1 //===-- CodeGen.cpp -- bridge to lower to LLVM ----------------------------===// 2 // 3 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. 4 // See https://llvm.org/LICENSE.txt for license information. 5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception 6 // 7 //===----------------------------------------------------------------------===// 8 // 9 // Coding style: https://mlir.llvm.org/getting_started/DeveloperGuide/ 10 // 11 //===----------------------------------------------------------------------===// 12 13 #include "flang/Optimizer/CodeGen/CodeGen.h" 14 #include "PassDetail.h" 15 #include "flang/ISO_Fortran_binding.h" 16 #include "flang/Optimizer/Dialect/FIRAttr.h" 17 #include "flang/Optimizer/Dialect/FIROps.h" 18 #include "mlir/Conversion/ArithmeticToLLVM/ArithmeticToLLVM.h" 19 #include "mlir/Conversion/LLVMCommon/Pattern.h" 20 #include "mlir/Conversion/StandardToLLVM/ConvertStandardToLLVM.h" 21 #include "mlir/IR/BuiltinTypes.h" 22 #include "mlir/IR/Matchers.h" 23 #include "mlir/Pass/Pass.h" 24 #include "llvm/ADT/ArrayRef.h" 25 26 #define DEBUG_TYPE "flang-codegen" 27 28 // fir::LLVMTypeConverter for converting to LLVM IR dialect types. 29 #include "TypeConverter.h" 30 31 /// `fir.box` attribute values as defined for CFI_attribute_t in 32 /// flang/ISO_Fortran_binding.h. 33 static constexpr unsigned kAttrPointer = CFI_attribute_pointer; 34 static constexpr unsigned kAttrAllocatable = CFI_attribute_allocatable; 35 36 static mlir::LLVM::ConstantOp 37 genConstantIndex(mlir::Location loc, mlir::Type ity, 38 mlir::ConversionPatternRewriter &rewriter, 39 std::int64_t offset) { 40 auto cattr = rewriter.getI64IntegerAttr(offset); 41 return rewriter.create<mlir::LLVM::ConstantOp>(loc, ity, cattr); 42 } 43 44 static Block *createBlock(mlir::ConversionPatternRewriter &rewriter, 45 mlir::Block *insertBefore) { 46 assert(insertBefore && "expected valid insertion block"); 47 return rewriter.createBlock(insertBefore->getParent(), 48 mlir::Region::iterator(insertBefore)); 49 } 50 51 namespace { 52 /// FIR conversion pattern template 53 template <typename FromOp> 54 class FIROpConversion : public mlir::ConvertOpToLLVMPattern<FromOp> { 55 public: 56 explicit FIROpConversion(fir::LLVMTypeConverter &lowering) 57 : mlir::ConvertOpToLLVMPattern<FromOp>(lowering) {} 58 59 protected: 60 mlir::Type convertType(mlir::Type ty) const { 61 return lowerTy().convertType(ty); 62 } 63 64 mlir::LLVM::ConstantOp 65 genConstantOffset(mlir::Location loc, 66 mlir::ConversionPatternRewriter &rewriter, 67 int offset) const { 68 auto ity = lowerTy().offsetType(); 69 auto cattr = rewriter.getI32IntegerAttr(offset); 70 return rewriter.create<mlir::LLVM::ConstantOp>(loc, ity, cattr); 71 } 72 73 /// Construct code sequence to extract the specifc value from a `fir.box`. 74 mlir::Value getValueFromBox(mlir::Location loc, mlir::Value box, 75 mlir::Type resultTy, 76 mlir::ConversionPatternRewriter &rewriter, 77 unsigned boxValue) const { 78 mlir::LLVM::ConstantOp c0 = genConstantOffset(loc, rewriter, 0); 79 mlir::LLVM::ConstantOp cValuePos = 80 genConstantOffset(loc, rewriter, boxValue); 81 auto pty = mlir::LLVM::LLVMPointerType::get(resultTy); 82 auto p = rewriter.create<mlir::LLVM::GEPOp>( 83 loc, pty, mlir::ValueRange{box, c0, cValuePos}); 84 return rewriter.create<mlir::LLVM::LoadOp>(loc, resultTy, p); 85 } 86 87 /// Method to construct code sequence to get the triple for dimension `dim` 88 /// from a box. 89 SmallVector<mlir::Value, 3> 90 getDimsFromBox(mlir::Location loc, ArrayRef<mlir::Type> retTys, 91 mlir::Value box, mlir::Value dim, 92 mlir::ConversionPatternRewriter &rewriter) const { 93 mlir::LLVM::ConstantOp c0 = genConstantOffset(loc, rewriter, 0); 94 mlir::LLVM::ConstantOp cDims = 95 genConstantOffset(loc, rewriter, kDimsPosInBox); 96 mlir::LLVM::LoadOp l0 = 97 loadFromOffset(loc, box, c0, cDims, dim, 0, retTys[0], rewriter); 98 mlir::LLVM::LoadOp l1 = 99 loadFromOffset(loc, box, c0, cDims, dim, 1, retTys[1], rewriter); 100 mlir::LLVM::LoadOp l2 = 101 loadFromOffset(loc, box, c0, cDims, dim, 2, retTys[2], rewriter); 102 return {l0.getResult(), l1.getResult(), l2.getResult()}; 103 } 104 105 mlir::LLVM::LoadOp 106 loadFromOffset(mlir::Location loc, mlir::Value a, mlir::LLVM::ConstantOp c0, 107 mlir::LLVM::ConstantOp cDims, mlir::Value dim, int off, 108 mlir::Type ty, 109 mlir::ConversionPatternRewriter &rewriter) const { 110 auto pty = mlir::LLVM::LLVMPointerType::get(ty); 111 mlir::LLVM::ConstantOp c = genConstantOffset(loc, rewriter, off); 112 mlir::LLVM::GEPOp p = genGEP(loc, pty, rewriter, a, c0, cDims, dim, c); 113 return rewriter.create<mlir::LLVM::LoadOp>(loc, ty, p); 114 } 115 116 /// Read base address from a fir.box. Returned address has type ty. 117 mlir::Value 118 loadBaseAddrFromBox(mlir::Location loc, mlir::Type ty, mlir::Value box, 119 mlir::ConversionPatternRewriter &rewriter) const { 120 mlir::LLVM::ConstantOp c0 = genConstantOffset(loc, rewriter, 0); 121 mlir::LLVM::ConstantOp cAddr = 122 genConstantOffset(loc, rewriter, kAddrPosInBox); 123 auto pty = mlir::LLVM::LLVMPointerType::get(ty); 124 mlir::LLVM::GEPOp p = genGEP(loc, pty, rewriter, box, c0, cAddr); 125 return rewriter.create<mlir::LLVM::LoadOp>(loc, ty, p); 126 } 127 128 mlir::Value 129 loadElementSizeFromBox(mlir::Location loc, mlir::Type ty, mlir::Value box, 130 mlir::ConversionPatternRewriter &rewriter) const { 131 mlir::LLVM::ConstantOp c0 = genConstantOffset(loc, rewriter, 0); 132 mlir::LLVM::ConstantOp cElemLen = 133 genConstantOffset(loc, rewriter, kElemLenPosInBox); 134 auto pty = mlir::LLVM::LLVMPointerType::get(ty); 135 mlir::LLVM::GEPOp p = genGEP(loc, pty, rewriter, box, c0, cElemLen); 136 return rewriter.create<mlir::LLVM::LoadOp>(loc, ty, p); 137 } 138 139 // Load the attribute from the \p box and perform a check against \p maskValue 140 // The final comparison is implemented as `(attribute & maskValue) != 0`. 141 mlir::Value genBoxAttributeCheck(mlir::Location loc, mlir::Value box, 142 mlir::ConversionPatternRewriter &rewriter, 143 unsigned maskValue) const { 144 mlir::Type attrTy = rewriter.getI32Type(); 145 mlir::Value attribute = 146 getValueFromBox(loc, box, attrTy, rewriter, kAttributePosInBox); 147 mlir::LLVM::ConstantOp attrMask = 148 genConstantOffset(loc, rewriter, maskValue); 149 auto maskRes = 150 rewriter.create<mlir::LLVM::AndOp>(loc, attrTy, attribute, attrMask); 151 mlir::LLVM::ConstantOp c0 = genConstantOffset(loc, rewriter, 0); 152 return rewriter.create<mlir::LLVM::ICmpOp>( 153 loc, mlir::LLVM::ICmpPredicate::ne, maskRes, c0); 154 } 155 156 template <typename... ARGS> 157 mlir::LLVM::GEPOp genGEP(mlir::Location loc, mlir::Type ty, 158 mlir::ConversionPatternRewriter &rewriter, 159 mlir::Value base, ARGS... args) const { 160 SmallVector<mlir::Value> cv{args...}; 161 return rewriter.create<mlir::LLVM::GEPOp>(loc, ty, base, cv); 162 } 163 164 /// Perform an extension or truncation as needed on an integer value. Lowering 165 /// to the specific target may involve some sign-extending or truncation of 166 /// values, particularly to fit them from abstract box types to the 167 /// appropriate reified structures. 168 mlir::Value integerCast(mlir::Location loc, 169 mlir::ConversionPatternRewriter &rewriter, 170 mlir::Type ty, mlir::Value val) const { 171 auto valTy = val.getType(); 172 // If the value was not yet lowered, lower its type so that it can 173 // be used in getPrimitiveTypeSizeInBits. 