, scope, adaptor.getValue(), adaptor.getOffset());
Value laneId = gpu::LaneIdOp::create(rewriter, loc, widthAttr);
Value resultLaneId =
arith::AddIOp::create(rewriter, loc, laneId, adaptor.getOffset());
validVal = arith::CmpIOp::create(rewriter, loc, arith::CmpIPredicate::ult,
resultLaneId, adaptor.getWidth());
break;
}
case gpu::ShuffleMode::UP: {
result = spirv::GroupNonUniformShuffleUpOp::create(
rewriter, loc, scope, adaptor.getValue(), adaptor.getOffset());
Value laneId = gpu::LaneIdOp::create(rewriter, loc, widthAttr);
Value resultLaneId =
arith::SubIOp::create(rewriter, loc, laneId, adaptor.getOffset());
auto i32Type = rewriter.getIntegerType(32);
validVal = arith::CmpIOp::create(
rewriter, loc, arith::CmpIPredicate::sge, resultLaneId,
arith::ConstantOp::create(rewriter, loc, i32Type,
rewriter.getIntegerAttr(i32Type, 0)));
break;
}
}
rewriter.replaceOp(shuffleOp, {result, validVal});
return success();
}
//===----------------------------------------------------------------------===//
// Rotate
//===----------------------------------------------------------------------===//
LogicalResult GPURotateConversion::matchAndRewrite(
gpu::RotateOp rotateOp, OpAdaptor adaptor,
ConversionPatternRewriter &rewriter) const {
const spirv::TargetEnv &targetEnv =
getTypeConverter<SPIRVTypeConverter>()->getTargetEnv();
unsigned subgroupSize =
targetEnv.getAttr().getResourceLimits().getSubgroupSize();
unsigned width = rotateOp.getWidth();
if (width > subgroupSize)
return rewriter.notifyMatchFailure(
rotateOp, "rotate width is larger than target subgroup size");
Location loc = rotateOp.getLoc();
auto scope = rewriter.getAttr<spirv::ScopeAttr>(spirv::Scope::Subgroup);
Value offsetVal =
arith::ConstantOp::create(rewriter, loc, adaptor.getOffsetAttr());
Value widthVal =
arith::ConstantOp::create(rewriter, loc, adaptor.getWidthAttr());
Value rotateResult = spirv::GroupNonUniformRotateKHROp::create(
rewriter, loc, scope, adaptor.getValue(), offsetVal, widthVal);
Value validVal;
if (width == subgroupSize) {
validVal = spirv::ConstantOp::getOne(rewriter.getI1Type(), loc, rewriter);
} else {
IntegerAttr widthAttr = adaptor.getWidthAttr();
Value laneId = gpu::LaneIdOp::create(rewriter, loc, widthAttr);
validVal = arith::CmpIOp::create(rewriter, loc, arith::CmpIPredicate::ult,
laneId, widthVal);
}
rewriter.replaceOp(rotateOp, {rotateResult, validVal});
return success();
}
//===----------------------------------------------------------------------===//
// Group ops
//===----------------------------------------------------------------------===//
template <typename UniformOp, typename NonUniformOp>
static Value createGroupReduceOpImpl(OpBuilder &builder, Location loc,
Value arg, bool isGroup, bool isUniform,
std::optional<uint32_t> clusterSize) {
Type type = arg.getType();
auto scope = mlir::spirv::ScopeAttr::get(builder.getContext(),
isGroup ? spirv::Scope::Workgroup
: spirv::Scope::Subgroup);
auto groupOp = spirv::GroupOperationAttr::get(
builder.getContext(), clusterSize.has_value()
? spirv::GroupOperation::ClusteredReduce
: spirv::GroupOperation::Reduce);
