GPUDialect.cpp

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//===- GPUDialect.cpp - MLIR Dialect for GPU Kernels implementation -------===//
//
// 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 the GPU kernel-related dialect and its operations.
//
//===----------------------------------------------------------------------===//
 
#include "mlir/Dialect/GPU/IR/GPUDialect.h"
 
#include "mlir/Bytecode/Encoding.h"
#include "mlir/Dialect/Arith/IR/Arith.h"
#include "mlir/Dialect/Bufferization/IR/BufferDeallocationOpInterface.h"
#include "mlir/Dialect/Math/IR/Math.h"
#include "mlir/Dialect/MemRef/IR/MemRef.h"
#include "mlir/Dialect/Utils/VerificationUtils.h"
#include "mlir/IR/Attributes.h"
#include "mlir/IR/Builders.h"
#include "mlir/IR/BuiltinAttributes.h"
#include "mlir/IR/BuiltinOps.h"
#include "mlir/IR/BuiltinTypes.h"
#include "mlir/IR/Diagnostics.h"
#include "mlir/IR/DialectImplementation.h"
#include "mlir/IR/Matchers.h"
#include "mlir/IR/OpImplementation.h"
#include "mlir/IR/PatternMatch.h"
#include "mlir/IR/SymbolTable.h"
#include "mlir/IR/TypeUtilities.h"
#include "mlir/Interfaces/FunctionImplementation.h"
#include "mlir/Interfaces/SideEffectInterfaces.h"
#include "mlir/Interfaces/ValueBoundsOpInterface.h"
#include "mlir/Transforms/InliningUtils.h"
#include "llvm/ADT/STLExtras.h"
#include "llvm/ADT/TypeSwitch.h"
#include "llvm/Support/ErrorHandling.h"
#include "llvm/Support/FormatVariadic.h"
#include "llvm/Support/InterleavedRange.h"
#include <cassert>
#include <numeric>
#include <optional>
 
using namespace mlir;
using namespace mlir::gpu;
 
#include "mlir/Dialect/GPU/IR/GPUOpsDialect.cpp.inc"
 
namespace {
// Attribute storage definitions live in MLIRGPUBase. Keep interface metadata
// here: some attribute interfaces build GPU/Arith/Math IR, and their models
// belong with the operation implementation rather than the representations.
template <typename... Attrs>
void registerAttributeMetadata(
    Dialect &dialect,
    function_ref<void(TypeID, AbstractAttribute &&)> addAttribute) {
  (addAttribute(Attrs::getTypeID(), AbstractAttribute::get<Attrs>(dialect)),
   ...);
}
 
struct GPUDialectBytecodeInterface : BytecodeDialectInterface {
  using BytecodeDialectInterface::BytecodeDialectInterface;
 
  void writeVersion(DialectBytecodeWriter &writer) const override {
    writer.writeVarInt(1);
  }
 
  std::unique_ptr<DialectVersion>
  readVersion(DialectBytecodeReader &reader) const override {
    uint64_t version;
    if (failed(reader.readVarInt(version)))
      return nullptr;
    if (version != 1) {
      reader.emitError("unsupported gpu dialect bytecode version");
      return nullptr;
    }
    return std::make_unique<DialectVersion>();
  }
};
} // namespace
 
int64_t GPUMappingMaskAttr::getMaxNumPhysicalIds() const { return 64; }
 
///                 8       4       0
/// Example mask  : 0 0 0 1 1 0 1 0 0
///
/// Active physical (resp. logical) is  2 (0), 4 (1) and 5 (2).
/// Logical id for e.g. 5 (2) constructs filter (1 << 5 - 1).
///
/// Example mask  : 0 0 0 1 1 0 1 0 0
/// Example filter: 0 0 0 0 1 1 1 1 1
/// Intersection  : 0 0 0 0 1 0 1 0 0
/// PopCnt        : 2
Value GPUMappingMaskAttr::createLogicalLinearMappingId(
    OpBuilder &b, Value physicalLinearMappingId) const {
  Location loc = physicalLinearMappingId.getLoc();
  Value mask =
      arith::ConstantOp::create(b, loc, b.getI64IntegerAttr(getMask()));
  Value one = arith::ConstantOp::create(b, loc, b.getI64IntegerAttr(1));
  Value filter = arith::ShLIOp::create(b, loc, one, physicalLinearMappingId);
  filter = arith::SubIOp::create(b, loc, filter, one);
  Value filteredId = arith::AndIOp::create(b, loc, mask, filter);
  return math::CtPopOp::create(b, loc, filteredId);
}
 
///                 8       4       0
/// Example mask  : 0 0 0 1 1 0 1 0 0
///
/// Active physical (resp. logical) is  2 (0), 4 (1) and 5 (2).
/// Logical id for e.g. 5 (2) constructs filter (1 << 5).
///
/// Example mask  : 0 0 0 1 1 0 1 0 0
/// Example filter: 0 0 0 1 0 0 0 0 0
/// Intersection  : 0 0 0 1 0 0 0 0 0
/// Cmp           : 1
Value GPUMappingMaskAttr::createIsActiveIdPredicate(
    OpBuilder &b, Value physicalLinearMappingId) const {
  Location loc = physicalLinearMappingId.getLoc();
  Value mask =
      arith::ConstantOp::create(b, loc, b.getI64IntegerAttr(getMask()));
  Value one = arith::ConstantOp::create(b, loc, b.getI64IntegerAttr(1));
  Value filter = arith::ShLIOp::create(b, loc, one, physicalLinearMappingId);
  Value filtered = arith::AndIOp::create(b, loc, mask, filter);
  Value zero = arith::ConstantOp::create(b, loc, b.getI64IntegerAttr(0));
  return arith::CmpIOp::create(b, loc, arith::CmpIPredicate::ne, filtered,
                               zero);
}
 
bool GPUDialect::isKernel(Operation *op) {
  if (auto gpuFunc = dyn_cast<GPUFuncOp>(op))
    return gpuFunc.isKernel();
  return static_cast<bool>(
      op->getDiscardableAttrOfType<UnitAttr>(getKernelFuncAttrName()));
}
 
namespace {
/// This class defines the interface for handling inlining with gpu
/// operations.
struct GPUInlinerInterface : public DialectInlinerInterface {
  using DialectInlinerInterface::DialectInlinerInterface;
 
  /// All gpu dialect ops can be inlined.
  bool isLegalToInline(Operation *, Region *, bool, IRMapping &) const final {
    return true;
  }
};
} // namespace
 
void GPUDialect::initialize() {
  addInterfaces<GPUDialectBytecodeInterface>();
  addTypes<AsyncTokenType>();
  addTypes<MMAMatrixType>();
  addTypes<NamedBarrierType>();
  addTypes<SparseDnTensorHandleType>();
  addTypes<SparseSpMatHandleType>();
  addTypes<SparseSpGEMMOpHandleType>();
  addOperations<
#define GET_OP_LIST
#include "mlir/Dialect/GPU/IR/GPUOps.cpp.inc"
      >();
  // Match addAttributes while keeping the storage and interface instantiations
  // in their respective implementation libraries.
  registerAttributeMetadata<
#define GET_ATTRDEF_LIST
#include "mlir/Dialect/GPU/IR/GPUOpsAttributes.cpp.inc"
      >(*this, [this](TypeID id, AbstractAttribute &&attribute) {
    addAttribute(id, std::move(attribute));
  });
  gpu::detail::registerAttributeStorage(getContext());
  addInterfaces<GPUInlinerInterface>();
  declarePromisedInterface<bufferization::BufferDeallocationOpInterface,
                           TerminatorOp>();
  declarePromisedInterfaces<ValueBoundsOpInterface, ClusterDimOp,
                            ClusterDimBlocksOp, ClusterIdOp, ClusterBlockIdOp,
                            BlockDimOp, BlockIdOp, GridDimOp, ThreadIdOp,
                            LaneIdOp, SubgroupIdOp, GlobalIdOp, NumSubgroupsOp,
                            SubgroupSizeOp, LaunchOp, SubgroupBroadcastOp>();
  declarePromisedInterfaces<memref::IndexedAccessOpInterface,
                            SubgroupMmaLoadMatrixOp,
                            SubgroupMmaStoreMatrixOp>();
}
 
static std::string getSparseHandleKeyword(SparseHandleKind kind) {
  switch (kind) {
  case SparseHandleKind::DnTensor:
    return "sparse.dntensor_handle";
  case SparseHandleKind::SpMat:
    return "sparse.spmat_handle";
  case SparseHandleKind::SpGEMMOp:
    return "sparse.spgemmop_handle";
  }
  llvm_unreachable("unknown sparse handle kind");
  return "";
}
 
Type GPUDialect::parseType(DialectAsmParser &parser) const {
  // Parse the main keyword for the type.
  StringRef keyword;
  if (parser.parseKeyword(&keyword))
    return Type();
  MLIRContext *context = getContext();
 
  // Handle 'async token' types.
  if (keyword == "async.token")
    return AsyncTokenType::get(context);
 
  if (keyword == "mma_matrix") {
    SMLoc beginLoc = parser.getNameLoc();
 
    // Parse '<'.
    if (parser.parseLess())
      return nullptr;
 
    // Parse the size and elementType.
    SmallVector<int64_t> shape;
    Type elementType;
    if (parser.parseDimensionList(shape, /*allowDynamic=*/false) ||
        parser.parseType(elementType))
      return nullptr;
 
    // Parse ','
    if (parser.parseComma())
      return nullptr;
 
    // Parse operand.
    std::string operand;
    if (failed(parser.parseOptionalString(&operand)))
      return nullptr;
 
    // Parse '>'.
    if (parser.parseGreater())
      return nullptr;
 
    return MMAMatrixType::getChecked(mlir::detail::getDefaultDiagnosticEmitFn(
                                         parser.getEncodedSourceLoc(beginLoc)),
                                     shape, elementType, operand);
  }
 
  if (keyword == "named_barrier")
    return NamedBarrierType::get(context);
 
  if (keyword == getSparseHandleKeyword(SparseHandleKind::DnTensor))
    return SparseDnTensorHandleType::get(context);
  if (keyword == getSparseHandleKeyword(SparseHandleKind::SpMat))
    return SparseSpMatHandleType::get(context);
  if (keyword == getSparseHandleKeyword(SparseHandleKind::SpGEMMOp))
    return SparseSpGEMMOpHandleType::get(context);
 
  parser.emitError(parser.getNameLoc(), "unknown gpu type: " + keyword);
  return Type();
}
// TODO: print refined type here. Notice that should be corresponding to the
// parser
void GPUDialect::printType(Type type, DialectAsmPrinter &os) const {
  TypeSwitch<Type>(type)
      .Case<AsyncTokenType>([&](Type) { os << "async.token"; })
      .Case<NamedBarrierType>([&](Type) { os << "named_barrier"; })
      .Case<SparseDnTensorHandleType>([&](Type) {
        os << getSparseHandleKeyword(SparseHandleKind::DnTensor);
      })
      .Case<SparseSpMatHandleType>(
          [&](Type) { os << getSparseHandleKeyword(SparseHandleKind::SpMat); })
      .Case<SparseSpGEMMOpHandleType>([&](Type) {
        os << getSparseHandleKeyword(SparseHandleKind::SpGEMMOp);
      })
      .Case([&](MMAMatrixType fragTy) {
        os << "mma_matrix<";
        auto shape = fragTy.getShape();
        for (auto dim = shape.begin(), e = shape.end() - 1; dim != e; ++dim)
          os << *dim << 'x';
        os << shape.back() << 'x' << fragTy.getElementType();
        os << ", \"" << fragTy.getOperand() << "\"" << '>';
      })
      .DefaultUnreachable("unexpected 'gpu' type kind");
}
 
static LogicalResult verifyKnownLaunchSizeAttr(Operation *op,
                                               NamedAttribute attr) {
  auto array = dyn_cast<DenseI32ArrayAttr>(attr.getValue());
  if (!array)
    return op->emitOpError(Twine(attr.getName()) +
                           " must be a dense i32 array");
  if (array.size() != 3)
    return op->emitOpError(Twine(attr.getName()) +
                           " must contain exactly 3 elements");
  return success();
}
 
LogicalResult GPUDialect::verifyOperationAttribute(Operation *op,
                                                   NamedAttribute attr) {
  if (attr.getName() == getKnownBlockSizeAttrHelper().getName())
    return verifyKnownLaunchSizeAttr(op, attr);
  if (attr.getName() == getKnownGridSizeAttrHelper().getName())
    return verifyKnownLaunchSizeAttr(op, attr);
  if (attr.getName() == getKnownClusterSizeAttrHelper().getName())
    return verifyKnownLaunchSizeAttr(op, attr);
  if (!llvm::isa<UnitAttr>(attr.getValue()) ||
      attr.getName() != getContainerModuleAttrName())
    return success();
 
  auto module = dyn_cast<ModuleOp>(op);
  if (!module)
    return op->emitError("expected '")
           << getContainerModuleAttrName() << "' attribute to be attached to '"
           << ModuleOp::getOperationName() << '\'';
  return success();
}
 