174 if (!valTy.isa<mlir::IntegerType>()) 175 valTy = convertType(valTy); 176 auto toSize = mlir::LLVM::getPrimitiveTypeSizeInBits(ty); 177 auto fromSize = mlir::LLVM::getPrimitiveTypeSizeInBits(valTy); 178 if (toSize < fromSize) 179 return rewriter.create<mlir::LLVM::TruncOp>(loc, ty, val); 180 if (toSize > fromSize) 181 return rewriter.create<mlir::LLVM::SExtOp>(loc, ty, val); 182 return val; 183 } 184 185 fir::LLVMTypeConverter &lowerTy() const { 186 return *static_cast<fir::LLVMTypeConverter *>(this->getTypeConverter()); 187 } 188 }; 189 190 /// FIR conversion pattern template 191 template <typename FromOp> 192 class FIROpAndTypeConversion : public FIROpConversion<FromOp> { 193 public: 194 using FIROpConversion<FromOp>::FIROpConversion; 195 using OpAdaptor = typename FromOp::Adaptor; 196 197 mlir::LogicalResult 198 matchAndRewrite(FromOp op, OpAdaptor adaptor, 199 mlir::ConversionPatternRewriter &rewriter) const final { 200 mlir::Type ty = this->convertType(op.getType()); 201 return doRewrite(op, ty, adaptor, rewriter); 202 } 203 204 virtual mlir::LogicalResult 205 doRewrite(FromOp addr, mlir::Type ty, OpAdaptor adaptor, 206 mlir::ConversionPatternRewriter &rewriter) const = 0; 207 }; 208 209 /// Create value signaling an absent optional argument in a call, e.g. 210 /// `fir.absent !fir.ref<i64>` --> `llvm.mlir.null : !llvm.ptr<i64>` 211 struct AbsentOpConversion : public FIROpConversion<fir::AbsentOp> { 212 using FIROpConversion::FIROpConversion; 213 214 mlir::LogicalResult 215 matchAndRewrite(fir::AbsentOp absent, OpAdaptor, 216 mlir::ConversionPatternRewriter &rewriter) const override { 217 mlir::Type ty = convertType(absent.getType()); 218 mlir::Location loc = absent.getLoc(); 219 220 if (absent.getType().isa<fir::BoxCharType>()) { 221 auto structTy = ty.cast<mlir::LLVM::LLVMStructType>(); 222 assert(!structTy.isOpaque() && !structTy.getBody().empty()); 223 auto undefStruct = rewriter.create<mlir::LLVM::UndefOp>(loc, ty); 224 auto nullField = 225 rewriter.create<mlir::LLVM::NullOp>(loc, structTy.getBody()[0]); 226 mlir::MLIRContext *ctx = absent.getContext(); 227 auto c0 = mlir::ArrayAttr::get(ctx, rewriter.getI32IntegerAttr(0)); 228 rewriter.replaceOpWithNewOp<mlir::LLVM::InsertValueOp>( 229 absent, ty, undefStruct, nullField, c0); 230 } else { 231 rewriter.replaceOpWithNewOp<mlir::LLVM::NullOp>(absent, ty); 232 } 233 return success(); 234 } 235 }; 236 237 // Lower `fir.address_of` operation to `llvm.address_of` operation. 238 struct AddrOfOpConversion : public FIROpConversion<fir::AddrOfOp> { 239 using FIROpConversion::FIROpConversion; 240 241 mlir::LogicalResult 242 matchAndRewrite(fir::AddrOfOp addr, OpAdaptor adaptor, 243 mlir::ConversionPatternRewriter &rewriter) const override { 244 auto ty = convertType(addr.getType()); 245 rewriter.replaceOpWithNewOp<mlir::LLVM::AddressOfOp>( 246 addr, ty, addr.symbol().getRootReference().getValue()); 247 return success(); 248 } 249 }; 250 } // namespace 251 252 /// Lookup the function to compute the memory size of this parametric derived 253 /// type. The size of the object may depend on the LEN type parameters of the 254 /// derived type. 255 static mlir::LLVM::LLVMFuncOp 256 getDependentTypeMemSizeFn(fir::RecordType recTy, fir::AllocaOp op, 257 mlir::ConversionPatternRewriter &rewriter) { 258 auto module = op->getParentOfType<mlir::ModuleOp>(); 259 std::string name = recTy.getName().str() + "P.mem.size"; 260 return module.lookupSymbol<mlir::LLVM::LLVMFuncOp>(name); 261 } 262 263 namespace { 264 /// convert to LLVM IR dialect `alloca` 265 struct AllocaOpConversion : public FIROpConversion<fir::AllocaOp> { 266 using FIROpConversion::FIROpConversion; 267 268 mlir::LogicalResult 269 matchAndRewrite(fir::AllocaOp alloc, OpAdaptor adaptor, 270 mlir::ConversionPatternRewriter &rewriter) const override { 271 mlir::ValueRange operands = adaptor.getOperands(); 272 auto loc = alloc.getLoc(); 273 mlir::Type ity = lowerTy().indexType(); 274 unsigned i = 0; 275 mlir::Value size = genConstantIndex(loc, ity, rewriter, 1).getResult(); 276 mlir::Type ty = convertType(alloc.getType()); 277 mlir::Type resultTy = ty; 278 if (alloc.hasLenParams()) { 279 unsigned end = alloc.numLenParams(); 280 llvm::SmallVector<mlir::Value> lenParams; 281 for (; i < end; ++i) 282 lenParams.push_back(operands[i]); 283 mlir::Type scalarType = fir::unwrapSequenceType(alloc.getInType()); 284 if (auto chrTy = scalarType.dyn_cast<fir::CharacterType>()) { 285 fir::CharacterType rawCharTy = fir::CharacterType::getUnknownLen( 286 chrTy.getContext(), chrTy.getFKind()); 287 ty = mlir::LLVM::LLVMPointerType::get(convertType(rawCharTy)); 288 assert(end == 1); 289 size = integerCast(loc, rewriter, ity, lenParams[0]); 290 } else if (auto recTy = scalarType.dyn_cast<fir::RecordType>()) { 291 mlir::LLVM::LLVMFuncOp memSizeFn = 292 getDependentTypeMemSizeFn(recTy, alloc, rewriter); 293 if (!memSizeFn) 294 emitError(loc, "did not find allocation function"); 295 mlir::NamedAttribute attr = rewriter.getNamedAttr( 296 "callee", mlir::SymbolRefAttr::get(memSizeFn)); 297 auto call = rewriter.create<mlir::LLVM::CallOp>( 298 loc, ity, lenParams, llvm::ArrayRef<mlir::NamedAttribute>{attr}); 299 size = call.getResult(0); 300 ty = mlir::LLVM::LLVMPointerType::get( 301 mlir::IntegerType::get(alloc.getContext(), 8)); 302 } else { 303 return emitError(loc, "unexpected type ") 304 << scalarType << " with type parameters"; 305 } 306 } 307 if (alloc.hasShapeOperands()) { 308 mlir::Type allocEleTy = fir::unwrapRefType(alloc.getType()); 309 // Scale the size by constant factors encoded in the array type. 310 if (auto seqTy = allocEleTy.dyn_cast<fir::SequenceType>()) { 311 fir::SequenceType::Extent constSize = 1; 312 for (auto extent : seqTy.getShape()) 313 if (extent != fir::SequenceType::getUnknownExtent()) 314 constSize *= extent; 315 mlir::Value constVal{ 316 genConstantIndex(loc, ity, rewriter, constSize).getResult()}; 317 size = rewriter.create<mlir::LLVM::MulOp>(loc, ity, size, constVal); 318 } 319 unsigned end = operands.size(); 320 for (; i < end; ++i) 321 size = rewriter.create<mlir::LLVM::MulOp>( 322 loc, ity, size, integerCast(loc, rewriter, ity, operands[i])); 323 } 324 if (ty == resultTy) { 325 // Do not emit the bitcast if ty and resultTy are the same. 326 rewriter.replaceOpWithNewOp<mlir::LLVM::AllocaOp>(alloc, ty, size, 327 alloc->getAttrs()); 328 } else { 329 auto al = rewriter.create<mlir::LLVM::AllocaOp>(loc, ty, size, 330 alloc->getAttrs()); 331 rewriter.replaceOpWithNewOp<mlir::LLVM::BitcastOp>(alloc, resultTy, al); 332 } 333 return success(); 334 } 335 }; 336 337 /// Lower `fir.box_addr` to the sequence of operations to extract the first 338 /// element of the box. 339 struct BoxAddrOpConversion : public FIROpConversion<fir::BoxAddrOp> { 340 using FIROpConversion::FIROpConversion; 341 342 mlir::LogicalResult 343 matchAndRewrite(fir::BoxAddrOp boxaddr, OpAdaptor adaptor, 344 mlir::ConversionPatternRewriter &rewriter) const override { 345 mlir::Value a = adaptor.getOperands()[0]; 346 auto loc = boxaddr.getLoc(); 347 mlir::Type ty = convertType(boxaddr.getType()); 348 if (auto argty = boxaddr.val().getType().dyn_cast<fir::BoxType>()) { 349 rewriter.replaceOp(boxaddr, loadBaseAddrFromBox(loc, ty, a, rewriter)); 350 } else { 351 auto c0attr = rewriter.getI32IntegerAttr(0); 352 auto c0 = mlir::ArrayAttr::get(boxaddr.getContext(), c0attr); 353 rewriter.replaceOpWithNewOp<mlir::LLVM::ExtractValueOp>(boxaddr, ty, a, 354 c0); 355 } 356 return success(); 357 } 358 }; 359 360 /// Lower `fir.box_dims` to a sequence of operations to extract the requested 361 /// dimension infomartion from the boxed value. 362 /// Result in a triple set of GEPs and loads. 