1 //===- SampleProfile.cpp - Incorporate sample profiles into the IR --------===//
2 //
3 //                      The LLVM Compiler Infrastructure
4 //
5 // This file is distributed under the University of Illinois Open Source
6 // License. See LICENSE.TXT for details.
7 //
8 //===----------------------------------------------------------------------===//
9 //
10 // This file implements the SampleProfileLoader transformation. This pass
11 // reads a profile file generated by a sampling profiler (e.g. Linux Perf -
12 // http://perf.wiki.kernel.org/) and generates IR metadata to reflect the
13 // profile information in the given profile.
14 //
15 // This pass generates branch weight annotations on the IR:
16 //
17 // - prof: Represents branch weights. This annotation is added to branches
18 //      to indicate the weights of each edge coming out of the branch.
19 //      The weight of each edge is the weight of the target block for
20 //      that edge. The weight of a block B is computed as the maximum
21 //      number of samples found in B.
22 //
23 //===----------------------------------------------------------------------===//
24 
25 #include "llvm/Transforms/SampleProfile.h"
26 #include "llvm/ADT/DenseMap.h"
27 #include "llvm/ADT/SmallPtrSet.h"
28 #include "llvm/ADT/SmallSet.h"
29 #include "llvm/ADT/StringRef.h"
30 #include "llvm/Analysis/AssumptionCache.h"
31 #include "llvm/Analysis/LoopInfo.h"
32 #include "llvm/Analysis/PostDominators.h"
33 #include "llvm/IR/Constants.h"
34 #include "llvm/IR/DebugInfo.h"
35 #include "llvm/IR/DiagnosticInfo.h"
36 #include "llvm/IR/Dominators.h"
37 #include "llvm/IR/Function.h"
38 #include "llvm/IR/InstIterator.h"
39 #include "llvm/IR/Instructions.h"
40 #include "llvm/IR/IntrinsicInst.h"
41 #include "llvm/IR/LLVMContext.h"
42 #include "llvm/IR/MDBuilder.h"
43 #include "llvm/IR/Metadata.h"
44 #include "llvm/IR/Module.h"
45 #include "llvm/Pass.h"
46 #include "llvm/ProfileData/SampleProfReader.h"
47 #include "llvm/Support/CommandLine.h"
48 #include "llvm/Support/Debug.h"
49 #include "llvm/Support/ErrorOr.h"
50 #include "llvm/Support/Format.h"
51 #include "llvm/Support/raw_ostream.h"
52 #include "llvm/Transforms/IPO.h"
53 #include "llvm/Transforms/Utils/Cloning.h"
54 #include <cctype>
55 
56 using namespace llvm;
57 using namespace sampleprof;
58 
59 #define DEBUG_TYPE "sample-profile"
60 
61 // Command line option to specify the file to read samples from. This is
62 // mainly used for debugging.
63 static cl::opt<std::string> SampleProfileFile(
64     "sample-profile-file", cl::init(""), cl::value_desc("filename"),
65     cl::desc("Profile file loaded by -sample-profile"), cl::Hidden);
66 static cl::opt<unsigned> SampleProfileMaxPropagateIterations(
67     "sample-profile-max-propagate-iterations", cl::init(100),
68     cl::desc("Maximum number of iterations to go through when propagating "
69              "sample block/edge weights through the CFG."));
70 static cl::opt<unsigned> SampleProfileRecordCoverage(
71     "sample-profile-check-record-coverage", cl::init(0), cl::value_desc("N"),
72     cl::desc("Emit a warning if less than N% of records in the input profile "
73              "are matched to the IR."));
74 static cl::opt<unsigned> SampleProfileSampleCoverage(
75     "sample-profile-check-sample-coverage", cl::init(0), cl::value_desc("N"),
76     cl::desc("Emit a warning if less than N% of samples in the input profile "
77              "are matched to the IR."));
78 static cl::opt<double> SampleProfileHotThreshold(
79     "sample-profile-inline-hot-threshold", cl::init(0.1), cl::value_desc("N"),
80     cl::desc("Inlined functions that account for more than N% of all samples "
81              "collected in the parent function, will be inlined again."));
82 
83 namespace {
84 typedef DenseMap<const BasicBlock *, uint64_t> BlockWeightMap;
85 typedef DenseMap<const BasicBlock *, const BasicBlock *> EquivalenceClassMap;
86 typedef std::pair<const BasicBlock *, const BasicBlock *> Edge;
87 typedef DenseMap<Edge, uint64_t> EdgeWeightMap;
88 typedef DenseMap<const BasicBlock *, SmallVector<const BasicBlock *, 8>>
89     BlockEdgeMap;
90 
91 /// \brief Sample profile pass.
92 ///
93 /// This pass reads profile data from the file specified by
94 /// -sample-profile-file and annotates every affected function with the
95 /// profile information found in that file.
96 class SampleProfileLoader {
97 public:
98   SampleProfileLoader(StringRef Name = SampleProfileFile)
99       : DT(nullptr), PDT(nullptr), LI(nullptr), ACT(nullptr), Reader(),
100         Samples(nullptr), Filename(Name), ProfileIsValid(false),
101         TotalCollectedSamples(0) {}
102 
103   bool doInitialization(Module &M);
104   bool runOnModule(Module &M);
105   void setACT(AssumptionCacheTracker *A) { ACT = A; }
106 
107   void dump() { Reader->dump(); }
108 
109 protected:
110   bool runOnFunction(Function &F);
111   unsigned getFunctionLoc(Function &F);
112   bool emitAnnotations(Function &F);
113   ErrorOr<uint64_t> getInstWeight(const Instruction &I) const;
114   ErrorOr<uint64_t> getBlockWeight(const BasicBlock *BB) const;
115   const FunctionSamples *findCalleeFunctionSamples(const CallInst &I) const;
116   const FunctionSamples *findFunctionSamples(const Instruction &I) const;
117   bool inlineHotFunctions(Function &F);
118   void printEdgeWeight(raw_ostream &OS, Edge E);
119   void printBlockWeight(raw_ostream &OS, const BasicBlock *BB) const;
120   void printBlockEquivalence(raw_ostream &OS, const BasicBlock *BB);
121   bool computeBlockWeights(Function &F);
122   void findEquivalenceClasses(Function &F);
123   void findEquivalencesFor(BasicBlock *BB1, ArrayRef<BasicBlock *> Descendants,
124                            DominatorTreeBase<BasicBlock> *DomTree);
125   void propagateWeights(Function &F);
126   uint64_t visitEdge(Edge E, unsigned *NumUnknownEdges, Edge *UnknownEdge);
127   void buildEdges(Function &F);
128   bool propagateThroughEdges(Function &F, bool UpdateBlockCount);
129   void computeDominanceAndLoopInfo(Function &F);
130   unsigned getOffset(unsigned L, unsigned H) const;
131   void clearFunctionData();
132 
133   /// \brief Map basic blocks to their computed weights.
134   ///
135   /// The weight of a basic block is defined to be the maximum
136   /// of all the instruction weights in that block.
137   BlockWeightMap BlockWeights;
138 
139   /// \brief Map edges to their computed weights.
140   ///
141   /// Edge weights are computed by propagating basic block weights in
142   /// SampleProfile::propagateWeights.
143   EdgeWeightMap EdgeWeights;
144 
145   /// \brief Set of visited blocks during propagation.
