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I am making a CG pass to depend on `FIROpenACCSupport` in #134346. This introduces a cyclic dependency between `FIROpenACCSupport` and `FIRCodeGen`. This patch splits `FIRCodeGen` into `FIRCodeGenDialect` (for FIR CG dialect definition) and `FIRCodeGen` (for the CG passes). Now, `FIROpenACCSupport` depends on `FIRCodeGenDialect`, and `FIRCodeGen` depends on `FIROpenACCSupport`.
4217 lines
180 KiB
C++
4217 lines
180 KiB
C++
//===-- CodeGen.cpp -- bridge to lower to LLVM ----------------------------===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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//
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// Coding style: https://mlir.llvm.org/getting_started/DeveloperGuide/
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//
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//===----------------------------------------------------------------------===//
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#include "flang/Optimizer/CodeGen/CodeGen.h"
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#include "flang/Optimizer/CodeGen/CodeGenOpenMP.h"
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#include "flang/Optimizer/CodeGen/FIROpPatterns.h"
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#include "flang/Optimizer/CodeGen/TypeConverter.h"
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#include "flang/Optimizer/Dialect/FIRAttr.h"
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#include "flang/Optimizer/Dialect/FIRCG/CGOps.h"
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#include "flang/Optimizer/Dialect/FIRDialect.h"
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#include "flang/Optimizer/Dialect/FIROps.h"
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#include "flang/Optimizer/Dialect/FIRType.h"
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#include "flang/Optimizer/Support/DataLayout.h"
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#include "flang/Optimizer/Support/InternalNames.h"
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#include "flang/Optimizer/Support/TypeCode.h"
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#include "flang/Optimizer/Support/Utils.h"
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#include "flang/Runtime/CUDA/descriptor.h"
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#include "flang/Runtime/CUDA/memory.h"
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#include "flang/Runtime/allocator-registry-consts.h"
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#include "flang/Runtime/descriptor-consts.h"
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#include "flang/Semantics/runtime-type-info.h"
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#include "mlir/Conversion/ArithCommon/AttrToLLVMConverter.h"
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#include "mlir/Conversion/ArithToLLVM/ArithToLLVM.h"
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#include "mlir/Conversion/ComplexToLLVM/ComplexToLLVM.h"
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#include "mlir/Conversion/ComplexToStandard/ComplexToStandard.h"
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#include "mlir/Conversion/ControlFlowToLLVM/ControlFlowToLLVM.h"
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#include "mlir/Conversion/FuncToLLVM/ConvertFuncToLLVM.h"
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#include "mlir/Conversion/LLVMCommon/Pattern.h"
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#include "mlir/Conversion/MathToFuncs/MathToFuncs.h"
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#include "mlir/Conversion/MathToLLVM/MathToLLVM.h"
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#include "mlir/Conversion/MathToLibm/MathToLibm.h"
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#include "mlir/Conversion/MathToROCDL/MathToROCDL.h"
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#include "mlir/Conversion/OpenMPToLLVM/ConvertOpenMPToLLVM.h"
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#include "mlir/Conversion/VectorToLLVM/ConvertVectorToLLVM.h"
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#include "mlir/Dialect/Arith/IR/Arith.h"
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#include "mlir/Dialect/DLTI/DLTI.h"
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#include "mlir/Dialect/GPU/IR/GPUDialect.h"
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#include "mlir/Dialect/LLVMIR/LLVMAttrs.h"
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#include "mlir/Dialect/LLVMIR/LLVMDialect.h"
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#include "mlir/Dialect/LLVMIR/NVVMDialect.h"
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#include "mlir/Dialect/LLVMIR/Transforms/AddComdats.h"
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#include "mlir/Dialect/OpenACC/OpenACC.h"
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#include "mlir/Dialect/OpenMP/OpenMPDialect.h"
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#include "mlir/IR/BuiltinTypes.h"
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#include "mlir/IR/Matchers.h"
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#include "mlir/Pass/Pass.h"
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#include "mlir/Pass/PassManager.h"
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#include "mlir/Target/LLVMIR/Import.h"
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#include "mlir/Target/LLVMIR/ModuleTranslation.h"
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#include "llvm/ADT/ArrayRef.h"
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#include "llvm/ADT/TypeSwitch.h"
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namespace fir {
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#define GEN_PASS_DEF_FIRTOLLVMLOWERING
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#include "flang/Optimizer/CodeGen/CGPasses.h.inc"
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} // namespace fir
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#define DEBUG_TYPE "flang-codegen"
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// TODO: This should really be recovered from the specified target.
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static constexpr unsigned defaultAlign = 8;
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/// `fir.box` attribute values as defined for CFI_attribute_t in
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/// flang/ISO_Fortran_binding.h.
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static constexpr unsigned kAttrPointer = CFI_attribute_pointer;
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static constexpr unsigned kAttrAllocatable = CFI_attribute_allocatable;
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static inline mlir::Type getLlvmPtrType(mlir::MLIRContext *context,
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unsigned addressSpace = 0) {
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return mlir::LLVM::LLVMPointerType::get(context, addressSpace);
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}
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static inline mlir::Type getI8Type(mlir::MLIRContext *context) {
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return mlir::IntegerType::get(context, 8);
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}
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static mlir::LLVM::ConstantOp
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genConstantIndex(mlir::Location loc, mlir::Type ity,
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mlir::ConversionPatternRewriter &rewriter,
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std::int64_t offset) {
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auto cattr = rewriter.getI64IntegerAttr(offset);
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return rewriter.create<mlir::LLVM::ConstantOp>(loc, ity, cattr);
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}
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static mlir::Block *createBlock(mlir::ConversionPatternRewriter &rewriter,
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mlir::Block *insertBefore) {
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assert(insertBefore && "expected valid insertion block");
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return rewriter.createBlock(insertBefore->getParent(),
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mlir::Region::iterator(insertBefore));
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}
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/// Extract constant from a value that must be the result of one of the
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/// ConstantOp operations.
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static int64_t getConstantIntValue(mlir::Value val) {
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if (auto constVal = fir::getIntIfConstant(val))
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return *constVal;
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fir::emitFatalError(val.getLoc(), "must be a constant");
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}
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static unsigned getTypeDescFieldId(mlir::Type ty) {
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auto isArray = mlir::isa<fir::SequenceType>(fir::dyn_cast_ptrOrBoxEleTy(ty));
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return isArray ? kOptTypePtrPosInBox : kDimsPosInBox;
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}
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static unsigned getLenParamFieldId(mlir::Type ty) {
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return getTypeDescFieldId(ty) + 1;
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}
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static llvm::SmallVector<mlir::NamedAttribute>
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addLLVMOpBundleAttrs(mlir::ConversionPatternRewriter &rewriter,
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llvm::ArrayRef<mlir::NamedAttribute> attrs,
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int32_t numCallOperands) {
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llvm::SmallVector<mlir::NamedAttribute> newAttrs;
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newAttrs.reserve(attrs.size() + 2);
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for (mlir::NamedAttribute attr : attrs) {
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if (attr.getName() != "operandSegmentSizes")
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newAttrs.push_back(attr);
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}
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newAttrs.push_back(rewriter.getNamedAttr(
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"operandSegmentSizes",
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rewriter.getDenseI32ArrayAttr({numCallOperands, 0})));
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newAttrs.push_back(rewriter.getNamedAttr("op_bundle_sizes",
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rewriter.getDenseI32ArrayAttr({})));
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return newAttrs;
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}
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namespace {
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/// Lower `fir.address_of` operation to `llvm.address_of` operation.
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struct AddrOfOpConversion : public fir::FIROpConversion<fir::AddrOfOp> {
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using FIROpConversion::FIROpConversion;
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llvm::LogicalResult
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matchAndRewrite(fir::AddrOfOp addr, OpAdaptor adaptor,
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mlir::ConversionPatternRewriter &rewriter) const override {
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auto ty = convertType(addr.getType());
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rewriter.replaceOpWithNewOp<mlir::LLVM::AddressOfOp>(
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addr, ty, addr.getSymbol().getRootReference().getValue());
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return mlir::success();
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}
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};
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} // namespace
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/// Lookup the function to compute the memory size of this parametric derived
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/// type. The size of the object may depend on the LEN type parameters of the
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/// derived type.
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static mlir::LLVM::LLVMFuncOp
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getDependentTypeMemSizeFn(fir::RecordType recTy, fir::AllocaOp op,
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mlir::ConversionPatternRewriter &rewriter) {
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auto module = op->getParentOfType<mlir::ModuleOp>();
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std::string name = recTy.getName().str() + "P.mem.size";
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if (auto memSizeFunc = module.lookupSymbol<mlir::LLVM::LLVMFuncOp>(name))
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return memSizeFunc;
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TODO(op.getLoc(), "did not find allocation function");
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}
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// Compute the alloc scale size (constant factors encoded in the array type).
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// We do this for arrays without a constant interior or arrays of character with
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// dynamic length arrays, since those are the only ones that get decayed to a
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// pointer to the element type.
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template <typename OP>
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static mlir::Value
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genAllocationScaleSize(OP op, mlir::Type ity,
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mlir::ConversionPatternRewriter &rewriter) {
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mlir::Location loc = op.getLoc();
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mlir::Type dataTy = op.getInType();
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auto seqTy = mlir::dyn_cast<fir::SequenceType>(dataTy);
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fir::SequenceType::Extent constSize = 1;
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if (seqTy) {
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int constRows = seqTy.getConstantRows();
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const fir::SequenceType::ShapeRef &shape = seqTy.getShape();
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if (constRows != static_cast<int>(shape.size())) {
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for (auto extent : shape) {
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if (constRows-- > 0)
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continue;
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if (extent != fir::SequenceType::getUnknownExtent())
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constSize *= extent;
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}
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}
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}
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if (constSize != 1) {
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mlir::Value constVal{
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genConstantIndex(loc, ity, rewriter, constSize).getResult()};
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return constVal;
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}
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return nullptr;
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}
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namespace {
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struct DeclareOpConversion : public fir::FIROpConversion<fir::cg::XDeclareOp> {
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public:
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using FIROpConversion::FIROpConversion;
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llvm::LogicalResult
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matchAndRewrite(fir::cg::XDeclareOp declareOp, OpAdaptor adaptor,
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mlir::ConversionPatternRewriter &rewriter) const override {
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auto memRef = adaptor.getOperands()[0];
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if (auto fusedLoc = mlir::dyn_cast<mlir::FusedLoc>(declareOp.getLoc())) {
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if (auto varAttr =
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mlir::dyn_cast_or_null<mlir::LLVM::DILocalVariableAttr>(
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fusedLoc.getMetadata())) {
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rewriter.create<mlir::LLVM::DbgDeclareOp>(memRef.getLoc(), memRef,
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varAttr, nullptr);
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}
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}
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rewriter.replaceOp(declareOp, memRef);
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return mlir::success();
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}
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};
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} // namespace
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namespace {
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/// convert to LLVM IR dialect `alloca`
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struct AllocaOpConversion : public fir::FIROpConversion<fir::AllocaOp> {
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using FIROpConversion::FIROpConversion;
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llvm::LogicalResult
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matchAndRewrite(fir::AllocaOp alloc, OpAdaptor adaptor,
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mlir::ConversionPatternRewriter &rewriter) const override {
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mlir::ValueRange operands = adaptor.getOperands();
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auto loc = alloc.getLoc();
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mlir::Type ity = lowerTy().indexType();
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unsigned i = 0;
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mlir::Value size = genConstantIndex(loc, ity, rewriter, 1).getResult();
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mlir::Type firObjType = fir::unwrapRefType(alloc.getType());
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mlir::Type llvmObjectType = convertObjectType(firObjType);
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if (alloc.hasLenParams()) {
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unsigned end = alloc.numLenParams();
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llvm::SmallVector<mlir::Value> lenParams;
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for (; i < end; ++i)
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lenParams.push_back(operands[i]);
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mlir::Type scalarType = fir::unwrapSequenceType(alloc.getInType());
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if (auto chrTy = mlir::dyn_cast<fir::CharacterType>(scalarType)) {
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fir::CharacterType rawCharTy = fir::CharacterType::getUnknownLen(
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chrTy.getContext(), chrTy.getFKind());
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llvmObjectType = convertType(rawCharTy);
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assert(end == 1);
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size = integerCast(loc, rewriter, ity, lenParams[0], /*fold=*/true);
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} else if (auto recTy = mlir::dyn_cast<fir::RecordType>(scalarType)) {
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mlir::LLVM::LLVMFuncOp memSizeFn =
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getDependentTypeMemSizeFn(recTy, alloc, rewriter);
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if (!memSizeFn)
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emitError(loc, "did not find allocation function");
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mlir::NamedAttribute attr = rewriter.getNamedAttr(
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"callee", mlir::SymbolRefAttr::get(memSizeFn));
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auto call = rewriter.create<mlir::LLVM::CallOp>(
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loc, ity, lenParams,
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addLLVMOpBundleAttrs(rewriter, {attr}, lenParams.size()));
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size = call.getResult();
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llvmObjectType = ::getI8Type(alloc.getContext());
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} else {
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return emitError(loc, "unexpected type ")
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<< scalarType << " with type parameters";
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}
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}
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if (auto scaleSize = genAllocationScaleSize(alloc, ity, rewriter))
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size =
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rewriter.createOrFold<mlir::LLVM::MulOp>(loc, ity, size, scaleSize);
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if (alloc.hasShapeOperands()) {
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unsigned end = operands.size();
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for (; i < end; ++i)
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size = rewriter.createOrFold<mlir::LLVM::MulOp>(
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loc, ity, size,
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integerCast(loc, rewriter, ity, operands[i], /*fold=*/true));
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}
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unsigned allocaAs = getAllocaAddressSpace(rewriter);
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unsigned programAs = getProgramAddressSpace(rewriter);
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if (mlir::isa<mlir::LLVM::ConstantOp>(size.getDefiningOp())) {
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// Set the Block in which the llvm alloca should be inserted.
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mlir::Operation *parentOp = rewriter.getInsertionBlock()->getParentOp();
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mlir::Region *parentRegion = rewriter.getInsertionBlock()->getParent();
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mlir::Block *insertBlock =
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getBlockForAllocaInsert(parentOp, parentRegion);
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// The old size might have had multiple users, some at a broader scope
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// than we can safely outline the alloca to. As it is only an
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// llvm.constant operation, it is faster to clone it than to calculate the
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// dominance to see if it really should be moved.
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mlir::Operation *clonedSize = rewriter.clone(*size.getDefiningOp());
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size = clonedSize->getResult(0);
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clonedSize->moveBefore(&insertBlock->front());
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rewriter.setInsertionPointAfter(size.getDefiningOp());
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}
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// NOTE: we used to pass alloc->getAttrs() in the builder for non opaque
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// pointers! Only propagate pinned and bindc_name to help debugging, but
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// this should have no functional purpose (and passing the operand segment
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// attribute like before is certainly bad).
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auto llvmAlloc = rewriter.create<mlir::LLVM::AllocaOp>(
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loc, ::getLlvmPtrType(alloc.getContext(), allocaAs), llvmObjectType,
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size);
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if (alloc.getPinned())
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llvmAlloc->setDiscardableAttr(alloc.getPinnedAttrName(),
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alloc.getPinnedAttr());
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if (alloc.getBindcName())
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llvmAlloc->setDiscardableAttr(alloc.getBindcNameAttrName(),
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alloc.getBindcNameAttr());
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if (allocaAs == programAs) {
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rewriter.replaceOp(alloc, llvmAlloc);
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} else {
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// if our allocation address space, is not the same as the program address
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// space, then we must emit a cast to the program address space before
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// use. An example case would be on AMDGPU, where the allocation address
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// space is the numeric value 5 (private), and the program address space
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// is 0 (generic).
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rewriter.replaceOpWithNewOp<mlir::LLVM::AddrSpaceCastOp>(
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alloc, ::getLlvmPtrType(alloc.getContext(), programAs), llvmAlloc);
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}
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return mlir::success();
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}
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};
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} // namespace
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namespace {
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/// Lower `fir.box_addr` to the sequence of operations to extract the first
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/// element of the box.
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struct BoxAddrOpConversion : public fir::FIROpConversion<fir::BoxAddrOp> {
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using FIROpConversion::FIROpConversion;
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llvm::LogicalResult
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matchAndRewrite(fir::BoxAddrOp boxaddr, OpAdaptor adaptor,
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mlir::ConversionPatternRewriter &rewriter) const override {
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mlir::Value a = adaptor.getOperands()[0];
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auto loc = boxaddr.getLoc();
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if (auto argty =
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mlir::dyn_cast<fir::BaseBoxType>(boxaddr.getVal().getType())) {
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TypePair boxTyPair = getBoxTypePair(argty);
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rewriter.replaceOp(boxaddr,
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getBaseAddrFromBox(loc, boxTyPair, a, rewriter));
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} else {
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rewriter.replaceOpWithNewOp<mlir::LLVM::ExtractValueOp>(boxaddr, a, 0);
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}
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return mlir::success();
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}
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};
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/// Convert `!fir.boxchar_len` to `!llvm.extractvalue` for the 2nd part of the
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/// boxchar.
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struct BoxCharLenOpConversion : public fir::FIROpConversion<fir::BoxCharLenOp> {
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using FIROpConversion::FIROpConversion;
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llvm::LogicalResult
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matchAndRewrite(fir::BoxCharLenOp boxCharLen, OpAdaptor adaptor,
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mlir::ConversionPatternRewriter &rewriter) const override {
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mlir::Value boxChar = adaptor.getOperands()[0];
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mlir::Location loc = boxChar.getLoc();
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mlir::Type returnValTy = boxCharLen.getResult().getType();
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constexpr int boxcharLenIdx = 1;
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auto len = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, boxChar,
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boxcharLenIdx);
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mlir::Value lenAfterCast = integerCast(loc, rewriter, returnValTy, len);
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rewriter.replaceOp(boxCharLen, lenAfterCast);
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return mlir::success();
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}
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};
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/// Lower `fir.box_dims` to a sequence of operations to extract the requested
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/// dimension information from the boxed value.
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/// Result in a triple set of GEPs and loads.
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struct BoxDimsOpConversion : public fir::FIROpConversion<fir::BoxDimsOp> {
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using FIROpConversion::FIROpConversion;
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llvm::LogicalResult
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matchAndRewrite(fir::BoxDimsOp boxdims, OpAdaptor adaptor,
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mlir::ConversionPatternRewriter &rewriter) const override {
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llvm::SmallVector<mlir::Type, 3> resultTypes = {
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convertType(boxdims.getResult(0).getType()),
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convertType(boxdims.getResult(1).getType()),
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convertType(boxdims.getResult(2).getType()),
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};
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TypePair boxTyPair = getBoxTypePair(boxdims.getVal().getType());
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auto results = getDimsFromBox(boxdims.getLoc(), resultTypes, boxTyPair,
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adaptor.getOperands()[0],
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adaptor.getOperands()[1], rewriter);
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rewriter.replaceOp(boxdims, results);
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return mlir::success();
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}
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};
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/// Lower `fir.box_elesize` to a sequence of operations ro extract the size of
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/// an element in the boxed value.
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struct BoxEleSizeOpConversion : public fir::FIROpConversion<fir::BoxEleSizeOp> {
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using FIROpConversion::FIROpConversion;
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llvm::LogicalResult
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matchAndRewrite(fir::BoxEleSizeOp boxelesz, OpAdaptor adaptor,
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mlir::ConversionPatternRewriter &rewriter) const override {
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mlir::Value box = adaptor.getOperands()[0];
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auto loc = boxelesz.getLoc();
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auto ty = convertType(boxelesz.getType());
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TypePair boxTyPair = getBoxTypePair(boxelesz.getVal().getType());
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auto elemSize = getElementSizeFromBox(loc, ty, boxTyPair, box, rewriter);
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rewriter.replaceOp(boxelesz, elemSize);
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return mlir::success();
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}
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};
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|
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/// Lower `fir.box_isalloc` to a sequence of operations to determine if the
|
|
/// boxed value was from an ALLOCATABLE entity.
|
|
struct BoxIsAllocOpConversion : public fir::FIROpConversion<fir::BoxIsAllocOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::BoxIsAllocOp boxisalloc, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
mlir::Value box = adaptor.getOperands()[0];
|
|
auto loc = boxisalloc.getLoc();
|
|
TypePair boxTyPair = getBoxTypePair(boxisalloc.getVal().getType());
|
|
mlir::Value check =
|
|
genBoxAttributeCheck(loc, boxTyPair, box, rewriter, kAttrAllocatable);
|
|
rewriter.replaceOp(boxisalloc, check);
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
/// Lower `fir.box_isarray` to a sequence of operations to determine if the
|
|
/// boxed is an array.
|
|
struct BoxIsArrayOpConversion : public fir::FIROpConversion<fir::BoxIsArrayOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::BoxIsArrayOp boxisarray, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
mlir::Value a = adaptor.getOperands()[0];
|
|
auto loc = boxisarray.getLoc();
|
|
TypePair boxTyPair = getBoxTypePair(boxisarray.getVal().getType());
|
|
mlir::Value rank = getRankFromBox(loc, boxTyPair, a, rewriter);
|
|
mlir::Value c0 = genConstantIndex(loc, rank.getType(), rewriter, 0);
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::ICmpOp>(
|
|
boxisarray, mlir::LLVM::ICmpPredicate::ne, rank, c0);
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
/// Lower `fir.box_isptr` to a sequence of operations to determined if the
|
|
/// boxed value was from a POINTER entity.
|
|
struct BoxIsPtrOpConversion : public fir::FIROpConversion<fir::BoxIsPtrOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::BoxIsPtrOp boxisptr, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
mlir::Value box = adaptor.getOperands()[0];
|
|
auto loc = boxisptr.getLoc();
|
|
TypePair boxTyPair = getBoxTypePair(boxisptr.getVal().getType());
|
|
mlir::Value check =
|
|
genBoxAttributeCheck(loc, boxTyPair, box, rewriter, kAttrPointer);
|
|
rewriter.replaceOp(boxisptr, check);
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
/// Lower `fir.box_rank` to the sequence of operation to extract the rank from
|
|
/// the box.
|
|
struct BoxRankOpConversion : public fir::FIROpConversion<fir::BoxRankOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::BoxRankOp boxrank, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
mlir::Value a = adaptor.getOperands()[0];
|
|
auto loc = boxrank.getLoc();
|
|
mlir::Type ty = convertType(boxrank.getType());
|
|
TypePair boxTyPair =
|
|
getBoxTypePair(fir::unwrapRefType(boxrank.getBox().getType()));
|
|
mlir::Value rank = getRankFromBox(loc, boxTyPair, a, rewriter);
|
|
mlir::Value result = integerCast(loc, rewriter, ty, rank);
|
|
rewriter.replaceOp(boxrank, result);
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
/// Lower `fir.boxproc_host` operation. Extracts the host pointer from the
|
|
/// boxproc.
|
|
/// TODO: Part of supporting Fortran 2003 procedure pointers.
|
|
struct BoxProcHostOpConversion
|
|
: public fir::FIROpConversion<fir::BoxProcHostOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::BoxProcHostOp boxprochost, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
TODO(boxprochost.getLoc(), "fir.boxproc_host codegen");
|
|
return mlir::failure();
|
|
}
|
|
};
|
|
|
|
/// Lower `fir.box_tdesc` to the sequence of operations to extract the type
|
|
/// descriptor from the box.
|
|
struct BoxTypeDescOpConversion
|
|
: public fir::FIROpConversion<fir::BoxTypeDescOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::BoxTypeDescOp boxtypedesc, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
mlir::Value box = adaptor.getOperands()[0];
|
|
TypePair boxTyPair = getBoxTypePair(boxtypedesc.getBox().getType());
|
|
auto typeDescAddr =
|
|
loadTypeDescAddress(boxtypedesc.getLoc(), boxTyPair, box, rewriter);
|
|
rewriter.replaceOp(boxtypedesc, typeDescAddr);
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
/// Lower `fir.box_typecode` to a sequence of operations to extract the type
|
|
/// code in the boxed value.
|
|
struct BoxTypeCodeOpConversion
|
|
: public fir::FIROpConversion<fir::BoxTypeCodeOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::BoxTypeCodeOp op, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
mlir::Value box = adaptor.getOperands()[0];
|
|
auto loc = box.getLoc();
|
|
auto ty = convertType(op.getType());
|
|
TypePair boxTyPair = getBoxTypePair(op.getBox().getType());
|
|
auto typeCode =
|
|
getValueFromBox(loc, boxTyPair, box, ty, rewriter, kTypePosInBox);
|
|
rewriter.replaceOp(op, typeCode);
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
/// Lower `fir.string_lit` to LLVM IR dialect operation.
|
|
struct StringLitOpConversion : public fir::FIROpConversion<fir::StringLitOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::StringLitOp constop, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
auto ty = convertType(constop.getType());
|
|
auto attr = constop.getValue();
|
|
if (mlir::isa<mlir::StringAttr>(attr)) {
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::ConstantOp>(constop, ty, attr);
|
|
return mlir::success();
|
|
}
|
|
|
|
auto charTy = mlir::cast<fir::CharacterType>(constop.getType());
|
|
unsigned bits = lowerTy().characterBitsize(charTy);
|
|
mlir::Type intTy = rewriter.getIntegerType(bits);
|
|
mlir::Location loc = constop.getLoc();
|
|
mlir::Value cst = rewriter.create<mlir::LLVM::UndefOp>(loc, ty);
|
|
if (auto arr = mlir::dyn_cast<mlir::DenseElementsAttr>(attr)) {
|
|
cst = rewriter.create<mlir::LLVM::ConstantOp>(loc, ty, arr);
|
|
} else if (auto arr = mlir::dyn_cast<mlir::ArrayAttr>(attr)) {
|
|
for (auto a : llvm::enumerate(arr.getValue())) {
|
|
// convert each character to a precise bitsize
|
|
auto elemAttr = mlir::IntegerAttr::get(
|
|
intTy,
|
|
mlir::cast<mlir::IntegerAttr>(a.value()).getValue().zextOrTrunc(
|
|
bits));
|
|
auto elemCst =
|
|
rewriter.create<mlir::LLVM::ConstantOp>(loc, intTy, elemAttr);
|
|
cst = rewriter.create<mlir::LLVM::InsertValueOp>(loc, cst, elemCst,
|
|
a.index());
|
|
}
|
|
} else {
|
|
return mlir::failure();
|
|
}
|
|
rewriter.replaceOp(constop, cst);
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
/// `fir.call` -> `llvm.call`
|
|
struct CallOpConversion : public fir::FIROpConversion<fir::CallOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::CallOp call, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
llvm::SmallVector<mlir::Type> resultTys;
|
|
mlir::Attribute memAttr =
|
|
call->getAttr(fir::FIROpsDialect::getFirCallMemoryAttrName());
|
|
if (memAttr)
|
|
call->removeAttr(fir::FIROpsDialect::getFirCallMemoryAttrName());
|
|
|
|
for (auto r : call.getResults())
|
|
resultTys.push_back(convertType(r.getType()));
|
|
// Convert arith::FastMathFlagsAttr to LLVM::FastMathFlagsAttr.