363 struct BoxDimsOpConversion : public FIROpConversion<fir::BoxDimsOp> { 364 using FIROpConversion::FIROpConversion; 365 366 mlir::LogicalResult 367 matchAndRewrite(fir::BoxDimsOp boxdims, OpAdaptor adaptor, 368 mlir::ConversionPatternRewriter &rewriter) const override { 369 SmallVector<mlir::Type, 3> resultTypes = { 370 convertType(boxdims.getResult(0).getType()), 371 convertType(boxdims.getResult(1).getType()), 372 convertType(boxdims.getResult(2).getType()), 373 }; 374 auto results = 375 getDimsFromBox(boxdims.getLoc(), resultTypes, adaptor.getOperands()[0], 376 adaptor.getOperands()[1], rewriter); 377 rewriter.replaceOp(boxdims, results); 378 return success(); 379 } 380 }; 381 382 /// Lower `fir.box_elesize` to a sequence of operations ro extract the size of 383 /// an element in the boxed value. 384 struct BoxEleSizeOpConversion : public FIROpConversion<fir::BoxEleSizeOp> { 385 using FIROpConversion::FIROpConversion; 386 387 mlir::LogicalResult 388 matchAndRewrite(fir::BoxEleSizeOp boxelesz, OpAdaptor adaptor, 389 mlir::ConversionPatternRewriter &rewriter) const override { 390 mlir::Value a = adaptor.getOperands()[0]; 391 auto loc = boxelesz.getLoc(); 392 auto ty = convertType(boxelesz.getType()); 393 auto elemSize = getValueFromBox(loc, a, ty, rewriter, kElemLenPosInBox); 394 rewriter.replaceOp(boxelesz, elemSize); 395 return success(); 396 } 397 }; 398 399 /// Lower `fir.box_isalloc` to a sequence of operations to determine if the 400 /// boxed value was from an ALLOCATABLE entity. 401 struct BoxIsAllocOpConversion : public FIROpConversion<fir::BoxIsAllocOp> { 402 using FIROpConversion::FIROpConversion; 403 404 mlir::LogicalResult 405 matchAndRewrite(fir::BoxIsAllocOp boxisalloc, OpAdaptor adaptor, 406 mlir::ConversionPatternRewriter &rewriter) const override { 407 mlir::Value box = adaptor.getOperands()[0]; 408 auto loc = boxisalloc.getLoc(); 409 mlir::Value check = 410 genBoxAttributeCheck(loc, box, rewriter, kAttrAllocatable); 411 rewriter.replaceOp(boxisalloc, check); 412 return success(); 413 } 414 }; 415 416 /// Lower `fir.box_isarray` to a sequence of operations to determine if the 417 /// boxed is an array. 418 struct BoxIsArrayOpConversion : public FIROpConversion<fir::BoxIsArrayOp> { 419 using FIROpConversion::FIROpConversion; 420 421 mlir::LogicalResult 422 matchAndRewrite(fir::BoxIsArrayOp boxisarray, OpAdaptor adaptor, 423 mlir::ConversionPatternRewriter &rewriter) const override { 424 mlir::Value a = adaptor.getOperands()[0]; 425 auto loc = boxisarray.getLoc(); 426 auto rank = 427 getValueFromBox(loc, a, rewriter.getI32Type(), rewriter, kRankPosInBox); 428 auto c0 = genConstantOffset(loc, rewriter, 0); 429 rewriter.replaceOpWithNewOp<mlir::LLVM::ICmpOp>( 430 boxisarray, mlir::LLVM::ICmpPredicate::ne, rank, c0); 431 return success(); 432 } 433 }; 434 435 /// Lower `fir.box_isptr` to a sequence of operations to determined if the 436 /// boxed value was from a POINTER entity. 437 struct BoxIsPtrOpConversion : public FIROpConversion<fir::BoxIsPtrOp> { 438 using FIROpConversion::FIROpConversion; 439 440 mlir::LogicalResult 441 matchAndRewrite(fir::BoxIsPtrOp boxisptr, OpAdaptor adaptor, 442 mlir::ConversionPatternRewriter &rewriter) const override { 443 mlir::Value box = adaptor.getOperands()[0]; 444 auto loc = boxisptr.getLoc(); 445 mlir::Value check = genBoxAttributeCheck(loc, box, rewriter, kAttrPointer); 446 rewriter.replaceOp(boxisptr, check); 447 return success(); 448 } 449 }; 450 451 /// Lower `fir.box_rank` to the sequence of operation to extract the rank from 452 /// the box. 453 struct BoxRankOpConversion : public FIROpConversion<fir::BoxRankOp> { 454 using FIROpConversion::FIROpConversion; 455 456 mlir::LogicalResult 457 matchAndRewrite(fir::BoxRankOp boxrank, OpAdaptor adaptor, 458 mlir::ConversionPatternRewriter &rewriter) const override { 459 mlir::Value a = adaptor.getOperands()[0]; 460 auto loc = boxrank.getLoc(); 461 mlir::Type ty = convertType(boxrank.getType()); 462 auto result = getValueFromBox(loc, a, ty, rewriter, kRankPosInBox); 463 rewriter.replaceOp(boxrank, result); 464 return success(); 465 } 466 }; 467 468 // `fir.call` -> `llvm.call` 469 struct CallOpConversion : public FIROpConversion<fir::CallOp> { 470 using FIROpConversion::FIROpConversion; 471 472 mlir::LogicalResult 473 matchAndRewrite(fir::CallOp call, OpAdaptor adaptor, 474 mlir::ConversionPatternRewriter &rewriter) const override { 475 SmallVector<mlir::Type> resultTys; 476 for (auto r : call.getResults()) 477 resultTys.push_back(convertType(r.getType())); 478 rewriter.replaceOpWithNewOp<mlir::LLVM::CallOp>( 479 call, resultTys, adaptor.getOperands(), call->getAttrs()); 480 return success(); 481 } 482 }; 483 484 static mlir::Type getComplexEleTy(mlir::Type complex) { 485 if (auto cc = complex.dyn_cast<mlir::ComplexType>()) 486 return cc.getElementType(); 487 return complex.cast<fir::ComplexType>().getElementType(); 488 } 489 490 /// convert value of from-type to value of to-type 491 struct ConvertOpConversion : public FIROpConversion<fir::ConvertOp> { 492 using FIROpConversion::FIROpConversion; 493 494 static bool isFloatingPointTy(mlir::Type ty) { 495 return ty.isa<mlir::FloatType>(); 496 } 497 498 mlir::LogicalResult 499 matchAndRewrite(fir::ConvertOp convert, OpAdaptor adaptor, 500 mlir::ConversionPatternRewriter &rewriter) const override { 501 auto fromTy = convertType(convert.value().getType()); 502 auto toTy = convertType(convert.res().getType()); 503 mlir::Value op0 = adaptor.getOperands()[0]; 504 if (fromTy == toTy) { 505 rewriter.replaceOp(convert, op0); 506 return success(); 507 } 508 auto loc = convert.getLoc(); 509 auto convertFpToFp = [&](mlir::Value val, unsigned fromBits, 510 unsigned toBits, mlir::Type toTy) -> mlir::Value { 511 if (fromBits == toBits) { 512 // TODO: Converting between two floating-point representations with the 513 // same bitwidth is not allowed for now. 514 mlir::emitError(loc, 515 "cannot implicitly convert between two floating-point " 516 "representations of the same bitwidth"); 517 return {}; 518 } 519 if (fromBits > toBits) 520 return rewriter.create<mlir::LLVM::FPTruncOp>(loc, toTy, val); 521 return rewriter.create<mlir::LLVM::FPExtOp>(loc, toTy, val); 522 }; 523 // Complex to complex conversion. 524 if (fir::isa_complex(convert.value().getType()) && 525 fir::isa_complex(convert.res().getType())) { 526 // Special case: handle the conversion of a complex such that both the 527 // real and imaginary parts are converted together. 528 auto zero = mlir::ArrayAttr::get(convert.getContext(), 529 rewriter.getI32IntegerAttr(0)); 530 auto one = mlir::ArrayAttr::get(convert.getContext(), 531 rewriter.getI32IntegerAttr(1)); 532 auto ty = convertType(getComplexEleTy(convert.value().getType())); 533 auto rp = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, ty, op0, zero); 534 auto ip = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, ty, op0, one); 535 auto nt = convertType(getComplexEleTy(convert.res().getType())); 536 auto fromBits = mlir::LLVM::getPrimitiveTypeSizeInBits(ty); 537 auto toBits = mlir::LLVM::getPrimitiveTypeSizeInBits(nt); 538 auto rc = convertFpToFp(rp, fromBits, toBits, nt); 539 auto ic = convertFpToFp(ip, fromBits, toBits, nt); 540 auto un = rewriter.create<mlir::LLVM::UndefOp>(loc, toTy); 541 auto i1 = 542 rewriter.create<mlir::LLVM::InsertValueOp>(loc, toTy, un, rc, zero); 543 rewriter.replaceOpWithNewOp<mlir::LLVM::InsertValueOp>(convert, toTy, i1, 544 ic, one); 545 return mlir::success(); 546 } 547 // Floating point to floating point conversion. 548 if (isFloatingPointTy(fromTy)) { 549 if (isFloatingPointTy(toTy)) { 550 auto fromBits = mlir::LLVM::getPrimitiveTypeSizeInBits(fromTy); 551 auto toBits = mlir::LLVM::getPrimitiveTypeSizeInBits(toTy); 552 auto v = convertFpToFp(op0, fromBits, toBits, toTy); 553 rewriter.replaceOp(convert, v); 554 return mlir::success(); 555 } 556 if (toTy.isa<mlir::IntegerType>()) { 557 rewriter.replaceOpWithNewOp<mlir::LLVM::FPToSIOp>(convert, toTy, op0); 558 return mlir::success(); 559 } 560 } else if (fromTy.isa<mlir::IntegerType>()) { 561 // Integer to integer conversion. 