146   SmallPtrSet<const BasicBlock *, 32> VisitedBlocks;
147 
148   /// \brief Set of visited edges during propagation.
149   SmallSet<Edge, 32> VisitedEdges;
150 
151   /// \brief Equivalence classes for block weights.
152   ///
153   /// Two blocks BB1 and BB2 are in the same equivalence class if they
154   /// dominate and post-dominate each other, and they are in the same loop
155   /// nest. When this happens, the two blocks are guaranteed to execute
156   /// the same number of times.
157   EquivalenceClassMap EquivalenceClass;
158 
159   /// \brief Dominance, post-dominance and loop information.
160   std::unique_ptr<DominatorTree> DT;
161   std::unique_ptr<DominatorTreeBase<BasicBlock>> PDT;
162   std::unique_ptr<LoopInfo> LI;
163 
164   AssumptionCacheTracker *ACT;
165 
166   /// \brief Predecessors for each basic block in the CFG.
167   BlockEdgeMap Predecessors;
168 
169   /// \brief Successors for each basic block in the CFG.
170   BlockEdgeMap Successors;
171 
172   /// \brief Profile reader object.
173   std::unique_ptr<SampleProfileReader> Reader;
174 
175   /// \brief Samples collected for the body of this function.
176   FunctionSamples *Samples;
177 
178   /// \brief Name of the profile file to load.
179   StringRef Filename;
180 
181   /// \brief Flag indicating whether the profile input loaded successfully.
182   bool ProfileIsValid;
183 
184   /// \brief Total number of samples collected in this profile.
185   ///
186   /// This is the sum of all the samples collected in all the functions executed
187   /// at runtime.
188   uint64_t TotalCollectedSamples;
189 };
190 
191 class SampleProfileLoaderLegacyPass : public ModulePass {
192 public:
193   // Class identification, replacement for typeinfo
194   static char ID;
195 
196   SampleProfileLoaderLegacyPass(StringRef Name = SampleProfileFile)
197       : ModulePass(ID), SampleLoader(Name) {
198     initializeSampleProfileLoaderLegacyPassPass(
199         *PassRegistry::getPassRegistry());
200   }
201 
202   void dump() { SampleLoader.dump(); }
203 
204   bool doInitialization(Module &M) override {
205     return SampleLoader.doInitialization(M);
206   }
207   const char *getPassName() const override { return "Sample profile pass"; }
208   bool runOnModule(Module &M) override;
209 
210   void getAnalysisUsage(AnalysisUsage &AU) const override {
211     AU.addRequired<AssumptionCacheTracker>();
212   }
213 private:
214   SampleProfileLoader SampleLoader;
215 };
216 
217 class SampleCoverageTracker {
218 public:
219   SampleCoverageTracker() : SampleCoverage(), TotalUsedSamples(0) {}
220 
221   bool markSamplesUsed(const FunctionSamples *FS, uint32_t LineOffset,
222                        uint32_t Discriminator, uint64_t Samples);
223   unsigned computeCoverage(unsigned Used, unsigned Total) const;
224   unsigned countUsedRecords(const FunctionSamples *FS) const;
225   unsigned countBodyRecords(const FunctionSamples *FS) const;
226   uint64_t getTotalUsedSamples() const { return TotalUsedSamples; }
227   uint64_t countBodySamples(const FunctionSamples *FS) const;
228   void clear() {
229     SampleCoverage.clear();
230     TotalUsedSamples = 0;
231   }
232 
233 private:
234   typedef std::map<LineLocation, unsigned> BodySampleCoverageMap;
235   typedef DenseMap<const FunctionSamples *, BodySampleCoverageMap>
236       FunctionSamplesCoverageMap;
237 
238   /// Coverage map for sampling records.
239   ///
240   /// This map keeps a record of sampling records that have been matched to
241   /// an IR instruction. This is used to detect some form of staleness in
242   /// profiles (see flag -sample-profile-check-coverage).
243   ///
244   /// Each entry in the map corresponds to a FunctionSamples instance.  This is
245   /// another map that counts how many times the sample record at the
246   /// given location has been used.
247   FunctionSamplesCoverageMap SampleCoverage;
248 
249   /// Number of samples used from the profile.
250   ///
251   /// When a sampling record is used for the first time, the samples from
252   /// that record are added to this accumulator.  Coverage is later computed
253   /// based on the total number of samples available in this function and
254   /// its callsites.
255   ///
256   /// Note that this accumulator tracks samples used from a single function
257   /// and all the inlined callsites. Strictly, we should have a map of counters
258   /// keyed by FunctionSamples pointers, but these stats are cleared after
259   /// every function, so we just need to keep a single counter.
260   uint64_t TotalUsedSamples;
261 };
262 
263 SampleCoverageTracker CoverageTracker;
264 
265 /// Return true if the given callsite is hot wrt to its caller.
266 ///
267 /// Functions that were inlined in the original binary will be represented
268 /// in the inline stack in the sample profile. If the profile shows that
269 /// the original inline decision was "good" (i.e., the callsite is executed
270 /// frequently), then we will recreate the inline decision and apply the
271 /// profile from the inlined callsite.
272 ///
273 /// To decide whether an inlined callsite is hot, we compute the fraction
274 /// of samples used by the callsite with respect to the total number of samples
275 /// collected in the caller.
276 ///
277 /// If that fraction is larger than the default given by
278 /// SampleProfileHotThreshold, the callsite will be inlined again.
279 bool callsiteIsHot(const FunctionSamples *CallerFS,
280                    const FunctionSamples *CallsiteFS) {
281   if (!CallsiteFS)
282     return false; // The callsite was not inlined in the original binary.
283 
284   uint64_t ParentTotalSamples = CallerFS->getTotalSamples();
285   if (ParentTotalSamples == 0)
286     return false; // Avoid division by zero.
287 
288   uint64_t CallsiteTotalSamples = CallsiteFS->getTotalSamples();
289   if (CallsiteTotalSamples == 0)
290     return false; // Callsite is trivially cold.
291 
292   double PercentSamples =
293       (double)CallsiteTotalSamples / (double)ParentTotalSamples * 100.0;
294   return PercentSamples >= SampleProfileHotThreshold;
295 }
296 }
297 
298 /// Mark as used the sample record for the given function samples at
299 /// (LineOffset, Discriminator).
300 ///
301 /// \returns true if this is the first time we mark the given record.
302 bool SampleCoverageTracker::markSamplesUsed(const FunctionSamples *FS,
303                                             uint32_t LineOffset,
304                                             uint32_t Discriminator,
305                                             uint64_t Samples) {
306   LineLocation Loc(LineOffset, Discriminator);
307   unsigned &Count = SampleCoverage[FS][Loc];
308   bool FirstTime = (++Count == 1);
309   if (FirstTime)
310     TotalUsedSamples += Samples;
311   return FirstTime;
312 }
313 
314 /// Return the number of sample records that were applied from this profile.
315 ///
316 /// This count does not include records from cold inlined callsites.
317 unsigned
318 SampleCoverageTracker::countUsedRecords(const FunctionSamples *FS) const {
319   auto I = SampleCoverage.find(FS);
320 
321   // The size of the coverage map for FS represents the number of records
322   // that were marked used at least once.
323   unsigned Count = (I != SampleCoverage.end()) ? I->second.size() : 0;
324 
325   // If there are inlined callsites in this function, count the samples found
326   // in the respective bodies. However, do not bother counting callees with 0
327   // total samples, these are callees that were never invoked at runtime.