|
|
mlir::arith::AttrConvertFastMathToLLVM<fir::CallOp, mlir::LLVM::CallOp>
|
|
attrConvert(call);
|
|
auto llvmCall = rewriter.replaceOpWithNewOp<mlir::LLVM::CallOp>(
|
|
call, resultTys, adaptor.getOperands(),
|
|
addLLVMOpBundleAttrs(rewriter, attrConvert.getAttrs(),
|
|
adaptor.getOperands().size()));
|
|
if (mlir::ArrayAttr argAttrsArray = call.getArgAttrsAttr()) {
|
|
// sret and byval type needs to be converted.
|
|
auto convertTypeAttr = [&](const mlir::NamedAttribute &attr) {
|
|
return mlir::TypeAttr::get(convertType(
|
|
llvm::cast<mlir::TypeAttr>(attr.getValue()).getValue()));
|
|
};
|
|
llvm::SmallVector<mlir::Attribute> newArgAttrsArray;
|
|
for (auto argAttrs : argAttrsArray) {
|
|
llvm::SmallVector<mlir::NamedAttribute> convertedAttrs;
|
|
for (const mlir::NamedAttribute &attr :
|
|
llvm::cast<mlir::DictionaryAttr>(argAttrs)) {
|
|
if (attr.getName().getValue() ==
|
|
mlir::LLVM::LLVMDialect::getByValAttrName()) {
|
|
convertedAttrs.push_back(rewriter.getNamedAttr(
|
|
mlir::LLVM::LLVMDialect::getByValAttrName(),
|
|
convertTypeAttr(attr)));
|
|
} else if (attr.getName().getValue() ==
|
|
mlir::LLVM::LLVMDialect::getStructRetAttrName()) {
|
|
convertedAttrs.push_back(rewriter.getNamedAttr(
|
|
mlir::LLVM::LLVMDialect::getStructRetAttrName(),
|
|
convertTypeAttr(attr)));
|
|
} else {
|
|
convertedAttrs.push_back(attr);
|
|
}
|
|
}
|
|
newArgAttrsArray.emplace_back(
|
|
mlir::DictionaryAttr::get(rewriter.getContext(), convertedAttrs));
|
|
}
|
|
llvmCall.setArgAttrsAttr(rewriter.getArrayAttr(newArgAttrsArray));
|
|
}
|
|
if (mlir::ArrayAttr resAttrs = call.getResAttrsAttr())
|
|
llvmCall.setResAttrsAttr(resAttrs);
|
|
|
|
if (memAttr)
|
|
llvmCall.setMemoryEffectsAttr(
|
|
mlir::cast<mlir::LLVM::MemoryEffectsAttr>(memAttr));
|
|
return mlir::success();
|
|
}
|
|
};
|
|
} // namespace
|
|
|
|
static mlir::Type getComplexEleTy(mlir::Type complex) {
|
|
return mlir::cast<mlir::ComplexType>(complex).getElementType();
|
|
}
|
|
|
|
namespace {
|
|
/// Compare complex values
|
|
///
|
|
/// Per 10.1, the only comparisons available are .EQ. (oeq) and .NE. (une).
|
|
///
|
|
/// For completeness, all other comparison are done on the real component only.
|
|
struct CmpcOpConversion : public fir::FIROpConversion<fir::CmpcOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::CmpcOp cmp, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
mlir::ValueRange operands = adaptor.getOperands();
|
|
mlir::Type resTy = convertType(cmp.getType());
|
|
mlir::Location loc = cmp.getLoc();
|
|
mlir::LLVM::FastmathFlags fmf =
|
|
mlir::arith::convertArithFastMathFlagsToLLVM(cmp.getFastmath());
|
|
mlir::LLVM::FCmpPredicate pred =
|
|
static_cast<mlir::LLVM::FCmpPredicate>(cmp.getPredicate());
|
|
auto rcp = rewriter.create<mlir::LLVM::FCmpOp>(
|
|
loc, resTy, pred,
|
|
rewriter.create<mlir::LLVM::ExtractValueOp>(loc, operands[0], 0),
|
|
rewriter.create<mlir::LLVM::ExtractValueOp>(loc, operands[1], 0), fmf);
|
|
auto icp = rewriter.create<mlir::LLVM::FCmpOp>(
|
|
loc, resTy, pred,
|
|
rewriter.create<mlir::LLVM::ExtractValueOp>(loc, operands[0], 1),
|
|
rewriter.create<mlir::LLVM::ExtractValueOp>(loc, operands[1], 1), fmf);
|
|
llvm::SmallVector<mlir::Value, 2> cp = {rcp, icp};
|
|
switch (cmp.getPredicate()) {
|
|
case mlir::arith::CmpFPredicate::OEQ: // .EQ.
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::AndOp>(cmp, resTy, cp);
|
|
break;
|
|
case mlir::arith::CmpFPredicate::UNE: // .NE.
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::OrOp>(cmp, resTy, cp);
|
|
break;
|
|
default:
|
|
rewriter.replaceOp(cmp, rcp.getResult());
|
|
break;
|
|
}
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
/// convert value of from-type to value of to-type
|
|
struct ConvertOpConversion : public fir::FIROpConversion<fir::ConvertOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
static bool isFloatingPointTy(mlir::Type ty) {
|
|
return mlir::isa<mlir::FloatType>(ty);
|
|
}
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::ConvertOp convert, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
auto fromFirTy = convert.getValue().getType();
|
|
auto toFirTy = convert.getRes().getType();
|
|
auto fromTy = convertType(fromFirTy);
|
|
auto toTy = convertType(toFirTy);
|
|
mlir::Value op0 = adaptor.getOperands()[0];
|
|
|
|
if (fromFirTy == toFirTy) {
|
|
rewriter.replaceOp(convert, op0);
|
|
return mlir::success();
|
|
}
|
|
|
|
auto loc = convert.getLoc();
|
|
auto i1Type = mlir::IntegerType::get(convert.getContext(), 1);
|
|
|
|
if (mlir::isa<fir::RecordType>(toFirTy)) {
|
|
// Convert to compatible BIND(C) record type.
|
|
// Double check that the record types are compatible (it should have
|
|
// already been checked by the verifier).
|
|
assert(mlir::cast<fir::RecordType>(fromFirTy).getTypeList() ==
|
|
mlir::cast<fir::RecordType>(toFirTy).getTypeList() &&
|
|
"incompatible record types");
|
|
|
|
auto toStTy = mlir::cast<mlir::LLVM::LLVMStructType>(toTy);
|
|
mlir::Value val = rewriter.create<mlir::LLVM::UndefOp>(loc, toStTy);
|
|
auto indexTypeMap = toStTy.getSubelementIndexMap();
|
|
assert(indexTypeMap.has_value() && "invalid record type");
|
|
|
|
for (auto [attr, type] : indexTypeMap.value()) {
|
|
int64_t index = mlir::cast<mlir::IntegerAttr>(attr).getInt();
|
|
auto extVal =
|
|
rewriter.create<mlir::LLVM::ExtractValueOp>(loc, op0, index);
|
|
val =
|
|
rewriter.create<mlir::LLVM::InsertValueOp>(loc, val, extVal, index);
|
|
}
|
|
|
|
rewriter.replaceOp(convert, val);
|
|
return mlir::success();
|
|
}
|
|
|
|
if (mlir::isa<fir::LogicalType>(fromFirTy) ||
|
|
mlir::isa<fir::LogicalType>(toFirTy)) {
|
|
// By specification fir::LogicalType value may be any number,
|
|
// where non-zero value represents .true. and zero value represents
|
|
// .false.
|
|
//
|
|
// integer<->logical conversion requires value normalization.
|
|
// Conversion from wide logical to narrow logical must set the result
|
|
// to non-zero iff the input is non-zero - the easiest way to implement
|
|
// it is to compare the input agains zero and set the result to
|
|
// the canonical 0/1.
|
|
// Conversion from narrow logical to wide logical may be implemented
|
|
// as a zero or sign extension of the input, but it may use value
|
|
// normalization as well.
|
|
if (!mlir::isa<mlir::IntegerType>(fromTy) ||
|
|
!mlir::isa<mlir::IntegerType>(toTy))
|
|
return mlir::emitError(loc)
|
|
<< "unsupported types for logical conversion: " << fromTy
|
|
<< " -> " << toTy;
|
|
|
|
// Do folding for constant inputs.
|
|
if (auto constVal = fir::getIntIfConstant(op0)) {
|
|
mlir::Value normVal =
|
|
genConstantIndex(loc, toTy, rewriter, *constVal ? 1 : 0);
|
|
rewriter.replaceOp(convert, normVal);
|
|
return mlir::success();
|
|
}
|
|
|
|
// If the input is i1, then we can just zero extend it, and
|
|
// the result will be normalized.
|
|
if (fromTy == i1Type) {
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::ZExtOp>(convert, toTy, op0);
|
|
return mlir::success();
|
|
}
|
|
|
|
// Compare the input with zero.
|
|
mlir::Value zero = genConstantIndex(loc, fromTy, rewriter, 0);
|
|
auto isTrue = rewriter.create<mlir::LLVM::ICmpOp>(
|
|
loc, mlir::LLVM::ICmpPredicate::ne, op0, zero);
|
|
|
|
// Zero extend the i1 isTrue result to the required type (unless it is i1
|
|
// itself).
|
|
if (toTy != i1Type)
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::ZExtOp>(convert, toTy, isTrue);
|
|
else
|
|
rewriter.replaceOp(convert, isTrue.getResult());
|
|
|
|
return mlir::success();
|
|
}
|
|
|
|
if (fromTy == toTy) {
|
|
rewriter.replaceOp(convert, op0);
|
|
return mlir::success();
|
|
}
|
|
auto convertFpToFp = [&](mlir::Value val, unsigned fromBits,
|
|
unsigned toBits, mlir::Type toTy) -> mlir::Value {
|
|
if (fromBits == toBits) {
|
|
// TODO: Converting between two floating-point representations with the
|
|
// same bitwidth is not allowed for now.
|
|
mlir::emitError(loc,
|
|
"cannot implicitly convert between two floating-point "
|
|
"representations of the same bitwidth");
|
|
return {};
|
|
}
|
|
if (fromBits > toBits)
|
|
return rewriter.create<mlir::LLVM::FPTruncOp>(loc, toTy, val);
|
|
return rewriter.create<mlir::LLVM::FPExtOp>(loc, toTy, val);
|
|
};
|
|
// Complex to complex conversion.
|
|
if (fir::isa_complex(fromFirTy) && fir::isa_complex(toFirTy)) {
|
|
// Special case: handle the conversion of a complex such that both the
|
|
// real and imaginary parts are converted together.
|
|
auto ty = convertType(getComplexEleTy(convert.getValue().getType()));
|
|
auto rp = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, op0, 0);
|
|
auto ip = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, op0, 1);
|
|
auto nt = convertType(getComplexEleTy(convert.getRes().getType()));
|
|
auto fromBits = mlir::LLVM::getPrimitiveTypeSizeInBits(ty);
|
|
auto toBits = mlir::LLVM::getPrimitiveTypeSizeInBits(nt);
|
|
auto rc = convertFpToFp(rp, fromBits, toBits, nt);
|
|
auto ic = convertFpToFp(ip, fromBits, toBits, nt);
|
|
auto un = rewriter.create<mlir::LLVM::UndefOp>(loc, toTy);
|
|
auto i1 = rewriter.create<mlir::LLVM::InsertValueOp>(loc, un, rc, 0);
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::InsertValueOp>(convert, i1, ic,
|
|
1);
|
|
return mlir::success();
|
|
}
|
|
|
|
// Floating point to floating point conversion.
|
|
if (isFloatingPointTy(fromTy)) {
|
|
if (isFloatingPointTy(toTy)) {
|
|
auto fromBits = mlir::LLVM::getPrimitiveTypeSizeInBits(fromTy);
|
|
auto toBits = mlir::LLVM::getPrimitiveTypeSizeInBits(toTy);
|
|
auto v = convertFpToFp(op0, fromBits, toBits, toTy);
|
|
rewriter.replaceOp(convert, v);
|
|
return mlir::success();
|
|
}
|
|
if (mlir::isa<mlir::IntegerType>(toTy)) {
|
|
// NOTE: We are checking the fir type here because toTy is an LLVM type
|
|
// which is signless, and we need to use the intrinsic that matches the
|
|
// sign of the output in fir.
|
|
if (toFirTy.isUnsignedInteger()) {
|
|
auto intrinsicName =
|
|
mlir::StringAttr::get(convert.getContext(), "llvm.fptoui.sat");
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::CallIntrinsicOp>(
|
|
convert, toTy, intrinsicName, op0);
|
|
} else {
|
|
auto intrinsicName =
|
|
mlir::StringAttr::get(convert.getContext(), "llvm.fptosi.sat");
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::CallIntrinsicOp>(
|
|
convert, toTy, intrinsicName, op0);
|
|
}
|
|
return mlir::success();
|
|
}
|
|
} else if (mlir::isa<mlir::IntegerType>(fromTy)) {
|
|
// Integer to integer conversion.
|
|
if (mlir::isa<mlir::IntegerType>(toTy)) {
|
|
auto fromBits = mlir::LLVM::getPrimitiveTypeSizeInBits(fromTy);
|
|
auto toBits = mlir::LLVM::getPrimitiveTypeSizeInBits(toTy);
|
|
assert(fromBits != toBits);
|
|
if (fromBits > toBits) {
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::TruncOp>(convert, toTy, op0);
|
|
return mlir::success();
|
|
}
|
|
if (fromFirTy == i1Type || fromFirTy.isUnsignedInteger()) {
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::ZExtOp>(convert, toTy, op0);
|
|
return mlir::success();
|
|
}
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::SExtOp>(convert, toTy, op0);
|
|
return mlir::success();
|
|
}
|
|
// Integer to floating point conversion.
|
|
if (isFloatingPointTy(toTy)) {
|
|
if (fromTy.isUnsignedInteger())
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::UIToFPOp>(convert, toTy, op0);
|
|
else
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::SIToFPOp>(convert, toTy, op0);
|
|
return mlir::success();
|
|
}
|
|
// Integer to pointer conversion.
|
|
if (mlir::isa<mlir::LLVM::LLVMPointerType>(toTy)) {
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::IntToPtrOp>(convert, toTy, op0);
|
|
return mlir::success();
|
|
}
|
|
} else if (mlir::isa<mlir::LLVM::LLVMPointerType>(fromTy)) {
|
|
// Pointer to integer conversion.
|
|
if (mlir::isa<mlir::IntegerType>(toTy)) {
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::PtrToIntOp>(convert, toTy, op0);
|
|
return mlir::success();
|
|
}
|
|
// Pointer to pointer conversion.
|
|
if (mlir::isa<mlir::LLVM::LLVMPointerType>(toTy)) {
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::BitcastOp>(convert, toTy, op0);
|
|
return mlir::success();
|
|
}
|
|
}
|
|
return emitError(loc) << "cannot convert " << fromTy << " to " << toTy;
|
|
}
|
|
};
|
|
|
|
/// `fir.type_info` operation has no specific CodeGen. The operation is
|
|
/// only used to carry information during FIR to FIR passes. It may be used
|
|
/// in the future to generate the runtime type info data structures instead
|
|
/// of generating them in lowering.
|
|
struct TypeInfoOpConversion : public fir::FIROpConversion<fir::TypeInfoOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::TypeInfoOp op, OpAdaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
rewriter.eraseOp(op);
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
/// `fir.dt_entry` operation has no specific CodeGen. The operation is only used
|
|
/// to carry information during FIR to FIR passes.
|
|
struct DTEntryOpConversion : public fir::FIROpConversion<fir::DTEntryOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::DTEntryOp op, OpAdaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
rewriter.eraseOp(op);
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
/// Lower `fir.global_len` operation.
|
|
struct GlobalLenOpConversion : public fir::FIROpConversion<fir::GlobalLenOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::GlobalLenOp globalLen, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
TODO(globalLen.getLoc(), "fir.global_len codegen");
|
|
return mlir::failure();
|
|
}
|
|
};
|
|
|
|
/// Lower fir.len_param_index
|
|
struct LenParamIndexOpConversion
|
|
: public fir::FIROpConversion<fir::LenParamIndexOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
// FIXME: this should be specialized by the runtime target
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::LenParamIndexOp lenp, OpAdaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
TODO(lenp.getLoc(), "fir.len_param_index codegen");
|
|
}
|
|
};
|
|
|
|
/// Convert `!fir.emboxchar<!fir.char<KIND, ?>, #n>` into a sequence of
|
|
/// instructions that generate `!llvm.struct<(ptr<ik>, i64)>`. The 1st element
|
|
/// in this struct is a pointer. Its type is determined from `KIND`. The 2nd
|
|
/// element is the length of the character buffer (`#n`).
|
|
struct EmboxCharOpConversion : public fir::FIROpConversion<fir::EmboxCharOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::EmboxCharOp emboxChar, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
mlir::ValueRange operands = adaptor.getOperands();
|
|
|
|
mlir::Value charBuffer = operands[0];
|
|
mlir::Value charBufferLen = operands[1];
|
|
|
|
mlir::Location loc = emboxChar.getLoc();
|
|
mlir::Type llvmStructTy = convertType(emboxChar.getType());
|
|
auto llvmStruct = rewriter.create<mlir::LLVM::UndefOp>(loc, llvmStructTy);
|
|
|
|
mlir::Type lenTy =
|
|
mlir::cast<mlir::LLVM::LLVMStructType>(llvmStructTy).getBody()[1];
|
|
mlir::Value lenAfterCast = integerCast(loc, rewriter, lenTy, charBufferLen);
|
|
|
|
mlir::Type addrTy =
|
|
mlir::cast<mlir::LLVM::LLVMStructType>(llvmStructTy).getBody()[0];
|
|
if (addrTy != charBuffer.getType())
|
|
charBuffer =
|
|
rewriter.create<mlir::LLVM::BitcastOp>(loc, addrTy, charBuffer);
|
|
|
|
auto insertBufferOp = rewriter.create<mlir::LLVM::InsertValueOp>(
|
|
loc, llvmStruct, charBuffer, 0);
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::InsertValueOp>(
|
|
emboxChar, insertBufferOp, lenAfterCast, 1);
|
|
|
|
return mlir::success();
|
|
}
|
|
};
|
|
} // namespace
|
|
|
|
template <typename ModuleOp>
|
|
static mlir::SymbolRefAttr
|
|
getMallocInModule(ModuleOp mod, fir::AllocMemOp op,
|
|
mlir::ConversionPatternRewriter &rewriter,
|
|
mlir::Type indexType) {
|
|
static constexpr char mallocName[] = "malloc";
|
|
if (auto mallocFunc =
|
|
mod.template lookupSymbol<mlir::LLVM::LLVMFuncOp>(mallocName))
|
|
return mlir::SymbolRefAttr::get(mallocFunc);
|
|
if (auto userMalloc =
|
|
mod.template lookupSymbol<mlir::func::FuncOp>(mallocName))
|
|
return mlir::SymbolRefAttr::get(userMalloc);
|
|
|
|
mlir::OpBuilder moduleBuilder(mod.getBodyRegion());
|
|
auto mallocDecl = moduleBuilder.create<mlir::LLVM::LLVMFuncOp>(
|
|
op.getLoc(), mallocName,
|
|
mlir::LLVM::LLVMFunctionType::get(getLlvmPtrType(op.getContext()),
|
|
indexType,
|
|
/*isVarArg=*/false));
|
|
return mlir::SymbolRefAttr::get(mallocDecl);
|
|
}
|
|
|
|
/// Return the LLVMFuncOp corresponding to the standard malloc call.
|
|
static mlir::SymbolRefAttr getMalloc(fir::AllocMemOp op,
|
|
mlir::ConversionPatternRewriter &rewriter,
|
|
mlir::Type indexType) {
|
|
if (auto mod = op->getParentOfType<mlir::gpu::GPUModuleOp>())
|
|
return getMallocInModule(mod, op, rewriter, indexType);
|
|
auto mod = op->getParentOfType<mlir::ModuleOp>();
|
|
return getMallocInModule(mod, op, rewriter, indexType);
|
|
}
|
|
|
|
/// Helper function for generating the LLVM IR that computes the distance
|
|
/// in bytes between adjacent elements pointed to by a pointer
|
|
/// of type \p ptrTy. The result is returned as a value of \p idxTy integer
|
|
/// type.
|
|
static mlir::Value
|
|
computeElementDistance(mlir::Location loc, mlir::Type llvmObjectType,
|
|
mlir::Type idxTy,
|
|
mlir::ConversionPatternRewriter &rewriter) {
|
|
// Note that we cannot use something like
|
|
// mlir::LLVM::getPrimitiveTypeSizeInBits() for the element type here. For
|
|
// example, it returns 10 bytes for mlir::Float80Type for targets where it
|
|
// occupies 16 bytes. Proper solution is probably to use
|
|
// mlir::DataLayout::getTypeABIAlignment(), but DataLayout is not being set
|
|
// yet (see llvm-project#57230). For the time being use the '(intptr_t)((type
|
|
// *)0 + 1)' trick for all types. The generated instructions are optimized
|
|
// into constant by the first pass of InstCombine, so it should not be a
|
|
// performance issue.
|
|
auto llvmPtrTy = ::getLlvmPtrType(llvmObjectType.getContext());
|
|
auto nullPtr = rewriter.create<mlir::LLVM::ZeroOp>(loc, llvmPtrTy);
|
|
auto gep = rewriter.create<mlir::LLVM::GEPOp>(
|
|
loc, llvmPtrTy, llvmObjectType, nullPtr,
|
|
llvm::ArrayRef<mlir::LLVM::GEPArg>{1});
|
|
return rewriter.create<mlir::LLVM::PtrToIntOp>(loc, idxTy, gep);
|
|
}
|
|
|
|
/// Return value of the stride in bytes between adjacent elements
|
|
/// of LLVM type \p llTy. The result is returned as a value of
|
|
/// \p idxTy integer type.
|
|
static mlir::Value
|
|
genTypeStrideInBytes(mlir::Location loc, mlir::Type idxTy,
|
|
mlir::ConversionPatternRewriter &rewriter,
|
|
mlir::Type llTy) {
|
|
// Create a pointer type and use computeElementDistance().
|
|
return computeElementDistance(loc, llTy, idxTy, rewriter);
|
|
}
|
|
|
|
namespace {
|
|
/// Lower a `fir.allocmem` instruction into `llvm.call @malloc`
|
|
struct AllocMemOpConversion : public fir::FIROpConversion<fir::AllocMemOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::AllocMemOp heap, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
mlir::Type heapTy = heap.getType();
|
|
mlir::Location loc = heap.getLoc();
|
|
auto ity = lowerTy().indexType();
|
|
mlir::Type dataTy = fir::unwrapRefType(heapTy);
|
|
mlir::Type llvmObjectTy = convertObjectType(dataTy);
|
|
if (fir::isRecordWithTypeParameters(fir::unwrapSequenceType(dataTy)))
|
|
TODO(loc, "fir.allocmem codegen of derived type with length parameters");
|
|
mlir::Value size = genTypeSizeInBytes(loc, ity, rewriter, llvmObjectTy);
|
|
if (auto scaleSize = genAllocationScaleSize(heap, ity, rewriter))
|
|
size = rewriter.create<mlir::LLVM::MulOp>(loc, ity, size, scaleSize);
|
|
for (mlir::Value opnd : adaptor.getOperands())
|
|
size = rewriter.create<mlir::LLVM::MulOp>(
|
|
loc, ity, size, integerCast(loc, rewriter, ity, opnd));
|
|
auto mallocTyWidth = lowerTy().getIndexTypeBitwidth();
|
|
auto mallocTy =
|
|
mlir::IntegerType::get(rewriter.getContext(), mallocTyWidth);
|
|
if (mallocTyWidth != ity.getIntOrFloatBitWidth())
|
|
size = integerCast(loc, rewriter, mallocTy, size);
|
|
heap->setAttr("callee", getMalloc(heap, rewriter, mallocTy));
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::CallOp>(
|
|
heap, ::getLlvmPtrType(heap.getContext()), size,
|
|
addLLVMOpBundleAttrs(rewriter, heap->getAttrs(), 1));
|
|
return mlir::success();
|
|
}
|
|
|
|
/// Compute the allocation size in bytes of the element type of
|
|
/// \p llTy pointer type. The result is returned as a value of \p idxTy
|
|
/// integer type.
|
|
mlir::Value genTypeSizeInBytes(mlir::Location loc, mlir::Type idxTy,
|
|
mlir::ConversionPatternRewriter &rewriter,
|
|
mlir::Type llTy) const {
|
|
return computeElementDistance(loc, llTy, idxTy, rewriter);
|
|
}
|
|
};
|
|
} // namespace
|
|
|
|
/// Return the LLVMFuncOp corresponding to the standard free call.
|
|
template <typename ModuleOp>
|
|
static mlir::SymbolRefAttr
|
|
getFreeInModule(ModuleOp mod, fir::FreeMemOp op,
|
|
mlir::ConversionPatternRewriter &rewriter) {
|
|
static constexpr char freeName[] = "free";
|
|
// Check if free already defined in the module.
|
|
if (auto freeFunc =
|
|
mod.template lookupSymbol<mlir::LLVM::LLVMFuncOp>(freeName))
|
|
return mlir::SymbolRefAttr::get(freeFunc);
|
|
if (auto freeDefinedByUser =
|
|
mod.template lookupSymbol<mlir::func::FuncOp>(freeName))
|
|
return mlir::SymbolRefAttr::get(freeDefinedByUser);
|
|
// Create llvm declaration for free.