/// Parses an optional list of async operands with an optional leading keyword.
/// (`async`)? (`[` ssa-id-list `]`)?
///
/// This method is used by the tablegen assembly format for async ops as well.
static ParseResult parseAsyncDependencies(
    OpAsmParser &parser, Type &asyncTokenType,
    SmallVectorImpl<OpAsmParser::UnresolvedOperand> &asyncDependencies) {
  auto loc = parser.getCurrentLocation();
  if (succeeded(parser.parseOptionalKeyword("async"))) {
    if (parser.getNumResults() == 0)
      return parser.emitError(loc, "needs to be named when marked 'async'");
    asyncTokenType = parser.getBuilder().getType<AsyncTokenType>();
  }
  return parser.parseOperandList(asyncDependencies,
                                 OpAsmParser::Delimiter::OptionalSquare);
}
 
/// Prints optional async dependencies with its leading keyword.
///   (`async`)? (`[` ssa-id-list `]`)?
// Used by the tablegen assembly format for several async ops.
static void printAsyncDependencies(OpAsmPrinter &printer, Operation *op,
                                   Type asyncTokenType,
                                   OperandRange asyncDependencies) {
  if (asyncTokenType)
    printer << "async";
  if (asyncDependencies.empty())
    return;
  if (asyncTokenType)
    printer << ' ';
  printer << llvm::interleaved_array(asyncDependencies);
}
 
// GPU Memory attributions functions shared by LaunchOp and GPUFuncOp.
/// Parses a GPU function memory attribution.
///
/// memory-attribution ::= (`workgroup` `(` ssa-id-and-type-list `)`)?
///                        (`private` `(` ssa-id-and-type-list `)`)?
///
/// Note that this function parses only one of the two similar parts, with the
/// keyword provided as argument.
static ParseResult
parseAttributions(OpAsmParser &parser, StringRef keyword,
                  SmallVectorImpl<OpAsmParser::Argument> &args) {
  // If we could not parse the keyword, just assume empty list and succeed.
  if (failed(parser.parseOptionalKeyword(keyword)))
    return success();
 
  return parser.parseArgumentList(args, OpAsmParser::Delimiter::Paren,
                                  /*allowType=*/true);
}
 
static void printAttributions(OpAsmPrinter &p, StringRef keyword,
                              ArrayRef<BlockArgument> values,
                              ArrayAttr attributes = {}) {
  if (values.empty())
    return;
 
  p << ' ' << keyword << '(';
  llvm::interleaveComma(
      llvm::enumerate(values), p, [&p, attributes](auto pair) {
        BlockArgument v = pair.value();
        p << v << " : " << v.getType();
 
        size_t attributionIndex = pair.index();
        DictionaryAttr attrs;
        if (attributes && attributionIndex < attributes.size())
          attrs = llvm::cast<DictionaryAttr>(attributes[attributionIndex]);
        if (attrs)
          p.printOptionalAttrDict(attrs.getValue());
      });
  p << ')';
}
 
/// Verifies a GPU function memory attribution.
static LogicalResult verifyAttributions(Operation *op,
                                        ArrayRef<BlockArgument> attributions,
                                        gpu::AddressSpace memorySpace) {
  for (Value v : attributions) {
    auto type = llvm::dyn_cast<MemRefType>(v.getType());
    if (!type)
      return op->emitOpError() << "expected memref type in attribution";
 
    // We can only verify the address space if it hasn't already been lowered
    // from the AddressSpaceAttr to a target-specific numeric value.
    auto addressSpace =
        llvm::dyn_cast_or_null<gpu::AddressSpaceAttr>(type.getMemorySpace());
    if (!addressSpace)
      continue;
    if (addressSpace.getValue() != memorySpace)
      return op->emitOpError()
             << "expected memory space " << stringifyAddressSpace(memorySpace)
             << " in attribution";
  }
  return success();
}
 
//===----------------------------------------------------------------------===//
// AllReduceOp
//===----------------------------------------------------------------------===//
 
static LogicalResult verifyReduceOpAndType(gpu::AllReduceOperation opName,
                                           Type resType) {
  using Kind = gpu::AllReduceOperation;
  if (llvm::is_contained({Kind::MINNUMF, Kind::MAXNUMF, Kind::MINIMUMF,
                          Kind::MAXIMUMF, Kind::MINIMUMNUMF, Kind::MAXIMUMNUMF},
                         opName)) {
    if (!isa<FloatType>(resType))
      return failure();
  }
 
  if (llvm::is_contained({Kind::MINSI, Kind::MINUI, Kind::MAXSI, Kind::MAXUI,
                          Kind::AND, Kind::OR, Kind::XOR},
                         opName)) {
    if (!isa<IntegerType>(resType))
      return failure();
  }
 
  return success();
}
 
LogicalResult gpu::AllReduceOp::verifyRegions() {
  if (getBody().empty() != getOp().has_value())
    return emitError("expected either an op attribute or a non-empty body");
  if (!getBody().empty()) {
    if (getBody().getNumArguments() != 2)
      return emitError("expected two region arguments");
    for (auto argument : getBody().getArguments()) {
      if (argument.getType() != getType())
        return emitError("incorrect region argument type");
    }
    unsigned yieldCount = 0;
    for (Block &block : getBody()) {
      if (auto yield = dyn_cast<gpu::YieldOp>(block.getTerminator())) {
        if (yield.getNumOperands() != 1)
          return emitError("expected one gpu.yield operand");
        if (yield.getOperand(0).getType() != getType())
          return emitError("incorrect gpu.yield type");
        ++yieldCount;
      }
    }
    if (yieldCount == 0)
      return emitError("expected gpu.yield op in region");
  } else {
    gpu::AllReduceOperation opName = *getOp();
    if (failed(verifyReduceOpAndType(opName, getType()))) {
      return emitError() << '`' << gpu::stringifyAllReduceOperation(opName)
                         << "` reduction operation is not compatible with type "
                         << getType();
    }
  }
 
  return success();
}
 
static bool canMakeGroupOpUniform(Operation *op) {
  auto launchOp = dyn_cast<gpu::LaunchOp>(op->getParentOp());
  if (!launchOp)
    return false;
 
  Region &body = launchOp.getBody();
  assert(!body.empty() && "Invalid region");
 
  // Only convert ops in gpu::launch entry block for now.
  return op->getBlock() == &body.front();
}
 
OpFoldResult gpu::AllReduceOp::fold(FoldAdaptor /*adaptor*/) {
  if (!getUniform() && canMakeGroupOpUniform(*this)) {
    setUniform(true);
    return getResult();
  }
 
  return nullptr;
}
 
//===----------------------------------------------------------------------===//
// SubgroupReduceOp
//===----------------------------------------------------------------------===//
 
LogicalResult gpu::SubgroupReduceOp::verify() {
  Type elemType = getType();
  if (auto vecTy = dyn_cast<VectorType>(elemType)) {
    if (vecTy.isScalable())
      return emitOpError() << "is not compatible with scalable vector types";
 
    elemType = vecTy.getElementType();
  }
 
  gpu::AllReduceOperation opName = getOp();
  if (failed(verifyReduceOpAndType(opName, elemType))) {
    return emitError() << '`' << gpu::stringifyAllReduceOperation(opName)
                       << "` reduction operation is not compatible with type "
                       << getType();
  }
 
  auto clusterSize = getClusterSize();
  if (clusterSize) {
    uint32_t size = *clusterSize;
    if (!llvm::isPowerOf2_32(size)) {
      return emitOpError() << "cluster size " << size
                           << " is not a power of two";
    }
  }
 
  uint32_t stride = getClusterStride();
  if (stride != 1 && !clusterSize) {
    return emitOpError() << "cluster stride can only be specified if cluster "
                            "size is specified";
  }
  if (!llvm::isPowerOf2_32(stride)) {
    return emitOpError() << "cluster stride " << stride
                         << " is not a power of two";
  }
 
  return success();
}
 
OpFoldResult gpu::SubgroupReduceOp::fold(FoldAdaptor /*adaptor*/) {
  if (getClusterSize() == 1)
    return getValue();
 
  if (!getUniform() && canMakeGroupOpUniform(*this)) {
    setUniform(true);
    return getResult();
  }
 
  return nullptr;
}
 
//===----------------------------------------------------------------------===//
// AsyncOpInterface
//===----------------------------------------------------------------------===//
 
void gpu::addAsyncDependency(Operation *op, Value token) {
  op->insertOperands(0, {token});
  if (!op->template hasTrait<OpTrait::AttrSizedOperandSegments>())
    return;
  auto attrName =
      OpTrait::AttrSizedOperandSegments<void>::getOperandSegmentSizeAttr();
  auto sizeAttr = dyn_cast_or_null<DenseI32ArrayAttr>(
      op->getInherentAttr(attrName).value_or(Attribute{}));
 
  // Async dependencies is the only variadic operand.
  if (!sizeAttr)
    return;
 
  SmallVector<int32_t, 8> sizes(sizeAttr.asArrayRef());
  ++sizes.front();
  op->setInherentAttr(StringAttr::get(op->getContext(), attrName),
                      Builder(op->getContext()).getDenseI32ArrayAttr(sizes));
}
 
//===----------------------------------------------------------------------===//
// LaunchOp
//===----------------------------------------------------------------------===//
 
void LaunchOp::build(OpBuilder &builder, OperationState &result,
                     Value gridSizeX, Value gridSizeY, Value gridSizeZ,
                     Value getBlockSizeX, Value getBlockSizeY,
                     Value getBlockSizeZ, Value dynamicSharedMemorySize,
                     Type asyncTokenType, ValueRange asyncDependencies,
                     Value asyncObject, TypeRange workgroupAttributions,
                     TypeRange privateAttributions, Value clusterSizeX,
                     Value clusterSizeY, Value clusterSizeZ,
                     FlatSymbolRefAttr module, FlatSymbolRefAttr function) {
  OpBuilder::InsertionGuard g(builder);
 
  if (!workgroupAttributions.empty())
    result.addAttribute(
        getWorkgroupAttributionsAttrName(result.name),
        builder.getI64IntegerAttr(workgroupAttributions.size()));
 
  // Add Op operands.
  result.addOperands(asyncDependencies);
  if (asyncTokenType)
    result.types.push_back(builder.getType<AsyncTokenType>());
 
  // Add grid and block sizes as op operands, followed by the data operands.
  result.addOperands({gridSizeX, gridSizeY, gridSizeZ, getBlockSizeX,
                      getBlockSizeY, getBlockSizeZ});
  if (clusterSizeX)
    result.addOperands(clusterSizeX);
  if (clusterSizeY)
    result.addOperands(clusterSizeY);
  if (clusterSizeZ)
    result.addOperands(clusterSizeZ);
  if (dynamicSharedMemorySize)
    result.addOperands(dynamicSharedMemorySize);
  if (asyncObject)
    result.addOperands(asyncObject);
 
  // Add optional module and function attributes.
  if (module)
    result.addAttribute(getModuleAttrName(result.name), module);
  if (function)
    result.addAttribute(getFunctionAttrName(result.name), function);
 
  // Create a kernel body region with kNumConfigRegionAttributes + N memory
  // attributions, where the first kNumConfigRegionAttributes arguments have
  // `index` type and the rest have the same types as the data operands.
  Region *kernelRegion = result.addRegion();
  Block *body = builder.createBlock(kernelRegion);
  // TODO: Allow passing in proper locations here.
  for (unsigned i = 0; i < kNumConfigRegionAttributes; ++i)
    body->addArgument(builder.getIndexType(), result.location);
  // Add WorkGroup & Private attributions to the region arguments.
  for (Type argTy : workgroupAttributions)
    body->addArgument(argTy, result.location);
  for (Type argTy : privateAttributions)
    body->addArgument(argTy, result.location);
  // Fill OperandSegmentSize Attribute.
  SmallVector<int32_t, 12> segmentSizes(12, 1);
  segmentSizes.front() = asyncDependencies.size();
  segmentSizes[7] = clusterSizeX ? 1 : 0;
  segmentSizes[8] = clusterSizeY ? 1 : 0;
  segmentSizes[9] = clusterSizeZ ? 1 : 0;
  segmentSizes[10] = dynamicSharedMemorySize ? 1 : 0;
  segmentSizes[11] = asyncObject ? 1 : 0;
  result.addAttribute(getOperandSegmentSizeAttr(),
                      builder.getDenseI32ArrayAttr(segmentSizes));
}
 