328   for (const auto &I : FS->getCallsiteSamples()) {
329     const FunctionSamples *CalleeSamples = &I.second;
330     if (callsiteIsHot(FS, CalleeSamples))
331       Count += countUsedRecords(CalleeSamples);
332   }
333 
334   return Count;
335 }
336 
337 /// Return the number of sample records in the body of this profile.
338 ///
339 /// This count does not include records from cold inlined callsites.
340 unsigned
341 SampleCoverageTracker::countBodyRecords(const FunctionSamples *FS) const {
342   unsigned Count = FS->getBodySamples().size();
343 
344   // Only count records in hot callsites.
345   for (const auto &I : FS->getCallsiteSamples()) {
346     const FunctionSamples *CalleeSamples = &I.second;
347     if (callsiteIsHot(FS, CalleeSamples))
348       Count += countBodyRecords(CalleeSamples);
349   }
350 
351   return Count;
352 }
353 
354 /// Return the number of samples collected in the body of this profile.
355 ///
356 /// This count does not include samples from cold inlined callsites.
357 uint64_t
358 SampleCoverageTracker::countBodySamples(const FunctionSamples *FS) const {
359   uint64_t Total = 0;
360   for (const auto &I : FS->getBodySamples())
361     Total += I.second.getSamples();
362 
363   // Only count samples in hot callsites.
364   for (const auto &I : FS->getCallsiteSamples()) {
365     const FunctionSamples *CalleeSamples = &I.second;
366     if (callsiteIsHot(FS, CalleeSamples))
367       Total += countBodySamples(CalleeSamples);
368   }
369 
370   return Total;
371 }
372 
373 /// Return the fraction of sample records used in this profile.
374 ///
375 /// The returned value is an unsigned integer in the range 0-100 indicating
376 /// the percentage of sample records that were used while applying this
377 /// profile to the associated function.
378 unsigned SampleCoverageTracker::computeCoverage(unsigned Used,
379                                                 unsigned Total) const {
380   assert(Used <= Total &&
381          "number of used records cannot exceed the total number of records");
382   return Total > 0 ? Used * 100 / Total : 100;
383 }
384 
385 /// Clear all the per-function data used to load samples and propagate weights.
386 void SampleProfileLoader::clearFunctionData() {
387   BlockWeights.clear();
388   EdgeWeights.clear();
389   VisitedBlocks.clear();
390   VisitedEdges.clear();
391   EquivalenceClass.clear();
392   DT = nullptr;
393   PDT = nullptr;
394   LI = nullptr;
395   Predecessors.clear();
396   Successors.clear();
397   CoverageTracker.clear();
398 }
399 
400 /// \brief Returns the offset of lineno \p L to head_lineno \p H
401 ///
402 /// \param L  Lineno
403 /// \param H  Header lineno of the function
404 ///
405 /// \returns offset to the header lineno. 16 bits are used to represent offset.
406 /// We assume that a single function will not exceed 65535 LOC.
407 unsigned SampleProfileLoader::getOffset(unsigned L, unsigned H) const {
408   return (L - H) & 0xffff;
409 }
410 
411 /// \brief Print the weight of edge \p E on stream \p OS.
412 ///
413 /// \param OS  Stream to emit the output to.
414 /// \param E  Edge to print.
415 void SampleProfileLoader::printEdgeWeight(raw_ostream &OS, Edge E) {
416   OS << "weight[" << E.first->getName() << "->" << E.second->getName()
417      << "]: " << EdgeWeights[E] << "\n";
418 }
419 
420 /// \brief Print the equivalence class of block \p BB on stream \p OS.
421 ///
422 /// \param OS  Stream to emit the output to.
423 /// \param BB  Block to print.
424 void SampleProfileLoader::printBlockEquivalence(raw_ostream &OS,
425                                                 const BasicBlock *BB) {
426   const BasicBlock *Equiv = EquivalenceClass[BB];
427   OS << "equivalence[" << BB->getName()
428      << "]: " << ((Equiv) ? EquivalenceClass[BB]->getName() : "NONE") << "\n";
429 }
430 
431 /// \brief Print the weight of block \p BB on stream \p OS.
432 ///
433 /// \param OS  Stream to emit the output to.
434 /// \param BB  Block to print.
435 void SampleProfileLoader::printBlockWeight(raw_ostream &OS,
436                                            const BasicBlock *BB) const {
437   const auto &I = BlockWeights.find(BB);
438   uint64_t W = (I == BlockWeights.end() ? 0 : I->second);
439   OS << "weight[" << BB->getName() << "]: " << W << "\n";
440 }
441 
442 /// \brief Get the weight for an instruction.
443 ///
444 /// The "weight" of an instruction \p Inst is the number of samples
445 /// collected on that instruction at runtime. To retrieve it, we
446 /// need to compute the line number of \p Inst relative to the start of its
447 /// function. We use HeaderLineno to compute the offset. We then
448 /// look up the samples collected for \p Inst using BodySamples.
449 ///
450 /// \param Inst Instruction to query.
451 ///
452 /// \returns the weight of \p Inst.
453 ErrorOr<uint64_t>
454 SampleProfileLoader::getInstWeight(const Instruction &Inst) const {
455   const DebugLoc &DLoc = Inst.getDebugLoc();
456   if (!DLoc)
457     return std::error_code();
458 
459   const FunctionSamples *FS = findFunctionSamples(Inst);
460   if (!FS)
461     return std::error_code();
462 
463   // Ignore all intrinsics and branch instructions.
464   // Branch instruction usually contains debug info from sources outside of
465   // the residing basic block, thus we ignore them during annotation.
466   if (isa<BranchInst>(Inst) || isa<IntrinsicInst>(Inst))
467     return std::error_code();
468 
469   // If a call instruction is inlined in profile, but not inlined here,
470   // it means that the inlined callsite has no sample, thus the call
471   // instruction should have 0 count.
472   const CallInst *CI = dyn_cast<CallInst>(&Inst);
473   if (CI && findCalleeFunctionSamples(*CI))
474     return 0;
475 
476   const DILocation *DIL = DLoc;
477   unsigned Lineno = DLoc.getLine();
478   unsigned HeaderLineno = DIL->getScope()->getSubprogram()->getLine();
479 
480   uint32_t LineOffset = getOffset(Lineno, HeaderLineno);
481   uint32_t Discriminator = DIL->getDiscriminator();
482   ErrorOr<uint64_t> R = FS->findSamplesAt(LineOffset, Discriminator);
483   if (R) {
484     bool FirstMark =
485         CoverageTracker.markSamplesUsed(FS, LineOffset, Discriminator, R.get());
486     if (FirstMark) {
487       const Function *F = Inst.getParent()->getParent();
488       LLVMContext &Ctx = F->getContext();
489       emitOptimizationRemark(
490           Ctx, DEBUG_TYPE, *F, DLoc,
491           Twine("Applied ") + Twine(*R) + " samples from profile (offset: " +
492               Twine(LineOffset) +
493               ((Discriminator) ? Twine(".") + Twine(Discriminator) : "") + ")");
494     }
495     DEBUG(dbgs() << "    " << Lineno << "." << DIL->getDiscriminator() << ":"
496                  << Inst << " (line offset: " << Lineno - HeaderLineno << "."
