llvm-project/mlir/lib/Dialect/GPU/TransformOps/GPUTransformOps.cpp

599 lines
25 KiB
C++

//===- GPUTransformOps.cpp - Implementation of GPU transform ops ----------===//
//
// 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/Dialect/GPU/TransformOps/GPUTransformOps.h"
#include "mlir/Dialect/Arith/IR/Arith.h"
#include "mlir/Dialect/GPU/IR/GPUDialect.h"
#include "mlir/Dialect/GPU/TransformOps/GPUTransformOps.h"
#include "mlir/Dialect/PDL/IR/PDL.h"
#include "mlir/Dialect/SCF/IR/DeviceMappingInterface.h"
#include "mlir/Dialect/SCF/IR/SCF.h"
#include "mlir/Dialect/Transform/IR/TransformDialect.h"
#include "mlir/Dialect/Transform/IR/TransformInterfaces.h"
#include "mlir/Dialect/Transform/IR/TransformUtils.h"
#include "mlir/IR/BlockAndValueMapping.h"
using namespace mlir;
using namespace mlir::gpu;
using namespace mlir::transform;
/// Check if given mapping attributes are one of the desired attributes
static DiagnosedSilenceableFailure
checkAttributeType(ArrayRef<DeviceMappingAttrInterface> threadMappingAttributes,
const Optional<ArrayAttr> &foreachMapping,
Optional<TransformOpInterface> transformOp) {
if (!foreachMapping.has_value())
return transformOp->emitSilenceableError() << "mapping must be present";
DenseSet<Attribute> seen;
for (Attribute map : foreachMapping->getValue()) {
if (!llvm::is_contained(threadMappingAttributes, map)) {
return transformOp->emitDefiniteFailure()
<< "mapping must be one of " << threadMappingAttributes;
}
if (llvm::is_contained(seen, map)) {
return transformOp->emitDefiniteFailure()
<< map
<< " is duplicated, cannot map different "
"loops to the same processor";
}
seen.insert(map);
}
return DiagnosedSilenceableFailure::success();
}
/// Determines if the size of the kernel configuration is supported by the GPU
/// architecture being used. It presently makes use of CUDA limitations, however
/// that aspect may be enhanced for other GPUs.
static DiagnosedSilenceableFailure
checkGpuLimits(TransformOpInterface transformOp, Optional<int64_t> gridDimX,
Optional<int64_t> gridDimY, Optional<int64_t> gridDimZ,
Optional<int64_t> blockDimX, Optional<int64_t> blockDimY,
Optional<int64_t> blockDimZ) {
static constexpr int maxTotalBlockdim = 1024;
static constexpr int maxBlockdimx = 1024;
static constexpr int maxBlockdimy = 1024;
static constexpr int maxBlockdimz = 64;
static constexpr int maxTotalGriddim = 2147483647;
static constexpr int maxGriddimx = 2147483647;
static constexpr int maxGriddimy = 65535;
static constexpr int maxGriddimz = 65535;
if ((blockDimX.value_or(1) * blockDimY.value_or(1) * blockDimZ.value_or(1)) >
maxTotalBlockdim ||
(gridDimX.value_or(1) * gridDimY.value_or(1) * gridDimZ.value_or(1)) >
maxTotalGriddim ||
blockDimX.value_or(1) > maxBlockdimx ||
blockDimY.value_or(1) > maxBlockdimy ||
blockDimZ.value_or(1) > maxBlockdimz ||
gridDimY.value_or(1) > maxGriddimy ||
gridDimZ.value_or(1) > maxGriddimz ||
gridDimX.value_or(1) > maxGriddimx) {
return transformOp.emitSilenceableError()
<< "Trying to launch a GPU kernel with gridDim = ("
<< gridDimX.value_or(1) << ", " << gridDimY.value_or(1) << ", "
<< gridDimZ.value_or(1) << ") blockDim = (" << blockDimX.value_or(1)
<< ", " << blockDimY.value_or(1) << ", " << blockDimZ.value_or(1)
<< "). It is larger than the limits.";
}
return DiagnosedSilenceableFailure::success();
}
/// Creates an empty-body gpu::LaunchOp using the provided kernel settings and
/// put a terminator within.