KernelDim3 LaunchOp::getBlockIds() {
  assert(!getBody().empty() && "LaunchOp body must not be empty.");
  auto args = getBody().getArguments();
  return KernelDim3{args[0], args[1], args[2]};
}
 
KernelDim3 LaunchOp::getThreadIds() {
  assert(!getBody().empty() && "LaunchOp body must not be empty.");
  auto args = getBody().getArguments();
  return KernelDim3{args[3], args[4], args[5]};
}
 
KernelDim3 LaunchOp::getGridSize() {
  assert(!getBody().empty() && "LaunchOp body must not be empty.");
  auto args = getBody().getArguments();
  return KernelDim3{args[6], args[7], args[8]};
}
 
KernelDim3 LaunchOp::getBlockSize() {
  assert(!getBody().empty() && "LaunchOp body must not be empty.");
  auto args = getBody().getArguments();
  return KernelDim3{args[9], args[10], args[11]};
}
 
std::optional<KernelDim3> LaunchOp::getClusterIds() {
  assert(!getBody().empty() && "LaunchOp body must not be empty.");
  if (!hasClusterSize())
    return std::nullopt;
  auto args = getBody().getArguments();
  return KernelDim3{args[12], args[13], args[14]};
}
 
std::optional<KernelDim3> LaunchOp::getClusterSize() {
  assert(!getBody().empty() && "LaunchOp body must not be empty.");
  if (!hasClusterSize())
    return std::nullopt;
  auto args = getBody().getArguments();
  return KernelDim3{args[15], args[16], args[17]};
}
 
KernelDim3 LaunchOp::getGridSizeOperandValues() {
  auto operands = getOperands().drop_front(getAsyncDependencies().size());
  return KernelDim3{operands[0], operands[1], operands[2]};
}
 
KernelDim3 LaunchOp::getBlockSizeOperandValues() {
  auto operands = getOperands().drop_front(getAsyncDependencies().size());
  return KernelDim3{operands[3], operands[4], operands[5]};
}
 
std::optional<KernelDim3> LaunchOp::getClusterSizeOperandValues() {
  auto operands = getOperands().drop_front(getAsyncDependencies().size());
  if (!hasClusterSize())
    return std::nullopt;
  return KernelDim3{operands[6], operands[7], operands[8]};
}
 
template <typename OpTy>
static LogicalResult verifyLaunchAsyncModel(OpTy op) {
  if (!op.getAsyncDependencies().empty() && !op.getAsyncToken())
    return op.emitOpError("dependency operands require the dependency-based "
                          "async model i.e. returning a token");
  if (op.getAsyncToken() && op.getAsyncObject())
    return op.emitOpError("stream-based and dependency-based async models are "
                          "mutually exclusive");
  if (op.getNumResults() == 0 && op.getAsyncToken())
    return op.emitOpError("needs to be named when async keyword is specified");
  return success();
}
 
LogicalResult LaunchOp::verify() {
  if (verifyLaunchAsyncModel(*this).failed())
    return failure();
 
  if (!(hasClusterSize()) &&
      (getClusterSizeX() || getClusterSizeY() || getClusterSizeZ()))
    return emitOpError() << "cluster size must be all present";
  return success();
}
 
LogicalResult LaunchOp::verifyRegions() {
  // Kernel launch takes kNumConfigOperands leading operands for grid/block
  // sizes and transforms them into kNumConfigRegionAttributes region arguments
  // for block/thread identifiers and grid/block sizes.
  if (getBody().empty()) {
    return emitOpError("body region is empty");
  }
  unsigned actualNumRegionArgs = getBody().getNumArguments();
  unsigned expectedNumRegionArgs =
      getNumConfigRegionAttributes() + getNumWorkgroupAttributions();
  if (actualNumRegionArgs < expectedNumRegionArgs) {
    return emitOpError("expected at least ")
           << expectedNumRegionArgs << " region arguments, but got "
           << actualNumRegionArgs;
  }
 
  // Verify Attributions Address Spaces.
  if (failed(verifyAttributions(getOperation(), getWorkgroupAttributionBBArgs(),
                                GPUDialect::getWorkgroupAddressSpace())) ||
      failed(verifyAttributions(getOperation(), getPrivateAttributions(),
                                GPUDialect::getPrivateAddressSpace())))
    return failure();
 
  // Block terminators without successors are expected to exit the kernel region
  // and must be `gpu.terminator`.
  for (Block &block : getBody()) {
    if (block.empty())
      continue;
    if (block.back().getNumSuccessors() != 0)
      continue;
    if (!isa<gpu::TerminatorOp>(&block.back())) {
      return block.back()
          .emitError()
          .append("expected '", gpu::TerminatorOp::getOperationName(),
                  "' or a terminator with successors")
          .attachNote(getLoc())
          .append("in '", LaunchOp::getOperationName(), "' body region");
    }
  }
 
  return success();
}
 
// Pretty-print the kernel grid/block size assignment as
//   (%iter-x, %iter-y, %iter-z) in
//   (%size-x = %ssa-use, %size-y = %ssa-use, %size-z = %ssa-use)
// where %size-* and %iter-* will correspond to the body region arguments.
static void printSizeAssignment(OpAsmPrinter &p, KernelDim3 size,
                                KernelDim3 operands, KernelDim3 ids) {
  p << '(' << ids.x << ", " << ids.y << ", " << ids.z << ") in (";
  p << size.x << " = " << operands.x << ", ";
  p << size.y << " = " << operands.y << ", ";
  p << size.z << " = " << operands.z << ')';
}
 
void LaunchOp::print(OpAsmPrinter &p) {
  if (auto asyncObject = getAsyncObject()) {
    p << " <" << asyncObject << " : " << asyncObject.getType() << ">";
  }
  if (getAsyncToken()) {
    p << " async";
    if (!getAsyncDependencies().empty())
      p << " [" << getAsyncDependencies() << ']';
  }
  // Print the launch configuration.
  if (hasClusterSize()) {
    p << ' ' << getClustersKeyword();
    printSizeAssignment(p, getClusterSize().value(),
                        getClusterSizeOperandValues().value(),
                        getClusterIds().value());
  }
  p << ' ' << getBlocksKeyword();
  printSizeAssignment(p, getGridSize(), getGridSizeOperandValues(),
                      getBlockIds());
  p << ' ' << getThreadsKeyword();
  printSizeAssignment(p, getBlockSize(), getBlockSizeOperandValues(),
                      getThreadIds());
  if (getDynamicSharedMemorySize())
    p << ' ' << getDynamicSharedMemorySizeKeyword() << ' '
      << getDynamicSharedMemorySize();
 
  // Print optional module attribute.
  StringRef moduleAttrName = getModuleAttrName();
  if (auto module = getModule()) {
    p << ' ' << moduleAttrName << '(';
    p.printSymbolName(*module);
    p << ')';
  }
  // Print optional function attribute.
  StringRef functionAttrName = getFunctionAttrName();
  if (auto function = getFunction()) {
    p << ' ' << functionAttrName << '(';
    p.printSymbolName(*function);
    p << ')';
  }
 
  if (getCooperative())
    p << " cooperative";
 
  printAttributions(p, getWorkgroupKeyword(), getWorkgroupAttributionBBArgs());
  printAttributions(p, getPrivateKeyword(), getPrivateAttributions());
 
  p << ' ';
 
  p.printRegion(getBody(), /*printEntryBlockArgs=*/false);
  p.printOptionalAttrDict(
      (*this)->getDiscardableAttrDictionary().getValue(), /*elidedAttrs=*/{
          LaunchOp::getOperandSegmentSizeAttr(),
          getWorkgroupAttributionsAttrName(), getCooperativeAttrName(),
          moduleAttrName, functionAttrName});
}
 
// Parse the size assignment blocks for blocks and threads.  These have the form
//   (%region_arg, %region_arg, %region_arg) in
//   (%region_arg = %operand, %region_arg = %operand, %region_arg = %operand)
// where %region_arg are percent-identifiers for the region arguments to be
// introduced further (SSA defs), and %operand are percent-identifiers for the
// SSA value uses.
static ParseResult
parseSizeAssignment(OpAsmParser &parser,
                    MutableArrayRef<OpAsmParser::UnresolvedOperand> sizes,
                    MutableArrayRef<OpAsmParser::UnresolvedOperand> regionSizes,
                    MutableArrayRef<OpAsmParser::UnresolvedOperand> indices,
                    StringRef keyword) {
  assert(indices.size() == 3 && "space for three indices expected");
  SmallVector<OpAsmParser::UnresolvedOperand, 3> args;
  if (parser.parseOperandList(args, OpAsmParser::Delimiter::Paren,
                              /*allowResultNumber=*/false) ||
      parser.parseKeyword("in") || parser.parseLParen())
    return failure();
 
  if (args.size() != 3) {
    return parser.emitError(parser.getNameLoc())
           << keyword << " expects 3 arguments, but got " << args.size();
  }
  std::move(args.begin(), args.end(), indices.begin());
 
  for (int i = 0; i < 3; ++i) {
    if (i != 0 && parser.parseComma())
      return failure();
    if (parser.parseOperand(regionSizes[i], /*allowResultNumber=*/false) ||
        parser.parseEqual() || parser.parseOperand(sizes[i]))
      return failure();
  }
 
  return parser.parseRParen();
}
 
/// Parses a Launch operation.
/// operation ::= `gpu.launch` (`<` ssa-use `:` type `>`)?
///       (`async` `[` ssa-id-list `]`)?
///       (`clusters` `(` ssa-id-list `)` `in` ssa-reassignment)?
///       `blocks` `(` ssa-id-list `)` `in` ssa-reassignment
///       `threads` `(` ssa-id-list `)` `in` ssa-reassignment
///       (`dynamic_shared_memory_size` ssa-use)?
///       (`module(` symbol-ref-id `)`)?
///       (`function(` symbol-ref-id `)`)?
///       memory-attribution
///       region attr-dict?
/// ssa-reassignment ::= `(` ssa-id `=` ssa-use (`,` ssa-id `=` ssa-use)* `)`
ParseResult LaunchOp::parse(OpAsmParser &parser, OperationState &result) {
  // Sizes of the grid and block.
  SmallVector<OpAsmParser::UnresolvedOperand, LaunchOp::kNumConfigOperands>
      sizes(LaunchOp::kNumConfigOperands);
 
  // Region arguments to be created.
  SmallVector<OpAsmParser::UnresolvedOperand, 16> regionArgs(
      LaunchOp::kNumConfigRegionAttributes);
 
  // Parse optional asyncObject: < value : type >
  OpAsmParser::UnresolvedOperand asyncObjectOperand;
  Type asyncObjectType;
  bool hasAsyncObject = false;
  if (succeeded(parser.parseOptionalLess())) {
    hasAsyncObject = true;
    if (parser.parseOperand(asyncObjectOperand) || parser.parseColon() ||
        parser.parseType(asyncObjectType) || parser.parseGreater())
      return failure();
  }
 
  // Parse optional async dependencies.
  SmallVector<OpAsmParser::UnresolvedOperand, 4> asyncDependencies;
  Type asyncTokenType;
  if (failed(
          parseAsyncDependencies(parser, asyncTokenType, asyncDependencies)) ||
      parser.resolveOperands(asyncDependencies, asyncTokenType,
                             result.operands))
    return failure();
  if (parser.getNumResults() > 0) {
    if (!asyncTokenType)
      return parser.emitError(
          parser.getNameLoc(),
          "gpu.launch requires 'async' keyword to return a value");
    result.types.push_back(asyncTokenType);
  }
 
  bool hasCluster = false;
  if (succeeded(parser.parseOptionalKeyword(LaunchOp::getClustersKeyword()))) {
    hasCluster = true;
    sizes.resize(9);
    regionArgs.resize(18);
  }
  MutableArrayRef<OpAsmParser::UnresolvedOperand> sizesRef(sizes);
  MutableArrayRef<OpAsmParser::UnresolvedOperand> regionArgsRef(regionArgs);
 