if (isUniform) {
return UniformOp::create(builder, loc, type, scope, groupOp, arg)
.getResult();
}
Value clusterSizeValue;
if (clusterSize.has_value())
clusterSizeValue = spirv::ConstantOp::create(
builder, loc, builder.getI32Type(),
builder.getIntegerAttr(builder.getI32Type(), *clusterSize));
return NonUniformOp::create(builder, loc, type, scope, groupOp, arg,
clusterSizeValue)
.getResult();
}
static std::optional<Value>
createGroupReduceOp(OpBuilder &builder, Location loc, Value arg,
gpu::AllReduceOperation opType, bool isGroup,
bool isUniform, std::optional<uint32_t> clusterSize) {
enum class ElemType { Float, Boolean, Integer };
using FuncT = Value (*)(OpBuilder &, Location, Value, bool, bool,
std::optional<uint32_t>);
struct OpHandler {
gpu::AllReduceOperation kind;
ElemType elemType;
FuncT func;
};
Type type = arg.getType();
ElemType elementType;
if (isa<FloatType>(type)) {
elementType = ElemType::Float;
} else if (auto intTy = dyn_cast<IntegerType>(type)) {
elementType = (intTy.getIntOrFloatBitWidth() == 1) ? ElemType::Boolean
: ElemType::Integer;
} else {
return std::nullopt;
}
// TODO(https://github.com/llvm/llvm-project/issues/73459): The SPIR-V spec
// does not specify how -0.0 / +0.0 and NaN values are handled in *FMin/*FMax
// reduction ops. We should account possible precision requirements in this
// conversion.
using ReduceType = gpu::AllReduceOperation;
const OpHandler handlers[] = {
{ReduceType::ADD, ElemType::Integer,
&createGroupReduceOpImpl<spirv::GroupIAddOp,
spirv::GroupNonUniformIAddOp>},
{ReduceType::ADD, ElemType::Float,
&createGroupReduceOpImpl<spirv::GroupFAddOp,
spirv::GroupNonUniformFAddOp>},
{ReduceType::MUL, ElemType::Integer,
&createGroupReduceOpImpl<spirv::GroupIMulKHROp,
spirv::GroupNonUniformIMulOp>},
{ReduceType::MUL, ElemType::Float,
&createGroupReduceOpImpl<spirv::GroupFMulKHROp,
spirv::GroupNonUniformFMulOp>},
{ReduceType::MINUI, ElemType::Integer,
&createGroupReduceOpImpl<spirv::GroupUMinOp,
spirv::GroupNonUniformUMinOp>},
{ReduceType::MINSI, ElemType::Integer,
&createGroupReduceOpImpl<spirv::GroupSMinOp,
spirv::GroupNonUniformSMinOp>},
{ReduceType::MINNUMF, ElemType::Float,
&createGroupReduceOpImpl<spirv::GroupFMinOp,
spirv::GroupNonUniformFMinOp>},
{ReduceType::MAXUI, ElemType::Integer,
&createGroupReduceOpImpl<spirv::GroupUMaxOp,
spirv::GroupNonUniformUMaxOp>},
{ReduceType::MAXSI, ElemType::Integer,
&createGroupReduceOpImpl<spirv::GroupSMaxOp,
spirv::GroupNonUniformSMaxOp>},
{ReduceType::MAXNUMF, ElemType::Float,
&createGroupReduceOpImpl<spirv::GroupFMaxOp,
spirv::GroupNonUniformFMaxOp>},
{ReduceType::MINIMUMF, ElemType::Float,
&createGroupReduceOpImpl<spirv::GroupFMinOp,
spirv::GroupNonUniformFMinOp>},
{ReduceType::MAXIMUMF, ElemType::Float,
&createGroupReduceOpImpl<spirv::GroupFMaxOp,
spirv::GroupNonUniformFMaxOp>}};
for (const OpHandler &handler : handlers)
if (handler.kind == opType && elementType == handler.elemType)
return handler.func(builder, loc, arg, isGroup, isUniform, clusterSize);
return std::nullopt;
}
/// Pattern to convert a gpu.all_reduce op into a SPIR-V group op.