static DiagnosedSilenceableFailure
createGpuLaunch(RewriterBase &rewriter, Location loc,
TransformOpInterface transformOp, LaunchOp &launchOp,
Optional<int64_t> gridDimX = std::nullopt,
Optional<int64_t> gridDimY = std::nullopt,
Optional<int64_t> gridDimZ = std::nullopt,
Optional<int64_t> blockDimX = std::nullopt,
Optional<int64_t> blockDimY = std::nullopt,
Optional<int64_t> blockDimZ = std::nullopt) {
DiagnosedSilenceableFailure diag =
checkGpuLimits(transformOp, gridDimX, gridDimY, gridDimZ, blockDimX,
blockDimY, blockDimZ);
if (!diag.succeeded())
return diag;
auto createConst = [&](int dim) {
return rewriter.create<arith::ConstantIndexOp>(loc, dim);
};
OpBuilder::InsertionGuard guard(rewriter);
Value one = createConst(1);
Value gridSizeX = gridDimX.has_value() ? createConst(gridDimX.value()) : one;
Value gridSizeY = gridDimY.has_value() ? createConst(gridDimY.value()) : one;
Value gridSizeZ = gridDimZ.has_value() ? createConst(gridDimZ.value()) : one;
Value blkSizeX = blockDimX.has_value() ? createConst(blockDimX.value()) : one;
Value blkSizeY = blockDimY.has_value() ? createConst(blockDimY.value()) : one;
Value blkSizeZ = blockDimZ.has_value() ? createConst(blockDimZ.value()) : one;
launchOp = rewriter.create<LaunchOp>(loc, gridSizeX, gridSizeY, gridSizeZ,
blkSizeX, blkSizeY, blkSizeZ);
rewriter.setInsertionPointToEnd(&launchOp.getBody().front());
rewriter.create<TerminatorOp>(loc);
return DiagnosedSilenceableFailure(success());
}
/// Alter kernel configuration of the given kernel.
static DiagnosedSilenceableFailure
alterGpuLaunch(TrivialPatternRewriter &rewriter, LaunchOp gpuLaunch,
TransformOpInterface transformOp,
Optional<int64_t> gridDimX = std::nullopt,
Optional<int64_t> gridDimY = std::nullopt,
Optional<int64_t> gridDimZ = std::nullopt,
Optional<int64_t> blockDimX = std::nullopt,
Optional<int64_t> blockDimY = std::nullopt,
Optional<int64_t> blockDimZ = std::nullopt) {
DiagnosedSilenceableFailure diag =
checkGpuLimits(transformOp, gridDimX, gridDimY, gridDimZ, blockDimX,
blockDimY, blockDimZ);
if (!diag.succeeded())
return diag;
KernelDim3 currentBlockdim = gpuLaunch.getBlockSizeOperandValues();
OpBuilder::InsertionGuard guard(rewriter);
rewriter.setInsertionPointAfterValue(currentBlockdim.x);
auto createConstValue = [&](int dim) {
return rewriter.create<arith::ConstantIndexOp>(currentBlockdim.x.getLoc(),
dim);
};
if (gridDimX.has_value())
gpuLaunch.getGridSizeXMutable().assign(createConstValue(gridDimX.value()));
if (gridDimY.has_value())
gpuLaunch.getGridSizeYMutable().assign(createConstValue(gridDimY.value()));
if (gridDimZ.has_value())
gpuLaunch.getGridSizeZMutable().assign(createConstValue(gridDimZ.value()));
if (blockDimX.has_value())
gpuLaunch.getBlockSizeXMutable().assign(
createConstValue(blockDimX.value()));
if (blockDimY.has_value())
gpuLaunch.getBlockSizeYMutable().assign(
createConstValue(blockDimY.value()));
if (blockDimZ.has_value())
gpuLaunch.getBlockSizeZMutable().assign(
createConstValue(blockDimZ.value()));
return DiagnosedSilenceableFailure::success();
}
//===----------------------------------------------------------------------===//
// MapForeachToBlocks
//===----------------------------------------------------------------------===//
DiagnosedSilenceableFailure mlir::transform::gpu::mapForeachToBlocksImpl(
RewriterBase &rewriter, scf::ForeachThreadOp foreachThreadOp,
function_ref<void(RewriterBase &, scf::ForeachThreadOp,
SmallVectorImpl<Value> &)>
blockIdGenerator,
SmallVectorImpl<int64_t> &gridDims, TransformOpInterface transformOp,
const ArrayRef<DeviceMappingAttrInterface> &mappingAttributes) {
// Step 0. Target-specific verifications. There is no good place to anchor
// those right now: the ForeachThreadOp is target-independent and the
// transform op does not apply to individual ForeachThreadOp.