  // Last three segment assigns the cluster size. In the region argument
  // list, this is last 6 arguments.
  if (hasCluster) {
    if (parseSizeAssignment(
            parser, sizesRef.drop_front(6), regionArgsRef.slice(15, 3),
            regionArgsRef.slice(12, 3), LaunchOp::getClustersKeyword()))
      return failure();
  }
  // Parse the size assignment segments: the first segment assigns grid sizes
  // and defines values for block identifiers; the second segment assigns block
  // sizes and defines values for thread identifiers.  In the region argument
  // list, identifiers precede sizes, and block-related values precede
  // thread-related values.
  if (parser.parseKeyword(LaunchOp::getBlocksKeyword()) ||
      parseSizeAssignment(parser, sizesRef.take_front(3),
                          regionArgsRef.slice(6, 3), regionArgsRef.slice(0, 3),
                          LaunchOp::getBlocksKeyword()) ||
      parser.parseKeyword(LaunchOp::getThreadsKeyword()) ||
      parseSizeAssignment(parser, sizesRef.drop_front(3),
                          regionArgsRef.slice(9, 3), regionArgsRef.slice(3, 3),
                          LaunchOp::getThreadsKeyword()) ||
      parser.resolveOperands(sizes, parser.getBuilder().getIndexType(),
                             result.operands))
    return failure();
 
  OpAsmParser::UnresolvedOperand dynamicSharedMemorySize;
  bool hasDynamicSharedMemorySize = false;
  if (!parser.parseOptionalKeyword(
          LaunchOp::getDynamicSharedMemorySizeKeyword())) {
    hasDynamicSharedMemorySize = true;
    if (parser.parseOperand(dynamicSharedMemorySize) ||
        parser.resolveOperand(dynamicSharedMemorySize,
                              parser.getBuilder().getI32Type(),
                              result.operands))
      return failure();
  }
 
  // Resolve the asyncObject operand
  if (hasAsyncObject && parser.resolveOperand(asyncObjectOperand,
                                              asyncObjectType, result.operands))
    return failure();
 
  // Parse optional module attribute.
  StringRef moduleAttrName = getModuleAttrName(result.name);
  if (succeeded(parser.parseOptionalKeyword(moduleAttrName))) {
    FlatSymbolRefAttr moduleSymbol;
    if (parser.parseLParen() ||
        parser.parseAttribute(moduleSymbol, Type(), moduleAttrName,
                              result.attributes) ||
        parser.parseRParen())
      return failure();
  }
  // Parse optional function attribute.
  StringRef functionAttrName = getFunctionAttrName(result.name);
  if (succeeded(parser.parseOptionalKeyword(functionAttrName))) {
    FlatSymbolRefAttr funcSymbol;
    if (parser.parseLParen() ||
        parser.parseAttribute(funcSymbol, Type(), functionAttrName,
                              result.attributes) ||
        parser.parseRParen())
      return failure();
  }
 
  // Parse optional cooperative keyword.
  if (succeeded(parser.parseOptionalKeyword("cooperative")))
    result.addAttribute("cooperative", parser.getBuilder().getUnitAttr());
 
  // Create the region arguments: fixed launch-config args (`index`), then
  // workgroup / private attribution args. The workgroup count is stored in the
  // inherent `workgroup_attributions` attribute when non-zero.
  Type index = parser.getBuilder().getIndexType();
  SmallVector<Type, LaunchOp::kNumConfigRegionAttributes> dataTypes(
      LaunchOp::kNumConfigRegionAttributes + 6, index);
 
  SmallVector<OpAsmParser::Argument> regionArguments;
  for (auto ssaValueAndType : llvm::zip(regionArgs, dataTypes)) {
    OpAsmParser::Argument arg;
    arg.ssaName = std::get<0>(ssaValueAndType);
    arg.type = std::get<1>(ssaValueAndType);
    regionArguments.push_back(arg);
  }
 
  Builder &builder = parser.getBuilder();
  // Parse workgroup memory attributions.
  if (failed(parseAttributions(parser, LaunchOp::getWorkgroupKeyword(),
                               regionArguments)))
    return failure();
 
  // Store the number of operands we just parsed as the number of workgroup
  // memory attributions.
  unsigned numWorkgroupAttrs = regionArguments.size() -
                               LaunchOp::kNumConfigRegionAttributes -
                               (hasCluster ? 6 : 0);
  if (numWorkgroupAttrs != 0)
    result.addAttribute(LaunchOp::getWorkgroupAttributionsAttrName(result.name),
                        builder.getI64IntegerAttr(numWorkgroupAttrs));
 
  // Parse private memory attributions.
  if (failed(parseAttributions(parser, LaunchOp::getPrivateKeyword(),
                               regionArguments)))
    return failure();
 
  // Introduce the body region and parse it. The region has
  // kNumConfigRegionAttributes arguments that correspond to
  // block/thread identifiers and grid/block sizes, all having `index` type.
  Region *body = result.addRegion();
  if (parser.parseRegion(*body, regionArguments) ||
      parser.parseOptionalAttrDict(result.attributes))
    return failure();
 
  SmallVector<int32_t, 12> segmentSizes(12, 1);
  segmentSizes.front() = asyncDependencies.size();
 
  if (!hasCluster) {
    segmentSizes[7] = 0;
    segmentSizes[8] = 0;
    segmentSizes[9] = 0;
  }
  segmentSizes[10] = hasDynamicSharedMemorySize ? 1 : 0;
  segmentSizes[11] = hasAsyncObject ? 1 : 0;
  result.addAttribute(LaunchOp::getOperandSegmentSizeAttr(),
                      parser.getBuilder().getDenseI32ArrayAttr(segmentSizes));
  return success();
}
 
/// Simplify the gpu.launch when the range of a thread or block ID is
/// trivially known to be one.
struct FoldLaunchArguments : public OpRewritePattern<LaunchOp> {
  using OpRewritePattern<LaunchOp>::OpRewritePattern;
  LogicalResult matchAndRewrite(LaunchOp op,
                                PatternRewriter &rewriter) const override {
    // If the range implies a single value for `id`, replace `id`'s uses by
    // zero.
    Value zero;
    bool simplified = false;
    auto constPropIdUses = [&](Value id, Value size) {
      // Check if size is trivially one.
      if (!matchPattern(size, m_One()))
        return;
      if (id.getUses().empty())
        return;
      if (!simplified) {
        // Create a zero value the first time.
        OpBuilder::InsertionGuard guard(rewriter);
        rewriter.setInsertionPointToStart(&op.getBody().front());
        zero =
            arith::ConstantIndexOp::create(rewriter, op.getLoc(), /*value=*/0);
      }
      rewriter.replaceAllUsesWith(id, zero);
      simplified = true;
    };
    constPropIdUses(op.getBlockIds().x, op.getGridSizeX());
    constPropIdUses(op.getBlockIds().y, op.getGridSizeY());
    constPropIdUses(op.getBlockIds().z, op.getGridSizeZ());
    constPropIdUses(op.getThreadIds().x, op.getBlockSizeX());
    constPropIdUses(op.getThreadIds().y, op.getBlockSizeY());
    constPropIdUses(op.getThreadIds().z, op.getBlockSizeZ());
 
    return success(simplified);
  }
};
 
void LaunchOp::getCanonicalizationPatterns(RewritePatternSet &rewrites,
                                           MLIRContext *context) {
  rewrites.add<FoldLaunchArguments>(context);
}
 
/// Adds a new block argument that corresponds to buffers located in
/// workgroup memory.
BlockArgument LaunchOp::addWorkgroupAttribution(Type type, Location loc) {
  int64_t cur = getWorkgroupAttributions().value_or(0);
  setWorkgroupAttributions(std::optional<int64_t>(cur + 1));
  return getBody().insertArgument(
      getNumConfigRegionAttributes() + static_cast<unsigned>(cur), type, loc);
}
 
/// Adds a new block argument that corresponds to buffers located in
/// private memory.
BlockArgument LaunchOp::addPrivateAttribution(Type type, Location loc) {
  // Buffers on the private memory always come after buffers on the workgroup
  // memory.
  return getBody().addArgument(type, loc);
}
 
//===----------------------------------------------------------------------===//
// LaunchFuncOp
//===----------------------------------------------------------------------===//
 
void LaunchFuncOp::build(OpBuilder &builder, OperationState &result,
                         SymbolRefAttr kernelSymbol, KernelDim3 gridSize,
                         KernelDim3 getBlockSize, Value dynamicSharedMemorySize,
                         ValueRange kernelOperands, Type asyncTokenType,
                         ValueRange asyncDependencies, Value asyncObject,
                         std::optional<KernelDim3> clusterSize) {
  assert(kernelSymbol.getNestedReferences().size() == 1 &&
         "expected a symbol reference with a single nested reference");
  result.addOperands(asyncDependencies);
  if (asyncTokenType)
    result.types.push_back(builder.getType<AsyncTokenType>());
 
  // Add grid and block sizes as op operands, followed by the data operands.
  result.addOperands({gridSize.x, gridSize.y, gridSize.z, getBlockSize.x,
                      getBlockSize.y, getBlockSize.z});
  if (clusterSize.has_value())
    result.addOperands({clusterSize->x, clusterSize->y, clusterSize->z});
  if (dynamicSharedMemorySize)
    result.addOperands(dynamicSharedMemorySize);
  result.addOperands(kernelOperands);
  if (asyncObject)
    result.addOperands(asyncObject);
 
  Properties &prop = result.getOrAddProperties<Properties>();
  prop.kernel = kernelSymbol;
  size_t segmentSizesLen = std::size(prop.operandSegmentSizes);
  // Initialize the segment sizes to 1.
  llvm::fill(prop.operandSegmentSizes, 1);
  prop.operandSegmentSizes[0] = asyncDependencies.size();
  if (!clusterSize.has_value()) {
    prop.operandSegmentSizes[segmentSizesLen - 4] = 0;
    prop.operandSegmentSizes[segmentSizesLen - 5] = 0;
    prop.operandSegmentSizes[segmentSizesLen - 6] = 0;
  }
  prop.operandSegmentSizes[segmentSizesLen - 3] =
      dynamicSharedMemorySize ? 1 : 0;
  prop.operandSegmentSizes[segmentSizesLen - 2] =
      static_cast<int32_t>(kernelOperands.size());
  prop.operandSegmentSizes[segmentSizesLen - 1] = asyncObject ? 1 : 0;
}
 
void LaunchFuncOp::build(OpBuilder &builder, OperationState &result,
                         GPUFuncOp kernelFunc, KernelDim3 gridSize,
                         KernelDim3 getBlockSize, Value dynamicSharedMemorySize,
                         ValueRange kernelOperands, Type asyncTokenType,
                         ValueRange asyncDependencies, Value asyncObject,
                         std::optional<KernelDim3> clusterSize) {
  auto kernelModule = kernelFunc->getParentOfType<GPUModuleOp>();
  auto kernelSymbol =
      SymbolRefAttr::get(kernelModule.getNameAttr(),
                         {SymbolRefAttr::get(kernelFunc.getNameAttr())});
  build(builder, result, kernelSymbol, gridSize, getBlockSize,
        dynamicSharedMemorySize, kernelOperands, asyncTokenType,
        asyncDependencies, asyncObject, clusterSize);
}
 
StringAttr LaunchFuncOp::getKernelModuleName() {
  return getKernel().getRootReference();
}
 
StringAttr LaunchFuncOp::getKernelName() {
  return getKernel().getLeafReference();
}
 
unsigned LaunchFuncOp::getNumKernelOperands() {
  return getKernelOperands().size();
}
 
Value LaunchFuncOp::getKernelOperand(unsigned i) {
  return getKernelOperands()[i];
}
 
KernelDim3 LaunchFuncOp::getGridSizeOperandValues() {
  auto operands = getOperands().drop_front(getAsyncDependencies().size());
  return KernelDim3{operands[0], operands[1], operands[2]};
}
 
KernelDim3 LaunchFuncOp::getBlockSizeOperandValues() {
  auto operands = getOperands().drop_front(getAsyncDependencies().size());
  return KernelDim3{operands[3], operands[4], operands[5]};
}
 
KernelDim3 LaunchFuncOp::getClusterSizeOperandValues() {
  assert(hasClusterSize() &&
         "cluster size is not set, check hasClusterSize() first");
  auto operands = getOperands().drop_front(getAsyncDependencies().size());
  return KernelDim3{operands[6], operands[7], operands[8]};
}
 
LogicalResult LaunchFuncOp::verify() {
  if (verifyLaunchAsyncModel(*this).failed())
    return failure();
 
  auto module = (*this)->getParentOfType<ModuleOp>();
  if (!module)
    return emitOpError("expected to belong to a module");
 
  if (!module->getDiscardableAttrOfType<UnitAttr>(
          GPUDialect::getContainerModuleAttrName()))
    return emitOpError("expected the closest surrounding module to have the '" +
                       GPUDialect::getContainerModuleAttrName() +
                       "' attribute");
 
  if (hasClusterSize()) {
    if (getClusterSizeY().getType() != getClusterSizeX().getType() ||
        getClusterSizeZ().getType() != getClusterSizeX().getType())
      return emitOpError()
             << "expects types of the cluster dimensions must be the same";
  }
 
  return success();
}
 
LogicalResult
LaunchFuncOp::verifySymbolUses(SymbolTableCollection &symbolTable) {
  LaunchFuncOp launchOp = *this;
  Operation *table = SymbolTable::getNearestSymbolTable(launchOp);
  // GPU modules cannot be nested within each other, escape to resolve the name.
  if (isa<GPUModuleOp>(table))
    table = SymbolTable::getNearestSymbolTable(table->getParentOp());
 
