llvm/lib/Transforms/IPO/SampleProfile.cpp
Dehao Chen 412d6685da Make HeaderLineno a local variable.
http://reviews.llvm.org/D13576

As we are using hierarchical profile, there is no need to keep HeaderLineno a member variable. This is because each level of the inline stack will have its own header lineno. One should use the head lineno of its own inline stack level instead of the actual symbol.


git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@249848 91177308-0d34-0410-b5e6-96231b3b80d8
2015-10-09 16:50:16 +00:00

908 lines
33 KiB
C++

//===- SampleProfile.cpp - Incorporate sample profiles into the IR --------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
//
// This file implements the SampleProfileLoader transformation. This pass
// reads a profile file generated by a sampling profiler (e.g. Linux Perf -
// http://perf.wiki.kernel.org/) and generates IR metadata to reflect the
// profile information in the given profile.
//
// This pass generates branch weight annotations on the IR:
//
// - prof: Represents branch weights. This annotation is added to branches
// to indicate the weights of each edge coming out of the branch.
// The weight of each edge is the weight of the target block for
// that edge. The weight of a block B is computed as the maximum
// number of samples found in B.
//
//===----------------------------------------------------------------------===//
#include "llvm/ADT/DenseMap.h"
#include "llvm/ADT/SmallPtrSet.h"
#include "llvm/ADT/SmallSet.h"
#include "llvm/ADT/StringRef.h"
#include "llvm/Analysis/LoopInfo.h"
#include "llvm/Analysis/PostDominators.h"
#include "llvm/IR/Constants.h"
#include "llvm/IR/DebugInfo.h"
#include "llvm/IR/DiagnosticInfo.h"
#include "llvm/IR/Dominators.h"
#include "llvm/IR/Function.h"
#include "llvm/IR/InstIterator.h"
#include "llvm/IR/Instructions.h"
#include "llvm/IR/LLVMContext.h"
#include "llvm/IR/MDBuilder.h"
#include "llvm/IR/Metadata.h"
#include "llvm/IR/Module.h"
#include "llvm/Pass.h"
#include "llvm/ProfileData/SampleProfReader.h"
#include "llvm/Support/CommandLine.h"
#include "llvm/Support/Debug.h"
#include "llvm/Support/ErrorOr.h"
#include "llvm/Support/raw_ostream.h"
#include "llvm/Transforms/IPO.h"
#include "llvm/Transforms/Utils/Cloning.h"
#include <cctype>
using namespace llvm;
using namespace sampleprof;
#define DEBUG_TYPE "sample-profile"
// Command line option to specify the file to read samples from. This is
// mainly used for debugging.
static cl::opt<std::string> SampleProfileFile(
"sample-profile-file", cl::init(""), cl::value_desc("filename"),
cl::desc("Profile file loaded by -sample-profile"), cl::Hidden);
static cl::opt<unsigned> SampleProfileMaxPropagateIterations(
"sample-profile-max-propagate-iterations", cl::init(100),
cl::desc("Maximum number of iterations to go through when propagating "
"sample block/edge weights through the CFG."));
namespace {
typedef DenseMap<const BasicBlock *, unsigned> BlockWeightMap;
typedef DenseMap<const BasicBlock *, const BasicBlock *> EquivalenceClassMap;
typedef std::pair<const BasicBlock *, const BasicBlock *> Edge;
typedef DenseMap<Edge, unsigned> EdgeWeightMap;
typedef DenseMap<const BasicBlock *, SmallVector<const BasicBlock *, 8>>
BlockEdgeMap;
/// \brief Sample profile pass.
///
/// This pass reads profile data from the file specified by
/// -sample-profile-file and annotates every affected function with the
/// profile information found in that file.