562 if (toTy.isa<mlir::IntegerType>()) { 563 auto fromBits = mlir::LLVM::getPrimitiveTypeSizeInBits(fromTy); 564 auto toBits = mlir::LLVM::getPrimitiveTypeSizeInBits(toTy); 565 assert(fromBits != toBits); 566 if (fromBits > toBits) { 567 rewriter.replaceOpWithNewOp<mlir::LLVM::TruncOp>(convert, toTy, op0); 568 return mlir::success(); 569 } 570 rewriter.replaceOpWithNewOp<mlir::LLVM::SExtOp>(convert, toTy, op0); 571 return mlir::success(); 572 } 573 // Integer to floating point conversion. 574 if (isFloatingPointTy(toTy)) { 575 rewriter.replaceOpWithNewOp<mlir::LLVM::SIToFPOp>(convert, toTy, op0); 576 return mlir::success(); 577 } 578 // Integer to pointer conversion. 579 if (toTy.isa<mlir::LLVM::LLVMPointerType>()) { 580 rewriter.replaceOpWithNewOp<mlir::LLVM::IntToPtrOp>(convert, toTy, op0); 581 return mlir::success(); 582 } 583 } else if (fromTy.isa<mlir::LLVM::LLVMPointerType>()) { 584 // Pointer to integer conversion. 585 if (toTy.isa<mlir::IntegerType>()) { 586 rewriter.replaceOpWithNewOp<mlir::LLVM::PtrToIntOp>(convert, toTy, op0); 587 return mlir::success(); 588 } 589 // Pointer to pointer conversion. 590 if (toTy.isa<mlir::LLVM::LLVMPointerType>()) { 591 rewriter.replaceOpWithNewOp<mlir::LLVM::BitcastOp>(convert, toTy, op0); 592 return mlir::success(); 593 } 594 } 595 return emitError(loc) << "cannot convert " << fromTy << " to " << toTy; 596 } 597 }; 598 599 /// Lower `fir.dispatch` operation. A virtual call to a method in a dispatch 600 /// table. 601 struct DispatchOpConversion : public FIROpConversion<fir::DispatchOp> { 602 using FIROpConversion::FIROpConversion; 603 604 mlir::LogicalResult 605 matchAndRewrite(fir::DispatchOp dispatch, OpAdaptor adaptor, 606 mlir::ConversionPatternRewriter &rewriter) const override { 607 return rewriter.notifyMatchFailure( 608 dispatch, "fir.dispatch codegen is not implemented yet"); 609 } 610 }; 611 612 /// Lower `fir.dispatch_table` operation. The dispatch table for a Fortran 613 /// derived type. 614 struct DispatchTableOpConversion 615 : public FIROpConversion<fir::DispatchTableOp> { 616 using FIROpConversion::FIROpConversion; 617 618 mlir::LogicalResult 619 matchAndRewrite(fir::DispatchTableOp dispTab, OpAdaptor adaptor, 620 mlir::ConversionPatternRewriter &rewriter) const override { 621 return rewriter.notifyMatchFailure( 622 dispTab, "fir.dispatch_table codegen is not implemented yet"); 623 } 624 }; 625 626 /// Lower `fir.dt_entry` operation. An entry in a dispatch table; binds a 627 /// method-name to a function. 628 struct DTEntryOpConversion : public FIROpConversion<fir::DTEntryOp> { 629 using FIROpConversion::FIROpConversion; 630 631 mlir::LogicalResult 632 matchAndRewrite(fir::DTEntryOp dtEnt, OpAdaptor adaptor, 633 mlir::ConversionPatternRewriter &rewriter) const override { 634 return rewriter.notifyMatchFailure( 635 dtEnt, "fir.dt_entry codegen is not implemented yet"); 636 } 637 }; 638 639 /// Lower `fir.has_value` operation to `llvm.return` operation. 640 struct HasValueOpConversion : public FIROpConversion<fir::HasValueOp> { 641 using FIROpConversion::FIROpConversion; 642 643 mlir::LogicalResult 644 matchAndRewrite(fir::HasValueOp op, OpAdaptor adaptor, 645 mlir::ConversionPatternRewriter &rewriter) const override { 646 rewriter.replaceOpWithNewOp<LLVM::ReturnOp>(op, adaptor.getOperands()); 647 return success(); 648 } 649 }; 650 651 /// Lower `fir.global` operation to `llvm.global` operation. 652 /// `fir.insert_on_range` operations are replaced with constant dense attribute 653 /// if they are applied on the full range. 654 struct GlobalOpConversion : public FIROpConversion<fir::GlobalOp> { 655 using FIROpConversion::FIROpConversion; 656 657 mlir::LogicalResult 658 matchAndRewrite(fir::GlobalOp global, OpAdaptor adaptor, 659 mlir::ConversionPatternRewriter &rewriter) const override { 660 auto tyAttr = convertType(global.getType()); 661 if (global.getType().isa<fir::BoxType>()) 662 tyAttr = tyAttr.cast<mlir::LLVM::LLVMPointerType>().getElementType(); 663 auto loc = global.getLoc(); 664 mlir::Attribute initAttr{}; 665 if (global.initVal()) 666 initAttr = global.initVal().getValue(); 667 auto linkage = convertLinkage(global.linkName()); 668 auto isConst = global.constant().hasValue(); 669 auto g = rewriter.create<mlir::LLVM::GlobalOp>( 670 loc, tyAttr, isConst, linkage, global.sym_name(), initAttr); 671 auto &gr = g.getInitializerRegion(); 672 rewriter.inlineRegionBefore(global.region(), gr, gr.end()); 673 if (!gr.empty()) { 674 // Replace insert_on_range with a constant dense attribute if the 675 // initialization is on the full range. 676 auto insertOnRangeOps = gr.front().getOps<fir::InsertOnRangeOp>(); 677 for (auto insertOp : insertOnRangeOps) { 678 if (isFullRange(insertOp.coor(), insertOp.getType())) { 679 auto seqTyAttr = convertType(insertOp.getType()); 680 auto *op = insertOp.val().getDefiningOp(); 681 auto constant = mlir::dyn_cast<mlir::arith::ConstantOp>(op); 682 if (!constant) { 683 auto convertOp = mlir::dyn_cast<fir::ConvertOp>(op); 684 if (!convertOp) 685 continue; 686 constant = cast<mlir::arith::ConstantOp>( 687 convertOp.value().getDefiningOp()); 688 } 689 mlir::Type vecType = mlir::VectorType::get( 690 insertOp.getType().getShape(), constant.getType()); 691 auto denseAttr = mlir::DenseElementsAttr::get( 692 vecType.cast<ShapedType>(), constant.value()); 693 rewriter.setInsertionPointAfter(insertOp); 694 rewriter.replaceOpWithNewOp<mlir::arith::ConstantOp>( 695 insertOp, seqTyAttr, denseAttr); 696 } 697 } 698 } 699 rewriter.eraseOp(global); 700 return success(); 701 } 702 703 bool isFullRange(mlir::ArrayAttr indexes, fir::SequenceType seqTy) const { 704 auto extents = seqTy.getShape(); 705 if (indexes.size() / 2 != extents.size()) 706 return false; 707 for (unsigned i = 0; i < indexes.size(); i += 2) { 708 if (indexes[i].cast<IntegerAttr>().getInt() != 0) 709 return false; 710 if (indexes[i + 1].cast<IntegerAttr>().getInt() != extents[i / 2] - 1) 711 return false; 712 } 713 return true; 714 } 715 716 // TODO: String comparaison should be avoided. Replace linkName with an 717 // enumeration. 718 mlir::LLVM::Linkage convertLinkage(Optional<StringRef> optLinkage) const { 719 if (optLinkage.hasValue()) { 720 auto name = optLinkage.getValue(); 721 if (name == "internal") 722 return mlir::LLVM::Linkage::Internal; 723 if (name == "linkonce") 724 return mlir::LLVM::Linkage::Linkonce; 725 if (name == "common") 726 return mlir::LLVM::Linkage::Common; 727 if (name == "weak") 728 return mlir::LLVM::Linkage::Weak; 729 } 730 return mlir::LLVM::Linkage::External; 731 } 732 }; 733 734 void genCondBrOp(mlir::Location loc, mlir::Value cmp, mlir::Block *dest, 735 Optional<mlir::ValueRange> destOps, 736 mlir::ConversionPatternRewriter &rewriter, 737 mlir::Block *newBlock) { 738 if (destOps.hasValue()) 739 rewriter.create<mlir::LLVM::CondBrOp>(loc, cmp, dest, destOps.getValue(), 740 newBlock, mlir::ValueRange()); 741 else 742 rewriter.create<mlir::LLVM::CondBrOp>(loc, cmp, dest, newBlock); 743 } 744 745 template <typename A, typename B> 746 void genBrOp(A caseOp, mlir::Block *dest, Optional<B> destOps, 747 mlir::ConversionPatternRewriter &rewriter) { 748 if (destOps.hasValue()) 749 rewriter.replaceOpWithNewOp<mlir::LLVM::BrOp>(caseOp, destOps.getValue(), 750 dest); 751 else 752 rewriter.replaceOpWithNewOp<mlir::LLVM::BrOp>(caseOp, llvm::None, dest); 753 } 754 755 void genCaseLadderStep(mlir::Location loc, mlir::Value cmp, mlir::Block *dest, 756 Optional<mlir::ValueRange> destOps, 757 mlir::ConversionPatternRewriter &rewriter) { 758 auto *thisBlock = rewriter.getInsertionBlock(); 759 auto *newBlock = createBlock(rewriter, dest); 760 rewriter.setInsertionPointToEnd(thisBlock); 761 genCondBrOp(loc, cmp, dest, destOps, rewriter, newBlock); 762 rewriter.setInsertionPointToEnd(newBlock); 763 } 764 765 /// Conversion of `fir.select_case` 766 /// 767 /// The `fir.select_case` operation is converted to a if-then-else ladder. 