  // Ignore launches that are nested more or less deep than functions in the
  // module we are currently checking.
  if (!launchOp->getParentOp() ||
      launchOp->getParentOp()->getParentOp() != table)
    return success();
 
  // Ignore launch ops with missing attributes here. The errors will be
  // reported by the verifiers of those ops.
  if (!launchOp.getKernelAttr())
    return success();
 
  // Check that `launch_func` refers to a well-formed GPU kernel container.
  StringAttr kernelContainerName = launchOp.getKernelModuleName();
  Operation *kernelContainer =
      symbolTable.lookupNearestSymbolFrom(table, kernelContainerName);
  if (!kernelContainer)
    return launchOp.emitOpError()
           << "kernel container '" << kernelContainerName.getValue()
           << "' is undefined";
 
  // If the container is a GPU binary op return success.
  if (isa<BinaryOp>(kernelContainer))
    return success();
 
  auto kernelModule = dyn_cast<GPUModuleOp>(kernelContainer);
  if (!kernelModule)
    return launchOp.emitOpError()
           << "kernel module '" << kernelContainerName.getValue()
           << "' is undefined";
 
  // Check that `launch_func` refers to a well-formed kernel function.
  Operation *kernelFunc = symbolTable.lookupNearestSymbolFrom(
      kernelModule, launchOp.getKernelName());
  if (!kernelFunc)
    return launchOp.emitOpError("kernel function '")
           << launchOp.getKernel() << "' is undefined";
  auto kernelConvertedFunction = dyn_cast<FunctionOpInterface>(kernelFunc);
  if (!kernelConvertedFunction) {
    InFlightDiagnostic diag = launchOp.emitOpError()
                              << "referenced kernel '" << launchOp.getKernel()
                              << "' is not a function";
    diag.attachNote(kernelFunc->getLoc()) << "see the kernel definition here";
    return diag;
  }
 
  if (!GPUDialect::isKernel(kernelFunc))
    return launchOp.emitOpError("kernel function is missing the '")
           << GPUDialect::getKernelFuncAttrName() << "' attribute";
 
  // TODO: If the kernel isn't a GPU function (which happens during separate
  // compilation), do not check type correspondence as it would require the
  // verifier to be aware of the type conversion.
  auto kernelGPUFunction = dyn_cast<gpu::GPUFuncOp>(kernelFunc);
  if (!kernelGPUFunction)
    return success();
 
  unsigned actualNumArguments = launchOp.getNumKernelOperands();
  unsigned expectedNumArguments = kernelGPUFunction.getNumArguments();
  if (expectedNumArguments != actualNumArguments)
    return launchOp.emitOpError("got ")
           << actualNumArguments << " kernel operands but expected "
           << expectedNumArguments;
 
  FunctionType functionType = kernelGPUFunction.getFunctionType();
  for (unsigned i = 0; i < expectedNumArguments; ++i) {
    if (launchOp.getKernelOperand(i).getType() != functionType.getInput(i)) {
      return launchOp.emitOpError("type of function argument ")
             << i << " does not match";
    }
  }
 
  return success();
}
 
static ParseResult
parseLaunchDimType(OpAsmParser &parser, Type &dimTy,
                   std::optional<OpAsmParser::UnresolvedOperand> clusterValue,
                   Type &clusterXTy, Type &clusterYTy, Type &clusterZTy) {
  if (succeeded(parser.parseOptionalColon())) {
    if (parser.parseType(dimTy))
      return failure();
  } else {
    dimTy = IndexType::get(parser.getContext());
  }
  if (clusterValue.has_value()) {
    clusterXTy = clusterYTy = clusterZTy = dimTy;
  }
  return success();
}
 
static void printLaunchDimType(OpAsmPrinter &printer, Operation *op, Type dimTy,
                               Value clusterValue, Type clusterXTy,
                               Type clusterYTy, Type clusterZTy) {
  if (!dimTy.isIndex())
    printer << ": " << dimTy;
}
 
static ParseResult parseLaunchFuncOperands(
    OpAsmParser &parser,
    SmallVectorImpl<OpAsmParser::UnresolvedOperand> &argNames,
    SmallVectorImpl<Type> &argTypes) {
  if (parser.parseOptionalKeyword("args"))
    return success();
 
  auto parseElement = [&]() -> ParseResult {
    return failure(parser.parseOperand(argNames.emplace_back()) ||
                   parser.parseColonType(argTypes.emplace_back()));
  };
 
  return parser.parseCommaSeparatedList(OpAsmParser::Delimiter::Paren,
                                        parseElement, " in argument list");
}
 
static void printLaunchFuncOperands(OpAsmPrinter &printer, Operation *,
                                    OperandRange operands, TypeRange types) {
  if (operands.empty())
    return;
  printer << "args(";
  llvm::interleaveComma(llvm::zip_equal(operands, types), printer,
                        [&](const auto &pair) {
                          auto [operand, type] = pair;
                          printer << operand << " : " << type;
                        });
  printer << ")";
}
 
//===----------------------------------------------------------------------===//
// ShuffleOp
//===----------------------------------------------------------------------===//
 
void ShuffleOp::build(OpBuilder &builder, OperationState &result, Value value,
                      int32_t offset, int32_t width, ShuffleMode mode) {
  build(builder, result, value,
        arith::ConstantOp::create(builder, result.location,
                                  builder.getI32IntegerAttr(offset)),
        arith::ConstantOp::create(builder, result.location,
                                  builder.getI32IntegerAttr(width)),
        mode);
}
 
//===----------------------------------------------------------------------===//
// RotateOp
//===----------------------------------------------------------------------===//
 
LogicalResult RotateOp::verify() {
  uint32_t offset = getOffset();
  uint32_t width = getWidth();
 
  if (offset >= width) {
    return emitOpError() << "offset must be in the range [0, " << width << ")";
  }
 
  return success();
}
 
//===----------------------------------------------------------------------===//
// BarrierOp
//===----------------------------------------------------------------------===//
 
LogicalResult BarrierOp::verify() {
  BarrierScope scope = getScope();
 
  if (getNamedBarrier() && scope != BarrierScope::Workgroup)
    return emitOpError("named barriers require workgroup scope");
 
  return success();
}
 
/// Remove gpu.barrier after gpu.barrier, the threads are already synchronized!
static LogicalResult eraseRedundantGpuBarrierOps(BarrierOp op,
                                                 PatternRewriter &rewriter) {
  auto nextOp = dyn_cast_or_null<BarrierOp>(op->getNextNode());
  if (!nextOp)
    return failure();
 
  // Cannot merge barriers of different scopes.
  if (op.getScope() != nextOp.getScope())
    return failure();
 
  // Cannot merge named barriers unless both refer to the same handle.
  if (op.getNamedBarrier() != nextOp.getNamedBarrier())
    return failure();
 
  std::optional<ArrayAttr> thisMemfence = op.getAddressSpaces();
  std::optional<ArrayAttr> nextMemfence = nextOp.getAddressSpaces();
 
  if (thisMemfence) {
    rewriter.modifyOpInPlace(op, [&]() {
      if (!nextMemfence) {
        op.removeAddressSpacesAttr();
        return;
      }
      // Fast path - merge where the two barriers fence the same spaces.
      if (*thisMemfence == *nextMemfence) {
        return;
      }
 
      llvm::SmallSetVector<Attribute, 4> mergedSpaces;
      for (Attribute attr : *thisMemfence)
        mergedSpaces.insert(attr);
      for (Attribute attr : *nextMemfence)
        mergedSpaces.insert(attr);
      op.setAddressSpacesAttr(rewriter.getArrayAttr(mergedSpaces.takeVector()));
    });
  }
 
  rewriter.eraseOp(nextOp);
  return success();
}
 
void BarrierOp::getCanonicalizationPatterns(RewritePatternSet &results,
                                            MLIRContext *context) {
  results.add(eraseRedundantGpuBarrierOps);
}
 
void BarrierOp::build(mlir::OpBuilder &odsBuilder,
                      mlir::OperationState &odsState,
                      std::optional<AddressSpace> addressSpace) {
  ArrayAttr addressSpacesAttr;
  if (addressSpace)
    addressSpacesAttr = odsBuilder.getArrayAttr(
        AddressSpaceAttr::get(odsBuilder.getContext(), addressSpace.value()));
  build(
      odsBuilder, odsState, addressSpacesAttr, /*named_barrier=*/Value{},
      BarrierScopeAttr::get(odsBuilder.getContext(), BarrierScope::Workgroup));
}
 
/// Builds a barrier that causes memory operations affecting `memrefToFence` to
/// be completed after the barrier is concluded. Currently, this means setting
/// the fenced address spaces to those of the given memref if it is a gpu
/// address space.
void BarrierOp::build(OpBuilder &builder, OperationState &odsState,
                      Value memrefToFence) {
  std::optional<AddressSpace> addrSpaceToFence;
  if (auto memrefType = dyn_cast<BaseMemRefType>(memrefToFence.getType()))
    if (auto addrSpaceAttr = dyn_cast_if_present<gpu::AddressSpaceAttr>(
            memrefType.getMemorySpace()))
      addrSpaceToFence = addrSpaceAttr.getValue();
  return build(builder, odsState, addrSpaceToFence);
}
 
//===----------------------------------------------------------------------===//
// GPUFuncOp
//===----------------------------------------------------------------------===//
 
/// Adds a new block argument that corresponds to buffers located in
/// workgroup memory.
BlockArgument GPUFuncOp::addWorkgroupAttribution(Type type, Location loc) {
  int64_t cur = getWorkgroupAttributions().value_or(0);
  setWorkgroupAttributions(std::optional<int64_t>(cur + 1));
  return getBody().insertArgument(
      getFunctionType().getNumInputs() + static_cast<unsigned>(cur), type, loc);
}
 
/// Adds a new block argument that corresponds to buffers located in
/// private memory.
BlockArgument GPUFuncOp::addPrivateAttribution(Type type, Location loc) {
  // Buffers on the private memory always come after buffers on the workgroup
  // memory.
  return getBody().addArgument(type, loc);
}
 
void GPUFuncOp::build(OpBuilder &builder, OperationState &result,
                      StringRef name, FunctionType type,
                      TypeRange workgroupAttributions,
                      TypeRange privateAttributions,
                      ArrayRef<NamedAttribute> attrs) {
  OpBuilder::InsertionGuard g(builder);
 
  result.getOrAddProperties<Properties>().sym_name =
      builder.getStringAttr(name);
  result.addAttribute(getFunctionTypeAttrName(result.name),
                      TypeAttr::get(type));
  result.addAttribute(getWorkgroupAttributionsAttrName(result.name),
                      builder.getI64IntegerAttr(workgroupAttributions.size()));
  result.addAttributes(attrs);
  Region *body = result.addRegion();
  Block *entryBlock = builder.createBlock(body);
 
  // TODO: Allow passing in proper locations here.
  for (Type argTy : type.getInputs())
    entryBlock->addArgument(argTy, result.location);
  for (Type argTy : workgroupAttributions)
    entryBlock->addArgument(argTy, result.location);
  for (Type argTy : privateAttributions)
    entryBlock->addArgument(argTy, result.location);
}
 
/// Parses a GPU function memory attribution.
///
/// memory-attribution ::= (`workgroup` `(` ssa-id-and-type-list `)`)?
///                        (`private` `(` ssa-id-and-type-list `)`)?
///
/// Note that this function parses only one of the two similar parts, with the
/// keyword provided as argument.
static ParseResult
parseAttributions(OpAsmParser &parser, StringRef keyword,
                  SmallVectorImpl<OpAsmParser::Argument> &args,
                  Attribute &attributionAttrs) {
  // If we could not parse the keyword, just assume empty list and succeed.
  if (failed(parser.parseOptionalKeyword(keyword)))
    return success();
 
  size_t existingArgs = args.size();
  ParseResult result =
      parser.parseArgumentList(args, OpAsmParser::Delimiter::Paren,
                               /*allowType=*/true, /*allowAttrs=*/true);
  if (failed(result))
    return result;
 
  bool hadAttrs = llvm::any_of(ArrayRef(args).drop_front(existingArgs),
                               [](const OpAsmParser::Argument &arg) -> bool {
                                 return arg.attrs && !arg.attrs.empty();
                               });
  if (!hadAttrs) {
    attributionAttrs = nullptr;
    return result;
  }
 