class SampleProfileLoader : public ModulePass {
public:
// Class identification, replacement for typeinfo
static char ID;
SampleProfileLoader(StringRef Name = SampleProfileFile)
: ModulePass(ID), DT(nullptr), PDT(nullptr), LI(nullptr), Reader(),
Samples(nullptr), Filename(Name), ProfileIsValid(false) {
initializeSampleProfileLoaderPass(*PassRegistry::getPassRegistry());
}
bool doInitialization(Module &M) override;
void dump() { Reader->dump(); }
const char *getPassName() const override { return "Sample profile pass"; }
bool runOnModule(Module &M) override;
void getAnalysisUsage(AnalysisUsage &AU) const override {
AU.setPreservesCFG();
}
protected:
bool runOnFunction(Function &F);
unsigned getFunctionLoc(Function &F);
bool emitAnnotations(Function &F);
ErrorOr<unsigned> getInstWeight(const Instruction &I) const;
ErrorOr<unsigned> getBlockWeight(const BasicBlock *BB) const;
const FunctionSamples *findCalleeFunctionSamples(const CallInst &I) const;
const FunctionSamples *findFunctionSamples(const Instruction &I) const;
bool inlineHotFunctions(Function &F);
void printEdgeWeight(raw_ostream &OS, Edge E);
void printBlockWeight(raw_ostream &OS, const BasicBlock *BB) const;
void printBlockEquivalence(raw_ostream &OS, const BasicBlock *BB);
bool computeBlockWeights(Function &F);
void findEquivalenceClasses(Function &F);
void findEquivalencesFor(BasicBlock *BB1,
SmallVector<BasicBlock *, 8> Descendants,
DominatorTreeBase<BasicBlock> *DomTree);
void propagateWeights(Function &F);
unsigned visitEdge(Edge E, unsigned *NumUnknownEdges, Edge *UnknownEdge);
void buildEdges(Function &F);
bool propagateThroughEdges(Function &F);
void computeDominanceAndLoopInfo(Function &F);
/// \brief Map basic blocks to their computed weights.
///
/// The weight of a basic block is defined to be the maximum
/// of all the instruction weights in that block.
BlockWeightMap BlockWeights;
/// \brief Map edges to their computed weights.
///
/// Edge weights are computed by propagating basic block weights in
/// SampleProfile::propagateWeights.
EdgeWeightMap EdgeWeights;
/// \brief Set of visited blocks during propagation.
SmallPtrSet<const BasicBlock *, 128> VisitedBlocks;
/// \brief Set of visited edges during propagation.
SmallSet<Edge, 128> VisitedEdges;
/// \brief Equivalence classes for block weights.
///
/// Two blocks BB1 and BB2 are in the same equivalence class if they
/// dominate and post-dominate each other, and they are in the same loop
/// nest. When this happens, the two blocks are guaranteed to execute
/// the same number of times.
EquivalenceClassMap EquivalenceClass;
/// \brief Dominance, post-dominance and loop information.
std::unique_ptr<DominatorTree> DT;
std::unique_ptr<DominatorTreeBase<BasicBlock>> PDT;
std::unique_ptr<LoopInfo> LI;
/// \brief Predecessors for each basic block in the CFG.
BlockEdgeMap Predecessors;
/// \brief Successors for each basic block in the CFG.
BlockEdgeMap Successors;
/// \brief Profile reader object.
std::unique_ptr<SampleProfileReader> Reader;
/// \brief Samples collected for the body of this function.
FunctionSamples *Samples;
/// \brief Name of the profile file to load.
StringRef Filename;
/// \brief Flag indicating whether the profile input loaded successfully.
bool ProfileIsValid;
};
}
/// \brief Print the weight of edge \p E on stream \p OS.
///
/// \param OS Stream to emit the output to.
/// \param E Edge to print.
void SampleProfileLoader::printEdgeWeight(raw_ostream &OS, Edge E) {
OS << "weight[" << E.first->getName() << "->" << E.second->getName()
<< "]: " << EdgeWeights[E] << "\n";
}
/// \brief Print the equivalence class of block \p BB on stream \p OS.
///
/// \param OS Stream to emit the output to.
/// \param BB Block to print.
void SampleProfileLoader::printBlockEquivalence(raw_ostream &OS,
const BasicBlock *BB) {
const BasicBlock *Equiv = EquivalenceClass[BB];
OS << "equivalence[" << BB->getName()
<< "]: " << ((Equiv) ? EquivalenceClass[BB]->getName() : "NONE") << "\n";
}
/// \brief Print the weight of block \p BB on stream \p OS.
///
/// \param OS Stream to emit the output to.
/// \param BB Block to print.
void SampleProfileLoader::printBlockWeight(raw_ostream &OS,
const BasicBlock *BB) const {
const auto &I = BlockWeights.find(BB);
unsigned W = (I == BlockWeights.end() ? 0 : I->second);
OS << "weight[" << BB->getName() << "]: " << W << "\n";
}
/// \brief Get the weight for an instruction.