|
|
mlir::OpBuilder moduleBuilder(mod.getBodyRegion());
|
|
auto voidType = mlir::LLVM::LLVMVoidType::get(op.getContext());
|
|
auto freeDecl = moduleBuilder.create<mlir::LLVM::LLVMFuncOp>(
|
|
rewriter.getUnknownLoc(), freeName,
|
|
mlir::LLVM::LLVMFunctionType::get(voidType,
|
|
getLlvmPtrType(op.getContext()),
|
|
/*isVarArg=*/false));
|
|
return mlir::SymbolRefAttr::get(freeDecl);
|
|
}
|
|
|
|
static mlir::SymbolRefAttr getFree(fir::FreeMemOp op,
|
|
mlir::ConversionPatternRewriter &rewriter) {
|
|
if (auto mod = op->getParentOfType<mlir::gpu::GPUModuleOp>())
|
|
return getFreeInModule(mod, op, rewriter);
|
|
auto mod = op->getParentOfType<mlir::ModuleOp>();
|
|
return getFreeInModule(mod, op, rewriter);
|
|
}
|
|
|
|
static unsigned getDimension(mlir::LLVM::LLVMArrayType ty) {
|
|
unsigned result = 1;
|
|
for (auto eleTy =
|
|
mlir::dyn_cast<mlir::LLVM::LLVMArrayType>(ty.getElementType());
|
|
eleTy; eleTy = mlir::dyn_cast<mlir::LLVM::LLVMArrayType>(
|
|
eleTy.getElementType()))
|
|
++result;
|
|
return result;
|
|
}
|
|
|
|
namespace {
|
|
/// Lower a `fir.freemem` instruction into `llvm.call @free`
|
|
struct FreeMemOpConversion : public fir::FIROpConversion<fir::FreeMemOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::FreeMemOp freemem, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
mlir::Location loc = freemem.getLoc();
|
|
freemem->setAttr("callee", getFree(freemem, rewriter));
|
|
rewriter.create<mlir::LLVM::CallOp>(
|
|
loc, mlir::TypeRange{}, mlir::ValueRange{adaptor.getHeapref()},
|
|
addLLVMOpBundleAttrs(rewriter, freemem->getAttrs(), 1));
|
|
rewriter.eraseOp(freemem);
|
|
return mlir::success();
|
|
}
|
|
};
|
|
} // namespace
|
|
|
|
// Convert subcomponent array indices from column-major to row-major ordering.
|
|
static llvm::SmallVector<mlir::Value>
|
|
convertSubcomponentIndices(mlir::Location loc, mlir::Type eleTy,
|
|
mlir::ValueRange indices,
|
|
mlir::Type *retTy = nullptr) {
|
|
llvm::SmallVector<mlir::Value> result;
|
|
llvm::SmallVector<mlir::Value> arrayIndices;
|
|
|
|
auto appendArrayIndices = [&] {
|
|
if (arrayIndices.empty())
|
|
return;
|
|
std::reverse(arrayIndices.begin(), arrayIndices.end());
|
|
result.append(arrayIndices.begin(), arrayIndices.end());
|
|
arrayIndices.clear();
|
|
};
|
|
|
|
for (mlir::Value index : indices) {
|
|
// Component indices can be field index to select a component, or array
|
|
// index, to select an element in an array component.
|
|
if (auto structTy = mlir::dyn_cast<mlir::LLVM::LLVMStructType>(eleTy)) {
|
|
std::int64_t cstIndex = getConstantIntValue(index);
|
|
assert(cstIndex < (int64_t)structTy.getBody().size() &&
|
|
"out-of-bounds struct field index");
|
|
eleTy = structTy.getBody()[cstIndex];
|
|
appendArrayIndices();
|
|
result.push_back(index);
|
|
} else if (auto arrayTy =
|
|
mlir::dyn_cast<mlir::LLVM::LLVMArrayType>(eleTy)) {
|
|
eleTy = arrayTy.getElementType();
|
|
arrayIndices.push_back(index);
|
|
} else
|
|
fir::emitFatalError(loc, "Unexpected subcomponent type");
|
|
}
|
|
appendArrayIndices();
|
|
if (retTy)
|
|
*retTy = eleTy;
|
|
return result;
|
|
}
|
|
|
|
static mlir::Value genSourceFile(mlir::Location loc, mlir::ModuleOp mod,
|
|
mlir::ConversionPatternRewriter &rewriter) {
|
|
auto ptrTy = mlir::LLVM::LLVMPointerType::get(rewriter.getContext());
|
|
if (auto flc = mlir::dyn_cast<mlir::FileLineColLoc>(loc)) {
|
|
auto fn = flc.getFilename().str() + '\0';
|
|
std::string globalName = fir::factory::uniqueCGIdent("cl", fn);
|
|
|
|
if (auto g = mod.lookupSymbol<fir::GlobalOp>(globalName)) {
|
|
return rewriter.create<mlir::LLVM::AddressOfOp>(loc, ptrTy, g.getName());
|
|
} else if (auto g = mod.lookupSymbol<mlir::LLVM::GlobalOp>(globalName)) {
|
|
return rewriter.create<mlir::LLVM::AddressOfOp>(loc, ptrTy, g.getName());
|
|
}
|
|
|
|
auto crtInsPt = rewriter.saveInsertionPoint();
|
|
rewriter.setInsertionPoint(mod.getBody(), mod.getBody()->end());
|
|
auto arrayTy = mlir::LLVM::LLVMArrayType::get(
|
|
mlir::IntegerType::get(rewriter.getContext(), 8), fn.size());
|
|
mlir::LLVM::GlobalOp globalOp = rewriter.create<mlir::LLVM::GlobalOp>(
|
|
loc, arrayTy, /*constant=*/true, mlir::LLVM::Linkage::Linkonce,
|
|
globalName, mlir::Attribute());
|
|
|
|
mlir::Region ®ion = globalOp.getInitializerRegion();
|
|
mlir::Block *block = rewriter.createBlock(®ion);
|
|
rewriter.setInsertionPoint(block, block->begin());
|
|
mlir::Value constValue = rewriter.create<mlir::LLVM::ConstantOp>(
|
|
loc, arrayTy, rewriter.getStringAttr(fn));
|
|
rewriter.create<mlir::LLVM::ReturnOp>(loc, constValue);
|
|
rewriter.restoreInsertionPoint(crtInsPt);
|
|
return rewriter.create<mlir::LLVM::AddressOfOp>(loc, ptrTy,
|
|
globalOp.getName());
|
|
}
|
|
return rewriter.create<mlir::LLVM::ZeroOp>(loc, ptrTy);
|
|
}
|
|
|
|
static mlir::Value genSourceLine(mlir::Location loc,
|
|
mlir::ConversionPatternRewriter &rewriter) {
|
|
if (auto flc = mlir::dyn_cast<mlir::FileLineColLoc>(loc))
|
|
return rewriter.create<mlir::LLVM::ConstantOp>(loc, rewriter.getI32Type(),
|
|
flc.getLine());
|
|
return rewriter.create<mlir::LLVM::ConstantOp>(loc, rewriter.getI32Type(), 0);
|
|
}
|
|
|
|
static mlir::Value
|
|
genCUFAllocDescriptor(mlir::Location loc,
|
|
mlir::ConversionPatternRewriter &rewriter,
|
|
mlir::ModuleOp mod, fir::BaseBoxType boxTy,
|
|
const fir::LLVMTypeConverter &typeConverter) {
|
|
std::optional<mlir::DataLayout> dl =
|
|
fir::support::getOrSetMLIRDataLayout(mod, /*allowDefaultLayout=*/true);
|
|
if (!dl)
|
|
mlir::emitError(mod.getLoc(),
|
|
"module operation must carry a data layout attribute "
|
|
"to generate llvm IR from FIR");
|
|
|
|
mlir::Value sourceFile = genSourceFile(loc, mod, rewriter);
|
|
mlir::Value sourceLine = genSourceLine(loc, rewriter);
|
|
|
|
mlir::MLIRContext *ctx = mod.getContext();
|
|
|
|
mlir::LLVM::LLVMPointerType llvmPointerType =
|
|
mlir::LLVM::LLVMPointerType::get(ctx);
|
|
mlir::Type llvmInt32Type = mlir::IntegerType::get(ctx, 32);
|
|
mlir::Type llvmIntPtrType =
|
|
mlir::IntegerType::get(ctx, typeConverter.getPointerBitwidth(0));
|
|
auto fctTy = mlir::LLVM::LLVMFunctionType::get(
|
|
llvmPointerType, {llvmIntPtrType, llvmPointerType, llvmInt32Type});
|
|
|
|
auto llvmFunc = mod.lookupSymbol<mlir::LLVM::LLVMFuncOp>(
|
|
RTNAME_STRING(CUFAllocDescriptor));
|
|
auto funcFunc =
|
|
mod.lookupSymbol<mlir::func::FuncOp>(RTNAME_STRING(CUFAllocDescriptor));
|
|
if (!llvmFunc && !funcFunc)
|
|
mlir::OpBuilder::atBlockEnd(mod.getBody())
|
|
.create<mlir::LLVM::LLVMFuncOp>(loc, RTNAME_STRING(CUFAllocDescriptor),
|
|
fctTy);
|
|
|
|
mlir::Type structTy = typeConverter.convertBoxTypeAsStruct(boxTy);
|
|
std::size_t boxSize = dl->getTypeSizeInBits(structTy) / 8;
|
|
mlir::Value sizeInBytes =
|
|
genConstantIndex(loc, llvmIntPtrType, rewriter, boxSize);
|
|
llvm::SmallVector args = {sizeInBytes, sourceFile, sourceLine};
|
|
return rewriter
|
|
.create<mlir::LLVM::CallOp>(loc, fctTy, RTNAME_STRING(CUFAllocDescriptor),
|
|
args)
|
|
.getResult();
|
|
}
|
|
|
|
/// Common base class for embox to descriptor conversion.
|
|
template <typename OP>
|
|
struct EmboxCommonConversion : public fir::FIROpConversion<OP> {
|
|
using fir::FIROpConversion<OP>::FIROpConversion;
|
|
using TypePair = typename fir::FIROpConversion<OP>::TypePair;
|
|
|
|
static int getCFIAttr(fir::BaseBoxType boxTy) {
|
|
auto eleTy = boxTy.getEleTy();
|
|
if (mlir::isa<fir::PointerType>(eleTy))
|
|
return CFI_attribute_pointer;
|
|
if (mlir::isa<fir::HeapType>(eleTy))
|
|
return CFI_attribute_allocatable;
|
|
return CFI_attribute_other;
|
|
}
|
|
|
|
mlir::Value getCharacterByteSize(mlir::Location loc,
|
|
mlir::ConversionPatternRewriter &rewriter,
|
|
fir::CharacterType charTy,
|
|
mlir::ValueRange lenParams) const {
|
|
auto i64Ty = mlir::IntegerType::get(rewriter.getContext(), 64);
|
|
mlir::Value size =
|
|
genTypeStrideInBytes(loc, i64Ty, rewriter, this->convertType(charTy));
|
|
if (charTy.hasConstantLen())
|
|
return size; // Length accounted for in the genTypeStrideInBytes GEP.
|
|
// Otherwise, multiply the single character size by the length.
|
|
assert(!lenParams.empty());
|
|
auto len64 = fir::FIROpConversion<OP>::integerCast(loc, rewriter, i64Ty,
|
|
lenParams.back());
|
|
return rewriter.create<mlir::LLVM::MulOp>(loc, i64Ty, size, len64);
|
|
}
|
|
|
|
// Get the element size and CFI type code of the boxed value.
|
|
std::tuple<mlir::Value, mlir::Value> getSizeAndTypeCode(
|
|
mlir::Location loc, mlir::ConversionPatternRewriter &rewriter,
|
|
mlir::Type boxEleTy, mlir::ValueRange lenParams = {}) const {
|
|
auto i64Ty = mlir::IntegerType::get(rewriter.getContext(), 64);
|
|
if (auto eleTy = fir::dyn_cast_ptrEleTy(boxEleTy))
|
|
boxEleTy = eleTy;
|
|
if (auto seqTy = mlir::dyn_cast<fir::SequenceType>(boxEleTy))
|
|
return getSizeAndTypeCode(loc, rewriter, seqTy.getEleTy(), lenParams);
|
|
if (mlir::isa<mlir::NoneType>(
|
|
boxEleTy)) // unlimited polymorphic or assumed type
|
|
return {rewriter.create<mlir::LLVM::ConstantOp>(loc, i64Ty, 0),
|
|
this->genConstantOffset(loc, rewriter, CFI_type_other)};
|
|
mlir::Value typeCodeVal = this->genConstantOffset(
|
|
loc, rewriter,
|
|
fir::getTypeCode(boxEleTy, this->lowerTy().getKindMap()));
|
|
if (fir::isa_integer(boxEleTy) ||
|
|
mlir::dyn_cast<fir::LogicalType>(boxEleTy) || fir::isa_real(boxEleTy) ||
|
|
fir::isa_complex(boxEleTy))
|
|
return {genTypeStrideInBytes(loc, i64Ty, rewriter,
|
|
this->convertType(boxEleTy)),
|
|
typeCodeVal};
|
|
if (auto charTy = mlir::dyn_cast<fir::CharacterType>(boxEleTy))
|
|
return {getCharacterByteSize(loc, rewriter, charTy, lenParams),
|
|
typeCodeVal};
|
|
if (fir::isa_ref_type(boxEleTy)) {
|
|
auto ptrTy = ::getLlvmPtrType(rewriter.getContext());
|
|
return {genTypeStrideInBytes(loc, i64Ty, rewriter, ptrTy), typeCodeVal};
|
|
}
|
|
if (mlir::isa<fir::RecordType>(boxEleTy))
|
|
return {genTypeStrideInBytes(loc, i64Ty, rewriter,
|
|
this->convertType(boxEleTy)),
|
|
typeCodeVal};
|
|
fir::emitFatalError(loc, "unhandled type in fir.box code generation");
|
|
}
|
|
|
|
/// Basic pattern to write a field in the descriptor
|
|
mlir::Value insertField(mlir::ConversionPatternRewriter &rewriter,
|
|
mlir::Location loc, mlir::Value dest,
|
|
llvm::ArrayRef<std::int64_t> fldIndexes,
|
|
mlir::Value value, bool bitcast = false) const {
|
|
auto boxTy = dest.getType();
|
|
auto fldTy = this->getBoxEleTy(boxTy, fldIndexes);
|
|
if (!bitcast)
|
|
value = this->integerCast(loc, rewriter, fldTy, value);
|
|
// bitcast are no-ops with LLVM opaque pointers.
|
|
return rewriter.create<mlir::LLVM::InsertValueOp>(loc, dest, value,
|
|
fldIndexes);
|
|
}
|
|
|
|
inline mlir::Value
|
|
insertBaseAddress(mlir::ConversionPatternRewriter &rewriter,
|
|
mlir::Location loc, mlir::Value dest,
|
|
mlir::Value base) const {
|
|
return insertField(rewriter, loc, dest, {kAddrPosInBox}, base,
|
|
/*bitCast=*/true);
|
|
}
|
|
|
|
inline mlir::Value insertLowerBound(mlir::ConversionPatternRewriter &rewriter,
|
|
mlir::Location loc, mlir::Value dest,
|
|
unsigned dim, mlir::Value lb) const {
|
|
return insertField(rewriter, loc, dest,
|
|
{kDimsPosInBox, dim, kDimLowerBoundPos}, lb);
|
|
}
|
|
|
|
inline mlir::Value insertExtent(mlir::ConversionPatternRewriter &rewriter,
|
|
mlir::Location loc, mlir::Value dest,
|
|
unsigned dim, mlir::Value extent) const {
|
|
return insertField(rewriter, loc, dest, {kDimsPosInBox, dim, kDimExtentPos},
|
|
extent);
|
|
}
|
|
|
|
inline mlir::Value insertStride(mlir::ConversionPatternRewriter &rewriter,
|
|
mlir::Location loc, mlir::Value dest,
|
|
unsigned dim, mlir::Value stride) const {
|
|
return insertField(rewriter, loc, dest, {kDimsPosInBox, dim, kDimStridePos},
|
|
stride);
|
|
}
|
|
|
|
/// Get the address of the type descriptor global variable that was created by
|
|
/// lowering for derived type \p recType.
|
|
template <typename ModOpTy>
|
|
mlir::Value
|
|
getTypeDescriptor(ModOpTy mod, mlir::ConversionPatternRewriter &rewriter,
|
|
mlir::Location loc, fir::RecordType recType) const {
|
|
std::string name =
|
|
this->options.typeDescriptorsRenamedForAssembly
|
|
? fir::NameUniquer::getTypeDescriptorAssemblyName(recType.getName())
|
|
: fir::NameUniquer::getTypeDescriptorName(recType.getName());
|
|
mlir::Type llvmPtrTy = ::getLlvmPtrType(mod.getContext());
|
|
if (auto global = mod.template lookupSymbol<fir::GlobalOp>(name)) {
|
|
return rewriter.create<mlir::LLVM::AddressOfOp>(loc, llvmPtrTy,
|
|
global.getSymName());
|
|
}
|
|
if (auto global = mod.template lookupSymbol<mlir::LLVM::GlobalOp>(name)) {
|
|
// The global may have already been translated to LLVM.
|
|
return rewriter.create<mlir::LLVM::AddressOfOp>(loc, llvmPtrTy,
|
|
global.getSymName());
|
|
}
|
|
// Type info derived types do not have type descriptors since they are the
|
|
// types defining type descriptors.
|
|
if (!this->options.ignoreMissingTypeDescriptors &&
|
|
!fir::NameUniquer::belongsToModule(
|
|
name, Fortran::semantics::typeInfoBuiltinModule))
|
|
fir::emitFatalError(
|
|
loc, "runtime derived type info descriptor was not generated");
|
|
return rewriter.create<mlir::LLVM::ZeroOp>(loc, llvmPtrTy);
|
|
}
|
|
|
|
template <typename ModOpTy>
|
|
mlir::Value populateDescriptor(mlir::Location loc, ModOpTy mod,
|
|
fir::BaseBoxType boxTy, mlir::Type inputType,
|
|
mlir::ConversionPatternRewriter &rewriter,
|
|
unsigned rank, mlir::Value eleSize,
|
|
mlir::Value cfiTy, mlir::Value typeDesc,
|
|
int allocatorIdx = kDefaultAllocator,
|
|
mlir::Value extraField = {}) const {
|
|
auto llvmBoxTy = this->lowerTy().convertBoxTypeAsStruct(boxTy, rank);
|
|
bool isUnlimitedPolymorphic = fir::isUnlimitedPolymorphicType(boxTy);
|
|
bool useInputType = fir::isPolymorphicType(boxTy) || isUnlimitedPolymorphic;
|
|
mlir::Value descriptor =
|
|
rewriter.create<mlir::LLVM::UndefOp>(loc, llvmBoxTy);
|
|
descriptor =
|
|
insertField(rewriter, loc, descriptor, {kElemLenPosInBox}, eleSize);
|
|
descriptor = insertField(rewriter, loc, descriptor, {kVersionPosInBox},
|
|
this->genI32Constant(loc, rewriter, CFI_VERSION));
|
|
descriptor = insertField(rewriter, loc, descriptor, {kRankPosInBox},
|
|
this->genI32Constant(loc, rewriter, rank));
|
|
descriptor = insertField(rewriter, loc, descriptor, {kTypePosInBox}, cfiTy);
|
|
descriptor =
|
|
insertField(rewriter, loc, descriptor, {kAttributePosInBox},
|
|
this->genI32Constant(loc, rewriter, getCFIAttr(boxTy)));
|
|
|
|
const bool hasAddendum = fir::boxHasAddendum(boxTy);
|
|
|
|
if (extraField) {
|
|
// Make sure to set the addendum presence flag according to the
|
|
// destination box.
|
|
if (hasAddendum) {
|
|
auto maskAttr = mlir::IntegerAttr::get(
|
|
rewriter.getIntegerType(8, /*isSigned=*/false),
|
|
llvm::APInt(8, (uint64_t)_CFI_ADDENDUM_FLAG, /*isSigned=*/false));
|
|
mlir::LLVM::ConstantOp mask = rewriter.create<mlir::LLVM::ConstantOp>(
|
|
loc, rewriter.getI8Type(), maskAttr);
|
|
extraField = rewriter.create<mlir::LLVM::OrOp>(loc, extraField, mask);
|
|
} else {
|
|
auto maskAttr = mlir::IntegerAttr::get(
|
|
rewriter.getIntegerType(8, /*isSigned=*/false),
|
|
llvm::APInt(8, (uint64_t)~_CFI_ADDENDUM_FLAG, /*isSigned=*/true));
|
|
mlir::LLVM::ConstantOp mask = rewriter.create<mlir::LLVM::ConstantOp>(
|
|
loc, rewriter.getI8Type(), maskAttr);
|
|
extraField = rewriter.create<mlir::LLVM::AndOp>(loc, extraField, mask);
|
|
}
|
|
// Extra field value is provided so just use it.
|
|
descriptor =
|
|
insertField(rewriter, loc, descriptor, {kExtraPosInBox}, extraField);
|
|
} else {
|
|
// Compute the value of the extra field based on allocator_idx and
|
|
// addendum present.
|
|
unsigned extra = allocatorIdx << _CFI_ALLOCATOR_IDX_SHIFT;
|
|
if (hasAddendum)
|
|
extra |= _CFI_ADDENDUM_FLAG;
|
|
descriptor = insertField(rewriter, loc, descriptor, {kExtraPosInBox},
|
|
this->genI32Constant(loc, rewriter, extra));
|
|
}
|
|
|
|
if (hasAddendum) {
|
|
unsigned typeDescFieldId = getTypeDescFieldId(boxTy);
|
|
if (!typeDesc) {
|
|
if (useInputType) {
|
|
mlir::Type innerType = fir::unwrapInnerType(inputType);
|
|
if (innerType && mlir::isa<fir::RecordType>(innerType)) {
|
|
auto recTy = mlir::dyn_cast<fir::RecordType>(innerType);
|
|
typeDesc = getTypeDescriptor(mod, rewriter, loc, recTy);
|
|
} else {
|
|
// Unlimited polymorphic type descriptor with no record type. Set
|
|
// type descriptor address to a clean state.
|
|
typeDesc = rewriter.create<mlir::LLVM::ZeroOp>(
|
|
loc, ::getLlvmPtrType(mod.getContext()));
|
|
}
|
|
} else {
|
|
typeDesc = getTypeDescriptor(mod, rewriter, loc,
|
|
fir::unwrapIfDerived(boxTy));
|
|
}
|
|
}
|
|
if (typeDesc)
|
|
descriptor =
|
|
insertField(rewriter, loc, descriptor, {typeDescFieldId}, typeDesc,
|
|
/*bitCast=*/true);
|
|
// Always initialize the length parameter field to zero to avoid issues
|
|
// with uninitialized values in Fortran code trying to compare physical
|
|
// representation of derived types with pointer/allocatable components.
|
|
// This has been seen in hashing algorithms using TRANSFER.
|
|
mlir::Value zero =
|
|
genConstantIndex(loc, rewriter.getI64Type(), rewriter, 0);
|
|
descriptor = insertField(rewriter, loc, descriptor,
|
|
{getLenParamFieldId(boxTy), 0}, zero);
|
|
}
|
|
return descriptor;
|
|
}
|
|
|
|
// Template used for fir::EmboxOp and fir::cg::XEmboxOp
|
|
template <typename BOX>
|
|
std::tuple<fir::BaseBoxType, mlir::Value, mlir::Value>
|
|
consDescriptorPrefix(BOX box, mlir::Type inputType,
|
|
mlir::ConversionPatternRewriter &rewriter, unsigned rank,
|
|
[[maybe_unused]] mlir::ValueRange substrParams,
|
|
mlir::ValueRange lenParams, mlir::Value sourceBox = {},
|
|
mlir::Type sourceBoxType = {}) const {
|
|
auto loc = box.getLoc();
|
|
auto boxTy = mlir::dyn_cast<fir::BaseBoxType>(box.getType());
|
|
bool useInputType = fir::isPolymorphicType(boxTy) &&
|
|
!fir::isUnlimitedPolymorphicType(inputType);
|
|
llvm::SmallVector<mlir::Value> typeparams = lenParams;
|
|
if constexpr (!std::is_same_v<BOX, fir::EmboxOp>) {
|
|
if (!box.getSubstr().empty() && fir::hasDynamicSize(boxTy.getEleTy()))
|
|
typeparams.push_back(substrParams[1]);
|
|
}
|
|
|
|
int allocatorIdx = 0;
|
|
if constexpr (std::is_same_v<BOX, fir::EmboxOp> ||
|
|
std::is_same_v<BOX, fir::cg::XEmboxOp>) {
|
|
if (box.getAllocatorIdx())
|
|
allocatorIdx = *box.getAllocatorIdx();
|
|
}
|
|
|
|
// Write each of the fields with the appropriate values.
|
|
// When emboxing an element to a polymorphic descriptor, use the
|
|
// input type since the destination descriptor type has not the exact
|
|
// information.
|
|
auto [eleSize, cfiTy] = getSizeAndTypeCode(
|
|
loc, rewriter, useInputType ? inputType : boxTy.getEleTy(), typeparams);
|
|
|
|
mlir::Value typeDesc;
|
|
mlir::Value extraField;
|
|
// When emboxing to a polymorphic box, get the type descriptor, type code
|
|
// and element size from the source box if any.
|
|
if (fir::isPolymorphicType(boxTy) && sourceBox) {
|
|
TypePair sourceBoxTyPair = this->getBoxTypePair(sourceBoxType);
|
|
typeDesc =
|
|
this->loadTypeDescAddress(loc, sourceBoxTyPair, sourceBox, rewriter);
|
|
mlir::Type idxTy = this->lowerTy().indexType();
|
|
eleSize = this->getElementSizeFromBox(loc, idxTy, sourceBoxTyPair,
|
|
sourceBox, rewriter);
|
|
cfiTy = this->getValueFromBox(loc, sourceBoxTyPair, sourceBox,
|
|
cfiTy.getType(), rewriter, kTypePosInBox);
|
|
extraField =
|
|
this->getExtraFromBox(loc, sourceBoxTyPair, sourceBox, rewriter);
|
|
}
|
|
|
|
mlir::Value descriptor;
|
|
if (auto gpuMod = box->template getParentOfType<mlir::gpu::GPUModuleOp>())
|
|
descriptor = populateDescriptor(loc, gpuMod, boxTy, inputType, rewriter,
|
|
rank, eleSize, cfiTy, typeDesc,
|
|
allocatorIdx, extraField);
|
|
else if (auto mod = box->template getParentOfType<mlir::ModuleOp>())
|
|
descriptor = populateDescriptor(loc, mod, boxTy, inputType, rewriter,
|
|
rank, eleSize, cfiTy, typeDesc,
|
|
allocatorIdx, extraField);
|
|
|
|
return {boxTy, descriptor, eleSize};
|
|
}
|
|
|
|
std::tuple<fir::BaseBoxType, mlir::Value, mlir::Value>
|
|
consDescriptorPrefix(fir::cg::XReboxOp box, mlir::Value loweredBox,
|
|
mlir::ConversionPatternRewriter &rewriter, unsigned rank,
|
|
mlir::ValueRange substrParams,
|
|
mlir::ValueRange lenParams,
|
|
mlir::Value typeDesc = {}) const {
|
|
auto loc = box.getLoc();
|
|
auto boxTy = mlir::dyn_cast<fir::BaseBoxType>(box.getType());
|
|
auto inputBoxTy = mlir::dyn_cast<fir::BaseBoxType>(box.getBox().getType());
|
|
auto inputBoxTyPair = this->getBoxTypePair(inputBoxTy);
|
|
llvm::SmallVector<mlir::Value> typeparams = lenParams;
|
|
if (!box.getSubstr().empty() && fir::hasDynamicSize(boxTy.getEleTy()))
|
|
typeparams.push_back(substrParams[1]);
|
|
|
|
auto [eleSize, cfiTy] =
|
|
getSizeAndTypeCode(loc, rewriter, boxTy.getEleTy(), typeparams);
|
|
|
|
// Reboxing to a polymorphic entity. eleSize and type code need to
|
|
// be retrieved from the initial box and propagated to the new box.