  Builder &builder = parser.getBuilder();
  SmallVector<Attribute> attributionAttrsVec;
  for (const auto &argument : ArrayRef(args).drop_front(existingArgs)) {
    if (!argument.attrs)
      attributionAttrsVec.push_back(builder.getDictionaryAttr({}));
    else
      attributionAttrsVec.push_back(argument.attrs);
  }
  attributionAttrs = builder.getArrayAttr(attributionAttrsVec);
  return result;
}
 
/// Parses a GPU function.
///
/// <operation> ::= `gpu.func` symbol-ref-id `(` argument-list `)`
///                 (`->` function-result-list)? memory-attribution `kernel`?
///                 function-attributes? region
ParseResult GPUFuncOp::parse(OpAsmParser &parser, OperationState &result) {
  SmallVector<OpAsmParser::Argument> entryArgs;
  SmallVector<DictionaryAttr> resultAttrs;
  SmallVector<Type> resultTypes;
  bool isVariadic;
 
  // Parse the function name.
  StringAttr nameAttr;
  if (parser.parseSymbolName(nameAttr, getSymNameAttrName(result.name),
                             result.attributes))
    return failure();
 
  auto signatureLocation = parser.getCurrentLocation();
  if (failed(function_interface_impl::parseFunctionSignatureWithArguments(
          parser, /*allowVariadic=*/false, entryArgs, isVariadic, resultTypes,
          resultAttrs)))
    return failure();
 
  if (!entryArgs.empty() && entryArgs[0].ssaName.name.empty())
    return parser.emitError(signatureLocation)
           << "gpu.func requires named arguments";
 
  // Construct the function type. More types will be added to the region, but
  // not to the function type.
  Builder &builder = parser.getBuilder();
 
  SmallVector<Type> argTypes;
  for (auto &arg : entryArgs)
    argTypes.push_back(arg.type);
  auto type = builder.getFunctionType(argTypes, resultTypes);
  result.addAttribute(getFunctionTypeAttrName(result.name),
                      TypeAttr::get(type));
 
  call_interface_impl::addArgAndResultAttrs(
      builder, result, entryArgs, resultAttrs, getArgAttrsAttrName(result.name),
      getResAttrsAttrName(result.name));
 
  Attribute workgroupAttributionAttrs;
  // Parse workgroup memory attributions.
  if (failed(parseAttributions(parser, GPUFuncOp::getWorkgroupKeyword(),
                               entryArgs, workgroupAttributionAttrs)))
    return failure();
 
  // Store the number of operands we just parsed as the number of workgroup
  // memory attributions.
  unsigned numWorkgroupAttrs = entryArgs.size() - type.getNumInputs();
  if (numWorkgroupAttrs != 0)
    result.addAttribute(
        GPUFuncOp::getWorkgroupAttributionsAttrName(result.name),
        builder.getI64IntegerAttr(numWorkgroupAttrs));
  if (workgroupAttributionAttrs)
    result.addAttribute(GPUFuncOp::getWorkgroupAttribAttrsAttrName(result.name),
                        workgroupAttributionAttrs);
 
  Attribute privateAttributionAttrs;
  // Parse private memory attributions.
  if (failed(parseAttributions(parser, GPUFuncOp::getPrivateKeyword(),
                               entryArgs, privateAttributionAttrs)))
    return failure();
  if (privateAttributionAttrs)
    result.addAttribute(GPUFuncOp::getPrivateAttribAttrsAttrName(result.name),
                        privateAttributionAttrs);
 
  // Parse the kernel attribute if present.
  if (succeeded(parser.parseOptionalKeyword(GPUFuncOp::getKernelKeyword())))
    result.addAttribute(GPUFuncOp::getKernelAttrName(result.name),
                        builder.getUnitAttr());
 
  // Parse attributes.
  if (failed(parser.parseOptionalAttrDictWithKeyword(result.attributes)))
    return failure();
 
  // Parse the region. If no argument names were provided, take all names
  // (including those of attributions) from the entry block.
  auto *body = result.addRegion();
  return parser.parseRegion(*body, entryArgs);
}
 
void GPUFuncOp::print(OpAsmPrinter &p) {
  p << ' ';
  p.printSymbolName(getName());
 
  FunctionType type = getFunctionType();
  function_interface_impl::printFunctionSignature(p, *this, type.getInputs(),
                                                  /*isVariadic=*/false,
                                                  type.getResults());
 
  printAttributions(p, getWorkgroupKeyword(), getWorkgroupAttributionBBArgs(),
                    getWorkgroupAttribAttrs().value_or(nullptr));
  printAttributions(p, getPrivateKeyword(), getPrivateAttributions(),
                    getPrivateAttribAttrs().value_or(nullptr));
  if (isKernel())
    p << ' ' << getKernelKeyword();
 
  function_interface_impl::printFunctionAttributes(
      p, *this,
      {getWorkgroupAttributionsAttrName(), getKernelAttrName(),
       GPUDialect::getKernelFuncAttrName(), getFunctionTypeAttrName(),
       getArgAttrsAttrName(), getResAttrsAttrName(),
       getWorkgroupAttribAttrsAttrName(), getPrivateAttribAttrsAttrName()});
  p << ' ';
  p.printRegion(getBody(), /*printEntryBlockArgs=*/false);
}
 
static DictionaryAttr getAttributionAttrs(GPUFuncOp op, unsigned index,
                                          StringAttr attrName) {
  ArrayAttr allAttrs = attrName == op.getWorkgroupAttribAttrsAttrName()
                           ? op.getWorkgroupAttribAttrsAttr()
                           : op.getPrivateAttribAttrsAttr();
  if (!allAttrs || index >= allAttrs.size())
    return DictionaryAttr();
  return llvm::cast<DictionaryAttr>(allAttrs[index]);
}
 
DictionaryAttr GPUFuncOp::getworkgroupAttributionAttrs(unsigned index) {
  return getAttributionAttrs(*this, index, getWorkgroupAttribAttrsAttrName());
}
 
DictionaryAttr GPUFuncOp::getPrivateAttributionAttrs(unsigned index) {
  return getAttributionAttrs(*this, index, getPrivateAttribAttrsAttrName());
}
 
static void setAttributionAttrs(GPUFuncOp op, unsigned index,
                                DictionaryAttr value, StringAttr attrName) {
  MLIRContext *ctx = op.getContext();
  ArrayAttr allAttrs = attrName == op.getWorkgroupAttribAttrsAttrName()
                           ? op.getWorkgroupAttribAttrsAttr()
                           : op.getPrivateAttribAttrsAttr();
  SmallVector<Attribute> elements;
  if (allAttrs)
    elements.append(allAttrs.begin(), allAttrs.end());
  while (elements.size() <= index)
    elements.push_back(DictionaryAttr::get(ctx));
  if (!value)
    elements[index] = DictionaryAttr::get(ctx);
  else
    elements[index] = value;
  ArrayAttr newValue = ArrayAttr::get(ctx, elements);
  if (attrName == op.getWorkgroupAttribAttrsAttrName())
    op.setWorkgroupAttribAttrsAttr(newValue);
  else
    op.setPrivateAttribAttrsAttr(newValue);
}
 
void GPUFuncOp::setworkgroupAttributionAttrs(unsigned index,
                                             DictionaryAttr value) {
  setAttributionAttrs(*this, index, value, getWorkgroupAttribAttrsAttrName());
}
 
void GPUFuncOp::setPrivateAttributionAttrs(unsigned int index,
                                           DictionaryAttr value) {
  setAttributionAttrs(*this, index, value, getPrivateAttribAttrsAttrName());
}
 
static Attribute getAttributionAttr(GPUFuncOp op, unsigned index,
                                    StringAttr name, StringAttr attrsName) {
  DictionaryAttr dict = getAttributionAttrs(op, index, attrsName);
  if (!dict)
    return Attribute();
  return dict.get(name);
}
 
Attribute GPUFuncOp::getWorkgroupAttributionAttr(unsigned index,
                                                 StringAttr name) {
  assert(index < getNumWorkgroupAttributions() &&
         "index must map to a workgroup attribution");
  return getAttributionAttr(*this, index, name,
                            getWorkgroupAttribAttrsAttrName());
}
 
Attribute GPUFuncOp::getPrivateAttributionAttr(unsigned index,
                                               StringAttr name) {
  assert(index < getNumPrivateAttributions() &&
         "index must map to a private attribution");
  return getAttributionAttr(*this, index, name,
                            getPrivateAttribAttrsAttrName());
}
 
static void setAttributionAttr(GPUFuncOp op, unsigned index, StringAttr name,
                               Attribute value, StringAttr attrsName) {
  MLIRContext *ctx = op.getContext();
  SmallVector<NamedAttribute> elems;
  DictionaryAttr oldDict = getAttributionAttrs(op, index, attrsName);
  if (oldDict)
    elems.append(oldDict.getValue().begin(), oldDict.getValue().end());
 
  bool found = false;
  bool mustSort = true;
  for (unsigned i = 0, e = elems.size(); i < e; ++i) {
    if (elems[i].getName() == name) {
      found = true;
      if (!value) {
        std::swap(elems[i], elems[elems.size() - 1]);
        elems.pop_back();
      } else {
        mustSort = false;
        elems[i] = NamedAttribute(elems[i].getName(), value);
      }
      break;
    }
  }
  if (!found) {
    if (!value)
      return;
    elems.emplace_back(name, value);
  }
  if (mustSort) {
    DictionaryAttr::sortInPlace(elems);
  }
  auto newDict = DictionaryAttr::getWithSorted(ctx, elems);
  setAttributionAttrs(op, index, newDict, attrsName);
}
 
void GPUFuncOp::setWorkgroupAttributionAttr(unsigned index, StringAttr name,
                                            Attribute value) {
  assert(index < getNumWorkgroupAttributions() &&
         "index must map to a workgroup attribution");
  setAttributionAttr(*this, index, name, value,
                     getWorkgroupAttribAttrsAttrName());
}
 
void GPUFuncOp::setPrivateAttributionAttr(unsigned index, StringAttr name,
                                          Attribute value) {
  assert(index < getNumPrivateAttributions() &&
         "index must map to a private attribution");
  setAttributionAttr(*this, index, name, value,
                     getPrivateAttribAttrsAttrName());
}
 
LogicalResult GPUFuncOp::verifyType() {
  if (isKernel() && getFunctionType().getNumResults() != 0)
    return emitOpError() << "expected void return type for kernel function";
 
  return success();
}
 
/// Verifies the body of the function.
LogicalResult GPUFuncOp::verifyBody() {
  if (empty())
    return emitOpError() << "expected body with at least one block";
  unsigned numFuncArguments = getNumArguments();
  unsigned numWorkgroupAttributions = getNumWorkgroupAttributions();
  unsigned numBlockArguments = front().getNumArguments();
  if (numBlockArguments < numFuncArguments + numWorkgroupAttributions)
    return emitOpError() << "expected at least "
                         << numFuncArguments + numWorkgroupAttributions
                         << " arguments to body region";
 
  ArrayRef<Type> funcArgTypes = getFunctionType().getInputs();
  for (unsigned i = 0; i < numFuncArguments; ++i) {
    Type blockArgType = front().getArgument(i).getType();
    if (funcArgTypes[i] != blockArgType)
      return emitOpError() << "expected body region argument #" << i
                           << " to be of type " << funcArgTypes[i] << ", got "
                           << blockArgType;
  }
 
  if (failed(verifyAttributions(getOperation(), getWorkgroupAttributionBBArgs(),
                                GPUDialect::getWorkgroupAddressSpace())) ||
      failed(verifyAttributions(getOperation(), getPrivateAttributions(),
                                GPUDialect::getPrivateAddressSpace())))
    return failure();
 
  return success();
}
 
//===----------------------------------------------------------------------===//
// ReturnOp
//===----------------------------------------------------------------------===//
 
LogicalResult gpu::ReturnOp::verify() {
  GPUFuncOp function = (*this)->getParentOfType<GPUFuncOp>();
 
  FunctionType funType = function.getFunctionType();
 
  if (funType.getNumResults() != getOperands().size())
    return emitOpError()
        .append("expected ", funType.getNumResults(), " result operands")
        .attachNote(function.getLoc())
        .append("return type declared here");
 
  for (const auto &pair : llvm::enumerate(
           llvm::zip(function.getFunctionType().getResults(), getOperands()))) {
    auto [type, operand] = pair.value();
    if (type != operand.getType())
      return emitOpError() << "unexpected type `" << operand.getType()
                           << "' for operand #" << pair.index();
  }
  return success();
}
 