///
/// The "weight" of an instruction \p Inst is the number of samples
/// collected on that instruction at runtime. To retrieve it, we
/// need to compute the line number of \p Inst relative to the start of its
/// function. We use HeaderLineno to compute the offset. We then
/// look up the samples collected for \p Inst using BodySamples.
///
/// \param Inst Instruction to query.
///
/// \returns the weight of \p Inst.
ErrorOr<unsigned>
SampleProfileLoader::getInstWeight(const Instruction &Inst) const {
DebugLoc DLoc = Inst.getDebugLoc();
if (!DLoc)
return std::error_code();
const FunctionSamples *FS = findFunctionSamples(Inst);
if (!FS)
return std::error_code();
const DILocation *DIL = DLoc;
unsigned Lineno = DLoc.getLine();
unsigned HeaderLineno = DIL->getScope()->getSubprogram()->getLine();
if (Lineno < HeaderLineno)
return std::error_code();
ErrorOr<unsigned> R =
FS->findSamplesAt(Lineno - HeaderLineno, DIL->getDiscriminator());
if (R)
DEBUG(dbgs() << " " << Lineno << "." << DIL->getDiscriminator() << ":"
<< Inst << " (line offset: " << Lineno - HeaderLineno << "."
<< DIL->getDiscriminator() << " - weight: " << R.get()
<< ")\n");
return R;
}
/// \brief Compute the weight of a basic block.
///
/// The weight of basic block \p BB is the maximum weight of all the
/// instructions in BB.
///
/// \param BB The basic block to query.
///
/// \returns the weight for \p BB.
ErrorOr<unsigned>
SampleProfileLoader::getBlockWeight(const BasicBlock *BB) const {
bool Found = false;
unsigned Weight = 0;
for (auto &I : BB->getInstList()) {
const ErrorOr<unsigned> &R = getInstWeight(I);
if (R && R.get() >= Weight) {
Weight = R.get();
Found = true;
}
}
if (Found)
return Weight;
else
return std::error_code();
}
/// \brief Compute and store the weights of every basic block.
///
/// This populates the BlockWeights map by computing
/// the weights of every basic block in the CFG.
///
/// \param F The function to query.
bool SampleProfileLoader::computeBlockWeights(Function &F) {
bool Changed = false;
DEBUG(dbgs() << "Block weights\n");
for (const auto &BB : F) {
ErrorOr<unsigned> Weight = getBlockWeight(&BB);
if (Weight) {
BlockWeights[&BB] = Weight.get();
VisitedBlocks.insert(&BB);
Changed = true;
}
DEBUG(printBlockWeight(dbgs(), &BB));
}
return Changed;
}
/// \brief Get the FunctionSamples for a call instruction.
///
/// The FunctionSamples of a call instruction \p Inst is the inlined
/// instance in which that call instruction is calling to. It contains
/// all samples that resides in the inlined instance. We first find the
/// inlined instance in which the call instruction is from, then we
/// traverse its children to find the callsite with the matching
/// location and callee function name.
///
/// \param Inst Call instruction to query.
///
/// \returns The FunctionSamples pointer to the inlined instance.
const FunctionSamples *
SampleProfileLoader::findCalleeFunctionSamples(const CallInst &Inst) const {
const DILocation *DIL = Inst.getDebugLoc();
if (!DIL) {
return nullptr;
}
DISubprogram *SP = DIL->getScope()->getSubprogram();
if (!SP || DIL->getLine() < SP->getLine())
return nullptr;
Function *CalleeFunc = Inst.getCalledFunction();
if (!CalleeFunc) {
return nullptr;
}
StringRef CalleeName = CalleeFunc->getName();
const FunctionSamples *FS = findFunctionSamples(Inst);
if (FS == nullptr)
return nullptr;
return FS->findFunctionSamplesAt(CallsiteLocation(
DIL->getLine() - SP->getLine(), DIL->getDiscriminator(), CalleeName));
}
/// \brief Get the FunctionSamples for an instruction.
///
/// The FunctionSamples of an instruction \p Inst is the inlined instance
/// in which that instruction is coming from. We traverse the inline stack
/// of that instruction, and match it with the tree nodes in the profile.