768 /// Depending on the case condition type, one or several comparison and 769 /// conditional branching can be generated. 770 /// 771 /// A a point value case such as `case(4)`, a lower bound case such as 772 /// `case(5:)` or an upper bound case such as `case(:3)` are converted to a 773 /// simple comparison between the selector value and the constant value in the 774 /// case. The block associated with the case condition is then executed if 775 /// the comparison succeed otherwise it branch to the next block with the 776 /// comparison for the the next case conditon. 777 /// 778 /// A closed interval case condition such as `case(7:10)` is converted with a 779 /// first comparison and conditional branching for the lower bound. If 780 /// successful, it branch to a second block with the comparison for the 781 /// upper bound in the same case condition. 782 /// 783 /// TODO: lowering of CHARACTER type cases is not handled yet. 784 struct SelectCaseOpConversion : public FIROpConversion<fir::SelectCaseOp> { 785 using FIROpConversion::FIROpConversion; 786 787 mlir::LogicalResult 788 matchAndRewrite(fir::SelectCaseOp caseOp, OpAdaptor adaptor, 789 mlir::ConversionPatternRewriter &rewriter) const override { 790 unsigned conds = caseOp.getNumConditions(); 791 llvm::ArrayRef<mlir::Attribute> cases = caseOp.getCases().getValue(); 792 // Type can be CHARACTER, INTEGER, or LOGICAL (C1145) 793 LLVM_ATTRIBUTE_UNUSED auto ty = caseOp.getSelector().getType(); 794 if (ty.isa<fir::CharacterType>()) 795 return rewriter.notifyMatchFailure(caseOp, 796 "conversion of fir.select_case with " 797 "character type not implemented yet"); 798 mlir::Value selector = caseOp.getSelector(adaptor.getOperands()); 799 auto loc = caseOp.getLoc(); 800 for (unsigned t = 0; t != conds; ++t) { 801 mlir::Block *dest = caseOp.getSuccessor(t); 802 llvm::Optional<mlir::ValueRange> destOps = 803 caseOp.getSuccessorOperands(adaptor.getOperands(), t); 804 llvm::Optional<mlir::ValueRange> cmpOps = 805 *caseOp.getCompareOperands(adaptor.getOperands(), t); 806 mlir::Value caseArg = *(cmpOps.getValue().begin()); 807 mlir::Attribute attr = cases[t]; 808 if (attr.isa<fir::PointIntervalAttr>()) { 809 auto cmp = rewriter.create<mlir::LLVM::ICmpOp>( 810 loc, mlir::LLVM::ICmpPredicate::eq, selector, caseArg); 811 genCaseLadderStep(loc, cmp, dest, destOps, rewriter); 812 continue; 813 } 814 if (attr.isa<fir::LowerBoundAttr>()) { 815 auto cmp = rewriter.create<mlir::LLVM::ICmpOp>( 816 loc, mlir::LLVM::ICmpPredicate::sle, caseArg, selector); 817 genCaseLadderStep(loc, cmp, dest, destOps, rewriter); 818 continue; 819 } 820 if (attr.isa<fir::UpperBoundAttr>()) { 821 auto cmp = rewriter.create<mlir::LLVM::ICmpOp>( 822 loc, mlir::LLVM::ICmpPredicate::sle, selector, caseArg); 823 genCaseLadderStep(loc, cmp, dest, destOps, rewriter); 824 continue; 825 } 826 if (attr.isa<fir::ClosedIntervalAttr>()) { 827 auto cmp = rewriter.create<mlir::LLVM::ICmpOp>( 828 loc, mlir::LLVM::ICmpPredicate::sle, caseArg, selector); 829 auto *thisBlock = rewriter.getInsertionBlock(); 830 auto *newBlock1 = createBlock(rewriter, dest); 831 auto *newBlock2 = createBlock(rewriter, dest); 832 rewriter.setInsertionPointToEnd(thisBlock); 833 rewriter.create<mlir::LLVM::CondBrOp>(loc, cmp, newBlock1, newBlock2); 834 rewriter.setInsertionPointToEnd(newBlock1); 835 mlir::Value caseArg0 = *(cmpOps.getValue().begin() + 1); 836 auto cmp0 = rewriter.create<mlir::LLVM::ICmpOp>( 837 loc, mlir::LLVM::ICmpPredicate::sle, selector, caseArg0); 838 genCondBrOp(loc, cmp0, dest, destOps, rewriter, newBlock2); 839 rewriter.setInsertionPointToEnd(newBlock2); 840 continue; 841 } 842 assert(attr.isa<mlir::UnitAttr>()); 843 assert((t + 1 == conds) && "unit must be last"); 844 genBrOp(caseOp, dest, destOps, rewriter); 845 } 846 return success(); 847 } 848 }; 849 850 template <typename OP> 851 void selectMatchAndRewrite(fir::LLVMTypeConverter &lowering, OP select, 852 typename OP::Adaptor adaptor, 853 mlir::ConversionPatternRewriter &rewriter) { 854 unsigned conds = select.getNumConditions(); 855 auto cases = select.getCases().getValue(); 856 mlir::Value selector = adaptor.selector(); 857 auto loc = select.getLoc(); 858 assert(conds > 0 && "select must have cases"); 859 860 llvm::SmallVector<mlir::Block *> destinations; 861 llvm::SmallVector<mlir::ValueRange> destinationsOperands; 862 mlir::Block *defaultDestination; 863 mlir::ValueRange defaultOperands; 864 llvm::SmallVector<int32_t> caseValues; 865 866 for (unsigned t = 0; t != conds; ++t) { 867 mlir::Block *dest = select.getSuccessor(t); 868 auto destOps = select.getSuccessorOperands(adaptor.getOperands(), t); 869 const mlir::Attribute &attr = cases[t]; 870 if (auto intAttr = attr.template dyn_cast<mlir::IntegerAttr>()) { 871 destinations.push_back(dest); 872 destinationsOperands.push_back(destOps.hasValue() ? *destOps 873 : ValueRange()); 874 caseValues.push_back(intAttr.getInt()); 875 continue; 876 } 877 assert(attr.template dyn_cast_or_null<mlir::UnitAttr>()); 878 assert((t + 1 == conds) && "unit must be last"); 879 defaultDestination = dest; 880 defaultOperands = destOps.hasValue() ? *destOps : ValueRange(); 881 } 882 883 // LLVM::SwitchOp takes a i32 type for the selector. 884 if (select.getSelector().getType() != rewriter.getI32Type()) 885 selector = 886 rewriter.create<LLVM::TruncOp>(loc, rewriter.getI32Type(), selector); 887 888 rewriter.replaceOpWithNewOp<mlir::LLVM::SwitchOp>( 889 select, selector, 890 /*defaultDestination=*/defaultDestination, 891 /*defaultOperands=*/defaultOperands, 892 /*caseValues=*/caseValues, 893 /*caseDestinations=*/destinations, 894 /*caseOperands=*/destinationsOperands, 895 /*branchWeights=*/ArrayRef<int32_t>()); 896 } 897 898 /// conversion of fir::SelectOp to an if-then-else ladder 899 struct SelectOpConversion : public FIROpConversion<fir::SelectOp> { 900 using FIROpConversion::FIROpConversion; 901 902 mlir::LogicalResult 903 matchAndRewrite(fir::SelectOp op, OpAdaptor adaptor, 904 mlir::ConversionPatternRewriter &rewriter) const override { 905 selectMatchAndRewrite<fir::SelectOp>(lowerTy(), op, adaptor, rewriter); 906 return success(); 907 } 908 }; 909 910 /// `fir.load` --> `llvm.load` 911 struct LoadOpConversion : public FIROpConversion<fir::LoadOp> { 912 using FIROpConversion::FIROpConversion; 913 914 mlir::LogicalResult 915 matchAndRewrite(fir::LoadOp load, OpAdaptor adaptor, 916 mlir::ConversionPatternRewriter &rewriter) const override { 917 // fir.box is a special case because it is considered as an ssa values in 918 // fir, but it is lowered as a pointer to a descriptor. So fir.ref<fir.box> 919 // and fir.box end up being the same llvm types and loading a 920 // fir.ref<fir.box> is actually a no op in LLVM. 921 if (load.getType().isa<fir::BoxType>()) { 922 rewriter.replaceOp(load, adaptor.getOperands()[0]); 923 } else { 924 mlir::Type ty = convertType(load.getType()); 925 ArrayRef<NamedAttribute> at = load->getAttrs(); 926 rewriter.replaceOpWithNewOp<mlir::LLVM::LoadOp>( 927 load, ty, adaptor.getOperands(), at); 928 } 929 return success(); 930 } 931 }; 932 933 /// Lower `fir.select_type` to LLVM IR dialect. 