1 ////===- SampleProfileLoadBaseImpl.h - Profile loader base impl --*- C++-*-===// 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 /// \file 10 /// This file provides the interface for the sampled PGO profile loader base 11 /// implementation. 12 // 13 //===----------------------------------------------------------------------===// 14 15 #ifndef LLVM_TRANSFORMS_UTILS_SAMPLEPROFILELOADERBASEIMPL_H 16 #define LLVM_TRANSFORMS_UTILS_SAMPLEPROFILELOADERBASEIMPL_H 17 18 #include "llvm/ADT/ArrayRef.h" 19 #include "llvm/ADT/DenseMap.h" 20 #include "llvm/ADT/DenseSet.h" 21 #include "llvm/ADT/IntrusiveRefCntPtr.h" 22 #include "llvm/ADT/SmallPtrSet.h" 23 #include "llvm/ADT/SmallSet.h" 24 #include "llvm/ADT/SmallVector.h" 25 #include "llvm/Analysis/LoopInfo.h" 26 #include "llvm/Analysis/OptimizationRemarkEmitter.h" 27 #include "llvm/Analysis/PostDominators.h" 28 #include "llvm/IR/BasicBlock.h" 29 #include "llvm/IR/CFG.h" 30 #include "llvm/IR/DebugInfoMetadata.h" 31 #include "llvm/IR/DebugLoc.h" 32 #include "llvm/IR/Dominators.h" 33 #include "llvm/IR/Function.h" 34 #include "llvm/IR/Instruction.h" 35 #include "llvm/IR/Instructions.h" 36 #include "llvm/IR/Module.h" 37 #include "llvm/IR/PseudoProbe.h" 38 #include "llvm/ProfileData/SampleProf.h" 39 #include "llvm/ProfileData/SampleProfReader.h" 40 #include "llvm/Support/CommandLine.h" 41 #include "llvm/Support/GenericDomTree.h" 42 #include "llvm/Support/raw_ostream.h" 43 #include "llvm/Transforms/Utils/SampleProfileInference.h" 44 #include "llvm/Transforms/Utils/SampleProfileLoaderBaseUtil.h" 45 46 namespace llvm { 47 using namespace sampleprof; 48 using namespace sampleprofutil; 49 using ProfileCount = Function::ProfileCount; 50 51 namespace vfs { 52 class FileSystem; 53 } // namespace vfs 54 55 #define DEBUG_TYPE "sample-profile-impl" 56 57 namespace afdo_detail { 58 59 template <typename BlockT> struct IRTraits; 60 template <> struct IRTraits<BasicBlock> { 61 using InstructionT = Instruction; 62 using BasicBlockT = BasicBlock; 63 using FunctionT = Function; 64 using BlockFrequencyInfoT = BlockFrequencyInfo; 65 using LoopT = Loop; 66 using LoopInfoPtrT = std::unique_ptr<LoopInfo>; 67 using DominatorTreePtrT = std::unique_ptr<DominatorTree>; 68 using PostDominatorTreeT = PostDominatorTree; 69 using PostDominatorTreePtrT = std::unique_ptr<PostDominatorTree>; 70 using OptRemarkEmitterT = OptimizationRemarkEmitter; 71 using OptRemarkAnalysisT = OptimizationRemarkAnalysis; 72 using PredRangeT = pred_range; 73 using SuccRangeT = succ_range; 74 static Function &getFunction(Function &F) { return F; } 75 static const BasicBlock *getEntryBB(const Function *F) { 76 return &F->getEntryBlock(); 77 } 78 static pred_range getPredecessors(BasicBlock *BB) { return predecessors(BB); } 79 static succ_range getSuccessors(BasicBlock *BB) { return successors(BB); } 80 }; 81 82 } // end namespace afdo_detail 83 84 // This class serves sample counts correlation for SampleProfileLoader by 85 // analyzing pseudo probes and their function descriptors injected by 86 // SampleProfileProber. 87 class PseudoProbeManager { 88 DenseMap<uint64_t, PseudoProbeDescriptor> GUIDToProbeDescMap; 89 90 public: 91 PseudoProbeManager(const Module &M) { 92 if (NamedMDNode *FuncInfo = 93 M.getNamedMetadata(PseudoProbeDescMetadataName)) { 94 for (const auto *Operand : FuncInfo->operands()) { 95 const auto *MD = cast<MDNode>(Operand); 96 auto GUID = mdconst::dyn_extract<ConstantInt>(MD->getOperand(0)) 97 ->getZExtValue(); 98 auto Hash = mdconst::dyn_extract<ConstantInt>(MD->getOperand(1)) 99 ->getZExtValue(); 100 GUIDToProbeDescMap.try_emplace(GUID, PseudoProbeDescriptor(GUID, Hash)); 101 } 102 } 103 } 104 105 const PseudoProbeDescriptor *getDesc(uint64_t GUID) const { 106 auto I = GUIDToProbeDescMap.find(GUID); 107 return I == GUIDToProbeDescMap.end() ? nullptr : &I->second; 108 } 109 110 const PseudoProbeDescriptor *getDesc(StringRef FProfileName) const { 111 return getDesc(Function::getGUID(FProfileName)); 112 } 113 114 const PseudoProbeDescriptor *getDesc(const Function &F) const { 115 return getDesc(Function::getGUID(FunctionSamples::getCanonicalFnName(F))); 116 } 117 118 bool profileIsHashMismatched(const PseudoProbeDescriptor &FuncDesc, 119 const FunctionSamples &Samples) const { 120 return FuncDesc.getFunctionHash() != Samples.getFunctionHash(); 121 } 122 123 bool moduleIsProbed(const Module &M) const { 124 return M.getNamedMetadata(PseudoProbeDescMetadataName); 125 } 126 127 bool profileIsValid(const Function &F, const FunctionSamples &Samples) const { 128 const auto *Desc = getDesc(F); 129 if (!Desc) { 130 LLVM_DEBUG(dbgs() << "Probe descriptor missing for Function " 131 << F.getName() << "\n"); 132 return false; 133 } 134 if (Desc->getFunctionHash() != Samples.getFunctionHash()) { 135 LLVM_DEBUG(dbgs() << "Hash mismatch for Function " << F.getName() 136 << "\n"); 137 return false; 138 } 139 return true; 140 } 141 }; 142 143 144 145 extern cl::opt<bool> SampleProfileUseProfi; 146 147 template <typename FT> class SampleProfileLoaderBaseImpl { 148 public: 149 SampleProfileLoaderBaseImpl(std::string Name, std::string RemapName, 150 IntrusiveRefCntPtr<vfs::FileSystem> FS) 151 : Filename(Name), RemappingFilename(RemapName), FS(std::move(FS)) {} 152 void dump() { Reader->dump(); } 153 154 using NodeRef = typename GraphTraits<FT *>::NodeRef; 155 using BT = std::remove_pointer_t<NodeRef>; 156 using InstructionT = typename afdo_detail::IRTraits<BT>::InstructionT; 157 using BasicBlockT = typename afdo_detail::IRTraits<BT>::BasicBlockT; 158 using BlockFrequencyInfoT = 159 typename afdo_detail::IRTraits<BT>::BlockFrequencyInfoT; 160 using FunctionT = typename afdo_detail::IRTraits<BT>::FunctionT; 161 using LoopT = typename afdo_detail::IRTraits<BT>::LoopT; 162 using LoopInfoPtrT = typename afdo_detail::IRTraits<BT>::LoopInfoPtrT; 163 using DominatorTreePtrT = 164 typename afdo_detail::IRTraits<BT>::DominatorTreePtrT; 165 using PostDominatorTreePtrT = 166 typename afdo_detail::IRTraits<BT>::PostDominatorTreePtrT; 167 using PostDominatorTreeT = 168 typename afdo_detail::IRTraits<BT>::PostDominatorTreeT; 169 using OptRemarkEmitterT = 170 typename afdo_detail::IRTraits<BT>::OptRemarkEmitterT; 171 using OptRemarkAnalysisT = 172 typename afdo_detail::IRTraits<BT>::OptRemarkAnalysisT; 173 using PredRangeT = typename afdo_detail::IRTraits<BT>::PredRangeT; 174 using SuccRangeT = typename afdo_detail::IRTraits<BT>::SuccRangeT; 175 176 using BlockWeightMap = DenseMap<const BasicBlockT *, uint64_t>; 177 using EquivalenceClassMap = 178 DenseMap<const BasicBlockT *, const BasicBlockT *>; 179 using Edge = std::pair<const BasicBlockT *, const BasicBlockT *>; 180 using EdgeWeightMap = DenseMap<Edge, uint64_t>; 181 using BlockEdgeMap = 182 DenseMap<const BasicBlockT *, SmallVector<const BasicBlockT *, 8>>; 183 184 protected: 185 ~SampleProfileLoaderBaseImpl() = default; 186 friend class SampleCoverageTracker; 187 188 Function &getFunction(FunctionT &F) { 189 return afdo_detail::IRTraits<BT>::getFunction(F); 190 } 191 const BasicBlockT *getEntryBB(const FunctionT *F) { 192 return afdo_detail::IRTraits<BT>::getEntryBB(F); 193 } 194 PredRangeT getPredecessors(BasicBlockT *BB) { 195 return afdo_detail::IRTraits<BT>::getPredecessors(BB); 196 } 197 SuccRangeT getSuccessors(BasicBlockT *BB) { 198 return afdo_detail::IRTraits<BT>::getSuccessors(BB); 199 } 200 201 unsigned getFunctionLoc(FunctionT &Func); 202 virtual ErrorOr<uint64_t> getInstWeight(const InstructionT &Inst); 203 ErrorOr<uint64_t> getInstWeightImpl(const InstructionT &Inst); 204 virtual ErrorOr<uint64_t> getProbeWeight(const InstructionT &Inst); 205 ErrorOr<uint64_t> getBlockWeight(const BasicBlockT *BB); 206 mutable DenseMap<const DILocation *, const FunctionSamples *> 207 DILocation2SampleMap; 208 virtual const FunctionSamples * 209 findFunctionSamples(const InstructionT &I) const; 210 void printEdgeWeight(raw_ostream &OS, Edge E); 211 void printBlockWeight(raw_ostream &OS, const BasicBlockT *BB) const; 212 void printBlockEquivalence(raw_ostream &OS, const BasicBlockT *BB); 213 bool computeBlockWeights(FunctionT &F); 214 void findEquivalenceClasses(FunctionT &F); 215 void findEquivalencesFor(BasicBlockT *BB1, 216 ArrayRef<BasicBlockT *> Descendants, 217 PostDominatorTreeT *DomTree); 218 void propagateWeights(FunctionT &F); 219 void applyProfi(FunctionT &F, BlockEdgeMap &Successors, 220 BlockWeightMap &SampleBlockWeights, 221 BlockWeightMap &BlockWeights, EdgeWeightMap &EdgeWeights); 222 uint64_t visitEdge(Edge E, unsigned *NumUnknownEdges, Edge *UnknownEdge); 223 void buildEdges(FunctionT &F); 224 bool propagateThroughEdges(FunctionT &F, bool UpdateBlockCount); 225 void clearFunctionData(bool ResetDT = true); 226 void computeDominanceAndLoopInfo(FunctionT &F); 227 bool 228 computeAndPropagateWeights(FunctionT &F, 229 const DenseSet<GlobalValue::GUID> &InlinedGUIDs); 230 void initWeightPropagation(FunctionT &F, 231 const DenseSet<GlobalValue::GUID> &InlinedGUIDs); 232 void 233 finalizeWeightPropagation(FunctionT &F, 234 const DenseSet<GlobalValue::GUID> &InlinedGUIDs); 235 void emitCoverageRemarks(FunctionT &F); 236 237 /// Map basic blocks to their computed weights. 238 /// 239 /// The weight of a basic block is defined to be the maximum 240 /// of all the instruction weights in that block. 241 BlockWeightMap BlockWeights; 242 243 /// Map edges to their computed weights. 244 /// 245 /// Edge weights are computed by propagating basic block weights in 246 /// SampleProfile::propagateWeights. 247 EdgeWeightMap EdgeWeights; 248 249 /// Set of visited blocks during propagation. 250 SmallPtrSet<const BasicBlockT *, 32> VisitedBlocks; 251 252 /// Set of visited edges during propagation. 253 SmallSet<Edge, 32> VisitedEdges; 254 255 /// Equivalence classes for block weights. 256 /// 257 /// Two blocks BB1 and BB2 are in the same equivalence class if they 258 /// dominate and post-dominate each other, and they are in the same loop 259 /// nest. When this happens, the two blocks are guaranteed to execute 260 /// the same number of times. 261 EquivalenceClassMap EquivalenceClass; 262 263 /// Dominance, post-dominance and loop information. 264 DominatorTreePtrT DT; 265 PostDominatorTreePtrT PDT; 266 LoopInfoPtrT LI; 267 268 /// Predecessors for each basic block in the CFG. 269 BlockEdgeMap Predecessors; 270 271 /// Successors for each basic block in the CFG. 272 BlockEdgeMap Successors; 273 274 /// Profile coverage tracker. 275 SampleCoverageTracker CoverageTracker; 276 277 /// Profile reader object. 278 std::unique_ptr<SampleProfileReader> Reader; 279 280 /// Synthetic samples created by duplicating the samples of inlined functions 281 /// from the original profile as if they were top level sample profiles. 282 /// Use std::map because insertion may happen while its content is referenced. 283 std::map<SampleContext, FunctionSamples> OutlineFunctionSamples; 284 285 // A pseudo probe helper to correlate the imported sample counts. 