//===----------------------------------------------------------------------===//
// GPUModuleOp
//===----------------------------------------------------------------------===//
 
LogicalResult GPUModuleOp::readProperties(DialectBytecodeReader &reader,
                                          OperationState &state) {
  auto &properties = state.getOrAddProperties<Properties>();
  // Preserve the pre-DLTI field order for unversioned bytecode.
  if (failed(reader.readOptionalAttribute(properties.offloadingHandler)) ||
      failed(reader.readAttribute(properties.sym_name)) ||
      failed(reader.readOptionalAttribute(properties.sym_visibility)) ||
      failed(reader.readOptionalAttribute(properties.targets)))
    return failure();
 
  if (failed(reader.getDialectVersion<GPUDialect>()))
    return success();
  return reader.readOptionalAttribute(properties.dlti);
}
 
void GPUModuleOp::writeProperties(DialectBytecodeWriter &writer) {
  Properties &properties = getProperties();
  writer.writeOptionalAttribute(properties.offloadingHandler);
  writer.writeAttribute(properties.sym_name);
  writer.writeOptionalAttribute(properties.sym_visibility);
  writer.writeOptionalAttribute(properties.targets);
  if (writer.getBytecodeVersion() >= bytecode::kDialectVersioning)
    writer.writeOptionalAttribute(properties.dlti);
}
 
void GPUModuleOp::build(OpBuilder &builder, OperationState &result,
                        StringRef name, ArrayAttr targets,
                        Attribute offloadingHandler) {
  result.addRegion()->emplaceBlock();
  Properties &props = result.getOrAddProperties<Properties>();
  if (targets)
    props.targets = targets;
  props.setSymName(builder.getStringAttr(name));
  props.offloadingHandler = offloadingHandler;
}
 
void GPUModuleOp::build(OpBuilder &builder, OperationState &result,
                        StringRef name, ArrayRef<Attribute> targets,
                        Attribute offloadingHandler) {
  build(builder, result, name,
        targets.empty() ? ArrayAttr() : builder.getArrayAttr(targets),
        offloadingHandler);
}
 
bool GPUModuleOp::hasTarget(Attribute target) {
  if (ArrayAttr targets = getTargetsAttr())
    return llvm::count(targets.getValue(), target);
  return false;
}
 
void GPUModuleOp::setTargets(ArrayRef<TargetAttrInterface> targets) {
  ArrayAttr &targetsAttr = getProperties().targets;
  SmallVector<Attribute> targetsVector(targets);
  targetsAttr = ArrayAttr::get(getContext(), targetsVector);
}
 
LogicalResult GPUModuleOp::verify() {
  auto targets = getTargetsAttr();
 
  if (!targets)
    return success();
 
  for (auto target : targets) {
    if (auto verifyTargetAttr =
            llvm::dyn_cast<TargetAttrVerifyInterface>(target)) {
      if (verifyTargetAttr.verifyTarget(getOperation()).failed())
        return failure();
    }
  }
  return success();
}
 
//===----------------------------------------------------------------------===//
// GPUBinaryOp
//===----------------------------------------------------------------------===//
void BinaryOp::build(OpBuilder &builder, OperationState &result, StringRef name,
                     Attribute offloadingHandler, ArrayAttr objects) {
  auto &properties = result.getOrAddProperties<Properties>();
  result.attributes.push_back(builder.getNamedAttr(
      getSymNameAttrName(result.name), builder.getStringAttr(name)));
  properties.objects = objects;
  if (offloadingHandler)
    properties.offloadingHandler = offloadingHandler;
  else
    properties.offloadingHandler = builder.getAttr<SelectObjectAttr>(nullptr);
}
 
void BinaryOp::build(OpBuilder &builder, OperationState &result, StringRef name,
                     Attribute offloadingHandler, ArrayRef<Attribute> objects) {
  build(builder, result, name, offloadingHandler,
        objects.empty() ? ArrayAttr() : builder.getArrayAttr(objects));
}
 
static ParseResult parseOffloadingHandler(OpAsmParser &parser,
                                          Attribute &offloadingHandler) {
  if (succeeded(parser.parseOptionalLess())) {
    if (parser.parseAttribute(offloadingHandler))
      return failure();
    if (parser.parseGreater())
      return failure();
  }
  if (!offloadingHandler)
    offloadingHandler = parser.getBuilder().getAttr<SelectObjectAttr>(nullptr);
  return success();
}
 
static void printOffloadingHandler(OpAsmPrinter &printer, Operation *op,
                                   Attribute offloadingHandler) {
  if (offloadingHandler != SelectObjectAttr::get(op->getContext(), nullptr))
    printer << '<' << offloadingHandler << '>';
}
 
//===----------------------------------------------------------------------===//
// GPUMemcpyOp
//===----------------------------------------------------------------------===//
 
LogicalResult MemcpyOp::verify() {
  auto srcType = getSrc().getType();
  auto dstType = getDst().getType();
 
  if (getElementTypeOrSelf(srcType) != getElementTypeOrSelf(dstType))
    return emitOpError("arguments have incompatible element type");
 
  if (failed(verifyCompatibleShape(srcType, dstType)))
    return emitOpError("arguments have incompatible shape");
 
  return success();
}
 
namespace {
/// Erases a common case of copy ops where a destination value is used only by
/// the copy op, alloc and dealloc ops.
struct EraseTrivialCopyOp : public OpRewritePattern<MemcpyOp> {
  using OpRewritePattern<MemcpyOp>::OpRewritePattern;
 
  LogicalResult matchAndRewrite(MemcpyOp op,
                                PatternRewriter &rewriter) const override {
    Value dest = op.getDst();
    Operation *destDefOp = dest.getDefiningOp();
    // `dest` must be defined by an op having Allocate memory effect in order to
    // perform the folding.
    if (!destDefOp ||
        !hasSingleEffect<MemoryEffects::Allocate>(destDefOp, dest))
      return failure();
    // We can erase `op` iff `dest` has no other use apart from its
    // use by `op` and dealloc ops.
    if (llvm::any_of(dest.getUsers(), [op, dest](Operation *user) {
          return user != op &&
                 !hasSingleEffect<MemoryEffects::Free>(user, dest);
        }))
      return failure();
    // We can perform the folding if and only if op has a single async
    // dependency and produces an async token as result, or if it does not have
    // any async dependency and does not produce any async token result.
    if (op.getAsyncDependencies().size() > 1 ||
        ((op.getAsyncDependencies().empty() && op.getAsyncToken()) ||
         (!op.getAsyncDependencies().empty() && !op.getAsyncToken())))
      return failure();
    rewriter.replaceOp(op, op.getAsyncDependencies());
    return success();
  }
};
} // end anonymous namespace
 
void MemcpyOp::getCanonicalizationPatterns(RewritePatternSet &results,
                                           MLIRContext *context) {
  results.add<EraseTrivialCopyOp>(context);
}
 
//===----------------------------------------------------------------------===//
// GPU_SubgroupMmaLoadMatrixOp
//===----------------------------------------------------------------------===//
 
LogicalResult SubgroupMmaLoadMatrixOp::verify() {
  auto srcType = getSrcMemref().getType();
  auto resType = getRes().getType();
  auto resMatrixType = llvm::cast<gpu::MMAMatrixType>(resType);
  auto operand = resMatrixType.getOperand();
  auto srcMemrefType = llvm::cast<MemRefType>(srcType);
 
  if (!srcMemrefType.isLastDimUnitStride())
    return emitError(
        "expected source memref most minor dim must have unit stride");
 
  if (operand != "AOp" && operand != "BOp" && operand != "COp")
    return emitError("only AOp, BOp and COp can be loaded");
 
  return success();
}
 
//===----------------------------------------------------------------------===//
// GPU_SubgroupMmaStoreMatrixOp
//===----------------------------------------------------------------------===//
 
LogicalResult SubgroupMmaStoreMatrixOp::verify() {
  auto srcType = getSrc().getType();
  auto dstType = getDstMemref().getType();
  auto srcMatrixType = llvm::cast<gpu::MMAMatrixType>(srcType);
  auto dstMemrefType = llvm::cast<MemRefType>(dstType);
 
  if (!dstMemrefType.isLastDimUnitStride())
    return emitError(
        "expected destination memref most minor dim must have unit stride");
 
  if (srcMatrixType.getOperand() != "COp")
    return emitError(
        "expected the operand matrix being stored to have 'COp' operand type");
 
  return success();
}
 
//===----------------------------------------------------------------------===//
// GPU_SubgroupMmaComputeOp
//===----------------------------------------------------------------------===//
 
LogicalResult SubgroupMmaComputeOp::verify() {
  enum OperandMap { A, B, C };
  SmallVector<MMAMatrixType, 3> opTypes;
  opTypes.push_back(llvm::cast<MMAMatrixType>(getOpA().getType()));
  opTypes.push_back(llvm::cast<MMAMatrixType>(getOpB().getType()));
  opTypes.push_back(llvm::cast<MMAMatrixType>(getOpC().getType()));
 
  if (opTypes[A].getOperand() != "AOp" || opTypes[B].getOperand() != "BOp" ||
      opTypes[C].getOperand() != "COp")
    return emitError("operands must be in the order AOp, BOp, COp");
 
  ArrayRef<int64_t> aShape, bShape, cShape;
  aShape = opTypes[A].getShape();
  bShape = opTypes[B].getShape();
  cShape = opTypes[C].getShape();
 
  if (aShape[1] != bShape[0] || aShape[0] != cShape[0] ||
      bShape[1] != cShape[1])
    return emitError("operand shapes do not satisfy matmul constraints");
 
  return success();
}
 
LogicalResult MemcpyOp::fold(FoldAdaptor adaptor,
                             SmallVectorImpl<::mlir::OpFoldResult> &results) {
  return memref::foldMemRefCast(*this);
}
 
LogicalResult MemsetOp::fold(FoldAdaptor adaptor,
                             SmallVectorImpl<::mlir::OpFoldResult> &results) {
  return memref::foldMemRefCast(*this);
}
 
//===----------------------------------------------------------------------===//
// GPU_WaitOp
//===----------------------------------------------------------------------===//
 
namespace {
/// Remove gpu.wait op use of gpu.wait op def without async dependencies.
/// %t = gpu.wait async []       // No async dependencies.
/// ...  gpu.wait ... [%t, ...]  // %t can be removed.
struct EraseRedundantGpuWaitOpPairs : public OpRewritePattern<WaitOp> {
public:
  using Base::Base;
 
  LogicalResult matchAndRewrite(WaitOp op,
                                PatternRewriter &rewriter) const final {
    auto predicate = [](Value value) {
      auto waitOp = value.getDefiningOp<WaitOp>();
      return waitOp && waitOp->getNumOperands() == 0;
    };
    if (llvm::none_of(op.getAsyncDependencies(), predicate))
      return failure();
    SmallVector<Value> validOperands;
    for (Value operand : op->getOperands()) {
      if (predicate(operand))
        continue;
      validOperands.push_back(operand);
    }
    rewriter.modifyOpInPlace(op, [&]() { op->setOperands(validOperands); });
    return success();
  }
};
 
/// Simplify trivial gpu.wait ops for the following patterns.
/// 1. %t = gpu.wait async ... ops, where %t has no uses (regardless of async
/// dependencies).
/// 2. %t1 = gpu.wait async [%t0], in this case, we can replace uses of %t1 with
/// %t0.
/// 3. gpu.wait [] ops, i.e gpu.wait ops that neither have any async
/// dependencies nor return any token.
struct SimplifyGpuWaitOp : public OpRewritePattern<WaitOp> {
public:
  using Base::Base;
 
  LogicalResult matchAndRewrite(WaitOp op,
                                PatternRewriter &rewriter) const final {
    // Erase gpu.wait ops that neither have any async dependencies nor return
    // any async token.
    if (op.getAsyncDependencies().empty() && !op.getAsyncToken()) {
      rewriter.eraseOp(op);
      return success();
    }
    // Replace uses of %t1 = gpu.wait async [%t0] ops with %t0 and erase the op.
    if (llvm::hasSingleElement(op.getAsyncDependencies()) &&
        op.getAsyncToken()) {
      rewriter.replaceOp(op, op.getAsyncDependencies());
      return success();
    }
    // Erase %t = gpu.wait async ... ops, where %t has no uses.
    if (op.getAsyncToken() && op.getAsyncToken().use_empty()) {
      rewriter.eraseOp(op);
      return success();
    }
    return failure();
  }
};
} // end anonymous namespace
 
void WaitOp::getCanonicalizationPatterns(RewritePatternSet &results,
                                         MLIRContext *context) {
  results.add<EraseRedundantGpuWaitOpPairs, SimplifyGpuWaitOp>(context);
}
 