934 struct SelectTypeOpConversion : public FIROpConversion<fir::SelectTypeOp> { 935 using FIROpConversion::FIROpConversion; 936 937 mlir::LogicalResult 938 matchAndRewrite(fir::SelectTypeOp select, OpAdaptor adaptor, 939 mlir::ConversionPatternRewriter &rewriter) const override { 940 return rewriter.notifyMatchFailure( 941 select, "fir.select_type codegen is not implemented yet"); 942 } 943 }; 944 945 /// conversion of fir::SelectRankOp to an if-then-else ladder 946 struct SelectRankOpConversion : public FIROpConversion<fir::SelectRankOp> { 947 using FIROpConversion::FIROpConversion; 948 949 mlir::LogicalResult 950 matchAndRewrite(fir::SelectRankOp op, OpAdaptor adaptor, 951 mlir::ConversionPatternRewriter &rewriter) const override { 952 selectMatchAndRewrite<fir::SelectRankOp>(lowerTy(), op, adaptor, rewriter); 953 return success(); 954 } 955 }; 956 957 /// `fir.store` --> `llvm.store` 958 struct StoreOpConversion : public FIROpConversion<fir::StoreOp> { 959 using FIROpConversion::FIROpConversion; 960 961 mlir::LogicalResult 962 matchAndRewrite(fir::StoreOp store, OpAdaptor adaptor, 963 mlir::ConversionPatternRewriter &rewriter) const override { 964 if (store.value().getType().isa<fir::BoxType>()) { 965 // fir.box value is actually in memory, load it first before storing it. 966 mlir::Location loc = store.getLoc(); 967 mlir::Type boxPtrTy = adaptor.getOperands()[0].getType(); 968 auto val = rewriter.create<mlir::LLVM::LoadOp>( 969 loc, boxPtrTy.cast<mlir::LLVM::LLVMPointerType>().getElementType(), 970 adaptor.getOperands()[0]); 971 rewriter.replaceOpWithNewOp<mlir::LLVM::StoreOp>( 972 store, val, adaptor.getOperands()[1]); 973 } else { 974 rewriter.replaceOpWithNewOp<mlir::LLVM::StoreOp>( 975 store, adaptor.getOperands()[0], adaptor.getOperands()[1]); 976 } 977 return success(); 978 } 979 }; 980 981 /// convert to LLVM IR dialect `undef` 982 struct UndefOpConversion : public FIROpConversion<fir::UndefOp> { 983 using FIROpConversion::FIROpConversion; 984 985 mlir::LogicalResult 986 matchAndRewrite(fir::UndefOp undef, OpAdaptor, 987 mlir::ConversionPatternRewriter &rewriter) const override { 988 rewriter.replaceOpWithNewOp<mlir::LLVM::UndefOp>( 989 undef, convertType(undef.getType())); 990 return success(); 991 } 992 }; 993 994 /// `fir.unreachable` --> `llvm.unreachable` 995 struct UnreachableOpConversion : public FIROpConversion<fir::UnreachableOp> { 996 using FIROpConversion::FIROpConversion; 997 998 mlir::LogicalResult 999 matchAndRewrite(fir::UnreachableOp unreach, OpAdaptor adaptor, 1000 mlir::ConversionPatternRewriter &rewriter) const override { 1001 rewriter.replaceOpWithNewOp<mlir::LLVM::UnreachableOp>(unreach); 1002 return success(); 1003 } 1004 }; 1005 1006 struct ZeroOpConversion : public FIROpConversion<fir::ZeroOp> { 1007 using FIROpConversion::FIROpConversion; 1008 1009 mlir::LogicalResult 1010 matchAndRewrite(fir::ZeroOp zero, OpAdaptor, 1011 mlir::ConversionPatternRewriter &rewriter) const override { 1012 auto ty = convertType(zero.getType()); 1013 if (ty.isa<mlir::LLVM::LLVMPointerType>()) { 1014 rewriter.replaceOpWithNewOp<mlir::LLVM::NullOp>(zero, ty); 1015 } else if (ty.isa<mlir::IntegerType>()) { 1016 rewriter.replaceOpWithNewOp<mlir::LLVM::ConstantOp>( 1017 zero, ty, mlir::IntegerAttr::get(zero.getType(), 0)); 1018 } else if (mlir::LLVM::isCompatibleFloatingPointType(ty)) { 1019 rewriter.replaceOpWithNewOp<mlir::LLVM::ConstantOp>( 1020 zero, ty, mlir::FloatAttr::get(zero.getType(), 0.0)); 1021 } else { 1022 // TODO: create ConstantAggregateZero for FIR aggregate/array types. 1023 return rewriter.notifyMatchFailure( 1024 zero, 1025 "conversion of fir.zero with aggregate type not implemented yet"); 1026 } 1027 return success(); 1028 } 1029 }; 1030 1031 // Code shared between insert_value and extract_value Ops. 1032 struct ValueOpCommon { 1033 // Translate the arguments pertaining to any multidimensional array to 1034 // row-major order for LLVM-IR. 1035 static void toRowMajor(SmallVectorImpl<mlir::Attribute> &attrs, 1036 mlir::Type ty) { 1037 assert(ty && "type is null"); 1038 const auto end = attrs.size(); 1039 for (std::remove_const_t<decltype(end)> i = 0; i < end; ++i) { 1040 if (auto seq = ty.dyn_cast<mlir::LLVM::LLVMArrayType>()) { 1041 const auto dim = getDimension(seq); 1042 if (dim > 1) { 1043 auto ub = std::min(i + dim, end); 1044 std::reverse(attrs.begin() + i, attrs.begin() + ub); 1045 i += dim - 1; 1046 } 1047 ty = getArrayElementType(seq); 1048 } else if (auto st = ty.dyn_cast<mlir::LLVM::LLVMStructType>()) { 1049 ty = st.getBody()[attrs[i].cast<mlir::IntegerAttr>().getInt()]; 1050 } else { 1051 llvm_unreachable("index into invalid type"); 1052 } 1053 } 1054 } 1055 1056 static llvm::SmallVector<mlir::Attribute> 1057 collectIndices(mlir::ConversionPatternRewriter &rewriter, 1058 mlir::ArrayAttr arrAttr) { 1059 llvm::SmallVector<mlir::Attribute> attrs; 1060 for (auto i = arrAttr.begin(), e = arrAttr.end(); i != e; ++i) { 1061 if (i->isa<mlir::IntegerAttr>()) { 1062 attrs.push_back(*i); 1063 } else { 1064 auto fieldName = i->cast<mlir::StringAttr>().getValue(); 1065 ++i; 1066 auto ty = i->cast<mlir::TypeAttr>().getValue(); 1067 auto index = ty.cast<fir::RecordType>().getFieldIndex(fieldName); 1068 attrs.push_back(mlir::IntegerAttr::get(rewriter.getI32Type(), index)); 1069 } 1070 } 1071 return attrs; 1072 } 1073 1074 private: 1075 static unsigned getDimension(mlir::LLVM::LLVMArrayType ty) { 1076 unsigned result = 1; 1077 for (auto eleTy = ty.getElementType().dyn_cast<mlir::LLVM::LLVMArrayType>(); 1078 eleTy; 1079 eleTy = eleTy.getElementType().dyn_cast<mlir::LLVM::LLVMArrayType>()) 1080 ++result; 1081 return result; 1082 } 1083 1084 static mlir::Type getArrayElementType(mlir::LLVM::LLVMArrayType ty) { 1085 auto eleTy = ty.getElementType(); 1086 while (auto arrTy = eleTy.dyn_cast<mlir::LLVM::LLVMArrayType>()) 1087 eleTy = arrTy.getElementType(); 1088 return eleTy; 1089 } 1090 }; 1091 1092 /// Extract a subobject value from an ssa-value of aggregate type 1093 struct ExtractValueOpConversion 1094 : public FIROpAndTypeConversion<fir::ExtractValueOp>, 1095 public ValueOpCommon { 1096 using FIROpAndTypeConversion::FIROpAndTypeConversion; 1097 1098 mlir::LogicalResult 1099 doRewrite(fir::ExtractValueOp extractVal, mlir::Type ty, OpAdaptor adaptor, 1100 mlir::ConversionPatternRewriter &rewriter) const override { 1101 auto attrs = collectIndices(rewriter, extractVal.coor()); 1102 toRowMajor(attrs, adaptor.getOperands()[0].getType()); 1103 auto position = mlir::ArrayAttr::get(extractVal.getContext(), attrs); 1104 rewriter.replaceOpWithNewOp<mlir::LLVM::ExtractValueOp>( 1105 extractVal, ty, adaptor.getOperands()[0], position); 1106 return success(); 1107 } 1108 }; 1109 1110 /// InsertValue is the generalized instruction for the composition of new 1111 /// aggregate type values. 1112 struct InsertValueOpConversion 1113 : public FIROpAndTypeConversion<fir::InsertValueOp>, 1114 public ValueOpCommon { 1115 using FIROpAndTypeConversion::FIROpAndTypeConversion; 1116 1117 mlir::LogicalResult 1118 doRewrite(fir::InsertValueOp insertVal, mlir::Type ty, OpAdaptor adaptor, 1119 mlir::ConversionPatternRewriter &rewriter) const override { 1120 auto attrs = collectIndices(rewriter, insertVal.coor()); 1121 toRowMajor(attrs, adaptor.getOperands()[0].getType()); 1122 auto position = mlir::ArrayAttr::get(insertVal.getContext(), attrs); 1123 rewriter.replaceOpWithNewOp<mlir::LLVM::InsertValueOp>( 1124 insertVal, ty, adaptor.getOperands()[0], adaptor.getOperands()[1], 1125 position); 1126 return success(); 1127 } 1128 }; 1129 1130 /// InsertOnRange inserts a value into a sequence over a range of offsets. 1131 struct InsertOnRangeOpConversion 1132 : public FIROpAndTypeConversion<fir::InsertOnRangeOp> { 1133 using FIROpAndTypeConversion::FIROpAndTypeConversion; 1134 1135 // Increments an array of subscripts in a row major fasion. 