286 std::unique_ptr<PseudoProbeManager> ProbeManager; 287 288 /// Samples collected for the body of this function. 289 FunctionSamples *Samples = nullptr; 290 291 /// Name of the profile file to load. 292 std::string Filename; 293 294 /// Name of the profile remapping file to load. 295 std::string RemappingFilename; 296 297 /// VirtualFileSystem to load profile files from. 298 IntrusiveRefCntPtr<vfs::FileSystem> FS; 299 300 /// Profile Summary Info computed from sample profile. 301 ProfileSummaryInfo *PSI = nullptr; 302 303 /// Optimization Remark Emitter used to emit diagnostic remarks. 304 OptRemarkEmitterT *ORE = nullptr; 305 }; 306 307 /// Clear all the per-function data used to load samples and propagate weights. 308 template <typename BT> 309 void SampleProfileLoaderBaseImpl<BT>::clearFunctionData(bool ResetDT) { 310 BlockWeights.clear(); 311 EdgeWeights.clear(); 312 VisitedBlocks.clear(); 313 VisitedEdges.clear(); 314 EquivalenceClass.clear(); 315 if (ResetDT) { 316 DT = nullptr; 317 PDT = nullptr; 318 LI = nullptr; 319 } 320 Predecessors.clear(); 321 Successors.clear(); 322 CoverageTracker.clear(); 323 } 324 325 #ifndef NDEBUG 326 /// Print the weight of edge \p E on stream \p OS. 327 /// 328 /// \param OS Stream to emit the output to. 329 /// \param E Edge to print. 330 template <typename BT> 331 void SampleProfileLoaderBaseImpl<BT>::printEdgeWeight(raw_ostream &OS, Edge E) { 332 OS << "weight[" << E.first->getName() << "->" << E.second->getName() 333 << "]: " << EdgeWeights[E] << "\n"; 334 } 335 336 /// Print the equivalence class of block \p BB on stream \p OS. 337 /// 338 /// \param OS Stream to emit the output to. 339 /// \param BB Block to print. 340 template <typename BT> 341 void SampleProfileLoaderBaseImpl<BT>::printBlockEquivalence( 342 raw_ostream &OS, const BasicBlockT *BB) { 343 const BasicBlockT *Equiv = EquivalenceClass[BB]; 344 OS << "equivalence[" << BB->getName() 345 << "]: " << ((Equiv) ? EquivalenceClass[BB]->getName() : "NONE") << "\n"; 346 } 347 348 /// Print the weight of block \p BB on stream \p OS. 349 /// 350 /// \param OS Stream to emit the output to. 351 /// \param BB Block to print. 352 template <typename BT> 353 void SampleProfileLoaderBaseImpl<BT>::printBlockWeight( 354 raw_ostream &OS, const BasicBlockT *BB) const { 355 const auto &I = BlockWeights.find(BB); 356 uint64_t W = (I == BlockWeights.end() ? 0 : I->second); 357 OS << "weight[" << BB->getName() << "]: " << W << "\n"; 358 } 359 #endif 360 361 /// Get the weight for an instruction. 362 /// 363 /// The "weight" of an instruction \p Inst is the number of samples 364 /// collected on that instruction at runtime. To retrieve it, we 365 /// need to compute the line number of \p Inst relative to the start of its 366 /// function. We use HeaderLineno to compute the offset. We then 367 /// look up the samples collected for \p Inst using BodySamples. 368 /// 369 /// \param Inst Instruction to query. 370 /// 371 /// \returns the weight of \p Inst. 372 template <typename BT> 373 ErrorOr<uint64_t> 374 SampleProfileLoaderBaseImpl<BT>::getInstWeight(const InstructionT &Inst) { 375 if (FunctionSamples::ProfileIsProbeBased) 376 return getProbeWeight(Inst); 377 return getInstWeightImpl(Inst); 378 } 379 380 template <typename BT> 381 ErrorOr<uint64_t> 382 SampleProfileLoaderBaseImpl<BT>::getInstWeightImpl(const InstructionT &Inst) { 383 const FunctionSamples *FS = findFunctionSamples(Inst); 384 if (!FS) 385 return std::error_code(); 386 387 const DebugLoc &DLoc = Inst.getDebugLoc(); 388 if (!DLoc) 389 return std::error_code(); 390 391 const DILocation *DIL = DLoc; 392 uint32_t LineOffset = FunctionSamples::getOffset(DIL); 393 uint32_t Discriminator; 394 if (EnableFSDiscriminator) 395 Discriminator = DIL->getDiscriminator(); 396 else 397 Discriminator = DIL->getBaseDiscriminator(); 398 399 ErrorOr<uint64_t> R = FS->findSamplesAt(LineOffset, Discriminator); 400 if (R) { 401 bool FirstMark = 402 CoverageTracker.markSamplesUsed(FS, LineOffset, Discriminator, R.get()); 403 if (FirstMark) { 404 ORE->emit([&]() { 405 OptRemarkAnalysisT Remark(DEBUG_TYPE, "AppliedSamples", &Inst); 406 Remark << "Applied " << ore::NV("NumSamples", *R); 407 Remark << " samples from profile (offset: "; 408 Remark << ore::NV("LineOffset", LineOffset); 409 if (Discriminator) { 410 Remark << "."; 411 Remark << ore::NV("Discriminator", Discriminator); 412 } 413 Remark << ")"; 414 return Remark; 415 }); 416 } 417 LLVM_DEBUG(dbgs() << " " << DLoc.getLine() << "." << Discriminator << ":" 418 << Inst << " (line offset: " << LineOffset << "." 419 << Discriminator << " - weight: " << R.get() << ")\n"); 420 } 421 return R; 422 } 423 424 // Here use error_code to represent: 1) The dangling probe. 2) Ignore the weight 425 // of non-probe instruction. So if all instructions of the BB give error_code, 426 // tell the inference algorithm to infer the BB weight. 427 template <typename BT> 428 ErrorOr<uint64_t> 429 SampleProfileLoaderBaseImpl<BT>::getProbeWeight(const InstructionT &Inst) { 430 assert(FunctionSamples::ProfileIsProbeBased && 431 "Profile is not pseudo probe based"); 432 std::optional<PseudoProbe> Probe = extractProbe(Inst); 433 // Ignore the non-probe instruction. If none of the instruction in the BB is 434 // probe, we choose to infer the BB's weight. 435 if (!Probe) 436 return std::error_code(); 437 438 const FunctionSamples *FS = findFunctionSamples(Inst); 439 // If none of the instruction has FunctionSample, we choose to return zero 440 // value sample to indicate the BB is cold. This could happen when the 441 // instruction is from inlinee and no profile data is found. 