///
/// \param Inst Instruction to query.
///
/// \returns the FunctionSamples pointer to the inlined instance.
const FunctionSamples *
SampleProfileLoader::findFunctionSamples(const Instruction &Inst) const {
SmallVector<CallsiteLocation, 10> S;
const DILocation *DIL = Inst.getDebugLoc();
if (!DIL) {
return Samples;
}
StringRef CalleeName;
for (const DILocation *DIL = Inst.getDebugLoc(); DIL;
DIL = DIL->getInlinedAt()) {
DISubprogram *SP = DIL->getScope()->getSubprogram();
if (!SP || DIL->getLine() < SP->getLine())
return nullptr;
if (!CalleeName.empty()) {
S.push_back(CallsiteLocation(DIL->getLine() - SP->getLine(),
DIL->getDiscriminator(), CalleeName));
}
CalleeName = SP->getLinkageName();
}
if (S.size() == 0)
return Samples;
const FunctionSamples *FS = Samples;
for (int i = S.size() - 1; i >= 0 && FS != nullptr; i--) {
FS = FS->findFunctionSamplesAt(S[i]);
}
return FS;
}
/// \brief Iteratively inline hot callsites of a function.
///
/// Iteratively traverse all callsites of the function \p F, and find if
/// the corresponding inlined instance exists and is hot in profile. If
/// it is hot enough, inline the callsites and adds new callsites of the
/// callee into the caller.
///
/// TODO: investigate the possibility of not invoking InlineFunction directly.
///
/// \param F function to perform iterative inlining.
///
/// \returns True if there is any inline happened.
bool SampleProfileLoader::inlineHotFunctions(Function &F) {
bool Changed = false;
while (true) {
bool LocalChanged = false;
SmallVector<CallInst *, 10> CIS;
for (auto &BB : F) {
for (auto &I : BB.getInstList()) {
CallInst *CI = dyn_cast<CallInst>(&I);
if (CI) {
const FunctionSamples *FS = findCalleeFunctionSamples(*CI);
if (FS && FS->getTotalSamples() > 0) {
CIS.push_back(CI);
}
}
}
}
for (auto CI : CIS) {
InlineFunctionInfo IFI;
if (InlineFunction(CI, IFI))
LocalChanged = true;
}
if (LocalChanged) {
Changed = true;
} else {
break;
}
}
return Changed;
}
/// \brief Find equivalence classes for the given block.
///
/// This finds all the blocks that are guaranteed to execute the same
/// number of times as \p BB1. To do this, it traverses all the
/// descendants of \p BB1 in the dominator or post-dominator tree.
///
/// A block BB2 will be in the same equivalence class as \p BB1 if
/// the following holds:
///
/// 1- \p BB1 is a descendant of BB2 in the opposite tree. So, if BB2
/// is a descendant of \p BB1 in the dominator tree, then BB2 should
/// dominate BB1 in the post-dominator tree.
///
/// 2- Both BB2 and \p BB1 must be in the same loop.
///
/// For every block BB2 that meets those two requirements, we set BB2's
/// equivalence class to \p BB1.
///
/// \param BB1 Block to check.
/// \param Descendants Descendants of \p BB1 in either the dom or pdom tree.
/// \param DomTree Opposite dominator tree. If \p Descendants is filled
/// with blocks from \p BB1's dominator tree, then
/// this is the post-dominator tree, and vice versa.
void SampleProfileLoader::findEquivalencesFor(
BasicBlock *BB1, SmallVector<BasicBlock *, 8> Descendants,
DominatorTreeBase<BasicBlock> *DomTree) {
const BasicBlock *EC = EquivalenceClass[BB1];
unsigned Weight = BlockWeights[EC];
for (const auto *BB2 : Descendants) {
bool IsDomParent = DomTree->dominates(BB2, BB1);
bool IsInSameLoop = LI->getLoopFor(BB1) == LI->getLoopFor(BB2);
if (BB1 != BB2 && IsDomParent && IsInSameLoop) {
EquivalenceClass[BB2] = EC;
// If BB2 is heavier than BB1, make BB2 have the same weight
// as BB1.