|
|
// If the initial box has an addendum, the type desc must be propagated as
|
|
// well.
|
|
if (fir::isPolymorphicType(boxTy)) {
|
|
mlir::Type idxTy = this->lowerTy().indexType();
|
|
eleSize = this->getElementSizeFromBox(loc, idxTy, inputBoxTyPair,
|
|
loweredBox, rewriter);
|
|
cfiTy = this->getValueFromBox(loc, inputBoxTyPair, loweredBox,
|
|
cfiTy.getType(), rewriter, kTypePosInBox);
|
|
// TODO: For initial box that are unlimited polymorphic entities, this
|
|
// code must be made conditional because unlimited polymorphic entities
|
|
// with intrinsic type spec does not have addendum.
|
|
if (fir::boxHasAddendum(inputBoxTy))
|
|
typeDesc = this->loadTypeDescAddress(loc, inputBoxTyPair, loweredBox,
|
|
rewriter);
|
|
}
|
|
|
|
mlir::Value extraField =
|
|
this->getExtraFromBox(loc, inputBoxTyPair, loweredBox, rewriter);
|
|
|
|
mlir::Value descriptor;
|
|
if (auto gpuMod = box->template getParentOfType<mlir::gpu::GPUModuleOp>())
|
|
descriptor =
|
|
populateDescriptor(loc, gpuMod, boxTy, box.getBox().getType(),
|
|
rewriter, rank, eleSize, cfiTy, typeDesc,
|
|
/*allocatorIdx=*/kDefaultAllocator, extraField);
|
|
else if (auto mod = box->template getParentOfType<mlir::ModuleOp>())
|
|
descriptor =
|
|
populateDescriptor(loc, mod, boxTy, box.getBox().getType(), rewriter,
|
|
rank, eleSize, cfiTy, typeDesc,
|
|
/*allocatorIdx=*/kDefaultAllocator, extraField);
|
|
|
|
return {boxTy, descriptor, eleSize};
|
|
}
|
|
|
|
// Compute the base address of a fir.box given the indices from the slice.
|
|
// The indices from the "outer" dimensions (every dimension after the first
|
|
// one (included) that is not a compile time constant) must have been
|
|
// multiplied with the related extents and added together into \p outerOffset.
|
|
mlir::Value
|
|
genBoxOffsetGep(mlir::ConversionPatternRewriter &rewriter, mlir::Location loc,
|
|
mlir::Value base, mlir::Type llvmBaseObjectType,
|
|
mlir::Value outerOffset, mlir::ValueRange cstInteriorIndices,
|
|
mlir::ValueRange componentIndices,
|
|
std::optional<mlir::Value> substringOffset) const {
|
|
llvm::SmallVector<mlir::LLVM::GEPArg> gepArgs{outerOffset};
|
|
mlir::Type resultTy = llvmBaseObjectType;
|
|
// Fortran is column major, llvm GEP is row major: reverse the indices here.
|
|
for (mlir::Value interiorIndex : llvm::reverse(cstInteriorIndices)) {
|
|
auto arrayTy = mlir::dyn_cast<mlir::LLVM::LLVMArrayType>(resultTy);
|
|
if (!arrayTy)
|
|
fir::emitFatalError(
|
|
loc,
|
|
"corrupted GEP generated being generated in fir.embox/fir.rebox");
|
|
resultTy = arrayTy.getElementType();
|
|
gepArgs.push_back(interiorIndex);
|
|
}
|
|
llvm::SmallVector<mlir::Value> gepIndices =
|
|
convertSubcomponentIndices(loc, resultTy, componentIndices, &resultTy);
|
|
gepArgs.append(gepIndices.begin(), gepIndices.end());
|
|
if (substringOffset) {
|
|
if (auto arrayTy = mlir::dyn_cast<mlir::LLVM::LLVMArrayType>(resultTy)) {
|
|
gepArgs.push_back(*substringOffset);
|
|
resultTy = arrayTy.getElementType();
|
|
} else {
|
|
// If the CHARACTER length is dynamic, the whole base type should have
|
|
// degenerated to an llvm.ptr<i[width]>, and there should not be any
|
|
// cstInteriorIndices/componentIndices. The substring offset can be
|
|
// added to the outterOffset since it applies on the same LLVM type.
|
|
if (gepArgs.size() != 1)
|
|
fir::emitFatalError(loc,
|
|
"corrupted substring GEP in fir.embox/fir.rebox");
|
|
mlir::Type outterOffsetTy =
|
|
llvm::cast<mlir::Value>(gepArgs[0]).getType();
|
|
mlir::Value cast =
|
|
this->integerCast(loc, rewriter, outterOffsetTy, *substringOffset);
|
|
|
|
gepArgs[0] = rewriter.create<mlir::LLVM::AddOp>(
|
|
loc, outterOffsetTy, llvm::cast<mlir::Value>(gepArgs[0]), cast);
|
|
}
|
|
}
|
|
mlir::Type llvmPtrTy = ::getLlvmPtrType(resultTy.getContext());
|
|
return rewriter.create<mlir::LLVM::GEPOp>(
|
|
loc, llvmPtrTy, llvmBaseObjectType, base, gepArgs);
|
|
}
|
|
|
|
template <typename BOX>
|
|
void
|
|
getSubcomponentIndices(BOX xbox, mlir::Value memref,
|
|
mlir::ValueRange operands,
|
|
mlir::SmallVectorImpl<mlir::Value> &indices) const {
|
|
// For each field in the path add the offset to base via the args list.
|
|
// In the most general case, some offsets must be computed since
|
|
// they are not be known until runtime.
|
|
if (fir::hasDynamicSize(fir::unwrapSequenceType(
|
|
fir::unwrapPassByRefType(memref.getType()))))
|
|
TODO(xbox.getLoc(),
|
|
"fir.embox codegen dynamic size component in derived type");
|
|
indices.append(operands.begin() + xbox.getSubcomponentOperandIndex(),
|
|
operands.begin() + xbox.getSubcomponentOperandIndex() +
|
|
xbox.getSubcomponent().size());
|
|
}
|
|
|
|
static bool isInGlobalOp(mlir::ConversionPatternRewriter &rewriter) {
|
|
auto *thisBlock = rewriter.getInsertionBlock();
|
|
return thisBlock &&
|
|
mlir::isa<mlir::LLVM::GlobalOp>(thisBlock->getParentOp());
|
|
}
|
|
|
|
/// If the embox is not in a globalOp body, allocate storage for the box;
|
|
/// store the value inside and return the generated alloca. Return the input
|
|
/// value otherwise.
|
|
mlir::Value
|
|
placeInMemoryIfNotGlobalInit(mlir::ConversionPatternRewriter &rewriter,
|
|
mlir::Location loc, mlir::Type boxTy,
|
|
mlir::Value boxValue,
|
|
bool needDeviceAllocation = false) const {
|
|
if (isInGlobalOp(rewriter))
|
|
return boxValue;
|
|
mlir::Type llvmBoxTy = boxValue.getType();
|
|
mlir::Value storage;
|
|
if (needDeviceAllocation) {
|
|
auto mod = boxValue.getDefiningOp()->getParentOfType<mlir::ModuleOp>();
|
|
auto baseBoxTy = mlir::dyn_cast<fir::BaseBoxType>(boxTy);
|
|
storage =
|
|
genCUFAllocDescriptor(loc, rewriter, mod, baseBoxTy, this->lowerTy());
|
|
} else {
|
|
storage = this->genAllocaAndAddrCastWithType(loc, llvmBoxTy, defaultAlign,
|
|
rewriter);
|
|
}
|
|
auto storeOp = rewriter.create<mlir::LLVM::StoreOp>(loc, boxValue, storage);
|
|
this->attachTBAATag(storeOp, boxTy, boxTy, nullptr);
|
|
return storage;
|
|
}
|
|
|
|
/// Compute the extent of a triplet slice (lb:ub:step).
|
|
mlir::Value computeTripletExtent(mlir::ConversionPatternRewriter &rewriter,
|
|
mlir::Location loc, mlir::Value lb,
|
|
mlir::Value ub, mlir::Value step,
|
|
mlir::Value zero, mlir::Type type) const {
|
|
lb = this->integerCast(loc, rewriter, type, lb);
|
|
ub = this->integerCast(loc, rewriter, type, ub);
|
|
step = this->integerCast(loc, rewriter, type, step);
|
|
zero = this->integerCast(loc, rewriter, type, zero);
|
|
mlir::Value extent = rewriter.create<mlir::LLVM::SubOp>(loc, type, ub, lb);
|
|
extent = rewriter.create<mlir::LLVM::AddOp>(loc, type, extent, step);
|
|
extent = rewriter.create<mlir::LLVM::SDivOp>(loc, type, extent, step);
|
|
// If the resulting extent is negative (`ub-lb` and `step` have different
|
|
// signs), zero must be returned instead.
|
|
auto cmp = rewriter.create<mlir::LLVM::ICmpOp>(
|
|
loc, mlir::LLVM::ICmpPredicate::sgt, extent, zero);
|
|
return rewriter.create<mlir::LLVM::SelectOp>(loc, cmp, extent, zero);
|
|
}
|
|
};
|
|
|
|
/// Create a generic box on a memory reference. This conversions lowers the
|
|
/// abstract box to the appropriate, initialized descriptor.
|
|
struct EmboxOpConversion : public EmboxCommonConversion<fir::EmboxOp> {
|
|
using EmboxCommonConversion::EmboxCommonConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::EmboxOp embox, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
mlir::ValueRange operands = adaptor.getOperands();
|
|
mlir::Value sourceBox;
|
|
mlir::Type sourceBoxType;
|
|
if (embox.getSourceBox()) {
|
|
sourceBox = operands[embox.getSourceBoxOperandIndex()];
|
|
sourceBoxType = embox.getSourceBox().getType();
|
|
}
|
|
assert(!embox.getShape() && "There should be no dims on this embox op");
|
|
auto [boxTy, dest, eleSize] = consDescriptorPrefix(
|
|
embox, fir::unwrapRefType(embox.getMemref().getType()), rewriter,
|
|
/*rank=*/0, /*substrParams=*/mlir::ValueRange{},
|
|
adaptor.getTypeparams(), sourceBox, sourceBoxType);
|
|
dest = insertBaseAddress(rewriter, embox.getLoc(), dest, operands[0]);
|
|
if (fir::isDerivedTypeWithLenParams(boxTy)) {
|
|
TODO(embox.getLoc(),
|
|
"fir.embox codegen of derived with length parameters");
|
|
return mlir::failure();
|
|
}
|
|
auto result =
|
|
placeInMemoryIfNotGlobalInit(rewriter, embox.getLoc(), boxTy, dest);
|
|
rewriter.replaceOp(embox, result);
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
static bool isDeviceAllocation(mlir::Value val, mlir::Value adaptorVal) {
|
|
if (auto loadOp = mlir::dyn_cast_or_null<fir::LoadOp>(val.getDefiningOp()))
|
|
return isDeviceAllocation(loadOp.getMemref(), {});
|
|
if (auto boxAddrOp =
|
|
mlir::dyn_cast_or_null<fir::BoxAddrOp>(val.getDefiningOp()))
|
|
return isDeviceAllocation(boxAddrOp.getVal(), {});
|
|
if (auto convertOp =
|
|
mlir::dyn_cast_or_null<fir::ConvertOp>(val.getDefiningOp()))
|
|
return isDeviceAllocation(convertOp.getValue(), {});
|
|
if (!val.getDefiningOp() && adaptorVal) {
|
|
if (auto blockArg = llvm::cast<mlir::BlockArgument>(adaptorVal)) {
|
|
if (blockArg.getOwner() && blockArg.getOwner()->getParentOp() &&
|
|
blockArg.getOwner()->isEntryBlock()) {
|
|
if (auto func = mlir::dyn_cast_or_null<mlir::FunctionOpInterface>(
|
|
*blockArg.getOwner()->getParentOp())) {
|
|
auto argAttrs = func.getArgAttrs(blockArg.getArgNumber());
|
|
for (auto attr : argAttrs) {
|
|
if (attr.getName().getValue().ends_with(cuf::getDataAttrName())) {
|
|
auto dataAttr =
|
|
mlir::dyn_cast<cuf::DataAttributeAttr>(attr.getValue());
|
|
if (dataAttr.getValue() != cuf::DataAttribute::Pinned &&
|
|
dataAttr.getValue() != cuf::DataAttribute::Unified)
|
|
return true;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
if (auto callOp = mlir::dyn_cast_or_null<fir::CallOp>(val.getDefiningOp()))
|
|
if (callOp.getCallee() &&
|
|
(callOp.getCallee().value().getRootReference().getValue().starts_with(
|
|
RTNAME_STRING(CUFMemAlloc)) ||
|
|
callOp.getCallee().value().getRootReference().getValue().starts_with(
|
|
RTNAME_STRING(CUFAllocDescriptor))))
|
|
return true;
|
|
return false;
|
|
}
|
|
|
|
/// Create a generic box on a memory reference.
|
|
struct XEmboxOpConversion : public EmboxCommonConversion<fir::cg::XEmboxOp> {
|
|
using EmboxCommonConversion::EmboxCommonConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::cg::XEmboxOp xbox, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
mlir::ValueRange operands = adaptor.getOperands();
|
|
mlir::Value sourceBox;
|
|
mlir::Type sourceBoxType;
|
|
if (xbox.getSourceBox()) {
|
|
sourceBox = operands[xbox.getSourceBoxOperandIndex()];
|
|
sourceBoxType = xbox.getSourceBox().getType();
|
|
}
|
|
auto [boxTy, dest, resultEleSize] = consDescriptorPrefix(
|
|
xbox, fir::unwrapRefType(xbox.getMemref().getType()), rewriter,
|
|
xbox.getOutRank(), adaptor.getSubstr(), adaptor.getLenParams(),
|
|
sourceBox, sourceBoxType);
|
|
// Generate the triples in the dims field of the descriptor
|
|
auto i64Ty = mlir::IntegerType::get(xbox.getContext(), 64);
|
|
assert(!xbox.getShape().empty() && "must have a shape");
|
|
unsigned shapeOffset = xbox.getShapeOperandIndex();
|
|
bool hasShift = !xbox.getShift().empty();
|
|
unsigned shiftOffset = xbox.getShiftOperandIndex();
|
|
bool hasSlice = !xbox.getSlice().empty();
|
|
unsigned sliceOffset = xbox.getSliceOperandIndex();
|
|
mlir::Location loc = xbox.getLoc();
|
|
mlir::Value zero = genConstantIndex(loc, i64Ty, rewriter, 0);
|
|
mlir::Value one = genConstantIndex(loc, i64Ty, rewriter, 1);
|
|
mlir::Value prevPtrOff = one;
|
|
mlir::Type eleTy = boxTy.getEleTy();
|
|
const unsigned rank = xbox.getRank();
|
|
llvm::SmallVector<mlir::Value> cstInteriorIndices;
|
|
unsigned constRows = 0;
|
|
mlir::Value ptrOffset = zero;
|
|
mlir::Type memEleTy = fir::dyn_cast_ptrEleTy(xbox.getMemref().getType());
|
|
assert(mlir::isa<fir::SequenceType>(memEleTy));
|
|
auto seqTy = mlir::cast<fir::SequenceType>(memEleTy);
|
|
mlir::Type seqEleTy = seqTy.getEleTy();
|
|
// Adjust the element scaling factor if the element is a dependent type.
|
|
if (fir::hasDynamicSize(seqEleTy)) {
|
|
if (auto charTy = mlir::dyn_cast<fir::CharacterType>(seqEleTy)) {
|
|
// The GEP pointer type decays to llvm.ptr<i[width]>.
|
|
// The scaling factor is the runtime value of the length.
|
|
assert(!adaptor.getLenParams().empty());
|
|
prevPtrOff = FIROpConversion::integerCast(
|
|
loc, rewriter, i64Ty, adaptor.getLenParams().back());
|
|
} else if (mlir::isa<fir::RecordType>(seqEleTy)) {
|
|
// prevPtrOff = ;
|
|
TODO(loc, "generate call to calculate size of PDT");
|
|
} else {
|
|
fir::emitFatalError(loc, "unexpected dynamic type");
|
|
}
|
|
} else {
|
|
constRows = seqTy.getConstantRows();
|
|
}
|
|
|
|
const auto hasSubcomp = !xbox.getSubcomponent().empty();
|
|
const bool hasSubstr = !xbox.getSubstr().empty();
|
|
// Initial element stride that will be use to compute the step in
|
|
// each dimension. Initially, this is the size of the input element.
|
|
// Note that when there are no components/substring, the resultEleSize
|
|
// that was previously computed matches the input element size.
|
|
mlir::Value prevDimByteStride = resultEleSize;
|
|
if (hasSubcomp) {
|
|
// We have a subcomponent. The step value needs to be the number of
|
|
// bytes per element (which is a derived type).
|
|
prevDimByteStride =
|
|
genTypeStrideInBytes(loc, i64Ty, rewriter, convertType(seqEleTy));
|
|
} else if (hasSubstr) {
|
|
// We have a substring. The step value needs to be the number of bytes
|
|
// per CHARACTER element.
|
|
auto charTy = mlir::cast<fir::CharacterType>(seqEleTy);
|
|
if (fir::hasDynamicSize(charTy)) {
|
|
prevDimByteStride =
|
|
getCharacterByteSize(loc, rewriter, charTy, adaptor.getLenParams());
|
|
} else {
|
|
prevDimByteStride = genConstantIndex(
|
|
loc, i64Ty, rewriter,
|
|
charTy.getLen() * lowerTy().characterBitsize(charTy) / 8);
|
|
}
|
|
}
|
|
|
|
// Process the array subspace arguments (shape, shift, etc.), if any,
|
|
// translating everything to values in the descriptor wherever the entity
|
|
// has a dynamic array dimension.
|
|
for (unsigned di = 0, descIdx = 0; di < rank; ++di) {
|
|
mlir::Value extent =
|
|
integerCast(loc, rewriter, i64Ty, operands[shapeOffset]);
|
|
mlir::Value outerExtent = extent;
|
|
bool skipNext = false;
|
|
if (hasSlice) {
|
|
mlir::Value off =
|
|
integerCast(loc, rewriter, i64Ty, operands[sliceOffset]);
|
|
mlir::Value adj = one;
|
|
if (hasShift)
|
|
adj = integerCast(loc, rewriter, i64Ty, operands[shiftOffset]);
|
|
auto ao = rewriter.create<mlir::LLVM::SubOp>(loc, i64Ty, off, adj);
|
|
if (constRows > 0) {
|
|
cstInteriorIndices.push_back(ao);
|
|
} else {
|
|
auto dimOff =
|
|
rewriter.create<mlir::LLVM::MulOp>(loc, i64Ty, ao, prevPtrOff);
|
|
ptrOffset =
|
|
rewriter.create<mlir::LLVM::AddOp>(loc, i64Ty, dimOff, ptrOffset);
|
|
}
|
|
if (mlir::isa_and_nonnull<fir::UndefOp>(
|
|
xbox.getSlice()[3 * di + 1].getDefiningOp())) {
|
|
// This dimension contains a scalar expression in the array slice op.
|
|
// The dimension is loop invariant, will be dropped, and will not
|
|
// appear in the descriptor.
|
|
skipNext = true;
|
|
}
|
|
}
|
|
if (!skipNext) {
|
|
// store extent
|
|
if (hasSlice)
|
|
extent = computeTripletExtent(rewriter, loc, operands[sliceOffset],
|
|
operands[sliceOffset + 1],
|
|
operands[sliceOffset + 2], zero, i64Ty);
|
|
// Lower bound is normalized to 0 for BIND(C) interoperability.
|
|
mlir::Value lb = zero;
|
|
const bool isaPointerOrAllocatable =
|
|
mlir::isa<fir::PointerType, fir::HeapType>(eleTy);
|
|
// Lower bound is defaults to 1 for POINTER, ALLOCATABLE, and
|
|
// denormalized descriptors.
|
|
if (isaPointerOrAllocatable || !normalizedLowerBound(xbox))
|
|
lb = one;
|
|
// If there is a shifted origin, and no fir.slice, and this is not
|
|
// a normalized descriptor then use the value from the shift op as
|
|
// the lower bound.
|
|
if (hasShift && !(hasSlice || hasSubcomp || hasSubstr) &&
|
|
(isaPointerOrAllocatable || !normalizedLowerBound(xbox))) {
|
|
lb = integerCast(loc, rewriter, i64Ty, operands[shiftOffset]);
|
|
auto extentIsEmpty = rewriter.create<mlir::LLVM::ICmpOp>(
|
|
loc, mlir::LLVM::ICmpPredicate::eq, extent, zero);
|
|
lb = rewriter.create<mlir::LLVM::SelectOp>(loc, extentIsEmpty, one,
|
|
lb);
|
|
}
|
|
dest = insertLowerBound(rewriter, loc, dest, descIdx, lb);
|
|
|
|
dest = insertExtent(rewriter, loc, dest, descIdx, extent);
|
|
|
|
// store step (scaled by shaped extent)
|
|
mlir::Value step = prevDimByteStride;
|
|
if (hasSlice) {
|
|
mlir::Value sliceStep =
|
|
integerCast(loc, rewriter, i64Ty, operands[sliceOffset + 2]);
|
|
step =
|
|
rewriter.create<mlir::LLVM::MulOp>(loc, i64Ty, step, sliceStep);
|
|
}
|
|
dest = insertStride(rewriter, loc, dest, descIdx, step);
|
|
++descIdx;
|
|
}
|
|
|
|
// compute the stride and offset for the next natural dimension
|
|
prevDimByteStride = rewriter.create<mlir::LLVM::MulOp>(
|
|
loc, i64Ty, prevDimByteStride, outerExtent);
|
|
if (constRows == 0)
|
|
prevPtrOff = rewriter.create<mlir::LLVM::MulOp>(loc, i64Ty, prevPtrOff,
|
|
outerExtent);
|
|
else
|
|
--constRows;
|
|
|
|
// increment iterators
|
|
++shapeOffset;
|
|
if (hasShift)
|
|
++shiftOffset;
|
|
if (hasSlice)
|
|
sliceOffset += 3;
|
|
}
|
|
mlir::Value base = adaptor.getMemref();
|
|
if (hasSlice || hasSubcomp || hasSubstr) {
|
|
// Shift the base address.
|
|
llvm::SmallVector<mlir::Value> fieldIndices;
|
|
std::optional<mlir::Value> substringOffset;
|
|
if (hasSubcomp)
|
|
getSubcomponentIndices(xbox, xbox.getMemref(), operands, fieldIndices);
|
|
if (hasSubstr)
|
|
substringOffset = operands[xbox.getSubstrOperandIndex()];
|
|
mlir::Type llvmBaseType =
|
|
convertType(fir::unwrapRefType(xbox.getMemref().getType()));
|
|
base = genBoxOffsetGep(rewriter, loc, base, llvmBaseType, ptrOffset,
|
|
cstInteriorIndices, fieldIndices, substringOffset);
|
|
}
|
|
dest = insertBaseAddress(rewriter, loc, dest, base);
|
|
if (fir::isDerivedTypeWithLenParams(boxTy))
|
|
TODO(loc, "fir.embox codegen of derived with length parameters");
|
|
mlir::Value result = placeInMemoryIfNotGlobalInit(
|
|
rewriter, loc, boxTy, dest,
|
|
isDeviceAllocation(xbox.getMemref(), adaptor.getMemref()));
|
|
rewriter.replaceOp(xbox, result);
|
|
return mlir::success();
|
|
}
|
|
|
|
/// Return true if `xbox` has a normalized lower bounds attribute. A box value
|
|
/// that is neither a POINTER nor an ALLOCATABLE should be normalized to a
|
|
/// zero origin lower bound for interoperability with BIND(C).
|
|
inline static bool normalizedLowerBound(fir::cg::XEmboxOp xbox) {
|
|
return xbox->hasAttr(fir::getNormalizedLowerBoundAttrName());
|
|
}
|
|
};
|
|
|
|
/// Create a new box given a box reference.
|
|
struct XReboxOpConversion : public EmboxCommonConversion<fir::cg::XReboxOp> {
|
|
using EmboxCommonConversion::EmboxCommonConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::cg::XReboxOp rebox, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
mlir::Location loc = rebox.getLoc();
|
|
mlir::Type idxTy = lowerTy().indexType();
|
|
mlir::Value loweredBox = adaptor.getOperands()[0];
|
|
mlir::ValueRange operands = adaptor.getOperands();
|
|
|
|
// Inside a fir.global, the input box was produced as an llvm.struct<>
|
|
// because objects cannot be handled in memory inside a fir.global body that
|
|
// must be constant foldable. However, the type translation are not
|
|
// contextual, so the fir.box<T> type of the operation that produced the
|
|
// fir.box was translated to an llvm.ptr<llvm.struct<>> and the MLIR pass
|
|
// manager inserted a builtin.unrealized_conversion_cast that was inserted
|
|
// and needs to be removed here.
|
|
if (isInGlobalOp(rewriter))
|
|
if (auto unrealizedCast =
|
|
loweredBox.getDefiningOp<mlir::UnrealizedConversionCastOp>())
|
|
loweredBox = unrealizedCast.getInputs()[0];
|
|
|
|
TypePair inputBoxTyPair = getBoxTypePair(rebox.getBox().getType());
|
|
|
|
// Create new descriptor and fill its non-shape related data.