442 // FIXME: This should not be affected by the source drift issue as 1) if the 443 // newly added function is top-level inliner, it won't match the CFG checksum 444 // in the function profile or 2) if it's the inlinee, the inlinee should have 445 // a profile, otherwise it wouldn't be inlined. For non-probe based profile, 446 // we can improve it by adding a switch for profile-sample-block-accurate for 447 // block level counts in the future. 448 if (!FS) 449 return 0; 450 451 auto R = FS->findSamplesAt(Probe->Id, Probe->Discriminator); 452 if (R) { 453 uint64_t Samples = R.get() * Probe->Factor; 454 bool FirstMark = CoverageTracker.markSamplesUsed(FS, Probe->Id, 0, Samples); 455 if (FirstMark) { 456 ORE->emit([&]() { 457 OptRemarkAnalysisT Remark(DEBUG_TYPE, "AppliedSamples", &Inst); 458 Remark << "Applied " << ore::NV("NumSamples", Samples); 459 Remark << " samples from profile (ProbeId="; 460 Remark << ore::NV("ProbeId", Probe->Id); 461 if (Probe->Discriminator) { 462 Remark << "."; 463 Remark << ore::NV("Discriminator", Probe->Discriminator); 464 } 465 Remark << ", Factor="; 466 Remark << ore::NV("Factor", Probe->Factor); 467 Remark << ", OriginalSamples="; 468 Remark << ore::NV("OriginalSamples", R.get()); 469 Remark << ")"; 470 return Remark; 471 }); 472 } 473 LLVM_DEBUG({dbgs() << " " << Probe->Id; 474 if (Probe->Discriminator) 475 dbgs() << "." << Probe->Discriminator; 476 dbgs() << ":" << Inst << " - weight: " << R.get() 477 << " - factor: " << format("%0.2f", Probe->Factor) << ")\n";}); 478 return Samples; 479 } 480 return R; 481 } 482 483 /// Compute the weight of a basic block. 484 /// 485 /// The weight of basic block \p BB is the maximum weight of all the 486 /// instructions in BB. 487 /// 488 /// \param BB The basic block to query. 489 /// 490 /// \returns the weight for \p BB. 491 template <typename BT> 492 ErrorOr<uint64_t> 493 SampleProfileLoaderBaseImpl<BT>::getBlockWeight(const BasicBlockT *BB) { 494 uint64_t Max = 0; 495 bool HasWeight = false; 496 for (auto &I : *BB) { 497 const ErrorOr<uint64_t> &R = getInstWeight(I); 498 if (R) { 499 Max = std::max(Max, R.get()); 500 HasWeight = true; 501 } 502 } 503 return HasWeight ? ErrorOr<uint64_t>(Max) : std::error_code(); 504 } 505 506 /// Compute and store the weights of every basic block. 507 /// 508 /// This populates the BlockWeights map by computing 509 /// the weights of every basic block in the CFG. 510 /// 511 /// \param F The function to query. 512 template <typename BT> 513 bool SampleProfileLoaderBaseImpl<BT>::computeBlockWeights(FunctionT &F) { 514 bool Changed = false; 515 LLVM_DEBUG(dbgs() << "Block weights\n"); 516 for (const auto &BB : F) { 517 ErrorOr<uint64_t> Weight = getBlockWeight(&BB); 518 if (Weight) { 519 BlockWeights[&BB] = Weight.get(); 520 VisitedBlocks.insert(&BB); 521 Changed = true; 522 } 523 LLVM_DEBUG(printBlockWeight(dbgs(), &BB)); 524 } 525 526 return Changed; 527 } 528 529 /// Get the FunctionSamples for an instruction. 530 /// 531 /// The FunctionSamples of an instruction \p Inst is the inlined instance 532 /// in which that instruction is coming from. We traverse the inline stack 533 /// of that instruction, and match it with the tree nodes in the profile. 534 /// 535 /// \param Inst Instruction to query. 536 /// 537 /// \returns the FunctionSamples pointer to the inlined instance. 538 template <typename BT> 539 const FunctionSamples *SampleProfileLoaderBaseImpl<BT>::findFunctionSamples( 540 const InstructionT &Inst) const { 541 const DILocation *DIL = Inst.getDebugLoc(); 542 if (!DIL) 543 return Samples; 544 545 auto it = DILocation2SampleMap.try_emplace(DIL, nullptr); 546 if (it.second) { 547 it.first->second = Samples->findFunctionSamples(DIL, Reader->getRemapper()); 548 } 549 return it.first->second; 550 } 551 552 /// Find equivalence classes for the given block. 553 /// 554 /// This finds all the blocks that are guaranteed to execute the same 555 /// number of times as \p BB1. To do this, it traverses all the 556 /// descendants of \p BB1 in the dominator or post-dominator tree. 557 /// 558 /// A block BB2 will be in the same equivalence class as \p BB1 if 559 /// the following holds: 560 /// 561 /// 1- \p BB1 is a descendant of BB2 in the opposite tree. So, if BB2 562 /// is a descendant of \p BB1 in the dominator tree, then BB2 should 563 /// dominate BB1 in the post-dominator tree. 564 /// 565 /// 2- Both BB2 and \p BB1 must be in the same loop. 566 /// 567 /// For every block BB2 that meets those two requirements, we set BB2's 568 /// equivalence class to \p BB1. 569 /// 570 /// \param BB1 Block to check. 571 /// \param Descendants Descendants of \p BB1 in either the dom or pdom tree. 572 /// \param DomTree Opposite dominator tree. If \p Descendants is filled 573 /// with blocks from \p BB1's dominator tree, then 574 /// this is the post-dominator tree, and vice versa. 575 template <typename BT> 576 void SampleProfileLoaderBaseImpl<BT>::findEquivalencesFor( 577 BasicBlockT *BB1, ArrayRef<BasicBlockT *> Descendants, 578 PostDominatorTreeT *DomTree) { 579 const BasicBlockT *EC = EquivalenceClass[BB1]; 580 uint64_t Weight = BlockWeights[EC]; 581 for (const auto *BB2 : Descendants) { 582 bool IsDomParent = DomTree->dominates(BB2, BB1); 583 bool IsInSameLoop = LI->getLoopFor(BB1) == LI->getLoopFor(BB2); 584 if (BB1 != BB2 && IsDomParent && IsInSameLoop) { 585 EquivalenceClass[BB2] = EC; 586 // If BB2 is visited, then the entire EC should be marked as visited. 