//
// Note that we don't worry about the opposite situation here
// (when BB2 is lighter than BB1). We will deal with this
// during the propagation phase. Right now, we just want to
// make sure that BB1 has the largest weight of all the
// members of its equivalence set.
Weight = std::max(Weight, BlockWeights[BB2]);
}
}
BlockWeights[EC] = Weight;
}
/// \brief Find equivalence classes.
///
/// Since samples may be missing from blocks, we can fill in the gaps by setting
/// the weights of all the blocks in the same equivalence class to the same
/// weight. To compute the concept of equivalence, we use dominance and loop
/// information. Two blocks B1 and B2 are in the same equivalence class if B1
/// dominates B2, B2 post-dominates B1 and both are in the same loop.
///
/// \param F The function to query.
void SampleProfileLoader::findEquivalenceClasses(Function &F) {
SmallVector<BasicBlock *, 8> DominatedBBs;
DEBUG(dbgs() << "\nBlock equivalence classes\n");
// Find equivalence sets based on dominance and post-dominance information.
for (auto &BB : F) {
BasicBlock *BB1 = &BB;
// Compute BB1's equivalence class once.
if (EquivalenceClass.count(BB1)) {
DEBUG(printBlockEquivalence(dbgs(), BB1));
continue;
}
// By default, blocks are in their own equivalence class.
EquivalenceClass[BB1] = BB1;
// Traverse all the blocks dominated by BB1. We are looking for
// every basic block BB2 such that:
//
// 1- BB1 dominates BB2.
// 2- BB2 post-dominates BB1.
// 3- BB1 and BB2 are in the same loop nest.
//
// If all those conditions hold, it means that BB2 is executed
// as many times as BB1, so they are placed in the same equivalence
// class by making BB2's equivalence class be BB1.
DominatedBBs.clear();
DT->getDescendants(BB1, DominatedBBs);
findEquivalencesFor(BB1, DominatedBBs, PDT.get());
DEBUG(printBlockEquivalence(dbgs(), BB1));
}
// Assign weights to equivalence classes.
//
// All the basic blocks in the same equivalence class will execute
// the same number of times. Since we know that the head block in
// each equivalence class has the largest weight, assign that weight
// to all the blocks in that equivalence class.
DEBUG(dbgs() << "\nAssign the same weight to all blocks in the same class\n");
for (auto &BI : F) {
const BasicBlock *BB = &BI;
const BasicBlock *EquivBB = EquivalenceClass[BB];
if (BB != EquivBB)
BlockWeights[BB] = BlockWeights[EquivBB];
DEBUG(printBlockWeight(dbgs(), BB));
}
}
/// \brief Visit the given edge to decide if it has a valid weight.
///
/// If \p E has not been visited before, we copy to \p UnknownEdge
/// and increment the count of unknown edges.
///
/// \param E Edge to visit.
/// \param NumUnknownEdges Current number of unknown edges.
/// \param UnknownEdge Set if E has not been visited before.
///
/// \returns E's weight, if known. Otherwise, return 0.
unsigned SampleProfileLoader::visitEdge(Edge E, unsigned *NumUnknownEdges,
Edge *UnknownEdge) {
if (!VisitedEdges.count(E)) {
(*NumUnknownEdges)++;
*UnknownEdge = E;
return 0;
}
return EdgeWeights[E];
}
/// \brief Propagate weights through incoming/outgoing edges.
///
/// If the weight of a basic block is known, and there is only one edge
/// with an unknown weight, we can calculate the weight of that edge.
///
/// Similarly, if all the edges have a known count, we can calculate the
/// count of the basic block, if needed.
///
/// \param F Function to process.
///
/// \returns True if new weights were assigned to edges or blocks.
bool SampleProfileLoader::propagateThroughEdges(Function &F) {
bool Changed = false;
DEBUG(dbgs() << "\nPropagation through edges\n");
for (const auto &BI : F) {
const BasicBlock *BB = &BI;
const BasicBlock *EC = EquivalenceClass[BB];
// Visit all the predecessor and successor edges to determine
// which ones have a weight assigned already. Note that it doesn't
// matter that we only keep track of a single unknown edge. The
// only case we are interested in handling is when only a single
// edge is unknown (see setEdgeOrBlockWeight).
for (unsigned i = 0; i < 2; i++) {
unsigned TotalWeight = 0;
unsigned NumUnknownEdges = 0;
Edge UnknownEdge, SelfReferentialEdge;
if (i == 0) {
// First, visit all predecessor edges.