|
|
llvm::SmallVector<mlir::Value, 2> lenParams;
|
|
mlir::Type inputEleTy = getInputEleTy(rebox);
|
|
if (auto charTy = mlir::dyn_cast<fir::CharacterType>(inputEleTy)) {
|
|
if (charTy.hasConstantLen()) {
|
|
mlir::Value len =
|
|
genConstantIndex(loc, idxTy, rewriter, charTy.getLen());
|
|
lenParams.emplace_back(len);
|
|
} else {
|
|
mlir::Value len = getElementSizeFromBox(loc, idxTy, inputBoxTyPair,
|
|
loweredBox, rewriter);
|
|
if (charTy.getFKind() != 1) {
|
|
assert(!isInGlobalOp(rewriter) &&
|
|
"character target in global op must have constant length");
|
|
mlir::Value width =
|
|
genConstantIndex(loc, idxTy, rewriter, charTy.getFKind());
|
|
len = rewriter.create<mlir::LLVM::SDivOp>(loc, idxTy, len, width);
|
|
}
|
|
lenParams.emplace_back(len);
|
|
}
|
|
} else if (auto recTy = mlir::dyn_cast<fir::RecordType>(inputEleTy)) {
|
|
if (recTy.getNumLenParams() != 0)
|
|
TODO(loc, "reboxing descriptor of derived type with length parameters");
|
|
}
|
|
|
|
// Rebox on polymorphic entities needs to carry over the dynamic type.
|
|
mlir::Value typeDescAddr;
|
|
if (mlir::isa<fir::ClassType>(inputBoxTyPair.fir) &&
|
|
mlir::isa<fir::ClassType>(rebox.getType()))
|
|
typeDescAddr =
|
|
loadTypeDescAddress(loc, inputBoxTyPair, loweredBox, rewriter);
|
|
|
|
auto [boxTy, dest, eleSize] =
|
|
consDescriptorPrefix(rebox, loweredBox, rewriter, rebox.getOutRank(),
|
|
adaptor.getSubstr(), lenParams, typeDescAddr);
|
|
|
|
// Read input extents, strides, and base address
|
|
llvm::SmallVector<mlir::Value> inputExtents;
|
|
llvm::SmallVector<mlir::Value> inputStrides;
|
|
const unsigned inputRank = rebox.getRank();
|
|
for (unsigned dim = 0; dim < inputRank; ++dim) {
|
|
llvm::SmallVector<mlir::Value, 3> dimInfo =
|
|
getDimsFromBox(loc, {idxTy, idxTy, idxTy}, inputBoxTyPair, loweredBox,
|
|
dim, rewriter);
|
|
inputExtents.emplace_back(dimInfo[1]);
|
|
inputStrides.emplace_back(dimInfo[2]);
|
|
}
|
|
|
|
mlir::Value baseAddr =
|
|
getBaseAddrFromBox(loc, inputBoxTyPair, loweredBox, rewriter);
|
|
|
|
if (!rebox.getSlice().empty() || !rebox.getSubcomponent().empty())
|
|
return sliceBox(rebox, adaptor, boxTy, dest, baseAddr, inputExtents,
|
|
inputStrides, operands, rewriter);
|
|
return reshapeBox(rebox, adaptor, boxTy, dest, baseAddr, inputExtents,
|
|
inputStrides, operands, rewriter);
|
|
}
|
|
|
|
private:
|
|
/// Write resulting shape and base address in descriptor, and replace rebox
|
|
/// op.
|
|
llvm::LogicalResult
|
|
finalizeRebox(fir::cg::XReboxOp rebox, OpAdaptor adaptor,
|
|
mlir::Type destBoxTy, mlir::Value dest, mlir::Value base,
|
|
mlir::ValueRange lbounds, mlir::ValueRange extents,
|
|
mlir::ValueRange strides,
|
|
mlir::ConversionPatternRewriter &rewriter) const {
|
|
mlir::Location loc = rebox.getLoc();
|
|
mlir::Value zero =
|
|
genConstantIndex(loc, lowerTy().indexType(), rewriter, 0);
|
|
mlir::Value one = genConstantIndex(loc, lowerTy().indexType(), rewriter, 1);
|
|
for (auto iter : llvm::enumerate(llvm::zip(extents, strides))) {
|
|
mlir::Value extent = std::get<0>(iter.value());
|
|
unsigned dim = iter.index();
|
|
mlir::Value lb = one;
|
|
if (!lbounds.empty()) {
|
|
lb = integerCast(loc, rewriter, lowerTy().indexType(), lbounds[dim]);
|
|
auto extentIsEmpty = rewriter.create<mlir::LLVM::ICmpOp>(
|
|
loc, mlir::LLVM::ICmpPredicate::eq, extent, zero);
|
|
lb = rewriter.create<mlir::LLVM::SelectOp>(loc, extentIsEmpty, one, lb);
|
|
};
|
|
dest = insertLowerBound(rewriter, loc, dest, dim, lb);
|
|
dest = insertExtent(rewriter, loc, dest, dim, extent);
|
|
dest = insertStride(rewriter, loc, dest, dim, std::get<1>(iter.value()));
|
|
}
|
|
dest = insertBaseAddress(rewriter, loc, dest, base);
|
|
mlir::Value result = placeInMemoryIfNotGlobalInit(
|
|
rewriter, rebox.getLoc(), destBoxTy, dest,
|
|
isDeviceAllocation(rebox.getBox(), adaptor.getBox()));
|
|
rewriter.replaceOp(rebox, result);
|
|
return mlir::success();
|
|
}
|
|
|
|
// Apply slice given the base address, extents and strides of the input box.
|
|
llvm::LogicalResult
|
|
sliceBox(fir::cg::XReboxOp rebox, OpAdaptor adaptor, mlir::Type destBoxTy,
|
|
mlir::Value dest, mlir::Value base, mlir::ValueRange inputExtents,
|
|
mlir::ValueRange inputStrides, mlir::ValueRange operands,
|
|
mlir::ConversionPatternRewriter &rewriter) const {
|
|
mlir::Location loc = rebox.getLoc();
|
|
mlir::Type byteTy = ::getI8Type(rebox.getContext());
|
|
mlir::Type idxTy = lowerTy().indexType();
|
|
mlir::Value zero = genConstantIndex(loc, idxTy, rewriter, 0);
|
|
// Apply subcomponent and substring shift on base address.
|
|
if (!rebox.getSubcomponent().empty() || !rebox.getSubstr().empty()) {
|
|
// Cast to inputEleTy* so that a GEP can be used.
|
|
mlir::Type inputEleTy = getInputEleTy(rebox);
|
|
mlir::Type llvmBaseObjectType = convertType(inputEleTy);
|
|
llvm::SmallVector<mlir::Value> fieldIndices;
|
|
std::optional<mlir::Value> substringOffset;
|
|
if (!rebox.getSubcomponent().empty())
|
|
getSubcomponentIndices(rebox, rebox.getBox(), operands, fieldIndices);
|
|
if (!rebox.getSubstr().empty())
|
|
substringOffset = operands[rebox.getSubstrOperandIndex()];
|
|
base = genBoxOffsetGep(rewriter, loc, base, llvmBaseObjectType, zero,
|
|
/*cstInteriorIndices=*/std::nullopt, fieldIndices,
|
|
substringOffset);
|
|
}
|
|
|
|
if (rebox.getSlice().empty())
|
|
// The array section is of the form array[%component][substring], keep
|
|
// the input array extents and strides.
|
|
return finalizeRebox(rebox, adaptor, destBoxTy, dest, base,
|
|
/*lbounds*/ std::nullopt, inputExtents, inputStrides,
|
|
rewriter);
|
|
|
|
// The slice is of the form array(i:j:k)[%component]. Compute new extents
|
|
// and strides.
|
|
llvm::SmallVector<mlir::Value> slicedExtents;
|
|
llvm::SmallVector<mlir::Value> slicedStrides;
|
|
mlir::Value one = genConstantIndex(loc, idxTy, rewriter, 1);
|
|
const bool sliceHasOrigins = !rebox.getShift().empty();
|
|
unsigned sliceOps = rebox.getSliceOperandIndex();
|
|
unsigned shiftOps = rebox.getShiftOperandIndex();
|
|
auto strideOps = inputStrides.begin();
|
|
const unsigned inputRank = inputStrides.size();
|
|
for (unsigned i = 0; i < inputRank;
|
|
++i, ++strideOps, ++shiftOps, sliceOps += 3) {
|
|
mlir::Value sliceLb =
|
|
integerCast(loc, rewriter, idxTy, operands[sliceOps]);
|
|
mlir::Value inputStride = *strideOps; // already idxTy
|
|
// Apply origin shift: base += (lb-shift)*input_stride
|
|
mlir::Value sliceOrigin =
|
|
sliceHasOrigins
|
|
? integerCast(loc, rewriter, idxTy, operands[shiftOps])
|
|
: one;
|
|
mlir::Value diff =
|
|
rewriter.create<mlir::LLVM::SubOp>(loc, idxTy, sliceLb, sliceOrigin);
|
|
mlir::Value offset =
|
|
rewriter.create<mlir::LLVM::MulOp>(loc, idxTy, diff, inputStride);
|
|
// Strides from the fir.box are in bytes.
|
|
base = genGEP(loc, byteTy, rewriter, base, offset);
|
|
// Apply upper bound and step if this is a triplet. Otherwise, the
|
|
// dimension is dropped and no extents/strides are computed.
|
|
mlir::Value upper = operands[sliceOps + 1];
|
|
const bool isTripletSlice =
|
|
!mlir::isa_and_nonnull<mlir::LLVM::UndefOp>(upper.getDefiningOp());
|
|
if (isTripletSlice) {
|
|
mlir::Value step =
|
|
integerCast(loc, rewriter, idxTy, operands[sliceOps + 2]);
|
|
// extent = ub-lb+step/step
|
|
mlir::Value sliceUb = integerCast(loc, rewriter, idxTy, upper);
|
|
mlir::Value extent = computeTripletExtent(rewriter, loc, sliceLb,
|
|
sliceUb, step, zero, idxTy);
|
|
slicedExtents.emplace_back(extent);
|
|
// stride = step*input_stride
|
|
mlir::Value stride =
|
|
rewriter.create<mlir::LLVM::MulOp>(loc, idxTy, step, inputStride);
|
|
slicedStrides.emplace_back(stride);
|
|
}
|
|
}
|
|
return finalizeRebox(rebox, adaptor, destBoxTy, dest, base,
|
|
/*lbounds*/ std::nullopt, slicedExtents, slicedStrides,
|
|
rewriter);
|
|
}
|
|
|
|
/// Apply a new shape to the data described by a box given the base address,
|
|
/// extents and strides of the box.
|
|
llvm::LogicalResult
|
|
reshapeBox(fir::cg::XReboxOp rebox, OpAdaptor adaptor, mlir::Type destBoxTy,
|
|
mlir::Value dest, mlir::Value base, mlir::ValueRange inputExtents,
|
|
mlir::ValueRange inputStrides, mlir::ValueRange operands,
|
|
mlir::ConversionPatternRewriter &rewriter) const {
|
|
mlir::ValueRange reboxShifts{
|
|
operands.begin() + rebox.getShiftOperandIndex(),
|
|
operands.begin() + rebox.getShiftOperandIndex() +
|
|
rebox.getShift().size()};
|
|
if (rebox.getShape().empty()) {
|
|
// Only setting new lower bounds.
|
|
return finalizeRebox(rebox, adaptor, destBoxTy, dest, base, reboxShifts,
|
|
inputExtents, inputStrides, rewriter);
|
|
}
|
|
|
|
mlir::Location loc = rebox.getLoc();
|
|
|
|
llvm::SmallVector<mlir::Value> newStrides;
|
|
llvm::SmallVector<mlir::Value> newExtents;
|
|
mlir::Type idxTy = lowerTy().indexType();
|
|
// First stride from input box is kept. The rest is assumed contiguous
|
|
// (it is not possible to reshape otherwise). If the input is scalar,
|
|
// which may be OK if all new extents are ones, the stride does not
|
|
// matter, use one.
|
|
mlir::Value stride = inputStrides.empty()
|
|
? genConstantIndex(loc, idxTy, rewriter, 1)
|
|
: inputStrides[0];
|
|
for (unsigned i = 0; i < rebox.getShape().size(); ++i) {
|
|
mlir::Value rawExtent = operands[rebox.getShapeOperandIndex() + i];
|
|
mlir::Value extent = integerCast(loc, rewriter, idxTy, rawExtent);
|
|
newExtents.emplace_back(extent);
|
|
newStrides.emplace_back(stride);
|
|
// nextStride = extent * stride;
|
|
stride = rewriter.create<mlir::LLVM::MulOp>(loc, idxTy, extent, stride);
|
|
}
|
|
return finalizeRebox(rebox, adaptor, destBoxTy, dest, base, reboxShifts,
|
|
newExtents, newStrides, rewriter);
|
|
}
|
|
|
|
/// Return scalar element type of the input box.
|
|
static mlir::Type getInputEleTy(fir::cg::XReboxOp rebox) {
|
|
auto ty = fir::dyn_cast_ptrOrBoxEleTy(rebox.getBox().getType());
|
|
if (auto seqTy = mlir::dyn_cast<fir::SequenceType>(ty))
|
|
return seqTy.getEleTy();
|
|
return ty;
|
|
}
|
|
};
|
|
|
|
/// Lower `fir.emboxproc` operation. Creates a procedure box.
|
|
/// TODO: Part of supporting Fortran 2003 procedure pointers.
|
|
struct EmboxProcOpConversion : public fir::FIROpConversion<fir::EmboxProcOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::EmboxProcOp emboxproc, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
TODO(emboxproc.getLoc(), "fir.emboxproc codegen");
|
|
return mlir::failure();
|
|
}
|
|
};
|
|
|
|
// Code shared between insert_value and extract_value Ops.
|
|
struct ValueOpCommon {
|
|
// Translate the arguments pertaining to any multidimensional array to
|
|
// row-major order for LLVM-IR.
|
|
static void toRowMajor(llvm::SmallVectorImpl<int64_t> &indices,
|
|
mlir::Type ty) {
|
|
assert(ty && "type is null");
|
|
const auto end = indices.size();
|
|
for (std::remove_const_t<decltype(end)> i = 0; i < end; ++i) {
|
|
if (auto seq = mlir::dyn_cast<mlir::LLVM::LLVMArrayType>(ty)) {
|
|
const auto dim = getDimension(seq);
|
|
if (dim > 1) {
|
|
auto ub = std::min(i + dim, end);
|
|
std::reverse(indices.begin() + i, indices.begin() + ub);
|
|
i += dim - 1;
|
|
}
|
|
ty = getArrayElementType(seq);
|
|
} else if (auto st = mlir::dyn_cast<mlir::LLVM::LLVMStructType>(ty)) {
|
|
ty = st.getBody()[indices[i]];
|
|
} else {
|
|
llvm_unreachable("index into invalid type");
|
|
}
|
|
}
|
|
}
|
|
|
|
static llvm::SmallVector<int64_t>
|
|
collectIndices(mlir::ConversionPatternRewriter &rewriter,
|
|
mlir::ArrayAttr arrAttr) {
|
|
llvm::SmallVector<int64_t> indices;
|
|
for (auto i = arrAttr.begin(), e = arrAttr.end(); i != e; ++i) {
|
|
if (auto intAttr = mlir::dyn_cast<mlir::IntegerAttr>(*i)) {
|
|
indices.push_back(intAttr.getInt());
|
|
} else {
|
|
auto fieldName = mlir::cast<mlir::StringAttr>(*i).getValue();
|
|
++i;
|
|
auto ty = mlir::cast<mlir::TypeAttr>(*i).getValue();
|
|
auto index = mlir::cast<fir::RecordType>(ty).getFieldIndex(fieldName);
|
|
indices.push_back(index);
|
|
}
|
|
}
|
|
return indices;
|
|
}
|
|
|
|
private:
|
|
static mlir::Type getArrayElementType(mlir::LLVM::LLVMArrayType ty) {
|
|
auto eleTy = ty.getElementType();
|
|
while (auto arrTy = mlir::dyn_cast<mlir::LLVM::LLVMArrayType>(eleTy))
|
|
eleTy = arrTy.getElementType();
|
|
return eleTy;
|
|
}
|
|
};
|
|
|
|
namespace {
|
|
/// Extract a subobject value from an ssa-value of aggregate type
|
|
struct ExtractValueOpConversion
|
|
: public fir::FIROpAndTypeConversion<fir::ExtractValueOp>,
|
|
public ValueOpCommon {
|
|
using FIROpAndTypeConversion::FIROpAndTypeConversion;
|
|
|
|
llvm::LogicalResult
|
|
doRewrite(fir::ExtractValueOp extractVal, mlir::Type ty, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
mlir::ValueRange operands = adaptor.getOperands();
|
|
auto indices = collectIndices(rewriter, extractVal.getCoor());
|
|
toRowMajor(indices, operands[0].getType());
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::ExtractValueOp>(
|
|
extractVal, operands[0], indices);
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
/// InsertValue is the generalized instruction for the composition of new
|
|
/// aggregate type values.
|
|
struct InsertValueOpConversion
|
|
: public mlir::OpConversionPattern<fir::InsertValueOp>,
|
|
public ValueOpCommon {
|
|
using OpConversionPattern::OpConversionPattern;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::InsertValueOp insertVal, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
mlir::ValueRange operands = adaptor.getOperands();
|
|
auto indices = collectIndices(rewriter, insertVal.getCoor());
|
|
toRowMajor(indices, operands[0].getType());
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::InsertValueOp>(
|
|
insertVal, operands[0], operands[1], indices);
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
/// InsertOnRange inserts a value into a sequence over a range of offsets.
|
|
struct InsertOnRangeOpConversion
|
|
: public fir::FIROpAndTypeConversion<fir::InsertOnRangeOp> {
|
|
using FIROpAndTypeConversion::FIROpAndTypeConversion;
|
|
|
|
// Increments an array of subscripts in a row major fasion.
|
|
void incrementSubscripts(llvm::ArrayRef<int64_t> dims,
|
|
llvm::SmallVectorImpl<int64_t> &subscripts) const {
|
|
for (size_t i = dims.size(); i > 0; --i) {
|
|
if (++subscripts[i - 1] < dims[i - 1]) {
|
|
return;
|
|
}
|
|
subscripts[i - 1] = 0;
|
|
}
|
|
}
|
|
|
|
llvm::LogicalResult
|
|
doRewrite(fir::InsertOnRangeOp range, mlir::Type ty, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
|
|
llvm::SmallVector<std::int64_t> dims;
|
|
auto type = adaptor.getOperands()[0].getType();
|
|
|
|
// Iteratively extract the array dimensions from the type.
|
|
while (auto t = mlir::dyn_cast<mlir::LLVM::LLVMArrayType>(type)) {
|
|
dims.push_back(t.getNumElements());
|
|
type = t.getElementType();
|
|
}
|
|
|
|
llvm::SmallVector<std::int64_t> lBounds;
|
|
llvm::SmallVector<std::int64_t> uBounds;
|
|
|
|
// Unzip the upper and lower bound and convert to a row major format.
|
|
mlir::DenseIntElementsAttr coor = range.getCoor();
|
|
auto reversedCoor = llvm::reverse(coor.getValues<int64_t>());
|
|
for (auto i = reversedCoor.begin(), e = reversedCoor.end(); i != e; ++i) {
|
|
uBounds.push_back(*i++);
|
|
lBounds.push_back(*i);
|
|
}
|
|
|
|
auto &subscripts = lBounds;
|
|
auto loc = range.getLoc();
|
|
mlir::Value lastOp = adaptor.getOperands()[0];
|
|
mlir::Value insertVal = adaptor.getOperands()[1];
|
|
|
|
while (subscripts != uBounds) {
|
|
lastOp = rewriter.create<mlir::LLVM::InsertValueOp>(
|
|
loc, lastOp, insertVal, subscripts);
|
|
|
|
incrementSubscripts(dims, subscripts);
|
|
}
|
|
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::InsertValueOp>(
|
|
range, lastOp, insertVal, subscripts);
|
|
|
|
return mlir::success();
|
|
}
|
|
};
|
|
} // namespace
|
|
|
|
namespace {
|
|
/// XArrayCoor is the address arithmetic on a dynamically shaped, sliced,
|
|
/// shifted etc. array.
|
|
/// (See the static restriction on coordinate_of.) array_coor determines the
|
|
/// coordinate (location) of a specific element.
|
|
struct XArrayCoorOpConversion
|
|
: public fir::FIROpAndTypeConversion<fir::cg::XArrayCoorOp> {
|
|
using FIROpAndTypeConversion::FIROpAndTypeConversion;
|
|
|
|
llvm::LogicalResult
|
|
doRewrite(fir::cg::XArrayCoorOp coor, mlir::Type llvmPtrTy, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
auto loc = coor.getLoc();
|
|
mlir::ValueRange operands = adaptor.getOperands();
|
|
unsigned rank = coor.getRank();
|
|
assert(coor.getIndices().size() == rank);
|
|
assert(coor.getShape().empty() || coor.getShape().size() == rank);
|
|
assert(coor.getShift().empty() || coor.getShift().size() == rank);
|
|
assert(coor.getSlice().empty() || coor.getSlice().size() == 3 * rank);
|
|
mlir::Type idxTy = lowerTy().indexType();
|
|
unsigned indexOffset = coor.getIndicesOperandIndex();
|
|
unsigned shapeOffset = coor.getShapeOperandIndex();
|
|
unsigned shiftOffset = coor.getShiftOperandIndex();
|
|
unsigned sliceOffset = coor.getSliceOperandIndex();
|
|
auto sliceOps = coor.getSlice().begin();
|
|
mlir::Value one = genConstantIndex(loc, idxTy, rewriter, 1);
|
|
mlir::Value prevExt = one;
|
|
mlir::Value offset = genConstantIndex(loc, idxTy, rewriter, 0);
|
|
const bool isShifted = !coor.getShift().empty();
|
|
const bool isSliced = !coor.getSlice().empty();
|
|
const bool baseIsBoxed =
|
|
mlir::isa<fir::BaseBoxType>(coor.getMemref().getType());
|
|
TypePair baseBoxTyPair =
|
|
baseIsBoxed ? getBoxTypePair(coor.getMemref().getType()) : TypePair{};
|
|
mlir::LLVM::IntegerOverflowFlags nsw =
|
|
mlir::LLVM::IntegerOverflowFlags::nsw;
|
|
|
|
// For each dimension of the array, generate the offset calculation.
|
|
for (unsigned i = 0; i < rank; ++i, ++indexOffset, ++shapeOffset,
|
|
++shiftOffset, sliceOffset += 3, sliceOps += 3) {
|
|
mlir::Value index =
|
|
integerCast(loc, rewriter, idxTy, operands[indexOffset]);
|
|
mlir::Value lb =
|
|
isShifted ? integerCast(loc, rewriter, idxTy, operands[shiftOffset])
|
|
: one;
|
|
mlir::Value step = one;
|
|
bool normalSlice = isSliced;
|
|
// Compute zero based index in dimension i of the element, applying
|
|
// potential triplets and lower bounds.
|
|
if (isSliced) {
|
|
mlir::Value originalUb = *(sliceOps + 1);
|
|
normalSlice =
|
|
!mlir::isa_and_nonnull<fir::UndefOp>(originalUb.getDefiningOp());
|
|
if (normalSlice)
|
|
step = integerCast(loc, rewriter, idxTy, operands[sliceOffset + 2]);
|
|
}
|
|
auto idx = rewriter.create<mlir::LLVM::SubOp>(loc, idxTy, index, lb, nsw);
|
|
mlir::Value diff =
|
|
rewriter.create<mlir::LLVM::MulOp>(loc, idxTy, idx, step, nsw);
|
|
if (normalSlice) {
|
|
mlir::Value sliceLb =
|
|
integerCast(loc, rewriter, idxTy, operands[sliceOffset]);
|
|
auto adj =
|
|
rewriter.create<mlir::LLVM::SubOp>(loc, idxTy, sliceLb, lb, nsw);
|
|
diff = rewriter.create<mlir::LLVM::AddOp>(loc, idxTy, diff, adj, nsw);
|
|
}
|
|
// Update the offset given the stride and the zero based index `diff`
|
|
// that was just computed.
|
|
if (baseIsBoxed) {
|
|
// Use stride in bytes from the descriptor.
|
|
mlir::Value stride =
|
|
getStrideFromBox(loc, baseBoxTyPair, operands[0], i, rewriter);
|
|
auto sc =
|
|
rewriter.create<mlir::LLVM::MulOp>(loc, idxTy, diff, stride, nsw);
|
|
offset =
|
|
rewriter.create<mlir::LLVM::AddOp>(loc, idxTy, sc, offset, nsw);
|
|
} else {
|
|
// Use stride computed at last iteration.
|
|
auto sc =
|
|
rewriter.create<mlir::LLVM::MulOp>(loc, idxTy, diff, prevExt, nsw);
|
|
offset =
|
|
rewriter.create<mlir::LLVM::AddOp>(loc, idxTy, sc, offset, nsw);
|
|
// Compute next stride assuming contiguity of the base array
|
|
// (in element number).
|
|
auto nextExt = integerCast(loc, rewriter, idxTy, operands[shapeOffset]);
|
|
prevExt = rewriter.create<mlir::LLVM::MulOp>(loc, idxTy, prevExt,
|
|
nextExt, nsw);
|
|
}
|
|
}
|
|
|
|
// Add computed offset to the base address.
|
|
if (baseIsBoxed) {
|
|
// Working with byte offsets. The base address is read from the fir.box.
|
|
// and used in i8* GEP to do the pointer arithmetic.
|
|
mlir::Type byteTy = ::getI8Type(coor.getContext());
|
|
mlir::Value base =
|
|
getBaseAddrFromBox(loc, baseBoxTyPair, operands[0], rewriter);
|
|
llvm::SmallVector<mlir::LLVM::GEPArg> args{offset};
|
|
auto addr = rewriter.create<mlir::LLVM::GEPOp>(loc, llvmPtrTy, byteTy,
|
|
base, args);
|
|
if (coor.getSubcomponent().empty()) {
|
|
rewriter.replaceOp(coor, addr);
|
|
return mlir::success();
|
|
}
|
|
// Cast the element address from void* to the derived type so that the
|
|
// derived type members can be addresses via a GEP using the index of
|
|
// components.
|
|
mlir::Type elementType =
|
|
getLlvmObjectTypeFromBoxType(coor.getMemref().getType());
|
|
while (auto arrayTy =
|
|
mlir::dyn_cast<mlir::LLVM::LLVMArrayType>(elementType))
|
|
elementType = arrayTy.getElementType();
|
|
args.clear();
|
|
args.push_back(0);
|
|
if (!coor.getLenParams().empty()) {
|
|
// If type parameters are present, then we don't want to use a GEPOp
|
|
// as below, as the LLVM struct type cannot be statically defined.