587 if (VisitedBlocks.count(BB2)) { 588 VisitedBlocks.insert(EC); 589 } 590 591 // If BB2 is heavier than BB1, make BB2 have the same weight 592 // as BB1. 593 // 594 // Note that we don't worry about the opposite situation here 595 // (when BB2 is lighter than BB1). We will deal with this 596 // during the propagation phase. Right now, we just want to 597 // make sure that BB1 has the largest weight of all the 598 // members of its equivalence set. 599 Weight = std::max(Weight, BlockWeights[BB2]); 600 } 601 } 602 const BasicBlockT *EntryBB = getEntryBB(EC->getParent()); 603 if (EC == EntryBB) { 604 BlockWeights[EC] = Samples->getHeadSamples() + 1; 605 } else { 606 BlockWeights[EC] = Weight; 607 } 608 } 609 610 /// Find equivalence classes. 611 /// 612 /// Since samples may be missing from blocks, we can fill in the gaps by setting 613 /// the weights of all the blocks in the same equivalence class to the same 614 /// weight. To compute the concept of equivalence, we use dominance and loop 615 /// information. Two blocks B1 and B2 are in the same equivalence class if B1 616 /// dominates B2, B2 post-dominates B1 and both are in the same loop. 617 /// 618 /// \param F The function to query. 619 template <typename BT> 620 void SampleProfileLoaderBaseImpl<BT>::findEquivalenceClasses(FunctionT &F) { 621 SmallVector<BasicBlockT *, 8> DominatedBBs; 622 LLVM_DEBUG(dbgs() << "\nBlock equivalence classes\n"); 623 // Find equivalence sets based on dominance and post-dominance information. 624 for (auto &BB : F) { 625 BasicBlockT *BB1 = &BB; 626 627 // Compute BB1's equivalence class once. 628 if (EquivalenceClass.count(BB1)) { 629 LLVM_DEBUG(printBlockEquivalence(dbgs(), BB1)); 630 continue; 631 } 632 633 // By default, blocks are in their own equivalence class. 634 EquivalenceClass[BB1] = BB1; 635 636 // Traverse all the blocks dominated by BB1. We are looking for 637 // every basic block BB2 such that: 638 // 639 // 1- BB1 dominates BB2. 640 // 2- BB2 post-dominates BB1. 641 // 3- BB1 and BB2 are in the same loop nest. 642 // 643 // If all those conditions hold, it means that BB2 is executed 644 // as many times as BB1, so they are placed in the same equivalence 645 // class by making BB2's equivalence class be BB1. 646 DominatedBBs.clear(); 647 DT->getDescendants(BB1, DominatedBBs); 648 findEquivalencesFor(BB1, DominatedBBs, &*PDT); 649 650 LLVM_DEBUG(printBlockEquivalence(dbgs(), BB1)); 651 } 652 653 // Assign weights to equivalence classes. 654 // 655 // All the basic blocks in the same equivalence class will execute 656 // the same number of times. Since we know that the head block in 657 // each equivalence class has the largest weight, assign that weight 658 // to all the blocks in that equivalence class. 659 LLVM_DEBUG( 660 dbgs() << "\nAssign the same weight to all blocks in the same class\n"); 661 for (auto &BI : F) { 662 const BasicBlockT *BB = &BI; 663 const BasicBlockT *EquivBB = EquivalenceClass[BB]; 664 if (BB != EquivBB) 665 BlockWeights[BB] = BlockWeights[EquivBB]; 666 LLVM_DEBUG(printBlockWeight(dbgs(), BB)); 667 } 668 } 669 670 /// Visit the given edge to decide if it has a valid weight. 671 /// 672 /// If \p E has not been visited before, we copy to \p UnknownEdge 673 /// and increment the count of unknown edges. 674 /// 675 /// \param E Edge to visit. 676 /// \param NumUnknownEdges Current number of unknown edges. 677 /// \param UnknownEdge Set if E has not been visited before. 678 /// 679 /// \returns E's weight, if known. Otherwise, return 0. 680 template <typename BT> 681 uint64_t SampleProfileLoaderBaseImpl<BT>::visitEdge(Edge E, 682 unsigned *NumUnknownEdges, 683 Edge *UnknownEdge) { 684 if (!VisitedEdges.count(E)) { 685 (*NumUnknownEdges)++; 686 *UnknownEdge = E; 687 return 0; 688 } 689 690 return EdgeWeights[E]; 691 } 692 693 /// Propagate weights through incoming/outgoing edges. 694 /// 695 /// If the weight of a basic block is known, and there is only one edge 696 /// with an unknown weight, we can calculate the weight of that edge. 697 /// 698 /// Similarly, if all the edges have a known count, we can calculate the 699 /// count of the basic block, if needed. 700 /// 701 /// \param F Function to process. 702 /// \param UpdateBlockCount Whether we should update basic block counts that 703 /// has already been annotated. 704 /// 705 /// \returns True if new weights were assigned to edges or blocks. 706 template <typename BT> 707 bool SampleProfileLoaderBaseImpl<BT>::propagateThroughEdges( 708 FunctionT &F, bool UpdateBlockCount) { 709 bool Changed = false; 710 LLVM_DEBUG(dbgs() << "\nPropagation through edges\n"); 711 for (const auto &BI : F) { 712 const BasicBlockT *BB = &BI; 713 const BasicBlockT *EC = EquivalenceClass[BB]; 714 715 // Visit all the predecessor and successor edges to determine 716 // which ones have a weight assigned already. Note that it doesn't 717 // matter that we only keep track of a single unknown edge. The 718 // only case we are interested in handling is when only a single 719 // edge is unknown (see setEdgeOrBlockWeight). 720 for (unsigned i = 0; i < 2; i++) { 721 uint64_t TotalWeight = 0; 722 unsigned NumUnknownEdges = 0, NumTotalEdges = 0; 723 Edge UnknownEdge, SelfReferentialEdge, SingleEdge; 724 725 if (i == 0) { 726 // First, visit all predecessor edges. 