Location loc = foreachThreadOp->getLoc();
if (foreachThreadOp.getNumResults() > 0)
return transformOp.emitSilenceableError()
<< "only bufferized scf.foreach_thread lowers to "
"gpu.block_id";
if (foreachThreadOp.getNumThreads().size() > 3)
return transformOp.emitSilenceableError()
<< "scf.foreach_thread with rank > 3 does not lower to "
"gpu.block_id";
if (llvm::any_of(foreachThreadOp.getNumThreads(), [](Value v) {
return !v.getDefiningOp<arith::ConstantIndexOp>();
})) {
return transformOp.emitSilenceableError()
<< "unsupported dynamic griddim size";
}
SmallVector<Attribute> blockMapping =
llvm::to_vector(foreachThreadOp.getMapping()->getValue());
// Step 1. Complete the blockMapping to a full mapping (with 1s) if necessary.
SmallVector<Value> numBlocks =
llvm::to_vector(foreachThreadOp.getNumThreads());
// Ensure we have 3 block sizes, one for each id.
Value one;
for (auto attr : mappingAttributes) {
if (std::find(blockMapping.begin(), blockMapping.end(), attr) ==
blockMapping.end()) {
blockMapping.push_back(attr);
one = one ? one : rewriter.create<arith::ConstantIndexOp>(loc, 1);
numBlocks.push_back(one);
}
}
// Step 2. sort the values by the corresponding DeviceMappingAttrInterface.
auto comparator = [&](DeviceMappingAttrInterface a,
DeviceMappingAttrInterface b) -> bool {
return a.getMappingId() < b.getMappingId();
};
SmallVector<Value> gridDimValues = scf::ForeachThreadOp::getValuesSortedByKey(
blockMapping, numBlocks, comparator);
for (Value v : gridDimValues)
gridDims.push_back(v.getDefiningOp<arith::ConstantIndexOp>().value());
// Step 3. Generate the blockIds using the provided generator and map the
// induction variables to the newly created ops.
SmallVector<Value> blockOps;
blockIdGenerator(rewriter, foreachThreadOp, blockOps);
BlockAndValueMapping bvm;
for (auto [blockIdx, blockDim] :
llvm::zip(foreachThreadOp.getThreadIndices(), blockMapping)) {
bvm.map(blockIdx,
blockOps[static_cast<int64_t>(
blockDim.cast<DeviceMappingAttrInterface>().getMappingId())]);
}
// Step 4. Move the body of foreachThreadOp.