|
|
TODO(loc, "derived type with type parameters");
|
|
}
|
|
llvm::SmallVector<mlir::Value> indices = convertSubcomponentIndices(
|
|
loc, elementType,
|
|
operands.slice(coor.getSubcomponentOperandIndex(),
|
|
coor.getSubcomponent().size()));
|
|
args.append(indices.begin(), indices.end());
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::GEPOp>(coor, llvmPtrTy,
|
|
elementType, addr, args);
|
|
return mlir::success();
|
|
}
|
|
|
|
// The array was not boxed, so it must be contiguous. offset is therefore an
|
|
// element offset and the base type is kept in the GEP unless the element
|
|
// type size is itself dynamic.
|
|
mlir::Type objectTy = fir::unwrapRefType(coor.getMemref().getType());
|
|
mlir::Type eleType = fir::unwrapSequenceType(objectTy);
|
|
mlir::Type gepObjectType = convertType(eleType);
|
|
llvm::SmallVector<mlir::LLVM::GEPArg> args;
|
|
if (coor.getSubcomponent().empty()) {
|
|
// No subcomponent.
|
|
if (!coor.getLenParams().empty()) {
|
|
// Type parameters. Adjust element size explicitly.
|
|
auto eleTy = fir::dyn_cast_ptrEleTy(coor.getType());
|
|
assert(eleTy && "result must be a reference-like type");
|
|
if (fir::characterWithDynamicLen(eleTy)) {
|
|
assert(coor.getLenParams().size() == 1);
|
|
auto length = integerCast(loc, rewriter, idxTy,
|
|
operands[coor.getLenParamsOperandIndex()]);
|
|
offset = rewriter.create<mlir::LLVM::MulOp>(loc, idxTy, offset,
|
|
length, nsw);
|
|
} else {
|
|
TODO(loc, "compute size of derived type with type parameters");
|
|
}
|
|
}
|
|
args.push_back(offset);
|
|
} else {
|
|
// There are subcomponents.
|
|
args.push_back(offset);
|
|
llvm::SmallVector<mlir::Value> indices = convertSubcomponentIndices(
|
|
loc, gepObjectType,
|
|
operands.slice(coor.getSubcomponentOperandIndex(),
|
|
coor.getSubcomponent().size()));
|
|
args.append(indices.begin(), indices.end());
|
|
}
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::GEPOp>(
|
|
coor, llvmPtrTy, gepObjectType, adaptor.getMemref(), args);
|
|
return mlir::success();
|
|
}
|
|
};
|
|
} // namespace
|
|
|
|
/// Convert to (memory) reference to a reference to a subobject.
|
|
/// The coordinate_of op is a Swiss army knife operation that can be used on
|
|
/// (memory) references to records, arrays, complex, etc. as well as boxes.
|
|
/// With unboxed arrays, there is the restriction that the array have a static
|
|
/// shape in all but the last column.
|
|
struct CoordinateOpConversion
|
|
: public fir::FIROpAndTypeConversion<fir::CoordinateOp> {
|
|
using FIROpAndTypeConversion::FIROpAndTypeConversion;
|
|
|
|
llvm::LogicalResult
|
|
doRewrite(fir::CoordinateOp coor, mlir::Type ty, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
mlir::ValueRange operands = adaptor.getOperands();
|
|
|
|
mlir::Location loc = coor.getLoc();
|
|
mlir::Value base = operands[0];
|
|
mlir::Type baseObjectTy = coor.getBaseType();
|
|
mlir::Type objectTy = fir::dyn_cast_ptrOrBoxEleTy(baseObjectTy);
|
|
assert(objectTy && "fir.coordinate_of expects a reference type");
|
|
mlir::Type llvmObjectTy = convertType(objectTy);
|
|
|
|
// Complex type - basically, extract the real or imaginary part
|
|
// FIXME: double check why this is done before the fir.box case below.
|
|
if (fir::isa_complex(objectTy)) {
|
|
mlir::Value gep =
|
|
genGEP(loc, llvmObjectTy, rewriter, base, 0, operands[1]);
|
|
rewriter.replaceOp(coor, gep);
|
|
return mlir::success();
|
|
}
|
|
|
|
// Boxed type - get the base pointer from the box
|
|
if (mlir::dyn_cast<fir::BaseBoxType>(baseObjectTy))
|
|
return doRewriteBox(coor, operands, loc, rewriter);
|
|
|
|
// Reference, pointer or a heap type
|
|
if (mlir::isa<fir::ReferenceType, fir::PointerType, fir::HeapType>(
|
|
baseObjectTy))
|
|
return doRewriteRefOrPtr(coor, llvmObjectTy, operands, loc, rewriter);
|
|
|
|
return rewriter.notifyMatchFailure(
|
|
coor, "fir.coordinate_of base operand has unsupported type");
|
|
}
|
|
|
|
static unsigned getFieldNumber(fir::RecordType ty, mlir::Value op) {
|
|
return fir::hasDynamicSize(ty)
|
|
? op.getDefiningOp()
|
|
->getAttrOfType<mlir::IntegerAttr>("field")
|
|
.getInt()
|
|
: getConstantIntValue(op);
|
|
}
|
|
|
|
static bool hasSubDimensions(mlir::Type type) {
|
|
return mlir::isa<fir::SequenceType, fir::RecordType, mlir::TupleType>(type);
|
|
}
|
|
|
|
// Helper structure to analyze the CoordinateOp path and decide if and how
|
|
// the GEP should be generated for it.
|
|
struct ShapeAnalysis {
|
|
bool hasKnownShape;
|
|
bool columnIsDeferred;
|
|
};
|
|
|
|
/// Walk the abstract memory layout and determine if the path traverses any
|
|
/// array types with unknown shape. Return true iff all the array types have a
|
|
/// constant shape along the path.
|
|
/// TODO: move the verification logic into the verifier.
|
|
static std::optional<ShapeAnalysis>
|
|
arraysHaveKnownShape(mlir::Type type, fir::CoordinateOp coor) {
|
|
fir::CoordinateIndicesAdaptor indices = coor.getIndices();
|
|
auto begin = indices.begin();
|
|
bool hasKnownShape = true;
|
|
bool columnIsDeferred = false;
|
|
for (auto it = begin, end = indices.end(); it != end;) {
|
|
if (auto arrTy = mlir::dyn_cast<fir::SequenceType>(type)) {
|
|
bool addressingStart = (it == begin);
|
|
unsigned arrayDim = arrTy.getDimension();
|
|
for (auto dimExtent : llvm::enumerate(arrTy.getShape())) {
|
|
if (dimExtent.value() == fir::SequenceType::getUnknownExtent()) {
|
|
hasKnownShape = false;
|
|
if (addressingStart && dimExtent.index() + 1 == arrayDim) {
|
|
// If this point was reached, the raws of the first array have
|
|
// constant extents.
|
|
columnIsDeferred = true;
|
|
} else {
|
|
// One of the array dimension that is not the column of the first
|
|
// array has dynamic extent. It will not possible to do
|
|
// code generation for the CoordinateOp if the base is not a
|
|
// fir.box containing the value of that extent.
|
|
return ShapeAnalysis{false, false};
|
|
}
|
|
}
|
|
// There may be less operands than the array size if the
|
|
// fir.coordinate_of result is not an element but a sub-array.
|
|
if (it != end)
|
|
++it;
|
|
}
|
|
type = arrTy.getEleTy();
|
|
continue;
|
|
}
|
|
if (auto strTy = mlir::dyn_cast<fir::RecordType>(type)) {
|
|
auto intAttr = llvm::dyn_cast<mlir::IntegerAttr>(*it);
|
|
if (!intAttr) {
|
|
mlir::emitError(coor.getLoc(),
|
|
"expected field name in fir.coordinate_of");
|
|
return std::nullopt;
|
|
}
|
|
type = strTy.getType(intAttr.getInt());
|
|
} else if (auto strTy = mlir::dyn_cast<mlir::TupleType>(type)) {
|
|
auto value = llvm::dyn_cast<mlir::Value>(*it);
|
|
if (!value) {
|
|
mlir::emitError(
|
|
coor.getLoc(),
|
|
"expected constant value to address tuple in fir.coordinate_of");
|
|
return std::nullopt;
|
|
}
|
|
type = strTy.getType(getConstantIntValue(value));
|
|
} else if (auto charType = mlir::dyn_cast<fir::CharacterType>(type)) {
|
|
// Addressing character in string. Fortran strings degenerate to arrays
|
|
// in LLVM, so they are handled like arrays of characters here.
|
|
if (charType.getLen() == fir::CharacterType::unknownLen())
|
|
return ShapeAnalysis{false, true};
|
|
type = fir::CharacterType::getSingleton(charType.getContext(),
|
|
charType.getFKind());
|
|
}
|
|
++it;
|
|
}
|
|
return ShapeAnalysis{hasKnownShape, columnIsDeferred};
|
|
}
|
|
|
|
private:
|
|
llvm::LogicalResult
|
|
doRewriteBox(fir::CoordinateOp coor, mlir::ValueRange operands,
|
|
mlir::Location loc,
|
|
mlir::ConversionPatternRewriter &rewriter) const {
|
|
mlir::Type boxObjTy = coor.getBaseType();
|
|
assert(mlir::dyn_cast<fir::BaseBoxType>(boxObjTy) &&
|
|
"This is not a `fir.box`");
|
|
TypePair boxTyPair = getBoxTypePair(boxObjTy);
|
|
|
|
mlir::Value boxBaseAddr = operands[0];
|
|
|
|
// 1. SPECIAL CASE (uses `fir.len_param_index`):
|
|
// %box = ... : !fir.box<!fir.type<derived{len1:i32}>>
|
|
// %lenp = fir.len_param_index len1, !fir.type<derived{len1:i32}>
|
|
// %addr = coordinate_of %box, %lenp
|
|
if (coor.getNumOperands() == 2) {
|
|
mlir::Operation *coordinateDef =
|
|
(*coor.getCoor().begin()).getDefiningOp();
|
|
if (mlir::isa_and_nonnull<fir::LenParamIndexOp>(coordinateDef))
|
|
TODO(loc,
|
|
"fir.coordinate_of - fir.len_param_index is not supported yet");
|
|
}
|
|
|
|
// 2. GENERAL CASE:
|
|
// 2.1. (`fir.array`)
|
|
// %box = ... : !fix.box<!fir.array<?xU>>
|
|
// %idx = ... : index
|
|
// %resultAddr = coordinate_of %box, %idx : !fir.ref<U>
|
|
// 2.2 (`fir.derived`)
|
|
// %box = ... : !fix.box<!fir.type<derived_type{field_1:i32}>>
|
|
// %idx = ... : i32
|
|
// %resultAddr = coordinate_of %box, %idx : !fir.ref<i32>
|
|
// 2.3 (`fir.derived` inside `fir.array`)
|
|
// %box = ... : !fir.box<!fir.array<10 x !fir.type<derived_1{field_1:f32,
|
|
// field_2:f32}>>> %idx1 = ... : index %idx2 = ... : i32 %resultAddr =
|
|
// coordinate_of %box, %idx1, %idx2 : !fir.ref<f32>
|
|
// 2.4. TODO: Either document or disable any other case that the following
|
|
// implementation might convert.
|
|
mlir::Value resultAddr =
|
|
getBaseAddrFromBox(loc, boxTyPair, boxBaseAddr, rewriter);
|
|
// Component Type
|
|
auto cpnTy = fir::dyn_cast_ptrOrBoxEleTy(boxObjTy);
|
|
mlir::Type llvmPtrTy = ::getLlvmPtrType(coor.getContext());
|
|
mlir::Type byteTy = ::getI8Type(coor.getContext());
|
|
mlir::LLVM::IntegerOverflowFlags nsw =
|
|
mlir::LLVM::IntegerOverflowFlags::nsw;
|
|
|
|
int nextIndexValue = 1;
|
|
fir::CoordinateIndicesAdaptor indices = coor.getIndices();
|
|
for (auto it = indices.begin(), end = indices.end(); it != end;) {
|
|
if (auto arrTy = mlir::dyn_cast<fir::SequenceType>(cpnTy)) {
|
|
if (it != indices.begin())
|
|
TODO(loc, "fir.array nested inside other array and/or derived type");
|
|
// Applies byte strides from the box. Ignore lower bound from box
|
|
// since fir.coordinate_of indexes are zero based. Lowering takes care
|
|
// of lower bound aspects. This both accounts for dynamically sized
|
|
// types and non contiguous arrays.
|
|
auto idxTy = lowerTy().indexType();
|
|
mlir::Value off = genConstantIndex(loc, idxTy, rewriter, 0);
|
|
unsigned arrayDim = arrTy.getDimension();
|
|
for (unsigned dim = 0; dim < arrayDim && it != end; ++dim, ++it) {
|
|
mlir::Value stride =
|
|
getStrideFromBox(loc, boxTyPair, operands[0], dim, rewriter);
|
|
auto sc = rewriter.create<mlir::LLVM::MulOp>(
|
|
loc, idxTy, operands[nextIndexValue + dim], stride, nsw);
|
|
off = rewriter.create<mlir::LLVM::AddOp>(loc, idxTy, sc, off, nsw);
|
|
}
|
|
nextIndexValue += arrayDim;
|
|
resultAddr = rewriter.create<mlir::LLVM::GEPOp>(
|
|
loc, llvmPtrTy, byteTy, resultAddr,
|
|
llvm::ArrayRef<mlir::LLVM::GEPArg>{off});
|
|
cpnTy = arrTy.getEleTy();
|
|
} else if (auto recTy = mlir::dyn_cast<fir::RecordType>(cpnTy)) {
|
|
auto intAttr = llvm::dyn_cast<mlir::IntegerAttr>(*it);
|
|
if (!intAttr)
|
|
return mlir::emitError(loc,
|
|
"expected field name in fir.coordinate_of");
|
|
int fieldIndex = intAttr.getInt();
|
|
++it;
|
|
cpnTy = recTy.getType(fieldIndex);
|
|
auto llvmRecTy = lowerTy().convertType(recTy);
|
|
resultAddr = rewriter.create<mlir::LLVM::GEPOp>(
|
|
loc, llvmPtrTy, llvmRecTy, resultAddr,
|
|
llvm::ArrayRef<mlir::LLVM::GEPArg>{0, fieldIndex});
|
|
} else {
|
|
fir::emitFatalError(loc, "unexpected type in coordinate_of");
|
|
}
|
|
}
|
|
|
|
rewriter.replaceOp(coor, resultAddr);
|
|
return mlir::success();
|
|
}
|
|
|
|
llvm::LogicalResult
|
|
doRewriteRefOrPtr(fir::CoordinateOp coor, mlir::Type llvmObjectTy,
|
|
mlir::ValueRange operands, mlir::Location loc,
|
|
mlir::ConversionPatternRewriter &rewriter) const {
|
|
mlir::Type baseObjectTy = coor.getBaseType();
|
|
|
|
// Component Type
|
|
mlir::Type cpnTy = fir::dyn_cast_ptrOrBoxEleTy(baseObjectTy);
|
|
|
|
const std::optional<ShapeAnalysis> shapeAnalysis =
|
|
arraysHaveKnownShape(cpnTy, coor);
|
|
if (!shapeAnalysis)
|
|
return mlir::failure();
|
|
|
|
if (fir::hasDynamicSize(fir::unwrapSequenceType(cpnTy)))
|
|
return mlir::emitError(
|
|
loc, "fir.coordinate_of with a dynamic element size is unsupported");
|
|
|
|
if (shapeAnalysis->hasKnownShape || shapeAnalysis->columnIsDeferred) {
|
|
llvm::SmallVector<mlir::LLVM::GEPArg> offs;
|
|
if (shapeAnalysis->hasKnownShape) {
|
|
offs.push_back(0);
|
|
}
|
|
// Else, only the column is `?` and we can simply place the column value
|
|
// in the 0-th GEP position.
|
|
|
|
std::optional<int> dims;
|
|
llvm::SmallVector<mlir::Value> arrIdx;
|
|
int nextIndexValue = 1;
|
|
for (auto index : coor.getIndices()) {
|
|
if (auto intAttr = llvm::dyn_cast<mlir::IntegerAttr>(index)) {
|
|
// Addressing derived type component.
|
|
auto recordType = llvm::dyn_cast<fir::RecordType>(cpnTy);
|
|
if (!recordType)
|
|
return mlir::emitError(
|
|
loc,
|
|
"fir.coordinate base type is not consistent with operands");
|
|
int fieldId = intAttr.getInt();
|
|
cpnTy = recordType.getType(fieldId);
|
|
offs.push_back(fieldId);
|
|
continue;
|
|
}
|
|
// Value index (addressing array, tuple, or complex part).
|
|
mlir::Value indexValue = operands[nextIndexValue++];
|
|
if (auto tupTy = mlir::dyn_cast<mlir::TupleType>(cpnTy)) {
|
|
cpnTy = tupTy.getType(getConstantIntValue(indexValue));
|
|
offs.push_back(indexValue);
|
|
} else {
|
|
if (!dims) {
|
|
if (auto arrayType = llvm::dyn_cast<fir::SequenceType>(cpnTy)) {
|
|
// Starting addressing array or array component.
|
|
dims = arrayType.getDimension();
|
|
cpnTy = arrayType.getElementType();
|
|
}
|
|
}
|
|
if (dims) {
|
|
arrIdx.push_back(indexValue);
|
|
if (--(*dims) == 0) {
|
|
// Append array range in reverse (FIR arrays are column-major).
|
|
offs.append(arrIdx.rbegin(), arrIdx.rend());
|
|
arrIdx.clear();
|
|
dims.reset();
|
|
}
|
|
} else {
|
|
offs.push_back(indexValue);
|
|
}
|
|
}
|
|
}
|
|
// It is possible the fir.coordinate_of result is a sub-array, in which
|
|
// case there may be some "unfinished" array indices to reverse and push.
|
|
if (!arrIdx.empty())
|
|
offs.append(arrIdx.rbegin(), arrIdx.rend());
|
|
|
|
mlir::Value base = operands[0];
|
|
mlir::Value retval = genGEP(loc, llvmObjectTy, rewriter, base, offs);
|
|
rewriter.replaceOp(coor, retval);
|
|
return mlir::success();
|
|
}
|
|
|
|
return mlir::emitError(
|
|
loc, "fir.coordinate_of base operand has unsupported type");
|
|
}
|
|
};
|
|
|
|
/// Convert `fir.field_index`. The conversion depends on whether the size of
|
|
/// the record is static or dynamic.
|
|
struct FieldIndexOpConversion : public fir::FIROpConversion<fir::FieldIndexOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
// NB: most field references should be resolved by this point
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::FieldIndexOp field, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
auto recTy = mlir::cast<fir::RecordType>(field.getOnType());
|
|
unsigned index = recTy.getFieldIndex(field.getFieldId());
|
|
|
|
if (!fir::hasDynamicSize(recTy)) {
|
|
// Derived type has compile-time constant layout. Return index of the
|
|
// component type in the parent type (to be used in GEP).
|
|
rewriter.replaceOp(field, mlir::ValueRange{genConstantOffset(
|
|
field.getLoc(), rewriter, index)});
|
|
return mlir::success();
|
|
}
|
|
|
|
// Derived type has compile-time constant layout. Call the compiler
|
|
// generated function to determine the byte offset of the field at runtime.
|
|
// This returns a non-constant.
|
|
mlir::FlatSymbolRefAttr symAttr = mlir::SymbolRefAttr::get(
|
|
field.getContext(), getOffsetMethodName(recTy, field.getFieldId()));
|
|
mlir::NamedAttribute callAttr = rewriter.getNamedAttr("callee", symAttr);
|
|
mlir::NamedAttribute fieldAttr = rewriter.getNamedAttr(
|
|
"field", mlir::IntegerAttr::get(lowerTy().indexType(), index));
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::CallOp>(
|
|
field, lowerTy().offsetType(), adaptor.getOperands(),
|
|
addLLVMOpBundleAttrs(rewriter, {callAttr, fieldAttr},
|
|
adaptor.getOperands().size()));
|
|
return mlir::success();
|
|
}
|
|
|
|
// Re-Construct the name of the compiler generated method that calculates the
|
|
// offset
|
|
inline static std::string getOffsetMethodName(fir::RecordType recTy,
|
|
llvm::StringRef field) {
|
|
return recTy.getName().str() + "P." + field.str() + ".offset";
|
|
}
|
|
};
|
|
|
|
/// Convert `fir.end`
|
|
struct FirEndOpConversion : public fir::FIROpConversion<fir::FirEndOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::FirEndOp firEnd, OpAdaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
TODO(firEnd.getLoc(), "fir.end codegen");
|
|
return mlir::failure();
|
|
}
|
|
};
|
|
|
|
/// Lower `fir.type_desc` to a global addr.
|
|
struct TypeDescOpConversion : public fir::FIROpConversion<fir::TypeDescOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::TypeDescOp typeDescOp, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
mlir::Type inTy = typeDescOp.getInType();
|
|
assert(mlir::isa<fir::RecordType>(inTy) && "expecting fir.type");
|
|
auto recordType = mlir::dyn_cast<fir::RecordType>(inTy);
|
|
auto module = typeDescOp.getOperation()->getParentOfType<mlir::ModuleOp>();
|
|
std::string typeDescName =
|
|
this->options.typeDescriptorsRenamedForAssembly
|
|
? fir::NameUniquer::getTypeDescriptorAssemblyName(
|
|
recordType.getName())
|
|
: fir::NameUniquer::getTypeDescriptorName(recordType.getName());
|
|
auto llvmPtrTy = ::getLlvmPtrType(typeDescOp.getContext());
|
|
if (auto global = module.lookupSymbol<mlir::LLVM::GlobalOp>(typeDescName)) {
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::AddressOfOp>(
|
|
typeDescOp, llvmPtrTy, global.getSymName());
|
|
return mlir::success();
|
|
} else if (auto global = module.lookupSymbol<fir::GlobalOp>(typeDescName)) {
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::AddressOfOp>(
|
|
typeDescOp, llvmPtrTy, global.getSymName());
|
|
return mlir::success();
|
|
}
|
|
return mlir::failure();
|
|
}
|
|
};
|
|
|
|
/// Lower `fir.has_value` operation to `llvm.return` operation.
|
|
struct HasValueOpConversion
|
|
: public mlir::OpConversionPattern<fir::HasValueOp> {
|
|
using OpConversionPattern::OpConversionPattern;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::HasValueOp op, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::ReturnOp>(op,
|
|
adaptor.getOperands());
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
#ifndef NDEBUG
|
|
// Check if attr's type is compatible with ty.
|
|
//
|
|
// This is done by comparing attr's element type, converted to LLVM type,
|
|
// with ty's element type.
|
|
//
|
|
// Only integer and floating point (including complex) attributes are
|
|
// supported. Also, attr is expected to have a TensorType and ty is expected
|
|
// to be of LLVMArrayType. If any of the previous conditions is false, then
|
|
// the specified attr and ty are not supported by this function and are
|
|
// assumed to be compatible.
|
|
static inline bool attributeTypeIsCompatible(mlir::MLIRContext *ctx,
|
|
mlir::Attribute attr,
|
|
mlir::Type ty) {
|
|
// Get attr's LLVM element type.
|
|
if (!attr)
|
|
return true;
|
|
auto intOrFpEleAttr = mlir::dyn_cast<mlir::DenseIntOrFPElementsAttr>(attr);
|
|
if (!intOrFpEleAttr)
|
|
return true;
|
|
auto tensorTy = mlir::dyn_cast<mlir::TensorType>(intOrFpEleAttr.getType());
|
|
if (!tensorTy)
|
|
return true;
|
|
mlir::Type attrEleTy =
|
|
mlir::LLVMTypeConverter(ctx).convertType(tensorTy.getElementType());
|
|
|
|
// Get ty's element type.
|
|
auto arrTy = mlir::dyn_cast<mlir::LLVM::LLVMArrayType>(ty);
|
|
if (!arrTy)
|
|
return true;
|
|
mlir::Type eleTy = arrTy.getElementType();
|
|
while ((arrTy = mlir::dyn_cast<mlir::LLVM::LLVMArrayType>(eleTy)))
|
|
eleTy = arrTy.getElementType();
|
|
|
|
return attrEleTy == eleTy;
|
|
}
|
|
#endif
|
|
|
|
/// Lower `fir.global` operation to `llvm.global` operation.
|
|
/// `fir.insert_on_range` operations are replaced with constant dense attribute
|
|
/// if they are applied on the full range.
|
|
struct GlobalOpConversion : public fir::FIROpConversion<fir::GlobalOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::GlobalOp global, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
|
|
llvm::SmallVector<mlir::Attribute> dbgExprs;
|
|
|
|
if (auto fusedLoc = mlir::dyn_cast<mlir::FusedLoc>(global.getLoc())) {
|
|
if (auto gvExprAttr = mlir::dyn_cast_if_present<mlir::ArrayAttr>(
|
|
fusedLoc.getMetadata())) {
|
|
for (auto attr : gvExprAttr.getAsRange<mlir::Attribute>())
|
|
if (auto dbgAttr =
|
|
mlir::dyn_cast<mlir::LLVM::DIGlobalVariableExpressionAttr>(
|
|
attr))
|
|
dbgExprs.push_back(dbgAttr);
|
|
}
|
|
}
|
|
|
|
auto tyAttr = convertType(global.getType());
|
|
if (auto boxType = mlir::dyn_cast<fir::BaseBoxType>(global.getType()))
|
|
tyAttr = this->lowerTy().convertBoxTypeAsStruct(boxType);
|
|
auto loc = global.getLoc();
|
|
mlir::Attribute initAttr = global.getInitVal().value_or(mlir::Attribute());
|
|
assert(attributeTypeIsCompatible(global.getContext(), initAttr, tyAttr));
|
|
auto linkage = convertLinkage(global.getLinkName());
|
|
auto isConst = global.getConstant().has_value();
|
|
mlir::SymbolRefAttr comdat;
|
|
llvm::ArrayRef<mlir::NamedAttribute> attrs;
|
|
auto g = rewriter.create<mlir::LLVM::GlobalOp>(
|
|
loc, tyAttr, isConst, linkage, global.getSymName(), initAttr, 0, 0,
|
|
false, false, comdat, attrs, dbgExprs);
|
|
|
|
if (global.getAlignment() && *global.getAlignment() > 0)
|
|
g.setAlignment(*global.getAlignment());
|
|
|
|
auto module = global->getParentOfType<mlir::ModuleOp>();
|
|
auto gpuMod = global->getParentOfType<mlir::gpu::GPUModuleOp>();
|
|
// Add comdat if necessary
|
|
if (fir::getTargetTriple(module).supportsCOMDAT() &&
|
|
(linkage == mlir::LLVM::Linkage::Linkonce ||
|
|
linkage == mlir::LLVM::Linkage::LinkonceODR) &&
|
|
!gpuMod) {
|
|
addComdat(g, rewriter, module);
|
|
}
|
|
|
|
// Apply all non-Fir::GlobalOp attributes to the LLVM::GlobalOp, preserving
|
|
// them; whilst taking care not to apply attributes that are lowered in
|
|
// other ways.