497                  << DIL->getDiscriminator() << " - weight: " << R.get()
498                  << ")\n");
499   }
500   return R;
501 }
502 
503 /// \brief Compute the weight of a basic block.
504 ///
505 /// The weight of basic block \p BB is the maximum weight of all the
506 /// instructions in BB.
507 ///
508 /// \param BB The basic block to query.
509 ///
510 /// \returns the weight for \p BB.
511 ErrorOr<uint64_t>
512 SampleProfileLoader::getBlockWeight(const BasicBlock *BB) const {
513   DenseMap<uint64_t, uint64_t> CM;
514   for (auto &I : BB->getInstList()) {
515     const ErrorOr<uint64_t> &R = getInstWeight(I);
516     if (R) CM[R.get()]++;
517   }
518   if (CM.size() == 0) return std::error_code();
519   uint64_t W = 0, C = 0;
520   for (const auto &C_W : CM) {
521     if (C_W.second == W) {
522       C = std::max(C, C_W.first);
523     } else if (C_W.second > W) {
524       C = C_W.first;
525       W = C_W.second;
526     }
527   }
528   return C;
529 }
530 
531 /// \brief Compute and store the weights of every basic block.
532 ///
533 /// This populates the BlockWeights map by computing
534 /// the weights of every basic block in the CFG.
535 ///
536 /// \param F The function to query.
537 bool SampleProfileLoader::computeBlockWeights(Function &F) {
538   bool Changed = false;
539   DEBUG(dbgs() << "Block weights\n");
540   for (const auto &BB : F) {
541     ErrorOr<uint64_t> Weight = getBlockWeight(&BB);
542     if (Weight) {
543       BlockWeights[&BB] = Weight.get();
544       VisitedBlocks.insert(&BB);
545       Changed = true;
546     }
547     DEBUG(printBlockWeight(dbgs(), &BB));
548   }
549 
550   return Changed;
551 }
552 
553 /// \brief Get the FunctionSamples for a call instruction.
554 ///
555 /// The FunctionSamples of a call instruction \p Inst is the inlined
556 /// instance in which that call instruction is calling to. It contains
557 /// all samples that resides in the inlined instance. We first find the
558 /// inlined instance in which the call instruction is from, then we
559 /// traverse its children to find the callsite with the matching
560 /// location and callee function name.
561 ///
562 /// \param Inst Call instruction to query.
563 ///
564 /// \returns The FunctionSamples pointer to the inlined instance.
565 const FunctionSamples *
566 SampleProfileLoader::findCalleeFunctionSamples(const CallInst &Inst) const {
567   const DILocation *DIL = Inst.getDebugLoc();
568   if (!DIL) {
569     return nullptr;
570   }
571   DISubprogram *SP = DIL->getScope()->getSubprogram();
572   if (!SP)
573     return nullptr;
574 
575   const FunctionSamples *FS = findFunctionSamples(Inst);
576   if (FS == nullptr)
577     return nullptr;
578 
579   return FS->findFunctionSamplesAt(LineLocation(
580       getOffset(DIL->getLine(), SP->getLine()), DIL->getDiscriminator()));
581 }
582 
583 /// \brief Get the FunctionSamples for an instruction.
584 ///
585 /// The FunctionSamples of an instruction \p Inst is the inlined instance
586 /// in which that instruction is coming from. We traverse the inline stack
587 /// of that instruction, and match it with the tree nodes in the profile.
588 ///
589 /// \param Inst Instruction to query.
590 ///
591 /// \returns the FunctionSamples pointer to the inlined instance.
592 const FunctionSamples *
593 SampleProfileLoader::findFunctionSamples(const Instruction &Inst) const {
594   SmallVector<LineLocation, 10> S;
595   const DILocation *DIL = Inst.getDebugLoc();
596   if (!DIL) {
597     return Samples;
598   }
599   for (DIL = DIL->getInlinedAt(); DIL; DIL = DIL->getInlinedAt()) {
600     DISubprogram *SP = DIL->getScope()->getSubprogram();
601     if (!SP)
602       return nullptr;
603     S.push_back(LineLocation(getOffset(DIL->getLine(), SP->getLine()),
604                              DIL->getDiscriminator()));
605   }
606   if (S.size() == 0)
607     return Samples;
608   const FunctionSamples *FS = Samples;
609   for (int i = S.size() - 1; i >= 0 && FS != nullptr; i--) {
610     FS = FS->findFunctionSamplesAt(S[i]);
611   }
612   return FS;
613 }
614 
615 
616 /// \brief Iteratively inline hot callsites of a function.
617 ///
618 /// Iteratively traverse all callsites of the function \p F, and find if
619 /// the corresponding inlined instance exists and is hot in profile. If
620 /// it is hot enough, inline the callsites and adds new callsites of the
621 /// callee into the caller.
622 ///
623 /// TODO: investigate the possibility of not invoking InlineFunction directly.
624 ///
625 /// \param F function to perform iterative inlining.
626 ///
627 /// \returns True if there is any inline happened.
628 bool SampleProfileLoader::inlineHotFunctions(Function &F) {
629   bool Changed = false;
630   LLVMContext &Ctx = F.getContext();
631   std::function<AssumptionCache &(Function &)> GetAssumptionCache = [&](
632       Function &F) -> AssumptionCache & { return ACT->getAssumptionCache(F); };
633   while (true) {
634     bool LocalChanged = false;
635     SmallVector<CallInst *, 10> CIS;
636     for (auto &BB : F) {
637       for (auto &I : BB.getInstList()) {
638         CallInst *CI = dyn_cast<CallInst>(&I);
639         if (CI && callsiteIsHot(Samples, findCalleeFunctionSamples(*CI)))
640           CIS.push_back(CI);
641       }
642     }
643     for (auto CI : CIS) {
644       InlineFunctionInfo IFI(nullptr, ACT ? &GetAssumptionCache : nullptr);
645       Function *CalledFunction = CI->getCalledFunction();
646       DebugLoc DLoc = CI->getDebugLoc();
647       uint64_t NumSamples = findCalleeFunctionSamples(*CI)->getTotalSamples();
648       if (InlineFunction(CI, IFI)) {
649         LocalChanged = true;
650         emitOptimizationRemark(Ctx, DEBUG_TYPE, F, DLoc,
651                                Twine("inlined hot callee '") +
652                                    CalledFunction->getName() + "' with " +
653                                    Twine(NumSamples) + " samples into '" +
654                                    F.getName() + "'");
655       }
656     }
657     if (LocalChanged) {
658       Changed = true;
659     } else {
660       break;
661     }
662   }
663   return Changed;
664 }
665 
666 /// \brief Find equivalence classes for the given block.
667 ///
668 /// This finds all the blocks that are guaranteed to execute the same
669 /// number of times as \p BB1. To do this, it traverses all the
670 /// descendants of \p BB1 in the dominator or post-dominator tree.
671 ///
672 /// A block BB2 will be in the same equivalence class as \p BB1 if
673 /// the following holds:
674 ///
675 /// 1- \p BB1 is a descendant of BB2 in the opposite tree. So, if BB2
676 ///    is a descendant of \p BB1 in the dominator tree, then BB2 should
677 ///    dominate BB1 in the post-dominator tree.
678 ///
679 /// 2- Both BB2 and \p BB1 must be in the same loop.
680 ///
681 /// For every block BB2 that meets those two requirements, we set BB2's
682 /// equivalence class to \p BB1.