// Erase the terminator first, it will not be used since we are on buffers.
rewriter.eraseOp(foreachThreadOp.getTerminator());
Block *targetBlock = foreachThreadOp->getBlock();
Block::iterator insertionPoint = Block::iterator(foreachThreadOp);
Block &sourceBlock = foreachThreadOp.getRegion().front();
targetBlock->getOperations().splice(insertionPoint,
sourceBlock.getOperations());
// Step 5. RAUW thread indices to thread ops.
for (Value loopIndex : foreachThreadOp.getThreadIndices()) {
Value blockIdx = bvm.lookup(loopIndex);
rewriter.replaceAllUsesWith(loopIndex, blockIdx);
}
// Step 6. Erase old op.
rewriter.eraseOp(foreachThreadOp);
return DiagnosedSilenceableFailure::success();
}
DiagnosedSilenceableFailure mlir::transform::gpu::findTopLevelForeachThreadOp(
Operation *target, scf::ForeachThreadOp &topLevelForeachThreadOp,
TransformOpInterface transformOp) {
auto walkResult = target->walk([&](scf::ForeachThreadOp foreachThreadOp) {
if (foreachThreadOp->getParentOfType<scf::ForeachThreadOp>())
return WalkResult::advance();
if (topLevelForeachThreadOp)
// TODO: Handle multiple foreach if there is no dependences between them
return WalkResult::interrupt();
topLevelForeachThreadOp = foreachThreadOp;
return WalkResult::advance();
});
if (walkResult.wasInterrupted())
return transformOp.emitSilenceableError()
<< "could not find a unique topLevel scf.foreach_thread";
return DiagnosedSilenceableFailure::success();
}
/// This is a helper that is only used in
/// rewriteTopLevelForeachThreadToGpuBlocks. It generates GPU dialects
/// block_id.
static void generateGpuBlockIds(RewriterBase &rewriter,
scf::ForeachThreadOp foreachOp,
SmallVectorImpl<Value> &blockOps) {
Location loc = foreachOp->getLoc();
OpBuilder::InsertionGuard guard(rewriter);
rewriter.setInsertionPoint(foreachOp);
IndexType indexType = rewriter.getIndexType();
blockOps = SmallVector<Value>{
rewriter.create<BlockIdOp>(loc, indexType, Dimension::x),
rewriter.create<BlockIdOp>(loc, indexType, Dimension::y),
rewriter.create<BlockIdOp>(loc, indexType, Dimension::z)};
}
DiagnosedSilenceableFailure
transform::MapForeachToBlocks::applyToOne(Operation *target,
SmallVectorImpl<Operation *> &results,
transform::TransformState &state) {
LaunchOp gpuLaunch = dyn_cast<LaunchOp>(target);
TrivialPatternRewriter rewriter(getContext());
auto transformOp = cast<TransformOpInterface>(getOperation());
if (!getGenerateGpuLaunch() && !gpuLaunch) {
results.assign({target});
DiagnosedSilenceableFailure diag =
emitSilenceableError()
<< "Given target is not gpu.launch, set `generate_gpu_launch` "
"attribute";
diag.attachNote(target->getLoc()) << "when applied to this payload op";
return diag;
}
scf::ForeachThreadOp topLevelForeachThreadOp;
DiagnosedSilenceableFailure diag =
mlir::transform::gpu::findTopLevelForeachThreadOp(
target, topLevelForeachThreadOp, transformOp);
if (!diag.succeeded()) {
results.assign({target});
diag.attachNote(target->getLoc()) << "when applied to this payload op";
return diag;
}
OpBuilder::InsertionGuard guard(rewriter);
rewriter.setInsertionPoint(topLevelForeachThreadOp);
// Generate gpu launch here and move the foreach_thread inside
if (getGenerateGpuLaunch()) {
DiagnosedSilenceableFailure diag =
createGpuLaunch(rewriter, target->getLoc(), transformOp, gpuLaunch);
if (!diag.succeeded()) {
results.assign({target});
return diag;
}
rewriter.setInsertionPointToStart(&gpuLaunch.getBody().front());