727 NumTotalEdges = Predecessors[BB].size(); 728 for (auto *Pred : Predecessors[BB]) { 729 Edge E = std::make_pair(Pred, BB); 730 TotalWeight += visitEdge(E, &NumUnknownEdges, &UnknownEdge); 731 if (E.first == E.second) 732 SelfReferentialEdge = E; 733 } 734 if (NumTotalEdges == 1) { 735 SingleEdge = std::make_pair(Predecessors[BB][0], BB); 736 } 737 } else { 738 // On the second round, visit all successor edges. 739 NumTotalEdges = Successors[BB].size(); 740 for (auto *Succ : Successors[BB]) { 741 Edge E = std::make_pair(BB, Succ); 742 TotalWeight += visitEdge(E, &NumUnknownEdges, &UnknownEdge); 743 } 744 if (NumTotalEdges == 1) { 745 SingleEdge = std::make_pair(BB, Successors[BB][0]); 746 } 747 } 748 749 // After visiting all the edges, there are three cases that we 750 // can handle immediately: 751 // 752 // - All the edge weights are known (i.e., NumUnknownEdges == 0). 753 // In this case, we simply check that the sum of all the edges 754 // is the same as BB's weight. If not, we change BB's weight 755 // to match. Additionally, if BB had not been visited before, 756 // we mark it visited. 757 // 758 // - Only one edge is unknown and BB has already been visited. 759 // In this case, we can compute the weight of the edge by 760 // subtracting the total block weight from all the known 761 // edge weights. If the edges weight more than BB, then the 762 // edge of the last remaining edge is set to zero. 763 // 764 // - There exists a self-referential edge and the weight of BB is 765 // known. In this case, this edge can be based on BB's weight. 766 // We add up all the other known edges and set the weight on 767 // the self-referential edge as we did in the previous case. 768 // 769 // In any other case, we must continue iterating. Eventually, 770 // all edges will get a weight, or iteration will stop when 771 // it reaches SampleProfileMaxPropagateIterations. 772 if (NumUnknownEdges <= 1) { 773 uint64_t &BBWeight = BlockWeights[EC]; 774 if (NumUnknownEdges == 0) { 775 if (!VisitedBlocks.count(EC)) { 776 // If we already know the weight of all edges, the weight of the 777 // basic block can be computed. It should be no larger than the sum 778 // of all edge weights. 779 if (TotalWeight > BBWeight) { 780 BBWeight = TotalWeight; 781 Changed = true; 782 LLVM_DEBUG(dbgs() << "All edge weights for " << BB->getName() 783 << " known. Set weight for block: "; 784 printBlockWeight(dbgs(), BB);); 785 } 786 } else if (NumTotalEdges == 1 && 787 EdgeWeights[SingleEdge] < BlockWeights[EC]) { 788 // If there is only one edge for the visited basic block, use the 789 // block weight to adjust edge weight if edge weight is smaller. 790 EdgeWeights[SingleEdge] = BlockWeights[EC]; 791 Changed = true; 792 } 793 } else if (NumUnknownEdges == 1 && VisitedBlocks.count(EC)) { 794 // If there is a single unknown edge and the block has been 795 // visited, then we can compute E's weight. 796 if (BBWeight >= TotalWeight) 797 EdgeWeights[UnknownEdge] = BBWeight - TotalWeight; 798 else 799 EdgeWeights[UnknownEdge] = 0; 800 const BasicBlockT *OtherEC; 801 if (i == 0) 802 OtherEC = EquivalenceClass[UnknownEdge.first]; 803 else 804 OtherEC = EquivalenceClass[UnknownEdge.second]; 805 // Edge weights should never exceed the BB weights it connects. 806 if (VisitedBlocks.count(OtherEC) && 807 EdgeWeights[UnknownEdge] > BlockWeights[OtherEC]) 808 EdgeWeights[UnknownEdge] = BlockWeights[OtherEC]; 809 VisitedEdges.insert(UnknownEdge); 810 Changed = true; 811 LLVM_DEBUG(dbgs() << "Set weight for edge: "; 812 printEdgeWeight(dbgs(), UnknownEdge)); 813 } 814 } else if (VisitedBlocks.count(EC) && BlockWeights[EC] == 0) { 815 // If a block Weights 0, all its in/out edges should weight 0. 816 if (i == 0) { 817 for (auto *Pred : Predecessors[BB]) { 818 Edge E = std::make_pair(Pred, BB); 819 EdgeWeights[E] = 0; 820 VisitedEdges.insert(E); 821 } 822 } else { 823 for (auto *Succ : Successors[BB]) { 824 Edge E = std::make_pair(BB, Succ); 825 EdgeWeights[E] = 0; 826 VisitedEdges.insert(E); 827 } 828 } 829 } else if (SelfReferentialEdge.first && VisitedBlocks.count(EC)) { 830 uint64_t &BBWeight = BlockWeights[BB]; 831 // We have a self-referential edge and the weight of BB is known. 832 if (BBWeight >= TotalWeight) 833 EdgeWeights[SelfReferentialEdge] = BBWeight - TotalWeight; 834 else 835 EdgeWeights[SelfReferentialEdge] = 0; 836 VisitedEdges.insert(SelfReferentialEdge); 837 Changed = true; 838 LLVM_DEBUG(dbgs() << "Set self-referential edge weight to: "; 839 printEdgeWeight(dbgs(), SelfReferentialEdge)); 840 } 841 if (UpdateBlockCount && !VisitedBlocks.count(EC) && TotalWeight > 0) { 842 BlockWeights[EC] = TotalWeight; 843 VisitedBlocks.insert(EC); 844 Changed = true; 845 } 846 } 847 } 848 849 return Changed; 850 } 851 852 /// Build in/out edge lists for each basic block in the CFG. 853 /// 854 /// We are interested in unique edges. If a block B1 has multiple 855 /// edges to another block B2, we only add a single B1->B2 edge. 856 template <typename BT> 857 void SampleProfileLoaderBaseImpl<BT>::buildEdges(FunctionT &F) { 858 for (auto &BI : F) { 859 BasicBlockT *B1 = &BI; 860 861 // Add predecessors for B1. 862 SmallPtrSet<BasicBlockT *, 16> Visited; 863 if (!Predecessors[B1].empty()) 864 llvm_unreachable("Found a stale predecessors list in a basic block."); 865 for (auto *B2 : getPredecessors(B1)) 866 if (Visited.insert(B2).second) 867 Predecessors[B1].push_back(B2); 868 869 // Add successors for B1. 