683 ///
684 /// \param BB1  Block to check.
685 /// \param Descendants  Descendants of \p BB1 in either the dom or pdom tree.
686 /// \param DomTree  Opposite dominator tree. If \p Descendants is filled
687 ///                 with blocks from \p BB1's dominator tree, then
688 ///                 this is the post-dominator tree, and vice versa.
689 void SampleProfileLoader::findEquivalencesFor(
690     BasicBlock *BB1, ArrayRef<BasicBlock *> Descendants,
691     DominatorTreeBase<BasicBlock> *DomTree) {
692   const BasicBlock *EC = EquivalenceClass[BB1];
693   uint64_t Weight = BlockWeights[EC];
694   for (const auto *BB2 : Descendants) {
695     bool IsDomParent = DomTree->dominates(BB2, BB1);
696     bool IsInSameLoop = LI->getLoopFor(BB1) == LI->getLoopFor(BB2);
697     if (BB1 != BB2 && IsDomParent && IsInSameLoop) {
698       EquivalenceClass[BB2] = EC;
699       // If BB2 is visited, then the entire EC should be marked as visited.
700       if (VisitedBlocks.count(BB2)) {
701         VisitedBlocks.insert(EC);
702       }
703 
704       // If BB2 is heavier than BB1, make BB2 have the same weight
705       // as BB1.
706       //
707       // Note that we don't worry about the opposite situation here
708       // (when BB2 is lighter than BB1). We will deal with this
709       // during the propagation phase. Right now, we just want to
710       // make sure that BB1 has the largest weight of all the
711       // members of its equivalence set.
712       Weight = std::max(Weight, BlockWeights[BB2]);
713     }
714   }
715   if (EC == &EC->getParent()->getEntryBlock()) {
716     BlockWeights[EC] = Samples->getHeadSamples() + 1;
717   } else {
718     BlockWeights[EC] = Weight;
719   }
720 }
721 
722 /// \brief Find equivalence classes.
723 ///
724 /// Since samples may be missing from blocks, we can fill in the gaps by setting
725 /// the weights of all the blocks in the same equivalence class to the same
726 /// weight. To compute the concept of equivalence, we use dominance and loop
727 /// information. Two blocks B1 and B2 are in the same equivalence class if B1
728 /// dominates B2, B2 post-dominates B1 and both are in the same loop.
729 ///
730 /// \param F The function to query.
731 void SampleProfileLoader::findEquivalenceClasses(Function &F) {
732   SmallVector<BasicBlock *, 8> DominatedBBs;
733   DEBUG(dbgs() << "\nBlock equivalence classes\n");
734   // Find equivalence sets based on dominance and post-dominance information.
735   for (auto &BB : F) {
736     BasicBlock *BB1 = &BB;
737 
738     // Compute BB1's equivalence class once.
739     if (EquivalenceClass.count(BB1)) {
740       DEBUG(printBlockEquivalence(dbgs(), BB1));
741       continue;
742     }
743 
744     // By default, blocks are in their own equivalence class.
745     EquivalenceClass[BB1] = BB1;
746 
747     // Traverse all the blocks dominated by BB1. We are looking for
748     // every basic block BB2 such that:
749     //
750     // 1- BB1 dominates BB2.
751     // 2- BB2 post-dominates BB1.
752     // 3- BB1 and BB2 are in the same loop nest.
753     //
754     // If all those conditions hold, it means that BB2 is executed
755     // as many times as BB1, so they are placed in the same equivalence
756     // class by making BB2's equivalence class be BB1.
757     DominatedBBs.clear();
758     DT->getDescendants(BB1, DominatedBBs);
759     findEquivalencesFor(BB1, DominatedBBs, PDT.get());
760 
761     DEBUG(printBlockEquivalence(dbgs(), BB1));
762   }
763 
764   // Assign weights to equivalence classes.
765   //
766   // All the basic blocks in the same equivalence class will execute
767   // the same number of times. Since we know that the head block in
768   // each equivalence class has the largest weight, assign that weight
769   // to all the blocks in that equivalence class.
770   DEBUG(dbgs() << "\nAssign the same weight to all blocks in the same class\n");
771   for (auto &BI : F) {
772     const BasicBlock *BB = &BI;
773     const BasicBlock *EquivBB = EquivalenceClass[BB];
774     if (BB != EquivBB)
775       BlockWeights[BB] = BlockWeights[EquivBB];
776     DEBUG(printBlockWeight(dbgs(), BB));
777   }
778 }
779 
780 /// \brief Visit the given edge to decide if it has a valid weight.
781 ///
782 /// If \p E has not been visited before, we copy to \p UnknownEdge
783 /// and increment the count of unknown edges.
784 ///
785 /// \param E  Edge to visit.
786 /// \param NumUnknownEdges  Current number of unknown edges.
787 /// \param UnknownEdge  Set if E has not been visited before.
788 ///
789 /// \returns E's weight, if known. Otherwise, return 0.
790 uint64_t SampleProfileLoader::visitEdge(Edge E, unsigned *NumUnknownEdges,
791                                         Edge *UnknownEdge) {
792   if (!VisitedEdges.count(E)) {
793     (*NumUnknownEdges)++;
794     *UnknownEdge = E;
795     return 0;
796   }
797 
798   return EdgeWeights[E];
799 }
800 
801 /// \brief Propagate weights through incoming/outgoing edges.
802 ///
803 /// If the weight of a basic block is known, and there is only one edge
804 /// with an unknown weight, we can calculate the weight of that edge.
805 ///
806 /// Similarly, if all the edges have a known count, we can calculate the
807 /// count of the basic block, if needed.
808 ///
809 /// \param F  Function to process.
810 /// \param UpdateBlockCount  Whether we should update basic block counts that
811 ///                          has already been annotated.
812 ///
813 /// \returns  True if new weights were assigned to edges or blocks.
814 bool SampleProfileLoader::propagateThroughEdges(Function &F,
815                                                 bool UpdateBlockCount) {
816   bool Changed = false;
817   DEBUG(dbgs() << "\nPropagation through edges\n");
818   for (const auto &BI : F) {
819     const BasicBlock *BB = &BI;
820     const BasicBlock *EC = EquivalenceClass[BB];
821 
822     // Visit all the predecessor and successor edges to determine
823     // which ones have a weight assigned already. Note that it doesn't
824     // matter that we only keep track of a single unknown edge. The
825     // only case we are interested in handling is when only a single
826     // edge is unknown (see setEdgeOrBlockWeight).
827     for (unsigned i = 0; i < 2; i++) {
828       uint64_t TotalWeight = 0;
829       unsigned NumUnknownEdges = 0, NumTotalEdges = 0;
830       Edge UnknownEdge, SelfReferentialEdge, SingleEdge;
831 
832       if (i == 0) {
833         // First, visit all predecessor edges.
834         NumTotalEdges = Predecessors[BB].size();
835         for (auto *Pred : Predecessors[BB]) {
836           Edge E = std::make_pair(Pred, BB);
837           TotalWeight += visitEdge(E, &NumUnknownEdges, &UnknownEdge);
838           if (E.first == E.second)
839             SelfReferentialEdge = E;
840         }
841         if (NumTotalEdges == 1) {
842           SingleEdge = std::make_pair(Predecessors[BB][0], BB);
843         }
844       } else {
845         // On the second round, visit all successor edges.