Operation *newForeachThreadOp = rewriter.clone(*topLevelForeachThreadOp);
rewriter.eraseOp(topLevelForeachThreadOp);
topLevelForeachThreadOp = cast<scf::ForeachThreadOp>(newForeachThreadOp);
}
SmallVector<int64_t> gridDim = extractFromI64ArrayAttr(getGridDim());
SmallVector<DeviceMappingAttrInterface> blockMappingAttributes = {
GPUBlockMappingAttr::get(getContext(), Blocks::DimX),
GPUBlockMappingAttr::get(getContext(), Blocks::DimY),
GPUBlockMappingAttr::get(getContext(), Blocks::DimZ)};
diag = checkAttributeType(blockMappingAttributes,
topLevelForeachThreadOp.getMapping(), transformOp);
if (diag.succeeded())
diag = mlir::transform::gpu::mapForeachToBlocksImpl(
rewriter, topLevelForeachThreadOp, generateGpuBlockIds, gridDim,
transformOp, blockMappingAttributes);
if (diag.succeeded()) {
diag = alterGpuLaunch(rewriter, gpuLaunch,
cast<TransformOpInterface>(getOperation()),
gridDim[0], gridDim[1], gridDim[2]);
}
results.assign({gpuLaunch});
return diag;
}
//===----------------------------------------------------------------------===//
// MapNestedForeachToThreads
//===----------------------------------------------------------------------===//
/// Searches `scf.foreach_thread` ops nested under `target` and maps each such
/// op to GPU threads. Mapping is one-to-one and the induction variables of
/// `scf.foreach_thread` are rewritten to gpu.thread_id according to the
/// thread_dim_apping attribute. Sibling `scf.foreach_thread` are supported in
/// which case, the union of the number of threads is computed and may result
/// in predication. Dynamic, `scf.foreach_thread` trip counts are currently
/// not supported. Dynamic block dim sizes are currently not supported.
static DiagnosedSilenceableFailure rewriteOneForeachThreadToGpuThreads(
RewriterBase &rewriter, scf::ForeachThreadOp foreachThreadOp,
const SmallVectorImpl<int64_t> &globalBlockDims, bool syncAfterDistribute,
llvm::Optional<TransformOpInterface> transformOp,
const ArrayRef<DeviceMappingAttrInterface> &threadMappingAttributes) {
// Step 0. Target-specific verifications. There is no good place to anchor
// those right now: the ForeachThreadOp is target-independent and the
// transform op does not apply to individual ForeachThreadOp.
auto failureHelper =
[&](const Twine &message) -> DiagnosedSilenceableFailure {
if (transformOp.has_value()) {
return transformOp->emitSilenceableError() << message;
}
return emitDefiniteFailure(foreachThreadOp, message);
};
Location loc = foreachThreadOp->getLoc();
if (foreachThreadOp.getNumResults() > 0)
return failureHelper(
"only bufferized scf.foreach_thread lowers to gpu.thread_id");
if (foreachThreadOp.getNumThreads().size() > 3)
return failureHelper(
"scf.foreach_thread with rank > 3 does not lower to gpu.thread_id");
if (llvm::any_of(foreachThreadOp.getNumThreads(), [](Value v) {
return !v.getDefiningOp<arith::ConstantIndexOp>();
})) {
return failureHelper("unsupported dynamic blockdim size");
}
if (!foreachThreadOp.getMapping().has_value())
return failureHelper("mapping must be present");
SmallVector<Attribute> threadMapping =
llvm::to_vector(foreachThreadOp.getMapping()->getValue());
// Step 1. Complete the threadMapping to a full mapping (with 1s) if
// necessary.
SmallVector<Value> numThreads =
llvm::to_vector(foreachThreadOp.getNumThreads());
// Ensure we have 3 block sizes, one for each id.
