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