870 Visited.clear(); 871 if (!Successors[B1].empty()) 872 llvm_unreachable("Found a stale successors list in a basic block."); 873 for (auto *B2 : getSuccessors(B1)) 874 if (Visited.insert(B2).second) 875 Successors[B1].push_back(B2); 876 } 877 } 878 879 /// Propagate weights into edges 880 /// 881 /// The following rules are applied to every block BB in the CFG: 882 /// 883 /// - If BB has a single predecessor/successor, then the weight 884 /// of that edge is the weight of the block. 885 /// 886 /// - If all incoming or outgoing edges are known except one, and the 887 /// weight of the block is already known, the weight of the unknown 888 /// edge will be the weight of the block minus the sum of all the known 889 /// edges. If the sum of all the known edges is larger than BB's weight, 890 /// we set the unknown edge weight to zero. 891 /// 892 /// - If there is a self-referential edge, and the weight of the block is 893 /// known, the weight for that edge is set to the weight of the block 894 /// minus the weight of the other incoming edges to that block (if 895 /// known). 896 template <typename BT> 897 void SampleProfileLoaderBaseImpl<BT>::propagateWeights(FunctionT &F) { 898 // Flow-based profile inference is only usable with BasicBlock instantiation 899 // of SampleProfileLoaderBaseImpl. 900 if (SampleProfileUseProfi) { 901 // Prepare block sample counts for inference. 902 BlockWeightMap SampleBlockWeights; 903 for (const auto &BI : F) { 904 ErrorOr<uint64_t> Weight = getBlockWeight(&BI); 905 if (Weight) 906 SampleBlockWeights[&BI] = Weight.get(); 907 } 908 // Fill in BlockWeights and EdgeWeights using an inference algorithm. 909 applyProfi(F, Successors, SampleBlockWeights, BlockWeights, EdgeWeights); 910 } else { 911 bool Changed = true; 912 unsigned I = 0; 913 914 // If BB weight is larger than its corresponding loop's header BB weight, 915 // use the BB weight to replace the loop header BB weight. 916 for (auto &BI : F) { 917 BasicBlockT *BB = &BI; 918 LoopT *L = LI->getLoopFor(BB); 919 if (!L) { 920 continue; 921 } 922 BasicBlockT *Header = L->getHeader(); 923 if (Header && BlockWeights[BB] > BlockWeights[Header]) { 924 BlockWeights[Header] = BlockWeights[BB]; 925 } 926 } 927 928 // Propagate until we converge or we go past the iteration limit. 929 while (Changed && I++ < SampleProfileMaxPropagateIterations) { 930 Changed = propagateThroughEdges(F, false); 931 } 932 933 // The first propagation propagates BB counts from annotated BBs to unknown 934 // BBs. The 2nd propagation pass resets edges weights, and use all BB 935 // weights to propagate edge weights. 936 VisitedEdges.clear(); 937 Changed = true; 938 while (Changed && I++ < SampleProfileMaxPropagateIterations) { 939 Changed = propagateThroughEdges(F, false); 940 } 941 942 // The 3rd propagation pass allows adjust annotated BB weights that are 943 // obviously wrong. 944 Changed = true; 945 while (Changed && I++ < SampleProfileMaxPropagateIterations) { 946 Changed = propagateThroughEdges(F, true); 947 } 948 } 949 } 950 951 template <typename FT> 952 void SampleProfileLoaderBaseImpl<FT>::applyProfi( 953 FunctionT &F, BlockEdgeMap &Successors, BlockWeightMap &SampleBlockWeights, 954 BlockWeightMap &BlockWeights, EdgeWeightMap &EdgeWeights) { 955 auto Infer = SampleProfileInference<FT>(F, Successors, SampleBlockWeights); 956 Infer.apply(BlockWeights, EdgeWeights); 957 } 958 959 /// Generate branch weight metadata for all branches in \p F. 960 /// 961 /// Branch weights are computed out of instruction samples using a 962 /// propagation heuristic. Propagation proceeds in 3 phases: 963 /// 964 /// 1- Assignment of block weights. All the basic blocks in the function 965 /// are initial assigned the same weight as their most frequently 966 /// executed instruction. 967 /// 968 /// 2- Creation of equivalence classes. Since samples may be missing from 969 /// blocks, we can fill in the gaps by setting the weights of all the 970 /// blocks in the same equivalence class to the same weight. To compute 971 /// the concept of equivalence, we use dominance and loop information. 972 /// Two blocks B1 and B2 are in the same equivalence class if B1 973 /// dominates B2, B2 post-dominates B1 and both are in the same loop. 974 /// 975 /// 3- Propagation of block weights into edges. This uses a simple 976 /// propagation heuristic. The following rules are applied to every 977 /// block BB in the CFG: 978 /// 979 /// - If BB has a single predecessor/successor, then the weight 980 /// of that edge is the weight of the block. 981 /// 982 /// - If all the edges are known except one, and the weight of the 983 /// block is already known, the weight of the unknown edge will 984 /// be the weight of the block minus the sum of all the known 985 /// edges. If the sum of all the known edges is larger than BB's weight, 986 /// we set the unknown edge weight to zero. 987 /// 988 /// - If there is a self-referential edge, and the weight of the block is 989 /// known, the weight for that edge is set to the weight of the block 990 /// minus the weight of the other incoming edges to that block (if 991 /// known). 992 /// 993 /// Since this propagation is not guaranteed to finalize for every CFG, we 994 /// only allow it to proceed for a limited number of iterations (controlled 995 /// by -sample-profile-max-propagate-iterations). 996 /// 997 /// FIXME: Try to replace this propagation heuristic with a scheme 998 /// that is guaranteed to finalize. A work-list approach similar to 999 /// the standard value propagation algorithm used by SSA-CCP might 1000 /// work here. 1001 /// 1002 /// \param F The function to query. 