1136 void incrementSubscripts(const SmallVector<uint64_t> &dims, 1137 SmallVector<uint64_t> &subscripts) const { 1138 for (size_t i = dims.size(); i > 0; --i) { 1139 if (++subscripts[i - 1] < dims[i - 1]) { 1140 return; 1141 } 1142 subscripts[i - 1] = 0; 1143 } 1144 } 1145 1146 mlir::LogicalResult 1147 doRewrite(fir::InsertOnRangeOp range, mlir::Type ty, OpAdaptor adaptor, 1148 mlir::ConversionPatternRewriter &rewriter) const override { 1149 1150 llvm::SmallVector<uint64_t> dims; 1151 auto type = adaptor.getOperands()[0].getType(); 1152 1153 // Iteratively extract the array dimensions from the type. 1154 while (auto t = type.dyn_cast<mlir::LLVM::LLVMArrayType>()) { 1155 dims.push_back(t.getNumElements()); 1156 type = t.getElementType(); 1157 } 1158 1159 SmallVector<uint64_t> lBounds; 1160 SmallVector<uint64_t> uBounds; 1161 1162 // Extract integer value from the attribute 1163 SmallVector<int64_t> coordinates = llvm::to_vector<4>( 1164 llvm::map_range(range.coor(), [](Attribute a) -> int64_t { 1165 return a.cast<IntegerAttr>().getInt(); 1166 })); 1167 1168 // Unzip the upper and lower bound and convert to a row major format. 1169 for (auto i = coordinates.rbegin(), e = coordinates.rend(); i != e; ++i) { 1170 uBounds.push_back(*i++); 1171 lBounds.push_back(*i); 1172 } 1173 1174 auto &subscripts = lBounds; 1175 auto loc = range.getLoc(); 1176 mlir::Value lastOp = adaptor.getOperands()[0]; 1177 mlir::Value insertVal = adaptor.getOperands()[1]; 1178 1179 auto i64Ty = rewriter.getI64Type(); 1180 while (subscripts != uBounds) { 1181 // Convert uint64_t's to Attribute's. 1182 SmallVector<mlir::Attribute> subscriptAttrs; 1183 for (const auto &subscript : subscripts) 1184 subscriptAttrs.push_back(IntegerAttr::get(i64Ty, subscript)); 1185 lastOp = rewriter.create<mlir::LLVM::InsertValueOp>( 1186 loc, ty, lastOp, insertVal, 1187 ArrayAttr::get(range.getContext(), subscriptAttrs)); 1188 1189 incrementSubscripts(dims, subscripts); 1190 } 1191 1192 // Convert uint64_t's to Attribute's. 1193 SmallVector<mlir::Attribute> subscriptAttrs; 1194 for (const auto &subscript : subscripts) 1195 subscriptAttrs.push_back( 1196 IntegerAttr::get(rewriter.getI64Type(), subscript)); 1197 mlir::ArrayRef<mlir::Attribute> arrayRef(subscriptAttrs); 1198 1199 rewriter.replaceOpWithNewOp<mlir::LLVM::InsertValueOp>( 1200 range, ty, lastOp, insertVal, 1201 ArrayAttr::get(range.getContext(), arrayRef)); 1202 1203 return success(); 1204 } 1205 }; 1206 1207 // 1208 // Primitive operations on Complex types 1209 // 1210 1211 /// Generate inline code for complex addition/subtraction 1212 template <typename LLVMOP, typename OPTY> 1213 mlir::LLVM::InsertValueOp complexSum(OPTY sumop, mlir::ValueRange opnds, 1214 mlir::ConversionPatternRewriter &rewriter, 1215 fir::LLVMTypeConverter &lowering) { 1216 mlir::Value a = opnds[0]; 1217 mlir::Value b = opnds[1]; 1218 auto loc = sumop.getLoc(); 1219 auto ctx = sumop.getContext(); 1220 auto c0 = mlir::ArrayAttr::get(ctx, rewriter.getI32IntegerAttr(0)); 1221 auto c1 = mlir::ArrayAttr::get(ctx, rewriter.getI32IntegerAttr(1)); 1222 mlir::Type eleTy = lowering.convertType(getComplexEleTy(sumop.getType())); 1223 mlir::Type ty = lowering.convertType(sumop.getType()); 1224 auto x0 = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, eleTy, a, c0); 1225 auto y0 = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, eleTy, a, c1); 1226 auto x1 = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, eleTy, b, c0); 1227 auto y1 = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, eleTy, b, c1); 1228 auto rx = rewriter.create<LLVMOP>(loc, eleTy, x0, x1); 1229 auto ry = rewriter.create<LLVMOP>(loc, eleTy, y0, y1); 1230 auto r0 = rewriter.create<mlir::LLVM::UndefOp>(loc, ty); 1231 auto r1 = rewriter.create<mlir::LLVM::InsertValueOp>(loc, ty, r0, rx, c0); 1232 return rewriter.create<mlir::LLVM::InsertValueOp>(loc, ty, r1, ry, c1); 1233 } 1234 1235 struct AddcOpConversion : public FIROpConversion<fir::AddcOp> { 1236 using FIROpConversion::FIROpConversion; 1237 1238 mlir::LogicalResult 1239 matchAndRewrite(fir::AddcOp addc, OpAdaptor adaptor, 1240 mlir::ConversionPatternRewriter &rewriter) const override { 1241 // given: (x + iy) + (x' + iy') 1242 // result: (x + x') + i(y + y') 1243 auto r = complexSum<mlir::LLVM::FAddOp>(addc, adaptor.getOperands(), 1244 rewriter, lowerTy()); 1245 rewriter.replaceOp(addc, r.getResult()); 1246 return success(); 1247 } 1248 }; 1249 1250 struct SubcOpConversion : public FIROpConversion<fir::SubcOp> { 1251 using FIROpConversion::FIROpConversion; 1252 1253 mlir::LogicalResult 1254 matchAndRewrite(fir::SubcOp subc, OpAdaptor adaptor, 1255 mlir::ConversionPatternRewriter &rewriter) const override { 1256 // given: (x + iy) - (x' + iy') 1257 // result: (x - x') + i(y - y') 1258 auto r = complexSum<mlir::LLVM::FSubOp>(subc, adaptor.getOperands(), 1259 rewriter, lowerTy()); 1260 rewriter.replaceOp(subc, r.getResult()); 1261 return success(); 1262 } 1263 }; 1264 1265 /// Inlined complex multiply 1266 struct MulcOpConversion : public FIROpConversion<fir::MulcOp> { 1267 using FIROpConversion::FIROpConversion; 1268 1269 mlir::LogicalResult 1270 matchAndRewrite(fir::MulcOp mulc, OpAdaptor adaptor, 1271 mlir::ConversionPatternRewriter &rewriter) const override { 1272 // TODO: Can we use a call to __muldc3 ? 1273 // given: (x + iy) * (x' + iy') 1274 // result: (xx'-yy')+i(xy'+yx') 1275 mlir::Value a = adaptor.getOperands()[0]; 1276 mlir::Value b = adaptor.getOperands()[1]; 1277 auto loc = mulc.getLoc(); 1278 auto *ctx = mulc.getContext(); 1279 auto c0 = mlir::ArrayAttr::get(ctx, rewriter.getI32IntegerAttr(0)); 1280 auto c1 = mlir::ArrayAttr::get(ctx, rewriter.getI32IntegerAttr(1)); 1281 mlir::Type eleTy = convertType(getComplexEleTy(mulc.getType())); 1282 mlir::Type ty = convertType(mulc.getType()); 1283 auto x0 = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, eleTy, a, c0); 1284 auto y0 = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, eleTy, a, c1); 1285 auto x1 = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, eleTy, b, c0); 1286 auto y1 = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, eleTy, b, c1); 1287 auto xx = rewriter.create<mlir::LLVM::FMulOp>(loc, eleTy, x0, x1); 1288 auto yx = rewriter.create<mlir::LLVM::FMulOp>(loc, eleTy, y0, x1); 1289 auto xy = rewriter.create<mlir::LLVM::FMulOp>(loc, eleTy, x0, y1); 1290 auto ri = rewriter.create<mlir::LLVM::FAddOp>(loc, eleTy, xy, yx); 1291 auto yy = rewriter.create<mlir::LLVM::FMulOp>(loc, eleTy, y0, y1); 1292 auto rr = rewriter.create<mlir::LLVM::FSubOp>(loc, eleTy, xx, yy); 1293 auto ra = rewriter.create<mlir::LLVM::UndefOp>(loc, ty); 1294 auto r1 = rewriter.create<mlir::LLVM::InsertValueOp>(loc, ty, ra, rr, c0); 1295 auto r0 = rewriter.create<mlir::LLVM::InsertValueOp>(loc, ty, r1, ri, c1); 1296 rewriter.replaceOp(mulc, r0.getResult()); 1297 return success(); 1298 } 1299 }; 1300 1301 /// Inlined complex division 1302 struct DivcOpConversion : public FIROpConversion<fir::DivcOp> { 1303 using FIROpConversion::FIROpConversion; 1304 1305 mlir::LogicalResult 1306 matchAndRewrite(fir::DivcOp divc, OpAdaptor adaptor, 1307 mlir::ConversionPatternRewriter &rewriter) const override { 1308 // TODO: Can we use a call to __divdc3 instead? 