Value one;
for (auto attr : threadMappingAttributes) {
if (std::find(threadMapping.begin(), threadMapping.end(), attr) ==
threadMapping.end()) {
threadMapping.push_back(attr);
one = one ? one : rewriter.create<arith::ConstantIndexOp>(loc, 1);
numThreads.push_back(one);
}
}
// Step 2. sort the values by the corresponding DeviceMappingAttrInterface.
auto comparator = [&](DeviceMappingAttrInterface a,
DeviceMappingAttrInterface b) -> bool {
return a.getMappingId() < b.getMappingId();
};
SmallVector<Value> blockDimValues =
scf::ForeachThreadOp::getValuesSortedByKey(threadMapping, numThreads,
comparator);
SmallVector<int64_t> blockDims =
llvm::to_vector(llvm::map_range(blockDimValues, [](Value v) {
return v.getDefiningOp<arith::ConstantIndexOp>().value();
}));
// Step 3. Create the gpu.thread ops and map the induction variables to the
// newly created ops.
IndexType indexType = rewriter.getIndexType();
SmallVector<Value> threadOps{
rewriter.create<ThreadIdOp>(loc, indexType, Dimension::x),
rewriter.create<ThreadIdOp>(loc, indexType, Dimension::y),
rewriter.create<ThreadIdOp>(loc, indexType, Dimension::z)};
BlockAndValueMapping bvm;
for (auto [blockIdx, blockDim] :
llvm::zip(foreachThreadOp.getThreadIndices(), threadMapping)) {
bvm.map(
blockIdx,
threadOps[blockDim.cast<DeviceMappingAttrInterface>().getMappingId()]);
}
// Step 4. Maybe create conditionals to predicate the region.
Value predicate;
for (auto [threadId, blockDim, globalBlockDim] :
llvm::zip(threadOps, blockDims, globalBlockDims)) {
if (blockDim > globalBlockDim) {
return failureHelper(
"The requested GPU threads are fewer than the number of loop trip "
"counts. Try to tile scf.foreach_thread before mapping or set "
"small blockDim.");
}
if (blockDim == globalBlockDim)
continue;
Value blockIdx = rewriter.create<arith::ConstantIndexOp>(loc, blockDim);
Value tmpPredicate = rewriter.create<arith::CmpIOp>(
loc, arith::CmpIPredicate::ult, threadId, blockIdx);
predicate =
predicate ? rewriter.create<arith::AndIOp>(loc, predicate, tmpPredicate)
: tmpPredicate;
}
// Step 5. Move the body of foreachThreadOp.
// Erase the terminator first, it will not be used.
rewriter.eraseOp(foreachThreadOp.getTerminator());
Block *targetBlock;
Block::iterator insertionPoint;
if (predicate) {
// Step 5.a. If predicated, move at the beginning.
auto ifOp =
rewriter.create<scf::IfOp>(loc, predicate, /*withElseRegion=*/false);
targetBlock = ifOp.thenBlock();
insertionPoint = ifOp.thenBlock()->begin();
} else {
// Step 5.b. Otherwise, move inline just before foreachThreadOp.
targetBlock = foreachThreadOp->getBlock();
insertionPoint = Block::iterator(foreachThreadOp);
}
Block &sourceBlock = foreachThreadOp.getRegion().front();
targetBlock->getOperations().splice(insertionPoint,
sourceBlock.getOperations());
// Step 6. RAUW thread indices to thread ops.
for (Value loopIndex : foreachThreadOp.getThreadIndices()) {
Value threadIdx = bvm.lookup(loopIndex);
rewriter.replaceAllUsesWith(loopIndex, threadIdx);
}
// Step 7. syncthreads.