for (auto *Pred : Predecessors[BB]) {
Edge E = std::make_pair(Pred, BB);
TotalWeight += visitEdge(E, &NumUnknownEdges, &UnknownEdge);
if (E.first == E.second)
SelfReferentialEdge = E;
}
} else {
// On the second round, visit all successor edges.
for (auto *Succ : Successors[BB]) {
Edge E = std::make_pair(BB, Succ);
TotalWeight += visitEdge(E, &NumUnknownEdges, &UnknownEdge);
}
}
// After visiting all the edges, there are three cases that we
// can handle immediately:
//
// - All the edge weights are known (i.e., NumUnknownEdges == 0).
// In this case, we simply check that the sum of all the edges
// is the same as BB's weight. If not, we change BB's weight
// to match. Additionally, if BB had not been visited before,
// we mark it visited.
//
// - Only one edge is unknown and BB has already been visited.
// In this case, we can compute the weight of the edge by
// subtracting the total block weight from all the known
// edge weights. If the edges weight more than BB, then the
// edge of the last remaining edge is set to zero.
//
// - There exists a self-referential edge and the weight of BB is
// known. In this case, this edge can be based on BB's weight.
// We add up all the other known edges and set the weight on
// the self-referential edge as we did in the previous case.
//
// In any other case, we must continue iterating. Eventually,
// all edges will get a weight, or iteration will stop when
// it reaches SampleProfileMaxPropagateIterations.
if (NumUnknownEdges <= 1) {
unsigned &BBWeight = BlockWeights[EC];
if (NumUnknownEdges == 0) {
// If we already know the weight of all edges, the weight of the
// basic block can be computed. It should be no larger than the sum
// of all edge weights.
if (TotalWeight > BBWeight) {
BBWeight = TotalWeight;
Changed = true;
DEBUG(dbgs() << "All edge weights for " << BB->getName()
<< " known. Set weight for block: ";
printBlockWeight(dbgs(), BB););
}
if (VisitedBlocks.insert(EC).second)
Changed = true;
} else if (NumUnknownEdges == 1 && VisitedBlocks.count(EC)) {
// If there is a single unknown edge and the block has been
// visited, then we can compute E's weight.
if (BBWeight >= TotalWeight)
EdgeWeights[UnknownEdge] = BBWeight - TotalWeight;
else
EdgeWeights[UnknownEdge] = 0;
VisitedEdges.insert(UnknownEdge);
Changed = true;
DEBUG(dbgs() << "Set weight for edge: ";
printEdgeWeight(dbgs(), UnknownEdge));
}
} else if (SelfReferentialEdge.first && VisitedBlocks.count(EC)) {
unsigned &BBWeight = BlockWeights[BB];
// We have a self-referential edge and the weight of BB is known.
if (BBWeight >= TotalWeight)
EdgeWeights[SelfReferentialEdge] = BBWeight - TotalWeight;
else
EdgeWeights[SelfReferentialEdge] = 0;
VisitedEdges.insert(SelfReferentialEdge);
Changed = true;
DEBUG(dbgs() << "Set self-referential edge weight to: ";
printEdgeWeight(dbgs(), SelfReferentialEdge));
}
}
}
return Changed;
}
/// \brief Build in/out edge lists for each basic block in the CFG.
///
/// We are interested in unique edges. If a block B1 has multiple
/// edges to another block B2, we only add a single B1->B2 edge.
void SampleProfileLoader::buildEdges(Function &F) {
for (auto &BI : F) {
BasicBlock *B1 = &BI;
// Add predecessors for B1.
SmallPtrSet<BasicBlock *, 16> Visited;
if (!Predecessors[B1].empty())
llvm_unreachable("Found a stale predecessors list in a basic block.");
for (pred_iterator PI = pred_begin(B1), PE = pred_end(B1); PI != PE; ++PI) {
BasicBlock *B2 = *PI;
if (Visited.insert(B2).second)
Predecessors[B1].push_back(B2);
}
// Add successors for B1.