class GPUAllReduceConversion final
: public OpConversionPattern<gpu::AllReduceOp> {
public:
using OpConversionPattern::OpConversionPattern;
LogicalResult
matchAndRewrite(gpu::AllReduceOp op, OpAdaptor adaptor,
ConversionPatternRewriter &rewriter) const override {
auto opType = op.getOp();
// gpu.all_reduce can have either reduction op attribute or reduction
// region. Only attribute version is supported.
if (!opType)
return failure();
auto result =
createGroupReduceOp(rewriter, op.getLoc(), adaptor.getValue(), *opType,
/*isGroup*/ true, op.getUniform(), std::nullopt);
if (!result)
return failure();
rewriter.replaceOp(op, *result);
return success();
}
};
/// Pattern to convert a gpu.subgroup_reduce op into a SPIR-V group op.
class GPUSubgroupReduceConversion final
: public OpConversionPattern<gpu::SubgroupReduceOp> {
public:
using OpConversionPattern::OpConversionPattern;
LogicalResult
matchAndRewrite(gpu::SubgroupReduceOp op, OpAdaptor adaptor,
ConversionPatternRewriter &rewriter) const override {
if (op.getClusterStride() > 1) {
return rewriter.notifyMatchFailure(
op, "lowering for cluster stride > 1 is not implemented");
}
if (!isa<spirv::ScalarType>(adaptor.getValue().getType()))
return rewriter.notifyMatchFailure(op, "reduction type is not a scalar");
auto result = createGroupReduceOp(
rewriter, op.getLoc(), adaptor.getValue(), adaptor.getOp(),
/*isGroup=*/false, adaptor.getUniform(), op.getClusterSize());
if (!result)
return failure();
rewriter.replaceOp(op, *result);
return success();
}
};
// Formulate a unique variable/constant name after
// searching in the module for existing variable/constant names.
// This is to avoid name collision with existing variables.
// Example: printfMsg0, printfMsg1, printfMsg2, ...
static std::string makeVarName(spirv::ModuleOp moduleOp, llvm::Twine prefix) {
std::string name;
unsigned number = 0;
do {
name.clear();
name = (prefix + llvm::Twine(number++)).str();
} while (moduleOp.lookupSymbol(name));
return name;
}
/// Pattern to convert a gpu.printf op into a SPIR-V CLPrintf op.
LogicalResult GPUPrintfConversion::matchAndRewrite(
gpu::PrintfOp gpuPrintfOp, OpAdaptor adaptor,
ConversionPatternRewriter &rewriter) const {
Location loc = gpuPrintfOp.getLoc();
auto moduleOp = gpuPrintfOp->getParentOfType<spirv::ModuleOp>();
if (!moduleOp)
return failure();
// SPIR-V global variable is used to initialize printf
// format string value, if there are multiple printf messages,
// each global var needs to be created with a unique name.
std::string globalVarName = makeVarName(moduleOp, llvm::Twine("printfMsg"));
spirv::GlobalVariableOp globalVar;
IntegerType i8Type = rewriter.getI8Type();
IntegerType i32Type = rewriter.getI32Type();
// Each character of printf format string is
// stored as a spec constant. We need to create
// unique name for this spec constant like
// @printfMsg0_sc0, @printfMsg0_sc1, ... by searching in the module
// for existing spec constant names.
auto createSpecConstant = [&](unsigned value) {
auto attr = rewriter.getI8IntegerAttr(value);
std::string specCstName =
makeVarName(moduleOp, llvm::Twine(globalVarName) + "_sc");
return spirv::SpecConstantOp::create(
rewriter, loc, rewriter.getStringAttr(specCstName), attr);
};
{
Operation *parent =
SymbolTable::getNearestSymbolTable(gpuPrintfOp->getParentOp());
ConversionPatternRewriter::InsertionGuard guard(rewriter);
Block &entryBlock = *parent->getRegion(0).begin();
rewriter.setInsertionPointToStart(
&entryBlock); // insertion point at module level
// Create Constituents with SpecConstant by scanning format string
// Each character of format string is stored as a spec constant
// and then these spec constants are used to create a
// SpecConstantCompositeOp.
llvm::SmallString<20> formatString(adaptor.getFormat());
formatString.push_back('\0'); // Null terminate for C.