846         NumTotalEdges = Successors[BB].size();
847         for (auto *Succ : Successors[BB]) {
848           Edge E = std::make_pair(BB, Succ);
849           TotalWeight += visitEdge(E, &NumUnknownEdges, &UnknownEdge);
850         }
851         if (NumTotalEdges == 1) {
852           SingleEdge = std::make_pair(BB, Successors[BB][0]);
853         }
854       }
855 
856       // After visiting all the edges, there are three cases that we
857       // can handle immediately:
858       //
859       // - All the edge weights are known (i.e., NumUnknownEdges == 0).
860       //   In this case, we simply check that the sum of all the edges
861       //   is the same as BB's weight. If not, we change BB's weight
862       //   to match. Additionally, if BB had not been visited before,
863       //   we mark it visited.
864       //
865       // - Only one edge is unknown and BB has already been visited.
866       //   In this case, we can compute the weight of the edge by
867       //   subtracting the total block weight from all the known
868       //   edge weights. If the edges weight more than BB, then the
869       //   edge of the last remaining edge is set to zero.
870       //
871       // - There exists a self-referential edge and the weight of BB is
872       //   known. In this case, this edge can be based on BB's weight.
873       //   We add up all the other known edges and set the weight on
874       //   the self-referential edge as we did in the previous case.
875       //
876       // In any other case, we must continue iterating. Eventually,
877       // all edges will get a weight, or iteration will stop when
878       // it reaches SampleProfileMaxPropagateIterations.
879       if (NumUnknownEdges <= 1) {
880         uint64_t &BBWeight = BlockWeights[EC];
881         if (NumUnknownEdges == 0) {
882           if (!VisitedBlocks.count(EC)) {
883             // If we already know the weight of all edges, the weight of the
884             // basic block can be computed. It should be no larger than the sum
885             // of all edge weights.
886             if (TotalWeight > BBWeight) {
887               BBWeight = TotalWeight;
888               Changed = true;
889               DEBUG(dbgs() << "All edge weights for " << BB->getName()
890                            << " known. Set weight for block: ";
891                     printBlockWeight(dbgs(), BB););
892             }
893           } else if (NumTotalEdges == 1 &&
894                      EdgeWeights[SingleEdge] < BlockWeights[EC]) {
895             // If there is only one edge for the visited basic block, use the
896             // block weight to adjust edge weight if edge weight is smaller.
897             EdgeWeights[SingleEdge] = BlockWeights[EC];
898             Changed = true;
899           }
900         } else if (NumUnknownEdges == 1 && VisitedBlocks.count(EC)) {
901           // If there is a single unknown edge and the block has been
902           // visited, then we can compute E's weight.
903           if (BBWeight >= TotalWeight)
904             EdgeWeights[UnknownEdge] = BBWeight - TotalWeight;
905           else
906             EdgeWeights[UnknownEdge] = 0;
907           const BasicBlock *OtherEC;
908           if (i == 0)
909             OtherEC = EquivalenceClass[UnknownEdge.first];
910           else
911             OtherEC = EquivalenceClass[UnknownEdge.second];
912           // Edge weights should never exceed the BB weights it connects.
913           if (VisitedBlocks.count(OtherEC) &&
914               EdgeWeights[UnknownEdge] > BlockWeights[OtherEC])
915             EdgeWeights[UnknownEdge] = BlockWeights[OtherEC];
916           VisitedEdges.insert(UnknownEdge);
917           Changed = true;
918           DEBUG(dbgs() << "Set weight for edge: ";
919                 printEdgeWeight(dbgs(), UnknownEdge));
920         }
921       } else if (VisitedBlocks.count(EC) && BlockWeights[EC] == 0) {
922         // If a block Weights 0, all its in/out edges should weight 0.
923         if (i == 0) {
924           for (auto *Pred : Predecessors[BB]) {
925             Edge E = std::make_pair(Pred, BB);
926             EdgeWeights[E] = 0;
927             VisitedEdges.insert(E);
928           }
929         } else {
930           for (auto *Succ : Successors[BB]) {
931             Edge E = std::make_pair(BB, Succ);
932             EdgeWeights[E] = 0;
933             VisitedEdges.insert(E);
934           }
935         }
936       } else if (SelfReferentialEdge.first && VisitedBlocks.count(EC)) {
937         uint64_t &BBWeight = BlockWeights[BB];
938         // We have a self-referential edge and the weight of BB is known.
939         if (BBWeight >= TotalWeight)
940           EdgeWeights[SelfReferentialEdge] = BBWeight - TotalWeight;
941         else
942           EdgeWeights[SelfReferentialEdge] = 0;
943         VisitedEdges.insert(SelfReferentialEdge);
944         Changed = true;
945         DEBUG(dbgs() << "Set self-referential edge weight to: ";
946               printEdgeWeight(dbgs(), SelfReferentialEdge));
947       }
948       if (UpdateBlockCount && !VisitedBlocks.count(EC) && TotalWeight > 0) {
949         BlockWeights[EC] = TotalWeight;
950         VisitedBlocks.insert(EC);
951         Changed = true;
952       }
953     }
954   }
955 
956   return Changed;
957 }
958 
959 /// \brief Build in/out edge lists for each basic block in the CFG.
960 ///
961 /// We are interested in unique edges. If a block B1 has multiple
962 /// edges to another block B2, we only add a single B1->B2 edge.
963 void SampleProfileLoader::buildEdges(Function &F) {
964   for (auto &BI : F) {
965     BasicBlock *B1 = &BI;
966 
967     // Add predecessors for B1.
968     SmallPtrSet<BasicBlock *, 16> Visited;
969     if (!Predecessors[B1].empty())
970       llvm_unreachable("Found a stale predecessors list in a basic block.");
971     for (pred_iterator PI = pred_begin(B1), PE = pred_end(B1); PI != PE; ++PI) {
972       BasicBlock *B2 = *PI;
973       if (Visited.insert(B2).second)
974         Predecessors[B1].push_back(B2);
975     }
976 
977     // Add successors for B1.
978     Visited.clear();
979     if (!Successors[B1].empty())
980       llvm_unreachable("Found a stale successors list in a basic block.");
981     for (succ_iterator SI = succ_begin(B1), SE = succ_end(B1); SI != SE; ++SI) {
982       BasicBlock *B2 = *SI;
983       if (Visited.insert(B2).second)
984         Successors[B1].push_back(B2);
985     }
986   }
987 }
988 
989 /// \brief Propagate weights into edges
990 ///
991 /// The following rules are applied to every block BB in the CFG:
992 ///
993 /// - If BB has a single predecessor/successor, then the weight
994 ///   of that edge is the weight of the block.
995 ///
996 /// - If all incoming or outgoing edges are known except one, and the
997 ///   weight of the block is already known, the weight of the unknown
998 ///   edge will be the weight of the block minus the sum of all the known
999 ///   edges. If the sum of all the known edges is larger than BB's weight,
1000 ///   we set the unknown edge weight to zero.
1001 ///
1002 /// - If there is a self-referential edge, and the weight of the block is
1003 ///   known, the weight for that edge is set to the weight of the block
1004 ///   minus the weight of the other incoming edges to that block (if
1005 ///   known).
1006 void SampleProfileLoader::propagateWeights(Function &F) {
1007   bool Changed = true;
1008   unsigned I = 0;
1009 
1010   // Add an entry count to the function using the samples gathered
1011   // at the function entry.