//===----------------------------------------------------------------------===//
// GPU_AllocOp
//===----------------------------------------------------------------------===//
 
LogicalResult AllocOp::verify() {
  auto memRefType = llvm::cast<MemRefType>(getMemref().getType());
 
  if (failed(verifyDynamicDimensionCount(getOperation(), memRefType,
                                         getDynamicSizes())))
    return failure();
 
  unsigned numSymbols = 0;
  if (!memRefType.getLayout().isIdentity())
    numSymbols = memRefType.getLayout().getAffineMap().getNumSymbols();
  if (getSymbolOperands().size() != numSymbols) {
    return emitOpError(
        "symbol operand count does not equal memref symbol count");
  }
 
  return success();
}
 
namespace {
/// Folding of memref.dim(gpu.alloc(%size), %idx) -> %size similar to
/// `memref::AllocOp`.
struct SimplifyDimOfAllocOp : public OpRewritePattern<memref::DimOp> {
  using OpRewritePattern<memref::DimOp>::OpRewritePattern;
 
  LogicalResult matchAndRewrite(memref::DimOp dimOp,
                                PatternRewriter &rewriter) const override {
    std::optional<int64_t> index = dimOp.getConstantIndex();
    if (!index)
      return failure();
 
    int64_t indexVal = index.value();
    auto memrefType = llvm::dyn_cast<MemRefType>(dimOp.getSource().getType());
    if (!memrefType || indexVal < 0 || indexVal >= memrefType.getRank() ||
        !memrefType.isDynamicDim(indexVal))
      return failure();
 
    auto alloc = dimOp.getSource().getDefiningOp<AllocOp>();
    if (!alloc)
      return failure();
 
    Value substituteOp = *(alloc.getDynamicSizes().begin() +
                           memrefType.getDynamicDimIndex(indexVal));
    rewriter.replaceOp(dimOp, substituteOp);
    return success();
  }
};
} // namespace
 
void AllocOp::getCanonicalizationPatterns(RewritePatternSet &results,
                                          MLIRContext *context) {
  results.add<SimplifyDimOfAllocOp>(context);
}
 
//===----------------------------------------------------------------------===//
// DynamicSharedMemoryOp
//===----------------------------------------------------------------------===//
 
LogicalResult gpu::DynamicSharedMemoryOp::verify() {
  if (!getOperation()->getParentWithTrait<OpTrait::SymbolTable>())
    return emitOpError() << "must be inside an op with symbol table";
 
  MemRefType memrefType = getResultMemref().getType();
  // Check address space
  if (!GPUDialect::hasWorkgroupMemoryAddressSpace(memrefType)) {
    return emitOpError() << "address space must be "
                         << gpu::AddressSpaceAttr::getMnemonic() << "<"
                         << stringifyEnum(gpu::AddressSpace::Workgroup) << ">";
  }
  if (memrefType.hasStaticShape()) {
    return emitOpError() << "result memref type must be memref<?xi8, "
                            "#gpu.address_space<workgroup>>";
  }
  return success();
}
 
//===----------------------------------------------------------------------===//
// GPU WarpExecuteOnLane0Op
//===----------------------------------------------------------------------===//
 
void WarpExecuteOnLane0Op::print(OpAsmPrinter &p) {
  p << "(" << getLaneid() << ")";
 
  SmallVector<StringRef> coreAttr = {getWarpSizeAttrName()};
  p << "[" << getWarpSize() << "]";
 
  if (!getArgs().empty())
    p << " args(" << getArgs() << " : " << getArgs().getTypes() << ")";
  if (!getResults().empty())
    p << " -> (" << getResults().getTypes() << ')';
  p << " ";
  p.printRegion(getRegion(),
                /*printEntryBlockArgs=*/true,
                /*printBlockTerminators=*/!getResults().empty());
  p.printOptionalAttrDict(
      getOperation()->getDiscardableAttrDictionary().getValue(), coreAttr);
}
 
ParseResult WarpExecuteOnLane0Op::parse(OpAsmParser &parser,
                                        OperationState &result) {
  // Create the region.
  result.regions.reserve(1);
  Region *warpRegion = result.addRegion();
 
  auto &builder = parser.getBuilder();
  OpAsmParser::UnresolvedOperand laneId;
 
  // Parse predicate operand.
  if (parser.parseLParen() ||
      parser.parseOperand(laneId, /*allowResultNumber=*/false) ||
      parser.parseRParen())
    return failure();
 
  int64_t warpSize;
  if (parser.parseLSquare() || parser.parseInteger(warpSize) ||
      parser.parseRSquare())
    return failure();
  result.addAttribute(getWarpSizeAttrName(OperationName(getOperationName(),
                                                        builder.getContext())),
                      builder.getI64IntegerAttr(warpSize));
 
  if (parser.resolveOperand(laneId, builder.getIndexType(), result.operands))
    return failure();
 
  llvm::SMLoc inputsOperandsLoc;
  SmallVector<OpAsmParser::UnresolvedOperand> inputsOperands;
  SmallVector<Type> inputTypes;
  if (succeeded(parser.parseOptionalKeyword("args"))) {
    if (parser.parseLParen())
      return failure();
 
    inputsOperandsLoc = parser.getCurrentLocation();
    if (parser.parseOperandList(inputsOperands) ||
        parser.parseColonTypeList(inputTypes) || parser.parseRParen())
      return failure();
  }
  if (parser.resolveOperands(inputsOperands, inputTypes, inputsOperandsLoc,
                             result.operands))
    return failure();
 
  // Parse optional results type list.
  if (parser.parseOptionalArrowTypeList(result.types))
    return failure();
  // Parse the region.
  if (parser.parseRegion(*warpRegion, /*arguments=*/{},
                         /*argTypes=*/{}))
    return failure();
  WarpExecuteOnLane0Op::ensureTerminator(*warpRegion, builder, result.location);
 
  // Parse the optional attribute list.
  if (parser.parseOptionalAttrDict(result.attributes))
    return failure();
  return success();
}
 
void WarpExecuteOnLane0Op::getSuccessorRegions(
    RegionBranchPoint point, SmallVectorImpl<RegionSuccessor> &regions) {
  if (!point.isParent()) {
    regions.push_back(RegionSuccessor(getOperation()));
    return;
  }
 
  // The warp region is always executed
  regions.push_back(RegionSuccessor(&getWarpRegion()));
}
 
ValueRange WarpExecuteOnLane0Op::getSuccessorInputs(RegionSuccessor successor) {
  return successor.isOperation() ? ValueRange(getResults()) : ValueRange();
}
void WarpExecuteOnLane0Op::build(OpBuilder &builder, OperationState &result,
                                 TypeRange resultTypes, Value laneId,
                                 int64_t warpSize) {
  build(builder, result, resultTypes, laneId, warpSize,
        /*operands=*/{}, /*argTypes=*/{});
}
 
void WarpExecuteOnLane0Op::build(OpBuilder &builder, OperationState &result,
                                 TypeRange resultTypes, Value laneId,
                                 int64_t warpSize, ValueRange args,
                                 TypeRange blockArgTypes) {
  result.addOperands(laneId);
  result.addAttribute(getAttributeNames()[0],
                      builder.getI64IntegerAttr(warpSize));
  result.addTypes(resultTypes);
  result.addOperands(args);
  assert(args.size() == blockArgTypes.size());
  OpBuilder::InsertionGuard guard(builder);
  Region *warpRegion = result.addRegion();
  Block *block = builder.createBlock(warpRegion);
  for (auto [type, arg] : llvm::zip_equal(blockArgTypes, args))
    block->addArgument(type, arg.getLoc());
}
 
/// Helper check if the distributed vector type is consistent with the expanded
/// type and distributed size.
static LogicalResult verifyDistributedType(Type expanded, Type distributed,
                                           int64_t warpSize, Operation *op) {
  // If the types matches there is no distribution.
  if (expanded == distributed)
    return success();
  auto expandedVecType = llvm::dyn_cast<VectorType>(expanded);
  auto distributedVecType = llvm::dyn_cast<VectorType>(distributed);
  if (!expandedVecType || !distributedVecType)
    return op->emitOpError("expected vector type for distributed operands.");
  if (expandedVecType.getRank() != distributedVecType.getRank() ||
      expandedVecType.getElementType() != distributedVecType.getElementType())
    return op->emitOpError(
        "expected distributed vectors to have same rank and element type.");
 
  SmallVector<int64_t> scales(expandedVecType.getRank(), 1);
  for (int64_t i = 0, e = expandedVecType.getRank(); i < e; i++) {
    int64_t eDim = expandedVecType.getDimSize(i);
    int64_t dDim = distributedVecType.getDimSize(i);
    if (eDim == dDim)
      continue;
    if (eDim % dDim != 0)
      return op->emitOpError()
             << "expected expanded vector dimension #" << i << " (" << eDim
             << ") to be a multipler of the distributed vector dimension ("
             << dDim << ")";
    scales[i] = eDim / dDim;
  }
  if (llvm::product_of(scales) != warpSize)
    return op->emitOpError()
           << "incompatible distribution dimensions from " << expandedVecType
           << " to " << distributedVecType << " with warp size = " << warpSize;
 
  return success();
}
 
LogicalResult WarpExecuteOnLane0Op::verify() {
  if (getArgs().size() != getWarpRegion().getNumArguments())
    return emitOpError(
        "expected same number op arguments and block arguments.");
  auto yield = dyn_cast<gpu::YieldOp>(getBody()->getTerminator());
  if (!yield)
    return emitOpError("expected body to be terminated with 'gpu.yield'");
  if (yield.getNumOperands() != getNumResults())
    return emitOpError(
        "expected same number of yield operands and return values.");
  int64_t warpSize = getWarpSize();
  for (auto [regionArg, arg] :
       llvm::zip_equal(getWarpRegion().getArguments(), getArgs())) {
    if (failed(verifyDistributedType(regionArg.getType(), arg.getType(),
                                     warpSize, getOperation())))
      return failure();
  }
  for (auto [yieldOperand, result] :
       llvm::zip_equal(yield.getOperands(), getResults())) {
    if (failed(verifyDistributedType(yieldOperand.getType(), result.getType(),
                                     warpSize, getOperation())))
      return failure();
  }
  return success();
}
bool WarpExecuteOnLane0Op::areTypesCompatible(Type lhs, Type rhs) {
  return succeeded(
      verifyDistributedType(lhs, rhs, getWarpSize(), getOperation()));
}
 
gpu::YieldOp WarpExecuteOnLane0Op::getTerminator() {
  return cast<gpu::YieldOp>(getBody()->getTerminator());
}
 
//===----------------------------------------------------------------------===//
// GPU_SubgroupBroadcastOp
//===----------------------------------------------------------------------===//
 
void gpu::SubgroupBroadcastOp::inferResultRanges(
    ArrayRef<ConstantIntRanges> argRanges, SetIntRangeFn setResultRange) {
  setResultRange(getResult(), argRanges.front());
}
 
Speculation::Speculatability gpu::SubgroupBroadcastOp::getSpeculatability() {
  switch (getBroadcastType()) {
  case BroadcastType::first_active_lane:
    // Cannot speculate first_lane broadcast, because speculating it across
    // control flow can change the active lanes.
    return Speculation::NotSpeculatable;
  case BroadcastType::specific_lane:
    // Speculation should be safe as long as we inside structured control flow.
    return Speculation::Speculatable;
  }
  llvm_unreachable("Unknown BroadcastType");
}
 
LogicalResult gpu::SubgroupBroadcastOp::verify() {
  switch (getBroadcastType()) {
  case BroadcastType::first_active_lane:
    if (getLane())
      return emitOpError()
             << "lane can only be specified for `specific_lane` broadcast";
    return success();
  case BroadcastType::specific_lane:
    if (!getLane())
      return emitOpError()
             << "lane must be specified for `specific_lane` broadcast";
    return success();
  }
  llvm_unreachable("Unknown BroadcastType");
}
 
OpFoldResult gpu::SubgroupBroadcastOp::fold(FoldAdaptor /*adaptor*/) {
  // Broadcast result is always uniform.
  if (auto prev = getSrc().getDefiningOp<SubgroupBroadcastOp>())
    return prev.getResult();
 
  return nullptr;
}
 
//===----------------------------------------------------------------------===//
// GPU_BallotOp
//===----------------------------------------------------------------------===//
 
// No custom implementations needed; ballot uses default behavior from ODS.
 
#include "mlir/Dialect/GPU/IR/GPUOpInterfaces.cpp.inc"
 
#define GET_OP_CLASSES
#include "mlir/Dialect/GPU/IR/GPUOps.cpp.inc"