|
|
llvm::SmallDenseSet<llvm::StringRef> elidedAttrsSet(
|
|
global.getAttributeNames().begin(), global.getAttributeNames().end());
|
|
for (auto &attr : global->getAttrs())
|
|
if (!elidedAttrsSet.contains(attr.getName().strref()))
|
|
g->setAttr(attr.getName(), attr.getValue());
|
|
|
|
auto &gr = g.getInitializerRegion();
|
|
rewriter.inlineRegionBefore(global.getRegion(), gr, gr.end());
|
|
if (!gr.empty()) {
|
|
// Replace insert_on_range with a constant dense attribute if the
|
|
// initialization is on the full range.
|
|
auto insertOnRangeOps = gr.front().getOps<fir::InsertOnRangeOp>();
|
|
for (auto insertOp : insertOnRangeOps) {
|
|
if (isFullRange(insertOp.getCoor(), insertOp.getType())) {
|
|
auto seqTyAttr = convertType(insertOp.getType());
|
|
auto *op = insertOp.getVal().getDefiningOp();
|
|
auto constant = mlir::dyn_cast<mlir::arith::ConstantOp>(op);
|
|
if (!constant) {
|
|
auto convertOp = mlir::dyn_cast<fir::ConvertOp>(op);
|
|
if (!convertOp)
|
|
continue;
|
|
constant = mlir::cast<mlir::arith::ConstantOp>(
|
|
convertOp.getValue().getDefiningOp());
|
|
}
|
|
mlir::Type vecType = mlir::VectorType::get(
|
|
insertOp.getType().getShape(), constant.getType());
|
|
auto denseAttr = mlir::DenseElementsAttr::get(
|
|
mlir::cast<mlir::ShapedType>(vecType), constant.getValue());
|
|
rewriter.setInsertionPointAfter(insertOp);
|
|
rewriter.replaceOpWithNewOp<mlir::arith::ConstantOp>(
|
|
insertOp, seqTyAttr, denseAttr);
|
|
}
|
|
}
|
|
}
|
|
|
|
if (global.getDataAttr() &&
|
|
*global.getDataAttr() == cuf::DataAttribute::Shared)
|
|
g.setAddrSpace(mlir::NVVM::NVVMMemorySpace::kSharedMemorySpace);
|
|
|
|
rewriter.eraseOp(global);
|
|
return mlir::success();
|
|
}
|
|
|
|
bool isFullRange(mlir::DenseIntElementsAttr indexes,
|
|
fir::SequenceType seqTy) const {
|
|
auto extents = seqTy.getShape();
|
|
if (indexes.size() / 2 != static_cast<int64_t>(extents.size()))
|
|
return false;
|
|
auto cur_index = indexes.value_begin<int64_t>();
|
|
for (unsigned i = 0; i < indexes.size(); i += 2) {
|
|
if (*(cur_index++) != 0)
|
|
return false;
|
|
if (*(cur_index++) != extents[i / 2] - 1)
|
|
return false;
|
|
}
|
|
return true;
|
|
}
|
|
|
|
// TODO: String comparaison should be avoided. Replace linkName with an
|
|
// enumeration.
|
|
mlir::LLVM::Linkage
|
|
convertLinkage(std::optional<llvm::StringRef> optLinkage) const {
|
|
if (optLinkage) {
|
|
auto name = *optLinkage;
|
|
if (name == "internal")
|
|
return mlir::LLVM::Linkage::Internal;
|
|
if (name == "linkonce")
|
|
return mlir::LLVM::Linkage::Linkonce;
|
|
if (name == "linkonce_odr")
|
|
return mlir::LLVM::Linkage::LinkonceODR;
|
|
if (name == "common")
|
|
return mlir::LLVM::Linkage::Common;
|
|
if (name == "weak")
|
|
return mlir::LLVM::Linkage::Weak;
|
|
}
|
|
return mlir::LLVM::Linkage::External;
|
|
}
|
|
|
|
private:
|
|
static void addComdat(mlir::LLVM::GlobalOp &global,
|
|
mlir::ConversionPatternRewriter &rewriter,
|
|
mlir::ModuleOp module) {
|
|
const char *comdatName = "__llvm_comdat";
|
|
mlir::LLVM::ComdatOp comdatOp =
|
|
module.lookupSymbol<mlir::LLVM::ComdatOp>(comdatName);
|
|
if (!comdatOp) {
|
|
comdatOp =
|
|
rewriter.create<mlir::LLVM::ComdatOp>(module.getLoc(), comdatName);
|
|
}
|
|
if (auto select = comdatOp.lookupSymbol<mlir::LLVM::ComdatSelectorOp>(
|
|
global.getSymName()))
|
|
return;
|
|
mlir::OpBuilder::InsertionGuard guard(rewriter);
|
|
rewriter.setInsertionPointToEnd(&comdatOp.getBody().back());
|
|
auto selectorOp = rewriter.create<mlir::LLVM::ComdatSelectorOp>(
|
|
comdatOp.getLoc(), global.getSymName(),
|
|
mlir::LLVM::comdat::Comdat::Any);
|
|
global.setComdatAttr(mlir::SymbolRefAttr::get(
|
|
rewriter.getContext(), comdatName,
|
|
mlir::FlatSymbolRefAttr::get(selectorOp.getSymNameAttr())));
|
|
}
|
|
};
|
|
|
|
/// `fir.load` --> `llvm.load`
|
|
struct LoadOpConversion : public fir::FIROpConversion<fir::LoadOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::LoadOp load, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
|
|
mlir::Type llvmLoadTy = convertObjectType(load.getType());
|
|
if (auto boxTy = mlir::dyn_cast<fir::BaseBoxType>(load.getType())) {
|
|
// fir.box is a special case because it is considered an ssa value in
|
|
// fir, but it is lowered as a pointer to a descriptor. So
|
|
// fir.ref<fir.box> and fir.box end up being the same llvm types and
|
|
// loading a fir.ref<fir.box> is implemented as taking a snapshot of the
|
|
// descriptor value into a new descriptor temp.
|
|
auto inputBoxStorage = adaptor.getOperands()[0];
|
|
mlir::Value newBoxStorage;
|
|
mlir::Location loc = load.getLoc();
|
|
if (auto callOp = mlir::dyn_cast_or_null<mlir::LLVM::CallOp>(
|
|
inputBoxStorage.getDefiningOp())) {
|
|
if (callOp.getCallee() &&
|
|
(*callOp.getCallee())
|
|
.starts_with(RTNAME_STRING(CUFAllocDescriptor))) {
|
|
// CUDA Fortran local descriptor are allocated in managed memory. So
|
|
// new storage must be allocated the same way.
|
|
auto mod = load->getParentOfType<mlir::ModuleOp>();
|
|
newBoxStorage =
|
|
genCUFAllocDescriptor(loc, rewriter, mod, boxTy, lowerTy());
|
|
}
|
|
}
|
|
if (!newBoxStorage)
|
|
newBoxStorage = genAllocaAndAddrCastWithType(loc, llvmLoadTy,
|
|
defaultAlign, rewriter);
|
|
|
|
TypePair boxTypePair{boxTy, llvmLoadTy};
|
|
mlir::Value boxSize =
|
|
computeBoxSize(loc, boxTypePair, inputBoxStorage, rewriter);
|
|
auto memcpy = rewriter.create<mlir::LLVM::MemcpyOp>(
|
|
loc, newBoxStorage, inputBoxStorage, boxSize, /*isVolatile=*/false);
|
|
|
|
if (std::optional<mlir::ArrayAttr> optionalTag = load.getTbaa())
|
|
memcpy.setTBAATags(*optionalTag);
|
|
else
|
|
attachTBAATag(memcpy, boxTy, boxTy, nullptr);
|
|
rewriter.replaceOp(load, newBoxStorage);
|
|
} else {
|
|
auto loadOp = rewriter.create<mlir::LLVM::LoadOp>(
|
|
load.getLoc(), llvmLoadTy, adaptor.getOperands(), load->getAttrs());
|
|
if (std::optional<mlir::ArrayAttr> optionalTag = load.getTbaa())
|
|
loadOp.setTBAATags(*optionalTag);
|
|
else
|
|
attachTBAATag(loadOp, load.getType(), load.getType(), nullptr);
|
|
rewriter.replaceOp(load, loadOp.getResult());
|
|
}
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
/// Lower `fir.no_reassoc` to LLVM IR dialect.
|
|
/// TODO: how do we want to enforce this in LLVM-IR? Can we manipulate the fast
|
|
/// math flags?
|
|
struct NoReassocOpConversion : public fir::FIROpConversion<fir::NoReassocOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::NoReassocOp noreassoc, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
rewriter.replaceOp(noreassoc, adaptor.getOperands()[0]);
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
static void genCondBrOp(mlir::Location loc, mlir::Value cmp, mlir::Block *dest,
|
|
std::optional<mlir::ValueRange> destOps,
|
|
mlir::ConversionPatternRewriter &rewriter,
|
|
mlir::Block *newBlock) {
|
|
if (destOps)
|
|
rewriter.create<mlir::LLVM::CondBrOp>(loc, cmp, dest, *destOps, newBlock,
|
|
mlir::ValueRange());
|
|
else
|
|
rewriter.create<mlir::LLVM::CondBrOp>(loc, cmp, dest, newBlock);
|
|
}
|
|
|
|
template <typename A, typename B>
|
|
static void genBrOp(A caseOp, mlir::Block *dest, std::optional<B> destOps,
|
|
mlir::ConversionPatternRewriter &rewriter) {
|
|
if (destOps)
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::BrOp>(caseOp, *destOps, dest);
|
|
else
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::BrOp>(caseOp, std::nullopt, dest);
|
|
}
|
|
|
|
static void genCaseLadderStep(mlir::Location loc, mlir::Value cmp,
|
|
mlir::Block *dest,
|
|
std::optional<mlir::ValueRange> destOps,
|
|
mlir::ConversionPatternRewriter &rewriter) {
|
|
auto *thisBlock = rewriter.getInsertionBlock();
|
|
auto *newBlock = createBlock(rewriter, dest);
|
|
rewriter.setInsertionPointToEnd(thisBlock);
|
|
genCondBrOp(loc, cmp, dest, destOps, rewriter, newBlock);
|
|
rewriter.setInsertionPointToEnd(newBlock);
|
|
}
|
|
|
|
/// Conversion of `fir.select_case`
|
|
///
|
|
/// The `fir.select_case` operation is converted to a if-then-else ladder.
|
|
/// Depending on the case condition type, one or several comparison and
|
|
/// conditional branching can be generated.
|
|
///
|
|
/// A point value case such as `case(4)`, a lower bound case such as
|
|
/// `case(5:)` or an upper bound case such as `case(:3)` are converted to a
|
|
/// simple comparison between the selector value and the constant value in the
|
|
/// case. The block associated with the case condition is then executed if
|
|
/// the comparison succeed otherwise it branch to the next block with the
|
|
/// comparison for the next case conditon.
|
|
///
|
|
/// A closed interval case condition such as `case(7:10)` is converted with a
|
|
/// first comparison and conditional branching for the lower bound. If
|
|
/// successful, it branch to a second block with the comparison for the
|
|
/// upper bound in the same case condition.
|
|
///
|
|
/// TODO: lowering of CHARACTER type cases is not handled yet.
|
|
struct SelectCaseOpConversion : public fir::FIROpConversion<fir::SelectCaseOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::SelectCaseOp caseOp, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
unsigned conds = caseOp.getNumConditions();
|
|
llvm::ArrayRef<mlir::Attribute> cases = caseOp.getCases().getValue();
|
|
// Type can be CHARACTER, INTEGER, or LOGICAL (C1145)
|
|
auto ty = caseOp.getSelector().getType();
|
|
if (mlir::isa<fir::CharacterType>(ty)) {
|
|
TODO(caseOp.getLoc(), "fir.select_case codegen with character type");
|
|
return mlir::failure();
|
|
}
|
|
mlir::Value selector = caseOp.getSelector(adaptor.getOperands());
|
|
auto loc = caseOp.getLoc();
|
|
for (unsigned t = 0; t != conds; ++t) {
|
|
mlir::Block *dest = caseOp.getSuccessor(t);
|
|
std::optional<mlir::ValueRange> destOps =
|
|
caseOp.getSuccessorOperands(adaptor.getOperands(), t);
|
|
std::optional<mlir::ValueRange> cmpOps =
|
|
*caseOp.getCompareOperands(adaptor.getOperands(), t);
|
|
mlir::Attribute attr = cases[t];
|
|
assert(mlir::isa<mlir::UnitAttr>(attr) || cmpOps.has_value());
|
|
if (mlir::isa<fir::PointIntervalAttr>(attr)) {
|
|
auto cmp = rewriter.create<mlir::LLVM::ICmpOp>(
|
|
loc, mlir::LLVM::ICmpPredicate::eq, selector, cmpOps->front());
|
|
genCaseLadderStep(loc, cmp, dest, destOps, rewriter);
|
|
continue;
|
|
}
|
|
if (mlir::isa<fir::LowerBoundAttr>(attr)) {
|
|
auto cmp = rewriter.create<mlir::LLVM::ICmpOp>(
|
|
loc, mlir::LLVM::ICmpPredicate::sle, cmpOps->front(), selector);
|
|
genCaseLadderStep(loc, cmp, dest, destOps, rewriter);
|
|
continue;
|
|
}
|
|
if (mlir::isa<fir::UpperBoundAttr>(attr)) {
|
|
auto cmp = rewriter.create<mlir::LLVM::ICmpOp>(
|
|
loc, mlir::LLVM::ICmpPredicate::sle, selector, cmpOps->front());
|
|
genCaseLadderStep(loc, cmp, dest, destOps, rewriter);
|
|
continue;
|
|
}
|
|
if (mlir::isa<fir::ClosedIntervalAttr>(attr)) {
|
|
mlir::Value caseArg0 = *cmpOps->begin();
|
|
auto cmp0 = rewriter.create<mlir::LLVM::ICmpOp>(
|
|
loc, mlir::LLVM::ICmpPredicate::sle, caseArg0, selector);
|
|
auto *thisBlock = rewriter.getInsertionBlock();
|
|
auto *newBlock1 = createBlock(rewriter, dest);
|
|
auto *newBlock2 = createBlock(rewriter, dest);
|
|
rewriter.setInsertionPointToEnd(thisBlock);
|
|
rewriter.create<mlir::LLVM::CondBrOp>(loc, cmp0, newBlock1, newBlock2);
|
|
rewriter.setInsertionPointToEnd(newBlock1);
|
|
mlir::Value caseArg1 = *(cmpOps->begin() + 1);
|
|
auto cmp1 = rewriter.create<mlir::LLVM::ICmpOp>(
|
|
loc, mlir::LLVM::ICmpPredicate::sle, selector, caseArg1);
|
|
genCondBrOp(loc, cmp1, dest, destOps, rewriter, newBlock2);
|
|
rewriter.setInsertionPointToEnd(newBlock2);
|
|
continue;
|
|
}
|
|
assert(mlir::isa<mlir::UnitAttr>(attr));
|
|
assert((t + 1 == conds) && "unit must be last");
|
|
genBrOp(caseOp, dest, destOps, rewriter);
|
|
}
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
/// Helper function for converting select ops. This function converts the
|
|
/// signature of the given block. If the new block signature is different from
|
|
/// `expectedTypes`, returns "failure".
|
|
static llvm::FailureOr<mlir::Block *>
|
|
getConvertedBlock(mlir::ConversionPatternRewriter &rewriter,
|
|
const mlir::TypeConverter *converter,
|
|
mlir::Operation *branchOp, mlir::Block *block,
|
|
mlir::TypeRange expectedTypes) {
|
|
assert(converter && "expected non-null type converter");
|
|
assert(!block->isEntryBlock() && "entry blocks have no predecessors");
|
|
|
|
// There is nothing to do if the types already match.
|
|
if (block->getArgumentTypes() == expectedTypes)
|
|
return block;
|
|
|
|
// Compute the new block argument types and convert the block.
|
|
std::optional<mlir::TypeConverter::SignatureConversion> conversion =
|
|
converter->convertBlockSignature(block);
|
|
if (!conversion)
|
|
return rewriter.notifyMatchFailure(branchOp,
|
|
"could not compute block signature");
|
|
if (expectedTypes != conversion->getConvertedTypes())
|
|
return rewriter.notifyMatchFailure(
|
|
branchOp,
|
|
"mismatch between adaptor operand types and computed block signature");
|
|
return rewriter.applySignatureConversion(block, *conversion, converter);
|
|
}
|
|
|
|
template <typename OP>
|
|
static llvm::LogicalResult
|
|
selectMatchAndRewrite(const fir::LLVMTypeConverter &lowering, OP select,
|
|
typename OP::Adaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter,
|
|
const mlir::TypeConverter *converter) {
|
|
unsigned conds = select.getNumConditions();
|
|
auto cases = select.getCases().getValue();
|
|
mlir::Value selector = adaptor.getSelector();
|
|
auto loc = select.getLoc();
|
|
assert(conds > 0 && "select must have cases");
|
|
|
|
llvm::SmallVector<mlir::Block *> destinations;
|
|
llvm::SmallVector<mlir::ValueRange> destinationsOperands;
|
|
mlir::Block *defaultDestination;
|
|
mlir::ValueRange defaultOperands;
|
|
llvm::SmallVector<int32_t> caseValues;
|
|
|
|
for (unsigned t = 0; t != conds; ++t) {
|
|
mlir::Block *dest = select.getSuccessor(t);
|
|
auto destOps = select.getSuccessorOperands(adaptor.getOperands(), t);
|
|
const mlir::Attribute &attr = cases[t];
|
|
if (auto intAttr = mlir::dyn_cast<mlir::IntegerAttr>(attr)) {
|
|
destinationsOperands.push_back(destOps ? *destOps : mlir::ValueRange{});
|
|
auto convertedBlock =
|
|
getConvertedBlock(rewriter, converter, select, dest,
|
|
mlir::TypeRange(destinationsOperands.back()));
|
|
if (mlir::failed(convertedBlock))
|
|
return mlir::failure();
|
|
destinations.push_back(*convertedBlock);
|
|
caseValues.push_back(intAttr.getInt());
|
|
continue;
|
|
}
|
|
assert(mlir::dyn_cast_or_null<mlir::UnitAttr>(attr));
|
|
assert((t + 1 == conds) && "unit must be last");
|
|
defaultOperands = destOps ? *destOps : mlir::ValueRange{};
|
|
auto convertedBlock = getConvertedBlock(rewriter, converter, select, dest,
|
|
mlir::TypeRange(defaultOperands));
|
|
if (mlir::failed(convertedBlock))
|
|
return mlir::failure();
|
|
defaultDestination = *convertedBlock;
|
|
}
|
|
|
|
// LLVM::SwitchOp takes a i32 type for the selector.
|
|
if (select.getSelector().getType() != rewriter.getI32Type())
|
|
selector = rewriter.create<mlir::LLVM::TruncOp>(loc, rewriter.getI32Type(),
|
|
selector);
|
|
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::SwitchOp>(
|
|
select, selector,
|
|
/*defaultDestination=*/defaultDestination,
|
|
/*defaultOperands=*/defaultOperands,
|
|
/*caseValues=*/caseValues,
|
|
/*caseDestinations=*/destinations,
|
|
/*caseOperands=*/destinationsOperands,
|
|
/*branchWeights=*/llvm::ArrayRef<std::int32_t>());
|
|
return mlir::success();
|
|
}
|
|
|
|
/// conversion of fir::SelectOp to an if-then-else ladder
|
|
struct SelectOpConversion : public fir::FIROpConversion<fir::SelectOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::SelectOp op, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
return selectMatchAndRewrite<fir::SelectOp>(lowerTy(), op, adaptor,
|
|
rewriter, getTypeConverter());
|
|
}
|
|
};
|
|
|
|
/// conversion of fir::SelectRankOp to an if-then-else ladder
|
|
struct SelectRankOpConversion : public fir::FIROpConversion<fir::SelectRankOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::SelectRankOp op, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
return selectMatchAndRewrite<fir::SelectRankOp>(
|
|
lowerTy(), op, adaptor, rewriter, getTypeConverter());
|
|
}
|
|
};
|
|
|
|
/// Lower `fir.select_type` to LLVM IR dialect.
|
|
struct SelectTypeOpConversion : public fir::FIROpConversion<fir::SelectTypeOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::SelectTypeOp select, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
mlir::emitError(select.getLoc(),
|
|
"fir.select_type should have already been converted");
|
|
return mlir::failure();
|
|
}
|
|
};
|
|
|
|
/// `fir.store` --> `llvm.store`
|
|
struct StoreOpConversion : public fir::FIROpConversion<fir::StoreOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::StoreOp store, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
mlir::Location loc = store.getLoc();
|
|
mlir::Type storeTy = store.getValue().getType();
|
|
mlir::Value llvmValue = adaptor.getValue();
|
|
mlir::Value llvmMemref = adaptor.getMemref();
|
|
mlir::LLVM::AliasAnalysisOpInterface newOp;
|
|
if (auto boxTy = mlir::dyn_cast<fir::BaseBoxType>(storeTy)) {
|
|
mlir::Type llvmBoxTy = lowerTy().convertBoxTypeAsStruct(boxTy);
|
|
// Always use memcpy because LLVM is not as effective at optimizing
|
|
// aggregate loads/stores as it is optimizing memcpy.
|
|
TypePair boxTypePair{boxTy, llvmBoxTy};
|
|
mlir::Value boxSize =
|
|
computeBoxSize(loc, boxTypePair, llvmValue, rewriter);
|
|
newOp = rewriter.create<mlir::LLVM::MemcpyOp>(
|
|
loc, llvmMemref, llvmValue, boxSize, /*isVolatile=*/false);
|
|
} else {
|
|
newOp = rewriter.create<mlir::LLVM::StoreOp>(loc, llvmValue, llvmMemref);
|
|
}
|
|
if (std::optional<mlir::ArrayAttr> optionalTag = store.getTbaa())
|
|
newOp.setTBAATags(*optionalTag);
|
|
else
|
|
attachTBAATag(newOp, storeTy, storeTy, nullptr);
|
|
rewriter.eraseOp(store);
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
/// `fir.copy` --> `llvm.memcpy` or `llvm.memmove`
|
|
struct CopyOpConversion : public fir::FIROpConversion<fir::CopyOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::CopyOp copy, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
mlir::Location loc = copy.getLoc();
|
|
mlir::Value llvmSource = adaptor.getSource();
|
|
mlir::Value llvmDestination = adaptor.getDestination();
|
|
mlir::Type i64Ty = mlir::IntegerType::get(rewriter.getContext(), 64);
|
|
mlir::Type copyTy = fir::unwrapRefType(copy.getSource().getType());
|
|
mlir::Value copySize =
|
|
genTypeStrideInBytes(loc, i64Ty, rewriter, convertType(copyTy));
|
|
|
|
mlir::LLVM::AliasAnalysisOpInterface newOp;
|
|
if (copy.getNoOverlap())
|
|
newOp = rewriter.create<mlir::LLVM::MemcpyOp>(
|
|
loc, llvmDestination, llvmSource, copySize, /*isVolatile=*/false);
|
|
else
|
|
newOp = rewriter.create<mlir::LLVM::MemmoveOp>(
|
|
loc, llvmDestination, llvmSource, copySize, /*isVolatile=*/false);
|
|
|
|
// TODO: propagate TBAA once FirAliasTagOpInterface added to CopyOp.
|
|
attachTBAATag(newOp, copyTy, copyTy, nullptr);
|
|
rewriter.eraseOp(copy);
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
namespace {
|
|
|
|
/// Convert `fir.unboxchar` into two `llvm.extractvalue` instructions. One for
|
|
/// the character buffer and one for the buffer length.
|
|
struct UnboxCharOpConversion : public fir::FIROpConversion<fir::UnboxCharOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::UnboxCharOp unboxchar, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
mlir::Type lenTy = convertType(unboxchar.getType(1));
|
|
mlir::Value tuple = adaptor.getOperands()[0];
|
|
|
|
mlir::Location loc = unboxchar.getLoc();
|
|
mlir::Value ptrToBuffer =
|
|
rewriter.create<mlir::LLVM::ExtractValueOp>(loc, tuple, 0);
|
|
|
|
auto len = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, tuple, 1);
|
|
mlir::Value lenAfterCast = integerCast(loc, rewriter, lenTy, len);
|
|
|
|
rewriter.replaceOp(unboxchar,
|
|
llvm::ArrayRef<mlir::Value>{ptrToBuffer, lenAfterCast});
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
/// Lower `fir.unboxproc` operation. Unbox a procedure box value, yielding its
|
|
/// components.
|
|
/// TODO: Part of supporting Fortran 2003 procedure pointers.
|
|
struct UnboxProcOpConversion : public fir::FIROpConversion<fir::UnboxProcOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::UnboxProcOp unboxproc, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
TODO(unboxproc.getLoc(), "fir.unboxproc codegen");
|
|
return mlir::failure();
|
|
}
|
|
};
|
|
|
|
/// convert to LLVM IR dialect `undef`
|
|
struct UndefOpConversion : public fir::FIROpConversion<fir::UndefOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::UndefOp undef, OpAdaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
if (mlir::isa<fir::DummyScopeType>(undef.getType())) {
|
|
// Dummy scoping is used for Fortran analyses like AA. Once it gets to
|
|
// pre-codegen rewrite it is erased and a fir.undef is created to
|
|
// feed to the fir declare operation. Thus, during codegen, we can
|
|
// simply erase is as it is no longer used.