1012   F.setEntryCount(Samples->getHeadSamples() + 1);
1013 
1014   // If BB weight is larger than its corresponding loop's header BB weight,
1015   // use the BB weight to replace the loop header BB weight.
1016   for (auto &BI : F) {
1017     BasicBlock *BB = &BI;
1018     Loop *L = LI->getLoopFor(BB);
1019     if (!L) {
1020       continue;
1021     }
1022     BasicBlock *Header = L->getHeader();
1023     if (Header && BlockWeights[BB] > BlockWeights[Header]) {
1024       BlockWeights[Header] = BlockWeights[BB];
1025     }
1026   }
1027 
1028   // Before propagation starts, build, for each block, a list of
1029   // unique predecessors and successors. This is necessary to handle
1030   // identical edges in multiway branches. Since we visit all blocks and all
1031   // edges of the CFG, it is cleaner to build these lists once at the start
1032   // of the pass.
1033   buildEdges(F);
1034 
1035   // Propagate until we converge or we go past the iteration limit.
1036   while (Changed && I++ < SampleProfileMaxPropagateIterations) {
1037     Changed = propagateThroughEdges(F, false);
1038   }
1039 
1040   // The first propagation propagates BB counts from annotated BBs to unknown
1041   // BBs. The 2nd propagation pass resets edges weights, and use all BB weights
1042   // to propagate edge weights.
1043   VisitedEdges.clear();
1044   Changed = true;
1045   while (Changed && I++ < SampleProfileMaxPropagateIterations) {
1046     Changed = propagateThroughEdges(F, false);
1047   }
1048 
1049   // The 3rd propagation pass allows adjust annotated BB weights that are
1050   // obviously wrong.
1051   Changed = true;
1052   while (Changed && I++ < SampleProfileMaxPropagateIterations) {
1053     Changed = propagateThroughEdges(F, true);
1054   }
1055 
1056   // Generate MD_prof metadata for every branch instruction using the
1057   // edge weights computed during propagation.
1058   DEBUG(dbgs() << "\nPropagation complete. Setting branch weights\n");
1059   LLVMContext &Ctx = F.getContext();
1060   MDBuilder MDB(Ctx);
1061   for (auto &BI : F) {
1062     BasicBlock *BB = &BI;
1063 
1064     if (BlockWeights[BB]) {
1065       for (auto &I : BB->getInstList()) {
1066         if (CallInst *CI = dyn_cast<CallInst>(&I)) {
1067           if (!dyn_cast<IntrinsicInst>(&I)) {
1068             SmallVector<uint32_t, 1> Weights;
1069             Weights.push_back(BlockWeights[BB]);
1070             CI->setMetadata(LLVMContext::MD_prof,
1071                             MDB.createBranchWeights(Weights));
1072           }
1073         }
1074       }
1075     }
1076     TerminatorInst *TI = BB->getTerminator();
1077     if (TI->getNumSuccessors() == 1)
1078       continue;
1079     if (!isa<BranchInst>(TI) && !isa<SwitchInst>(TI))
1080       continue;
1081 
1082     DEBUG(dbgs() << "\nGetting weights for branch at line "
1083                  << TI->getDebugLoc().getLine() << ".\n");
1084     SmallVector<uint32_t, 4> Weights;
1085     uint32_t MaxWeight = 0;
1086     DebugLoc MaxDestLoc;
1087     for (unsigned I = 0; I < TI->getNumSuccessors(); ++I) {
1088       BasicBlock *Succ = TI->getSuccessor(I);
1089       Edge E = std::make_pair(BB, Succ);
1090       uint64_t Weight = EdgeWeights[E];
1091       DEBUG(dbgs() << "\t"; printEdgeWeight(dbgs(), E));
1092       // Use uint32_t saturated arithmetic to adjust the incoming weights,
1093       // if needed. Sample counts in profiles are 64-bit unsigned values,
1094       // but internally branch weights are expressed as 32-bit values.
1095       if (Weight > std::numeric_limits<uint32_t>::max()) {
1096         DEBUG(dbgs() << " (saturated due to uint32_t overflow)");
1097         Weight = std::numeric_limits<uint32_t>::max();
1098       }
1099       // Weight is added by one to avoid propagation errors introduced by
1100       // 0 weights.
1101       Weights.push_back(static_cast<uint32_t>(Weight + 1));
1102       if (Weight != 0) {
1103         if (Weight > MaxWeight) {
1104           MaxWeight = Weight;
1105           MaxDestLoc = Succ->getFirstNonPHIOrDbgOrLifetime()->getDebugLoc();
1106         }
1107       }
1108     }
1109 
1110     // Only set weights if there is at least one non-zero weight.
1111     // In any other case, let the analyzer set weights.
1112     DEBUG(dbgs() << "SUCCESS. Found non-zero weights.\n");
1113     TI->setMetadata(llvm::LLVMContext::MD_prof,
1114                     MDB.createBranchWeights(Weights));
1115     DebugLoc BranchLoc = TI->getDebugLoc();
1116     emitOptimizationRemark(
1117         Ctx, DEBUG_TYPE, F, MaxDestLoc,
1118         Twine("most popular destination for conditional branches at ") +
1119             ((BranchLoc) ? Twine(BranchLoc->getFilename() + ":" +
1120                                  Twine(BranchLoc.getLine()) + ":" +
1121                                  Twine(BranchLoc.getCol()))
1122                          : Twine("<UNKNOWN LOCATION>")));
1123   }
1124 }
1125 
1126 /// \brief Get the line number for the function header.
1127 ///
1128 /// This looks up function \p F in the current compilation unit and
1129 /// retrieves the line number where the function is defined. This is
1130 /// line 0 for all the samples read from the profile file. Every line
1131 /// number is relative to this line.
1132 ///
1133 /// \param F  Function object to query.
1134 ///
1135 /// \returns the line number where \p F is defined. If it returns 0,
1136 ///          it means that there is no debug information available for \p F.
1137 unsigned SampleProfileLoader::getFunctionLoc(Function &F) {
1138   if (DISubprogram *S = F.getSubprogram())
1139     return S->getLine();
1140 
1141   // If the start of \p F is missing, emit a diagnostic to inform the user
1142   // about the missed opportunity.
1143   F.getContext().diagnose(DiagnosticInfoSampleProfile(
1144       "No debug information found in function " + F.getName() +
1145           ": Function profile not used",
1146       DS_Warning));
1147   return 0;
1148 }
1149 
1150 void SampleProfileLoader::computeDominanceAndLoopInfo(Function &F) {
1151   DT.reset(new DominatorTree);
1152   DT->recalculate(F);
1153 
1154   PDT.reset(new DominatorTreeBase<BasicBlock>(true));
1155   PDT->recalculate(F);
1156 
1157   LI.reset(new LoopInfo);
1158   LI->analyze(*DT);
1159 }
1160 
1161 /// \brief Generate branch weight metadata for all branches in \p F.
1162 ///
1163 /// Branch weights are computed out of instruction samples using a
1164 /// propagation heuristic. Propagation proceeds in 3 phases:
1165 ///
1166 /// 1- Assignment of block weights. All the basic blocks in the function
1167 ///    are initial assigned the same weight as their most frequently
1168 ///    executed instruction.