1309 // Just generate inline code for now. 1310 // given: (x + iy) / (x' + iy') 1311 // result: ((xx'+yy')/d) + i((yx'-xy')/d) where d = x'x' + y'y' 1312 mlir::Value a = adaptor.getOperands()[0]; 1313 mlir::Value b = adaptor.getOperands()[1]; 1314 auto loc = divc.getLoc(); 1315 auto *ctx = divc.getContext(); 1316 auto c0 = mlir::ArrayAttr::get(ctx, rewriter.getI32IntegerAttr(0)); 1317 auto c1 = mlir::ArrayAttr::get(ctx, rewriter.getI32IntegerAttr(1)); 1318 mlir::Type eleTy = convertType(getComplexEleTy(divc.getType())); 1319 mlir::Type ty = convertType(divc.getType()); 1320 auto x0 = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, eleTy, a, c0); 1321 auto y0 = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, eleTy, a, c1); 1322 auto x1 = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, eleTy, b, c0); 1323 auto y1 = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, eleTy, b, c1); 1324 auto xx = rewriter.create<mlir::LLVM::FMulOp>(loc, eleTy, x0, x1); 1325 auto x1x1 = rewriter.create<mlir::LLVM::FMulOp>(loc, eleTy, x1, x1); 1326 auto yx = rewriter.create<mlir::LLVM::FMulOp>(loc, eleTy, y0, x1); 1327 auto xy = rewriter.create<mlir::LLVM::FMulOp>(loc, eleTy, x0, y1); 1328 auto yy = rewriter.create<mlir::LLVM::FMulOp>(loc, eleTy, y0, y1); 1329 auto y1y1 = rewriter.create<mlir::LLVM::FMulOp>(loc, eleTy, y1, y1); 1330 auto d = rewriter.create<mlir::LLVM::FAddOp>(loc, eleTy, x1x1, y1y1); 1331 auto rrn = rewriter.create<mlir::LLVM::FAddOp>(loc, eleTy, xx, yy); 1332 auto rin = rewriter.create<mlir::LLVM::FSubOp>(loc, eleTy, yx, xy); 1333 auto rr = rewriter.create<mlir::LLVM::FDivOp>(loc, eleTy, rrn, d); 1334 auto ri = rewriter.create<mlir::LLVM::FDivOp>(loc, eleTy, rin, d); 1335 auto ra = rewriter.create<mlir::LLVM::UndefOp>(loc, ty); 1336 auto r1 = rewriter.create<mlir::LLVM::InsertValueOp>(loc, ty, ra, rr, c0); 1337 auto r0 = rewriter.create<mlir::LLVM::InsertValueOp>(loc, ty, r1, ri, c1); 1338 rewriter.replaceOp(divc, r0.getResult()); 1339 return success(); 1340 } 1341 }; 1342 1343 /// Inlined complex negation 1344 struct NegcOpConversion : public FIROpConversion<fir::NegcOp> { 1345 using FIROpConversion::FIROpConversion; 1346 1347 mlir::LogicalResult 1348 matchAndRewrite(fir::NegcOp neg, OpAdaptor adaptor, 1349 mlir::ConversionPatternRewriter &rewriter) const override { 1350 // given: -(x + iy) 1351 // result: -x - iy 1352 auto *ctxt = neg.getContext(); 1353 auto eleTy = convertType(getComplexEleTy(neg.getType())); 1354 auto ty = convertType(neg.getType()); 1355 auto loc = neg.getLoc(); 1356 mlir::Value o0 = adaptor.getOperands()[0]; 1357 auto c0 = mlir::ArrayAttr::get(ctxt, rewriter.getI32IntegerAttr(0)); 1358 auto c1 = mlir::ArrayAttr::get(ctxt, rewriter.getI32IntegerAttr(1)); 1359 auto rp = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, eleTy, o0, c0); 1360 auto ip = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, eleTy, o0, c1); 1361 auto nrp = rewriter.create<mlir::LLVM::FNegOp>(loc, eleTy, rp); 1362 auto nip = rewriter.create<mlir::LLVM::FNegOp>(loc, eleTy, ip); 1363 auto r = rewriter.create<mlir::LLVM::InsertValueOp>(loc, ty, o0, nrp, c0); 1364 rewriter.replaceOpWithNewOp<mlir::LLVM::InsertValueOp>(neg, ty, r, nip, c1); 1365 return success(); 1366 } 1367 }; 1368 1369 /// `fir.is_present` --> 1370 /// ``` 1371 /// %0 = llvm.mlir.constant(0 : i64) 1372 /// %1 = llvm.ptrtoint %0 1373 /// %2 = llvm.icmp "ne" %1, %0 : i64 1374 /// ``` 1375 struct IsPresentOpConversion : public FIROpConversion<fir::IsPresentOp> { 1376 using FIROpConversion::FIROpConversion; 1377 1378 mlir::LogicalResult 1379 matchAndRewrite(fir::IsPresentOp isPresent, OpAdaptor adaptor, 1380 mlir::ConversionPatternRewriter &rewriter) const override { 1381 mlir::Type idxTy = lowerTy().indexType(); 1382 mlir::Location loc = isPresent.getLoc(); 1383 auto ptr = adaptor.getOperands()[0]; 1384 1385 if (isPresent.val().getType().isa<fir::BoxCharType>()) { 1386 auto structTy = ptr.getType().cast<mlir::LLVM::LLVMStructType>(); 1387 assert(!structTy.isOpaque() && !structTy.getBody().empty()); 1388 1389 mlir::Type ty = structTy.getBody()[0]; 1390 mlir::MLIRContext *ctx = isPresent.getContext(); 1391 auto c0 = mlir::ArrayAttr::get(ctx, rewriter.getI32IntegerAttr(0)); 1392 ptr = rewriter.create<mlir::LLVM::ExtractValueOp>(loc, ty, ptr, c0); 1393 } 1394 mlir::LLVM::ConstantOp c0 = 1395 genConstantIndex(isPresent.getLoc(), idxTy, rewriter, 0); 1396 auto addr = rewriter.create<mlir::LLVM::PtrToIntOp>(loc, idxTy, ptr); 1397 rewriter.replaceOpWithNewOp<mlir::LLVM::ICmpOp>( 1398 isPresent, mlir::LLVM::ICmpPredicate::ne, addr, c0); 1399 1400 return success(); 1401 } 1402 }; 1403 1404 /// Convert `!fir.emboxchar<!fir.char<KIND, ?>, #n>` into a sequence of 1405 /// instructions that generate `!llvm.struct<(ptr<ik>, i64)>`. The 1st element 1406 /// in this struct is a pointer. Its type is determined from `KIND`. The 2nd 1407 /// element is the length of the character buffer (`#n`). 1408 struct EmboxCharOpConversion : public FIROpConversion<fir::EmboxCharOp> { 1409 using FIROpConversion::FIROpConversion; 1410 1411 mlir::LogicalResult 1412 matchAndRewrite(fir::EmboxCharOp emboxChar, OpAdaptor adaptor, 1413 mlir::ConversionPatternRewriter &rewriter) const override { 1414 mlir::ValueRange operands = adaptor.getOperands(); 1415 MLIRContext *ctx = emboxChar.getContext(); 1416 1417 mlir::Value charBuffer = operands[0]; 1418 mlir::Value charBufferLen = operands[1]; 1419 1420 mlir::Location loc = emboxChar.getLoc(); 1421 mlir::Type llvmStructTy = convertType(emboxChar.getType()); 1422 auto llvmStruct = rewriter.create<mlir::LLVM::UndefOp>(loc, llvmStructTy); 1423 1424 mlir::Type lenTy = 1425 llvmStructTy.cast<mlir::LLVM::LLVMStructType>().getBody()[1]; 1426 mlir::Value lenAfterCast = integerCast(loc, rewriter, lenTy, charBufferLen); 1427 1428 auto c0 = mlir::ArrayAttr::get(ctx, rewriter.getI32IntegerAttr(0)); 1429 auto c1 = mlir::ArrayAttr::get(ctx, rewriter.getI32IntegerAttr(1)); 1430 auto insertBufferOp = rewriter.create<mlir::LLVM::InsertValueOp>( 1431 loc, llvmStructTy, llvmStruct, charBuffer, c0); 1432 rewriter.replaceOpWithNewOp<mlir::LLVM::InsertValueOp>( 1433 emboxChar, llvmStructTy, insertBufferOp, lenAfterCast, c1); 1434 1435 return success(); 1436 } 1437 }; 1438 } // namespace 1439 1440 namespace { 1441 /// Convert FIR dialect to LLVM dialect 1442 /// 1443 /// This pass lowers all FIR dialect operations to LLVM IR dialect. An 1444 /// MLIR pass is used to lower residual Std dialect to LLVM IR dialect. 1445 /// 1446 /// This pass is not complete yet. We are upstreaming it in small patches. 1447 class FIRToLLVMLowering : public fir::FIRToLLVMLoweringBase<FIRToLLVMLowering> { 1448 public: 1449 mlir::ModuleOp getModule() { return getOperation(); } 1450 1451 void runOnOperation() override final { 1452 auto mod = getModule(); 1453 if (!forcedTargetTriple.empty()) { 1454 fir::setTargetTriple(mod, forcedTargetTriple); 1455 } 1456 1457 auto *context = getModule().getContext(); 1458 fir::LLVMTypeConverter typeConverter{getModule()}; 1459 mlir::OwningRewritePatternList pattern(context); 1460 pattern.insert< 1461 AbsentOpConversion, AddcOpConversion, AddrOfOpConversion, 1462 AllocaOpConversion, BoxAddrOpConversion, BoxDimsOpConversion, 1463 BoxEleSizeOpConversion, BoxIsAllocOpConversion, BoxIsArrayOpConversion, 1464 BoxIsPtrOpConversion, BoxRankOpConversion, CallOpConversion, 1465 ConvertOpConversion, DispatchOpConversion, DispatchTableOpConversion, 1466 DTEntryOpConversion, DivcOpConversion, EmboxCharOpConversion, 1467 ExtractValueOpConversion, HasValueOpConversion, GlobalOpConversion, 1468 InsertOnRangeOpConversion, InsertValueOpConversion, 1469 IsPresentOpConversion, LoadOpConversion, NegcOpConversion, 1470 MulcOpConversion, SelectCaseOpConversion, SelectOpConversion, 1471 SelectRankOpConversion, SelectTypeOpConversion, StoreOpConversion, 1472 SubcOpConversion, UndefOpConversion, UnreachableOpConversion, 1473 ZeroOpConversion>(typeConverter); 1474 mlir::populateStdToLLVMConversionPatterns(typeConverter, pattern); 1475 mlir::arith::populateArithmeticToLLVMConversionPatterns(typeConverter, 1476 pattern); 1477 mlir::ConversionTarget target{*context}; 1478 target.addLegalDialect<mlir::LLVM::LLVMDialect>(); 1479 1480 // required NOPs for applying a full conversion 1481 target.addLegalOp<mlir::ModuleOp>(); 1482 1483 // apply the patterns 1484 if (mlir::failed(mlir::applyFullConversion(getModule(), target, 1485 std::move(pattern)))) { 1486 signalPassFailure(); 1487 } 1488 } 1489 }; 1490 } // namespace 1491 1492 std::unique_ptr<mlir::Pass> fir::createFIRToLLVMPass() { 1493 return std::make_unique<FIRToLLVMLowering>(); 1494 } 1495