|
|
rewriter.eraseOp(undef);
|
|
return mlir::success();
|
|
}
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::UndefOp>(
|
|
undef, convertType(undef.getType()));
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
struct ZeroOpConversion : public fir::FIROpConversion<fir::ZeroOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::ZeroOp zero, OpAdaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
mlir::Type ty = convertType(zero.getType());
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::ZeroOp>(zero, ty);
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
/// `fir.unreachable` --> `llvm.unreachable`
|
|
struct UnreachableOpConversion
|
|
: public fir::FIROpConversion<fir::UnreachableOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::UnreachableOp unreach, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::UnreachableOp>(unreach);
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
/// `fir.is_present` -->
|
|
/// ```
|
|
/// %0 = llvm.mlir.constant(0 : i64)
|
|
/// %1 = llvm.ptrtoint %0
|
|
/// %2 = llvm.icmp "ne" %1, %0 : i64
|
|
/// ```
|
|
struct IsPresentOpConversion : public fir::FIROpConversion<fir::IsPresentOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::IsPresentOp isPresent, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
mlir::Type idxTy = lowerTy().indexType();
|
|
mlir::Location loc = isPresent.getLoc();
|
|
auto ptr = adaptor.getOperands()[0];
|
|
|
|
if (mlir::isa<fir::BoxCharType>(isPresent.getVal().getType())) {
|
|
[[maybe_unused]] auto structTy =
|
|
mlir::cast<mlir::LLVM::LLVMStructType>(ptr.getType());
|
|
assert(!structTy.isOpaque() && !structTy.getBody().empty());
|
|
|
|
ptr = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, ptr, 0);
|
|
}
|
|
mlir::LLVM::ConstantOp c0 =
|
|
genConstantIndex(isPresent.getLoc(), idxTy, rewriter, 0);
|
|
auto addr = rewriter.create<mlir::LLVM::PtrToIntOp>(loc, idxTy, ptr);
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::ICmpOp>(
|
|
isPresent, mlir::LLVM::ICmpPredicate::ne, addr, c0);
|
|
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
/// Create value signaling an absent optional argument in a call, e.g.
|
|
/// `fir.absent !fir.ref<i64>` --> `llvm.mlir.zero : !llvm.ptr<i64>`
|
|
struct AbsentOpConversion : public fir::FIROpConversion<fir::AbsentOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::AbsentOp absent, OpAdaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
mlir::Type ty = convertType(absent.getType());
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::ZeroOp>(absent, ty);
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
//
|
|
// Primitive operations on Complex types
|
|
//
|
|
|
|
template <typename OPTY>
|
|
static inline mlir::LLVM::FastmathFlagsAttr getLLVMFMFAttr(OPTY op) {
|
|
return mlir::LLVM::FastmathFlagsAttr::get(
|
|
op.getContext(),
|
|
mlir::arith::convertArithFastMathFlagsToLLVM(op.getFastmath()));
|
|
}
|
|
|
|
/// Generate inline code for complex addition/subtraction
|
|
template <typename LLVMOP, typename OPTY>
|
|
static mlir::LLVM::InsertValueOp
|
|
complexSum(OPTY sumop, mlir::ValueRange opnds,
|
|
mlir::ConversionPatternRewriter &rewriter,
|
|
const fir::LLVMTypeConverter &lowering) {
|
|
mlir::LLVM::FastmathFlagsAttr fmf = getLLVMFMFAttr(sumop);
|
|
mlir::Value a = opnds[0];
|
|
mlir::Value b = opnds[1];
|
|
auto loc = sumop.getLoc();
|
|
mlir::Type eleTy = lowering.convertType(getComplexEleTy(sumop.getType()));
|
|
mlir::Type ty = lowering.convertType(sumop.getType());
|
|
auto x0 = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, a, 0);
|
|
auto y0 = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, a, 1);
|
|
auto x1 = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, b, 0);
|
|
auto y1 = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, b, 1);
|
|
auto rx = rewriter.create<LLVMOP>(loc, eleTy, x0, x1, fmf);
|
|
auto ry = rewriter.create<LLVMOP>(loc, eleTy, y0, y1, fmf);
|
|
auto r0 = rewriter.create<mlir::LLVM::UndefOp>(loc, ty);
|
|
auto r1 = rewriter.create<mlir::LLVM::InsertValueOp>(loc, r0, rx, 0);
|
|
return rewriter.create<mlir::LLVM::InsertValueOp>(loc, r1, ry, 1);
|
|
}
|
|
} // namespace
|
|
|
|
namespace {
|
|
struct AddcOpConversion : public fir::FIROpConversion<fir::AddcOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::AddcOp addc, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
// given: (x + iy) + (x' + iy')
|
|
// result: (x + x') + i(y + y')
|
|
auto r = complexSum<mlir::LLVM::FAddOp>(addc, adaptor.getOperands(),
|
|
rewriter, lowerTy());
|
|
rewriter.replaceOp(addc, r.getResult());
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
struct SubcOpConversion : public fir::FIROpConversion<fir::SubcOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::SubcOp subc, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
// given: (x + iy) - (x' + iy')
|
|
// result: (x - x') + i(y - y')
|
|
auto r = complexSum<mlir::LLVM::FSubOp>(subc, adaptor.getOperands(),
|
|
rewriter, lowerTy());
|
|
rewriter.replaceOp(subc, r.getResult());
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
/// Inlined complex multiply
|
|
struct MulcOpConversion : public fir::FIROpConversion<fir::MulcOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::MulcOp mulc, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
// TODO: Can we use a call to __muldc3 ?
|
|
// given: (x + iy) * (x' + iy')
|
|
// result: (xx'-yy')+i(xy'+yx')
|
|
mlir::LLVM::FastmathFlagsAttr fmf = getLLVMFMFAttr(mulc);
|
|
mlir::Value a = adaptor.getOperands()[0];
|
|
mlir::Value b = adaptor.getOperands()[1];
|
|
auto loc = mulc.getLoc();
|
|
mlir::Type eleTy = convertType(getComplexEleTy(mulc.getType()));
|
|
mlir::Type ty = convertType(mulc.getType());
|
|
auto x0 = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, a, 0);
|
|
auto y0 = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, a, 1);
|
|
auto x1 = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, b, 0);
|
|
auto y1 = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, b, 1);
|
|
auto xx = rewriter.create<mlir::LLVM::FMulOp>(loc, eleTy, x0, x1, fmf);
|
|
auto yx = rewriter.create<mlir::LLVM::FMulOp>(loc, eleTy, y0, x1, fmf);
|
|
auto xy = rewriter.create<mlir::LLVM::FMulOp>(loc, eleTy, x0, y1, fmf);
|
|
auto ri = rewriter.create<mlir::LLVM::FAddOp>(loc, eleTy, xy, yx, fmf);
|
|
auto yy = rewriter.create<mlir::LLVM::FMulOp>(loc, eleTy, y0, y1, fmf);
|
|
auto rr = rewriter.create<mlir::LLVM::FSubOp>(loc, eleTy, xx, yy, fmf);
|
|
auto ra = rewriter.create<mlir::LLVM::UndefOp>(loc, ty);
|
|
auto r1 = rewriter.create<mlir::LLVM::InsertValueOp>(loc, ra, rr, 0);
|
|
auto r0 = rewriter.create<mlir::LLVM::InsertValueOp>(loc, r1, ri, 1);
|
|
rewriter.replaceOp(mulc, r0.getResult());
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
/// Inlined complex division
|
|
struct DivcOpConversion : public fir::FIROpConversion<fir::DivcOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::DivcOp divc, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
// TODO: Can we use a call to __divdc3 instead?
|
|
// Just generate inline code for now.
|
|
// given: (x + iy) / (x' + iy')
|
|
// result: ((xx'+yy')/d) + i((yx'-xy')/d) where d = x'x' + y'y'
|
|
mlir::LLVM::FastmathFlagsAttr fmf = getLLVMFMFAttr(divc);
|
|
mlir::Value a = adaptor.getOperands()[0];
|
|
mlir::Value b = adaptor.getOperands()[1];
|
|
auto loc = divc.getLoc();
|
|
mlir::Type eleTy = convertType(getComplexEleTy(divc.getType()));
|
|
mlir::Type ty = convertType(divc.getType());
|
|
auto x0 = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, a, 0);
|
|
auto y0 = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, a, 1);
|
|
auto x1 = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, b, 0);
|
|
auto y1 = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, b, 1);
|
|
auto xx = rewriter.create<mlir::LLVM::FMulOp>(loc, eleTy, x0, x1, fmf);
|
|
auto x1x1 = rewriter.create<mlir::LLVM::FMulOp>(loc, eleTy, x1, x1, fmf);
|
|
auto yx = rewriter.create<mlir::LLVM::FMulOp>(loc, eleTy, y0, x1, fmf);
|
|
auto xy = rewriter.create<mlir::LLVM::FMulOp>(loc, eleTy, x0, y1, fmf);
|
|
auto yy = rewriter.create<mlir::LLVM::FMulOp>(loc, eleTy, y0, y1, fmf);
|
|
auto y1y1 = rewriter.create<mlir::LLVM::FMulOp>(loc, eleTy, y1, y1, fmf);
|
|
auto d = rewriter.create<mlir::LLVM::FAddOp>(loc, eleTy, x1x1, y1y1, fmf);
|
|
auto rrn = rewriter.create<mlir::LLVM::FAddOp>(loc, eleTy, xx, yy, fmf);
|
|
auto rin = rewriter.create<mlir::LLVM::FSubOp>(loc, eleTy, yx, xy, fmf);
|
|
auto rr = rewriter.create<mlir::LLVM::FDivOp>(loc, eleTy, rrn, d, fmf);
|
|
auto ri = rewriter.create<mlir::LLVM::FDivOp>(loc, eleTy, rin, d, fmf);
|
|
auto ra = rewriter.create<mlir::LLVM::UndefOp>(loc, ty);
|
|
auto r1 = rewriter.create<mlir::LLVM::InsertValueOp>(loc, ra, rr, 0);
|
|
auto r0 = rewriter.create<mlir::LLVM::InsertValueOp>(loc, r1, ri, 1);
|
|
rewriter.replaceOp(divc, r0.getResult());
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
/// Inlined complex negation
|
|
struct NegcOpConversion : public fir::FIROpConversion<fir::NegcOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::NegcOp neg, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
// given: -(x + iy)
|
|
// result: -x - iy
|
|
auto eleTy = convertType(getComplexEleTy(neg.getType()));
|
|
auto loc = neg.getLoc();
|
|
mlir::Value o0 = adaptor.getOperands()[0];
|
|
auto rp = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, o0, 0);
|
|
auto ip = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, o0, 1);
|
|
auto nrp = rewriter.create<mlir::LLVM::FNegOp>(loc, eleTy, rp);
|
|
auto nip = rewriter.create<mlir::LLVM::FNegOp>(loc, eleTy, ip);
|
|
auto r = rewriter.create<mlir::LLVM::InsertValueOp>(loc, o0, nrp, 0);
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::InsertValueOp>(neg, r, nip, 1);
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
struct BoxOffsetOpConversion : public fir::FIROpConversion<fir::BoxOffsetOp> {
|
|
using FIROpConversion::FIROpConversion;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(fir::BoxOffsetOp boxOffset, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const override {
|
|
|
|
mlir::Type pty = ::getLlvmPtrType(boxOffset.getContext());
|
|
mlir::Type boxType = fir::unwrapRefType(boxOffset.getBoxRef().getType());
|
|
mlir::Type llvmBoxTy =
|
|
lowerTy().convertBoxTypeAsStruct(mlir::cast<fir::BaseBoxType>(boxType));
|
|
int fieldId = boxOffset.getField() == fir::BoxFieldAttr::derived_type
|
|
? getTypeDescFieldId(boxType)
|
|
: kAddrPosInBox;
|
|
rewriter.replaceOpWithNewOp<mlir::LLVM::GEPOp>(
|
|
boxOffset, pty, llvmBoxTy, adaptor.getBoxRef(),
|
|
llvm::ArrayRef<mlir::LLVM::GEPArg>{0, fieldId});
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
/// Conversion pattern for operation that must be dead. The information in these
|
|
/// operations is used by other operation. At this point they should not have
|
|
/// anymore uses.
|
|
/// These operations are normally dead after the pre-codegen pass.
|
|
template <typename FromOp>
|
|
struct MustBeDeadConversion : public fir::FIROpConversion<FromOp> {
|
|
explicit MustBeDeadConversion(const fir::LLVMTypeConverter &lowering,
|
|
const fir::FIRToLLVMPassOptions &options)
|
|
: fir::FIROpConversion<FromOp>(lowering, options) {}
|
|
using OpAdaptor = typename FromOp::Adaptor;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(FromOp op, OpAdaptor adaptor,
|
|
mlir::ConversionPatternRewriter &rewriter) const final {
|
|
if (!op->getUses().empty())
|
|
return rewriter.notifyMatchFailure(op, "op must be dead");
|
|
rewriter.eraseOp(op);
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
struct ShapeOpConversion : public MustBeDeadConversion<fir::ShapeOp> {
|
|
using MustBeDeadConversion::MustBeDeadConversion;
|
|
};
|
|
|
|
struct ShapeShiftOpConversion : public MustBeDeadConversion<fir::ShapeShiftOp> {
|
|
using MustBeDeadConversion::MustBeDeadConversion;
|
|
};
|
|
|
|
struct ShiftOpConversion : public MustBeDeadConversion<fir::ShiftOp> {
|
|
using MustBeDeadConversion::MustBeDeadConversion;
|
|
};
|
|
|
|
struct SliceOpConversion : public MustBeDeadConversion<fir::SliceOp> {
|
|
using MustBeDeadConversion::MustBeDeadConversion;
|
|
};
|
|
|
|
} // namespace
|
|
|
|
namespace {
|
|
class RenameMSVCLibmCallees
|
|
: public mlir::OpRewritePattern<mlir::LLVM::CallOp> {
|
|
public:
|
|
using OpRewritePattern::OpRewritePattern;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(mlir::LLVM::CallOp op,
|
|
mlir::PatternRewriter &rewriter) const override {
|
|
rewriter.startOpModification(op);
|
|
auto callee = op.getCallee();
|
|
if (callee)
|
|
if (*callee == "hypotf")
|
|
op.setCalleeAttr(mlir::SymbolRefAttr::get(op.getContext(), "_hypotf"));
|
|
|
|
rewriter.finalizeOpModification(op);
|
|
return mlir::success();
|
|
}
|
|
};
|
|
|
|
class RenameMSVCLibmFuncs
|
|
: public mlir::OpRewritePattern<mlir::LLVM::LLVMFuncOp> {
|
|
public:
|
|
using OpRewritePattern::OpRewritePattern;
|
|
|
|
llvm::LogicalResult
|
|
matchAndRewrite(mlir::LLVM::LLVMFuncOp op,
|
|
mlir::PatternRewriter &rewriter) const override {
|
|
rewriter.startOpModification(op);
|
|
if (op.getSymName() == "hypotf")
|
|
op.setSymNameAttr(rewriter.getStringAttr("_hypotf"));
|
|
rewriter.finalizeOpModification(op);
|
|
return mlir::success();
|
|
}
|
|
};
|
|
} // namespace
|
|
|
|
namespace {
|
|
/// Convert FIR dialect to LLVM dialect
|
|
///
|
|
/// This pass lowers all FIR dialect operations to LLVM IR dialect. An
|
|
/// MLIR pass is used to lower residual Std dialect to LLVM IR dialect.
|
|
class FIRToLLVMLowering
|
|
: public fir::impl::FIRToLLVMLoweringBase<FIRToLLVMLowering> {
|
|
public:
|
|
FIRToLLVMLowering() = default;
|
|
FIRToLLVMLowering(fir::FIRToLLVMPassOptions options) : options{options} {}
|
|
mlir::ModuleOp getModule() { return getOperation(); }
|
|
|
|
void runOnOperation() override final {
|
|
auto mod = getModule();
|
|
if (!forcedTargetTriple.empty())
|
|
fir::setTargetTriple(mod, forcedTargetTriple);
|
|
|
|
if (!forcedDataLayout.empty()) {
|
|
llvm::DataLayout dl(forcedDataLayout);
|
|
fir::support::setMLIRDataLayout(mod, dl);
|
|
}
|
|
|
|
if (!forcedTargetCPU.empty())
|
|
fir::setTargetCPU(mod, forcedTargetCPU);
|
|
|
|
if (!forcedTuneCPU.empty())
|
|
fir::setTuneCPU(mod, forcedTuneCPU);
|
|
|
|
if (!forcedTargetFeatures.empty())
|
|
fir::setTargetFeatures(mod, forcedTargetFeatures);
|
|
|
|
if (typeDescriptorsRenamedForAssembly)
|
|
options.typeDescriptorsRenamedForAssembly =
|
|
typeDescriptorsRenamedForAssembly;
|
|
|
|
// Run dynamic pass pipeline for converting Math dialect
|
|
// operations into other dialects (llvm, func, etc.).
|
|
// Some conversions of Math operations cannot be done
|
|
// by just using conversion patterns. This is true for
|
|
// conversions that affect the ModuleOp, e.g. create new
|
|
// function operations in it. We have to run such conversions
|
|
// as passes here.
|
|
mlir::OpPassManager mathConvertionPM("builtin.module");
|
|
|
|
bool isAMDGCN = fir::getTargetTriple(mod).isAMDGCN();
|
|
// If compiling for AMD target some math operations must be lowered to AMD
|
|
// GPU library calls, the rest can be converted to LLVM intrinsics, which
|
|
// is handled in the mathToLLVM conversion. The lowering to libm calls is
|
|
// not needed since all math operations are handled this way.
|
|
if (isAMDGCN)
|
|
mathConvertionPM.addPass(mlir::createConvertMathToROCDL());
|
|
|
|
// Convert math::FPowI operations to inline implementation
|
|
// only if the exponent's width is greater than 32, otherwise,
|
|
// it will be lowered to LLVM intrinsic operation by a later conversion.
|
|
mlir::ConvertMathToFuncsOptions mathToFuncsOptions{};
|
|
mathToFuncsOptions.minWidthOfFPowIExponent = 33;
|
|
mathConvertionPM.addPass(
|
|
mlir::createConvertMathToFuncs(mathToFuncsOptions));
|
|
mathConvertionPM.addPass(mlir::createConvertComplexToStandardPass());
|
|
// Convert Math dialect operations into LLVM dialect operations.
|
|
// There is no way to prefer MathToLLVM patterns over MathToLibm
|
|
// patterns (applied below), so we have to run MathToLLVM conversion here.
|
|
mathConvertionPM.addNestedPass<mlir::func::FuncOp>(
|
|
mlir::createConvertMathToLLVMPass());
|
|
if (mlir::failed(runPipeline(mathConvertionPM, mod)))
|
|
return signalPassFailure();
|
|
|
|
std::optional<mlir::DataLayout> dl =
|
|
fir::support::getOrSetMLIRDataLayout(mod, /*allowDefaultLayout=*/true);
|
|
if (!dl) {
|
|
mlir::emitError(mod.getLoc(),
|
|
"module operation must carry a data layout attribute "
|
|
"to generate llvm IR from FIR");
|
|
signalPassFailure();
|
|
return;
|
|
}
|
|
|
|
auto *context = getModule().getContext();
|
|
fir::LLVMTypeConverter typeConverter{getModule(),
|
|
options.applyTBAA || applyTBAA,
|
|
options.forceUnifiedTBAATree, *dl};
|
|
mlir::RewritePatternSet pattern(context);
|
|
fir::populateFIRToLLVMConversionPatterns(typeConverter, pattern, options);
|
|
mlir::populateFuncToLLVMConversionPatterns(typeConverter, pattern);
|
|
mlir::populateOpenMPToLLVMConversionPatterns(typeConverter, pattern);
|
|
mlir::arith::populateArithToLLVMConversionPatterns(typeConverter, pattern);
|
|
mlir::cf::populateControlFlowToLLVMConversionPatterns(typeConverter,
|
|
pattern);
|
|
mlir::cf::populateAssertToLLVMConversionPattern(typeConverter, pattern);
|
|
// Math operations that have not been converted yet must be converted
|
|
// to Libm.
|
|
if (!isAMDGCN)
|
|
mlir::populateMathToLibmConversionPatterns(pattern);
|
|
mlir::populateComplexToLLVMConversionPatterns(typeConverter, pattern);
|
|
mlir::populateVectorToLLVMConversionPatterns(typeConverter, pattern);
|
|
|
|
// Flang specific overloads for OpenMP operations, to allow for special
|
|
// handling of things like Box types.
|
|
fir::populateOpenMPFIRToLLVMConversionPatterns(typeConverter, pattern);
|
|
|
|
mlir::ConversionTarget target{*context};
|
|
target.addLegalDialect<mlir::LLVM::LLVMDialect>();
|
|
// The OpenMP dialect is legal for Operations without regions, for those
|
|
// which contains regions it is legal if the region contains only the
|
|
// LLVM dialect. Add OpenMP dialect as a legal dialect for conversion and
|
|
// legalize conversion of OpenMP operations without regions.
|
|
mlir::configureOpenMPToLLVMConversionLegality(target, typeConverter);
|
|
target.addLegalDialect<mlir::omp::OpenMPDialect>();
|
|
target.addLegalDialect<mlir::acc::OpenACCDialect>();
|
|
target.addLegalDialect<mlir::gpu::GPUDialect>();
|
|
|
|
// required NOPs for applying a full conversion
|
|
target.addLegalOp<mlir::ModuleOp>();
|
|
|
|
// If we're on Windows, we might need to rename some libm calls.
|
|
bool isMSVC = fir::getTargetTriple(mod).isOSMSVCRT();
|
|
if (isMSVC) {
|
|
pattern.insert<RenameMSVCLibmCallees, RenameMSVCLibmFuncs>(context);
|
|
|
|
target.addDynamicallyLegalOp<mlir::LLVM::CallOp>(
|
|
[](mlir::LLVM::CallOp op) {
|
|
auto callee = op.getCallee();
|
|
if (!callee)
|
|
return true;
|
|
return *callee != "hypotf";
|
|
});
|
|
target.addDynamicallyLegalOp<mlir::LLVM::LLVMFuncOp>(
|
|
[](mlir::LLVM::LLVMFuncOp op) {
|
|
return op.getSymName() != "hypotf";
|
|
});
|
|
}
|
|
|
|
// apply the patterns
|
|
if (mlir::failed(mlir::applyFullConversion(getModule(), target,
|
|
std::move(pattern)))) {
|
|
signalPassFailure();
|
|
}
|
|
|
|
// Run pass to add comdats to functions that have weak linkage on relevant
|
|
// platforms
|
|
if (fir::getTargetTriple(mod).supportsCOMDAT()) {
|
|
mlir::OpPassManager comdatPM("builtin.module");
|
|
comdatPM.addPass(mlir::LLVM::createLLVMAddComdats());
|
|
if (mlir::failed(runPipeline(comdatPM, mod)))
|
|
return signalPassFailure();
|
|
}
|
|
}
|
|
|
|
private:
|
|
fir::FIRToLLVMPassOptions options;
|
|
};
|
|
|
|
/// Lower from LLVM IR dialect to proper LLVM-IR and dump the module
|
|
struct LLVMIRLoweringPass
|
|
: public mlir::PassWrapper<LLVMIRLoweringPass,
|
|
mlir::OperationPass<mlir::ModuleOp>> {
|
|
MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(LLVMIRLoweringPass)
|
|
|
|
LLVMIRLoweringPass(llvm::raw_ostream &output, fir::LLVMIRLoweringPrinter p)
|
|
: output{output}, printer{p} {}
|
|
|
|
mlir::ModuleOp getModule() { return getOperation(); }
|
|
|
|
void runOnOperation() override final {
|
|
auto *ctx = getModule().getContext();
|
|
auto optName = getModule().getName();
|
|
llvm::LLVMContext llvmCtx;
|
|
if (auto llvmModule = mlir::translateModuleToLLVMIR(
|
|
getModule(), llvmCtx, optName ? *optName : "FIRModule")) {
|
|
printer(*llvmModule, output);
|
|
return;
|
|
}
|
|
|
|
mlir::emitError(mlir::UnknownLoc::get(ctx), "could not emit LLVM-IR\n");
|
|
signalPassFailure();
|
|
}
|
|
|
|
private:
|
|
llvm::raw_ostream &output;
|
|
fir::LLVMIRLoweringPrinter printer;
|
|
};
|
|
|
|
} // namespace
|
|
|
|
std::unique_ptr<mlir::Pass> fir::createFIRToLLVMPass() {
|
|
return std::make_unique<FIRToLLVMLowering>();
|
|
}
|
|
|
|
std::unique_ptr<mlir::Pass>
|
|
fir::createFIRToLLVMPass(fir::FIRToLLVMPassOptions options) {
|
|
return std::make_unique<FIRToLLVMLowering>(options);
|
|
}
|
|
|
|
std::unique_ptr<mlir::Pass>
|
|
fir::createLLVMDialectToLLVMPass(llvm::raw_ostream &output,
|
|
fir::LLVMIRLoweringPrinter printer) {
|
|
return std::make_unique<LLVMIRLoweringPass>(output, printer);
|
|
}
|
|
|
|
void fir::populateFIRToLLVMConversionPatterns(
|
|
const fir::LLVMTypeConverter &converter, mlir::RewritePatternSet &patterns,
|
|
fir::FIRToLLVMPassOptions &options) {
|
|
patterns.insert<
|
|
AbsentOpConversion, AddcOpConversion, AddrOfOpConversion,
|
|
AllocaOpConversion, AllocMemOpConversion, BoxAddrOpConversion,
|
|
BoxCharLenOpConversion, BoxDimsOpConversion, BoxEleSizeOpConversion,
|
|
BoxIsAllocOpConversion, BoxIsArrayOpConversion, BoxIsPtrOpConversion,
|
|
BoxOffsetOpConversion, BoxProcHostOpConversion, BoxRankOpConversion,
|
|
BoxTypeCodeOpConversion, BoxTypeDescOpConversion, CallOpConversion,
|
|
CmpcOpConversion, ConvertOpConversion, CoordinateOpConversion,
|
|
CopyOpConversion, DTEntryOpConversion, DeclareOpConversion,
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DivcOpConversion, EmboxOpConversion, EmboxCharOpConversion,
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EmboxProcOpConversion, ExtractValueOpConversion, FieldIndexOpConversion,
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FirEndOpConversion, FreeMemOpConversion, GlobalLenOpConversion,
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GlobalOpConversion, InsertOnRangeOpConversion, IsPresentOpConversion,
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LenParamIndexOpConversion, LoadOpConversion, MulcOpConversion,
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NegcOpConversion, NoReassocOpConversion, SelectCaseOpConversion,
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SelectOpConversion, SelectRankOpConversion, SelectTypeOpConversion,
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ShapeOpConversion, ShapeShiftOpConversion, ShiftOpConversion,
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SliceOpConversion, StoreOpConversion, StringLitOpConversion,
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SubcOpConversion, TypeDescOpConversion, TypeInfoOpConversion,
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UnboxCharOpConversion, UnboxProcOpConversion, UndefOpConversion,
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UnreachableOpConversion, XArrayCoorOpConversion, XEmboxOpConversion,
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XReboxOpConversion, ZeroOpConversion>(converter, options);
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|
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// Patterns that are populated without a type converter do not trigger
|
|
// target materializations for the operands of the root op.
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patterns.insert<HasValueOpConversion, InsertValueOpConversion>(
|
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patterns.getContext());
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}
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