// TODO: Need warpsync
if (syncAfterDistribute)
rewriter.create<BarrierOp>(loc);
// Step 8. Erase old op.
rewriter.eraseOp(foreachThreadOp);
return DiagnosedSilenceableFailure::success();
}
DiagnosedSilenceableFailure mlir::transform::gpu::mapNestedForeachToThreadsImpl(
RewriterBase &rewriter, Operation *target,
const SmallVectorImpl<int64_t> &blockDim, bool syncAfterDistribute,
llvm::Optional<TransformOpInterface> transformOp,
const ArrayRef<DeviceMappingAttrInterface> &threadMappingAttributes) {
DiagnosedSilenceableFailure diag = DiagnosedSilenceableFailure::success();
target->walk([&](scf::ForeachThreadOp foreachThreadOp) {
diag = checkAttributeType(threadMappingAttributes,
foreachThreadOp.getMapping(), transformOp);
if (diag.succeeded()) {
rewriter.setInsertionPoint(foreachThreadOp);
diag = rewriteOneForeachThreadToGpuThreads(
rewriter, foreachThreadOp, blockDim, syncAfterDistribute, transformOp,
threadMappingAttributes);
}
return diag.succeeded() ? WalkResult::advance() : WalkResult::interrupt();
});
return diag;
}
DiagnosedSilenceableFailure transform::MapNestedForeachToThreads::applyToOne(
::mlir::Operation *target,
::llvm::SmallVectorImpl<::mlir::Operation *> &results,
::mlir::transform::TransformState &state) {
LaunchOp gpuLaunch = dyn_cast<LaunchOp>(target);
auto transformOp = cast<TransformOpInterface>(getOperation());
if (!gpuLaunch) {
results.assign({target});
return emitSilenceableError() << "Given target is not gpu.launch";
}
SmallVector<int64_t> blockDim = extractFromI64ArrayAttr(getBlockDim());
blockDim.resize(/*size=*/3, /*value=*/1);
DiagnosedSilenceableFailure diag =
checkGpuLimits(transformOp, std::nullopt, std::nullopt, std::nullopt,
blockDim[0], blockDim[1], blockDim[2]);
if (diag.isSilenceableFailure()) {
results.assign({target});
diag.attachNote(getLoc()) << getBlockDimAttrName() << " is very large";
return diag;
}
MLIRContext *ctx = getContext();
TrivialPatternRewriter rewriter(ctx);
rewriter.setInsertionPoint(target);
SmallVector<DeviceMappingAttrInterface> threadMappingAttributes = {
GPUThreadMappingAttr::get(ctx, Threads::DimX),
GPUThreadMappingAttr::get(ctx, Threads::DimY),
GPUThreadMappingAttr::get(ctx, Threads::DimZ)};
diag = mlir::transform::gpu::mapNestedForeachToThreadsImpl(
rewriter, target, blockDim, getSyncAfterDistribute(), transformOp,
threadMappingAttributes);
if (diag.succeeded()) {
diag = alterGpuLaunch(rewriter, gpuLaunch, transformOp, std::nullopt,
std::nullopt, std::nullopt, blockDim[0], blockDim[1],
blockDim[2]);
}
results.assign({gpuLaunch});
return diag;
}
//===----------------------------------------------------------------------===//
// Transform op registration
//===----------------------------------------------------------------------===//
namespace {
/// Registers new ops and declares PDL as dependent dialect since the
/// additional ops are using PDL types for operands and results.
class GPUTransformDialectExtension
: public transform::TransformDialectExtension<
GPUTransformDialectExtension> {
public:
GPUTransformDialectExtension() {
declareDependentDialect<pdl::PDLDialect>();
declareGeneratedDialect<scf::SCFDialect>();
declareGeneratedDialect<arith::ArithDialect>();
declareGeneratedDialect<GPUDialect>();
registerTransformOps<
#define GET_OP_LIST
#include "mlir/Dialect/GPU/TransformOps/GPUTransformOps.cpp.inc"
>();
}
};
} // namespace
#define GET_OP_CLASSES
#include "mlir/Dialect/GPU/TransformOps/GPUTransformOps.cpp.inc"
void mlir::gpu::registerTransformDialectExtension(DialectRegistry &registry) {
registry.addExtensions<GPUTransformDialectExtension>();
}