1003 /// 1004 /// \returns true if \p F was modified. Returns false, otherwise. 1005 template <typename BT> 1006 bool SampleProfileLoaderBaseImpl<BT>::computeAndPropagateWeights( 1007 FunctionT &F, const DenseSet<GlobalValue::GUID> &InlinedGUIDs) { 1008 bool Changed = (InlinedGUIDs.size() != 0); 1009 1010 // Compute basic block weights. 1011 Changed |= computeBlockWeights(F); 1012 1013 if (Changed) { 1014 // Initialize propagation. 1015 initWeightPropagation(F, InlinedGUIDs); 1016 1017 // Propagate weights to all edges. 1018 propagateWeights(F); 1019 1020 // Post-process propagated weights. 1021 finalizeWeightPropagation(F, InlinedGUIDs); 1022 } 1023 1024 return Changed; 1025 } 1026 1027 template <typename BT> 1028 void SampleProfileLoaderBaseImpl<BT>::initWeightPropagation( 1029 FunctionT &F, const DenseSet<GlobalValue::GUID> &InlinedGUIDs) { 1030 // Add an entry count to the function using the samples gathered at the 1031 // function entry. 1032 // Sets the GUIDs that are inlined in the profiled binary. This is used 1033 // for ThinLink to make correct liveness analysis, and also make the IR 1034 // match the profiled binary before annotation. 1035 getFunction(F).setEntryCount( 1036 ProfileCount(Samples->getHeadSamples() + 1, Function::PCT_Real), 1037 &InlinedGUIDs); 1038 1039 if (!SampleProfileUseProfi) { 1040 // Compute dominance and loop info needed for propagation. 1041 computeDominanceAndLoopInfo(F); 1042 1043 // Find equivalence classes. 1044 findEquivalenceClasses(F); 1045 } 1046 1047 // Before propagation starts, build, for each block, a list of 1048 // unique predecessors and successors. This is necessary to handle 1049 // identical edges in multiway branches. Since we visit all blocks and all 1050 // edges of the CFG, it is cleaner to build these lists once at the start 1051 // of the pass. 1052 buildEdges(F); 1053 } 1054 1055 template <typename BT> 1056 void SampleProfileLoaderBaseImpl<BT>::finalizeWeightPropagation( 1057 FunctionT &F, const DenseSet<GlobalValue::GUID> &InlinedGUIDs) { 1058 // If we utilize a flow-based count inference, then we trust the computed 1059 // counts and set the entry count as computed by the algorithm. This is 1060 // primarily done to sync the counts produced by profi and BFI inference, 1061 // which uses the entry count for mass propagation. 1062 // If profi produces a zero-value for the entry count, we fallback to 1063 // Samples->getHeadSamples() + 1 to avoid functions with zero count. 1064 if (SampleProfileUseProfi) { 1065 const BasicBlockT *EntryBB = getEntryBB(&F); 1066 ErrorOr<uint64_t> EntryWeight = getBlockWeight(EntryBB); 1067 if (BlockWeights[EntryBB] > 0) { 1068 getFunction(F).setEntryCount( 1069 ProfileCount(BlockWeights[EntryBB], Function::PCT_Real), 1070 &InlinedGUIDs); 1071 } 1072 } 1073 } 1074 1075 template <typename BT> 1076 void SampleProfileLoaderBaseImpl<BT>::emitCoverageRemarks(FunctionT &F) { 1077 // If coverage checking was requested, compute it now. 1078 const Function &Func = getFunction(F); 1079 if (SampleProfileRecordCoverage) { 1080 unsigned Used = CoverageTracker.countUsedRecords(Samples, PSI); 1081 unsigned Total = CoverageTracker.countBodyRecords(Samples, PSI); 1082 unsigned Coverage = CoverageTracker.computeCoverage(Used, Total); 1083 if (Coverage < SampleProfileRecordCoverage) { 1084 Func.getContext().diagnose(DiagnosticInfoSampleProfile( 1085 Func.getSubprogram()->getFilename(), getFunctionLoc(F), 1086 Twine(Used) + " of " + Twine(Total) + " available profile records (" + 1087 Twine(Coverage) + "%) were applied", 1088 DS_Warning)); 1089 } 1090 } 1091 1092 if (SampleProfileSampleCoverage) { 1093 uint64_t Used = CoverageTracker.getTotalUsedSamples(); 1094 uint64_t Total = CoverageTracker.countBodySamples(Samples, PSI); 1095 unsigned Coverage = CoverageTracker.computeCoverage(Used, Total); 1096 if (Coverage < SampleProfileSampleCoverage) { 1097 Func.getContext().diagnose(DiagnosticInfoSampleProfile( 1098 Func.getSubprogram()->getFilename(), getFunctionLoc(F), 1099 Twine(Used) + " of " + Twine(Total) + " available profile samples (" + 1100 Twine(Coverage) + "%) were applied", 1101 DS_Warning)); 1102 } 1103 } 1104 } 1105 1106 /// Get the line number for the function header. 1107 /// 1108 /// This looks up function \p F in the current compilation unit and 1109 /// retrieves the line number where the function is defined. This is 1110 /// line 0 for all the samples read from the profile file. Every line 1111 /// number is relative to this line. 1112 /// 1113 /// \param F Function object to query. 1114 /// 1115 /// \returns the line number where \p F is defined. If it returns 0, 1116 /// it means that there is no debug information available for \p F. 1117 template <typename BT> 1118 unsigned SampleProfileLoaderBaseImpl<BT>::getFunctionLoc(FunctionT &F) { 1119 const Function &Func = getFunction(F); 1120 if (DISubprogram *S = Func.getSubprogram()) 1121 return S->getLine(); 1122 1123 if (NoWarnSampleUnused) 1124 return 0; 1125 1126 // If the start of \p F is missing, emit a diagnostic to inform the user 1127 // about the missed opportunity. 1128 Func.getContext().diagnose(DiagnosticInfoSampleProfile( 1129 "No debug information found in function " + Func.getName() + 1130 ": Function profile not used", 1131 DS_Warning)); 1132 return 0; 1133 } 1134 1135 #undef DEBUG_TYPE 1136 1137 } // namespace llvm 1138 #endif // LLVM_TRANSFORMS_UTILS_SAMPLEPROFILELOADERBASEIMPL_H 1139