SmallVector<Attribute, 4> constituents;
for (char c : formatString) {
spirv::SpecConstantOp cSpecConstantOp = createSpecConstant(c);
constituents.push_back(SymbolRefAttr::get(cSpecConstantOp));
}
// Create SpecConstantCompositeOp to initialize the global variable
size_t contentSize = constituents.size();
auto globalType = spirv::ArrayType::get(i8Type, contentSize);
spirv::SpecConstantCompositeOp specCstComposite;
// There will be one SpecConstantCompositeOp per printf message/global var,
// so no need do lookup for existing ones.
std::string specCstCompositeName =
(llvm::Twine(globalVarName) + "_scc").str();
specCstComposite = spirv::SpecConstantCompositeOp::create(
rewriter, loc, TypeAttr::get(globalType),
rewriter.getStringAttr(specCstCompositeName),
rewriter.getArrayAttr(constituents));
auto ptrType = spirv::PointerType::get(
globalType, spirv::StorageClass::UniformConstant);
// Define a GlobalVarOp initialized using specialized constants
// that is used to specify the printf format string
// to be passed to the SPIRV CLPrintfOp.
globalVar = spirv::GlobalVariableOp::create(
rewriter, loc, ptrType, globalVarName,
FlatSymbolRefAttr::get(specCstComposite));
globalVar->setAttr("Constant", rewriter.getUnitAttr());
}
// Get SSA value of Global variable and create pointer to i8 to point to
// the format string.
Value globalPtr = spirv::AddressOfOp::create(rewriter, loc, globalVar);
Value fmtStr = spirv::BitcastOp::create(
rewriter, loc,
spirv::PointerType::get(i8Type, spirv::StorageClass::UniformConstant),
globalPtr);
// Get printf arguments.
auto printfArgs = llvm::to_vector_of<Value, 4>(adaptor.getArgs());
spirv::CLPrintfOp::create(rewriter, loc, i32Type, fmtStr, printfArgs);
// Need to erase the gpu.printf op as gpu.printf does not use result vs
// spirv::CLPrintfOp has i32 resultType so cannot replace with new SPIR-V
// printf op.
rewriter.eraseOp(gpuPrintfOp);
return success();
}
//===----------------------------------------------------------------------===//
// GPU To SPIRV Patterns.
//===----------------------------------------------------------------------===//
void mlir::populateGPUToSPIRVPatterns(const SPIRVTypeConverter &typeConverter,
RewritePatternSet &patterns) {
patterns.add<
GPUBarrierConversion, GPUFuncOpConversion, GPUModuleConversion,
GPUReturnOpConversion, GPUShuffleConversion, GPURotateConversion,
LaunchConfigConversion<gpu::BlockIdOp, spirv::BuiltIn::WorkgroupId>,
LaunchConfigConversion<gpu::GridDimOp, spirv::BuiltIn::NumWorkgroups>,
LaunchConfigConversion<gpu::BlockDimOp, spirv::BuiltIn::WorkgroupSize>,
LaunchConfigConversion<gpu::ThreadIdOp,
spirv::BuiltIn::LocalInvocationId>,
LaunchConfigConversion<gpu::GlobalIdOp,
spirv::BuiltIn::GlobalInvocationId>,
SingleDimLaunchConfigConversion<gpu::SubgroupIdOp,
spirv::BuiltIn::SubgroupId>,
SingleDimLaunchConfigConversion<gpu::NumSubgroupsOp,
spirv::BuiltIn::NumSubgroups>,
SingleDimLaunchConfigConversion<gpu::SubgroupSizeOp,
spirv::BuiltIn::SubgroupSize>,
SingleDimLaunchConfigConversion<
gpu::LaneIdOp, spirv::BuiltIn::SubgroupLocalInvocationId>,
WorkGroupSizeConversion, GPUAllReduceConversion,
GPUSubgroupReduceConversion, GPUPrintfConversion>(typeConverter,
patterns.getContext());
}