1169 ///
1170 /// 2- Creation of equivalence classes. Since samples may be missing from
1171 ///    blocks, we can fill in the gaps by setting the weights of all the
1172 ///    blocks in the same equivalence class to the same weight. To compute
1173 ///    the concept of equivalence, we use dominance and loop information.
1174 ///    Two blocks B1 and B2 are in the same equivalence class if B1
1175 ///    dominates B2, B2 post-dominates B1 and both are in the same loop.
1176 ///
1177 /// 3- Propagation of block weights into edges. This uses a simple
1178 ///    propagation heuristic. The following rules are applied to every
1179 ///    block BB in the CFG:
1180 ///
1181 ///    - If BB has a single predecessor/successor, then the weight
1182 ///      of that edge is the weight of the block.
1183 ///
1184 ///    - If all the edges are known except one, and the weight of the
1185 ///      block is already known, the weight of the unknown edge will
1186 ///      be the weight of the block minus the sum of all the known
1187 ///      edges. If the sum of all the known edges is larger than BB's weight,
1188 ///      we set the unknown edge weight to zero.
1189 ///
1190 ///    - If there is a self-referential edge, and the weight of the block is
1191 ///      known, the weight for that edge is set to the weight of the block
1192 ///      minus the weight of the other incoming edges to that block (if
1193 ///      known).
1194 ///
1195 /// Since this propagation is not guaranteed to finalize for every CFG, we
1196 /// only allow it to proceed for a limited number of iterations (controlled
1197 /// by -sample-profile-max-propagate-iterations).
1198 ///
1199 /// FIXME: Try to replace this propagation heuristic with a scheme
1200 /// that is guaranteed to finalize. A work-list approach similar to
1201 /// the standard value propagation algorithm used by SSA-CCP might
1202 /// work here.
1203 ///
1204 /// Once all the branch weights are computed, we emit the MD_prof
1205 /// metadata on BB using the computed values for each of its branches.
1206 ///
1207 /// \param F The function to query.
1208 ///
1209 /// \returns true if \p F was modified. Returns false, otherwise.
1210 bool SampleProfileLoader::emitAnnotations(Function &F) {
1211   bool Changed = false;
1212 
1213   if (getFunctionLoc(F) == 0)
1214     return false;
1215 
1216   DEBUG(dbgs() << "Line number for the first instruction in " << F.getName()
1217                << ": " << getFunctionLoc(F) << "\n");
1218 
1219   Changed |= inlineHotFunctions(F);
1220 
1221   // Compute basic block weights.
1222   Changed |= computeBlockWeights(F);
1223 
1224   if (Changed) {
1225     // Compute dominance and loop info needed for propagation.
1226     computeDominanceAndLoopInfo(F);
1227 
1228     // Find equivalence classes.
1229     findEquivalenceClasses(F);
1230 
1231     // Propagate weights to all edges.
1232     propagateWeights(F);
1233   }
1234 
1235   // If coverage checking was requested, compute it now.
1236   if (SampleProfileRecordCoverage) {
1237     unsigned Used = CoverageTracker.countUsedRecords(Samples);
1238     unsigned Total = CoverageTracker.countBodyRecords(Samples);
1239     unsigned Coverage = CoverageTracker.computeCoverage(Used, Total);
1240     if (Coverage < SampleProfileRecordCoverage) {
1241       F.getContext().diagnose(DiagnosticInfoSampleProfile(
1242           F.getSubprogram()->getFilename(), getFunctionLoc(F),
1243           Twine(Used) + " of " + Twine(Total) + " available profile records (" +
1244               Twine(Coverage) + "%) were applied",
1245           DS_Warning));
1246     }
1247   }
1248 
1249   if (SampleProfileSampleCoverage) {
1250     uint64_t Used = CoverageTracker.getTotalUsedSamples();
1251     uint64_t Total = CoverageTracker.countBodySamples(Samples);
1252     unsigned Coverage = CoverageTracker.computeCoverage(Used, Total);
1253     if (Coverage < SampleProfileSampleCoverage) {
1254       F.getContext().diagnose(DiagnosticInfoSampleProfile(
1255           F.getSubprogram()->getFilename(), getFunctionLoc(F),
1256           Twine(Used) + " of " + Twine(Total) + " available profile samples (" +
1257               Twine(Coverage) + "%) were applied",
1258           DS_Warning));
1259     }
1260   }
1261   return Changed;
1262 }
1263 
1264 char SampleProfileLoaderLegacyPass::ID = 0;
1265 INITIALIZE_PASS_BEGIN(SampleProfileLoaderLegacyPass, "sample-profile",
1266                 "Sample Profile loader", false, false)
1267 INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker)
1268 INITIALIZE_PASS_END(SampleProfileLoaderLegacyPass, "sample-profile",
1269                 "Sample Profile loader", false, false)
1270 
1271 bool SampleProfileLoader::doInitialization(Module &M) {
1272   auto &Ctx = M.getContext();
1273   auto ReaderOrErr = SampleProfileReader::create(Filename, Ctx);
1274   if (std::error_code EC = ReaderOrErr.getError()) {
1275     std::string Msg = "Could not open profile: " + EC.message();
1276     Ctx.diagnose(DiagnosticInfoSampleProfile(Filename, Msg));
1277     return false;
1278   }
1279   Reader = std::move(ReaderOrErr.get());
1280   ProfileIsValid = (Reader->read() == sampleprof_error::success);
1281   return true;
1282 }
1283 
1284 ModulePass *llvm::createSampleProfileLoaderPass() {
1285   return new SampleProfileLoaderLegacyPass(SampleProfileFile);
1286 }
1287 
1288 ModulePass *llvm::createSampleProfileLoaderPass(StringRef Name) {
1289   return new SampleProfileLoaderLegacyPass(Name);
1290 }
1291 
1292 bool SampleProfileLoader::runOnModule(Module &M) {
1293   if (!ProfileIsValid)
1294     return false;
1295 
1296   // Compute the total number of samples collected in this profile.
1297   for (const auto &I : Reader->getProfiles())
1298     TotalCollectedSamples += I.second.getTotalSamples();
1299 
1300   bool retval = false;
1301   for (auto &F : M)
1302     if (!F.isDeclaration()) {
1303       clearFunctionData();
1304       retval |= runOnFunction(F);
1305     }
1306   M.setProfileSummary(Reader->getSummary().getMD(M.getContext()));
1307   return retval;
1308 }
1309 
1310 bool SampleProfileLoaderLegacyPass::runOnModule(Module &M) {
1311   // FIXME: pass in AssumptionCache correctly for the new pass manager.
1312   SampleLoader.setACT(&getAnalysis<AssumptionCacheTracker>());
1313   return SampleLoader.runOnModule(M);
1314 }
1315 
1316 bool SampleProfileLoader::runOnFunction(Function &F) {
1317   F.setEntryCount(0);
1318   Samples = Reader->getSamplesFor(F);
1319   if (!Samples->empty())
1320     return emitAnnotations(F);
1321   return false;
1322 }
1323 
1324 PreservedAnalyses SampleProfileLoaderPass::run(Module &M,
1325                                                ModuleAnalysisManager &AM) {
1326 
1327   SampleProfileLoader SampleLoader(SampleProfileFile);
1328 
1329   SampleLoader.doInitialization(M);
1330 
1331   if (!SampleLoader.runOnModule(M))
1332     return PreservedAnalyses::all();
1333 
1334   return PreservedAnalyses::none();
1335 }
1336