Visited.clear();
if (!Successors[B1].empty())
llvm_unreachable("Found a stale successors list in a basic block.");
for (succ_iterator SI = succ_begin(B1), SE = succ_end(B1); SI != SE; ++SI) {
BasicBlock *B2 = *SI;
if (Visited.insert(B2).second)
Successors[B1].push_back(B2);
}
}
}
/// \brief Propagate weights into edges
///
/// The following rules are applied to every block BB in the CFG:
///
/// - If BB has a single predecessor/successor, then the weight
/// of that edge is the weight of the block.
///
/// - If all incoming or outgoing edges are known except one, and the
/// weight of the block is already known, the weight of the unknown
/// edge will be the weight of the block minus the sum of all the known
/// edges. If the sum of all the known edges is larger than BB's weight,
/// we set the unknown edge weight to zero.
///
/// - If there is a self-referential edge, and the weight of the block is
/// known, the weight for that edge is set to the weight of the block
/// minus the weight of the other incoming edges to that block (if
/// known).
void SampleProfileLoader::propagateWeights(Function &F) {
bool Changed = true;
unsigned i = 0;
// Add an entry count to the function using the samples gathered
// at the function entry.
F.setEntryCount(Samples->getHeadSamples());
// Before propagation starts, build, for each block, a list of
// unique predecessors and successors. This is necessary to handle
// identical edges in multiway branches. Since we visit all blocks and all
// edges of the CFG, it is cleaner to build these lists once at the start
// of the pass.
buildEdges(F);
// Propagate until we converge or we go past the iteration limit.
while (Changed && i++ < SampleProfileMaxPropagateIterations) {
Changed = propagateThroughEdges(F);
}
// Generate MD_prof metadata for every branch instruction using the
// edge weights computed during propagation.
DEBUG(dbgs() << "\nPropagation complete. Setting branch weights\n");
MDBuilder MDB(F.getContext());
for (auto &BI : F) {
BasicBlock *BB = &BI;
TerminatorInst *TI = BB->getTerminator();
if (TI->getNumSuccessors() == 1)
continue;
if (!isa<BranchInst>(TI) && !isa<SwitchInst>(TI))
continue;
DEBUG(dbgs() << "\nGetting weights for branch at line "
<< TI->getDebugLoc().getLine() << ".\n");
SmallVector<unsigned, 4> Weights;
bool AllWeightsZero = true;
for (unsigned I = 0; I < TI->getNumSuccessors(); ++I) {
BasicBlock *Succ = TI->getSuccessor(I);
Edge E = std::make_pair(BB, Succ);
unsigned Weight = EdgeWeights[E];
DEBUG(dbgs() << "\t"; printEdgeWeight(dbgs(), E));
Weights.push_back(Weight);
if (Weight != 0)
AllWeightsZero = false;
}
// Only set weights if there is at least one non-zero weight.
// In any other case, let the analyzer set weights.
if (!AllWeightsZero) {
DEBUG(dbgs() << "SUCCESS. Found non-zero weights.\n");
TI->setMetadata(llvm::LLVMContext::MD_prof,
MDB.createBranchWeights(Weights));
} else {
DEBUG(dbgs() << "SKIPPED. All branch weights are zero.\n");
}
}
}
/// \brief Get the line number for the function header.
///
/// This looks up function \p F in the current compilation unit and
/// retrieves the line number where the function is defined. This is
/// line 0 for all the samples read from the profile file. Every line
/// number is relative to this line.
///
/// \param F Function object to query.
///
/// \returns the line number where \p F is defined. If it returns 0,
/// it means that there is no debug information available for \p F.
unsigned SampleProfileLoader::getFunctionLoc(Function &F) {
if (DISubprogram *S = getDISubprogram(&F))
return S->getLine();
// If could not find the start of \p F, emit a diagnostic to inform the user
// about the missed opportunity.
F.getContext().diagnose(DiagnosticInfoSampleProfile(
"No debug information found in function " + F.getName() +
": Function profile not used",
DS_Warning));
return 0;
}
void SampleProfileLoader::computeDominanceAndLoopInfo(Function &F) {
DT.reset(new DominatorTree);
DT->recalculate(F);
PDT.reset(new DominatorTreeBase<BasicBlock>(true));
PDT->recalculate(F);
LI.reset(new LoopInfo);
LI->analyze(*DT);
}
/// \brief Generate branch weight metadata for all branches in \p F.
///
/// Branch weights are computed out of instruction samples using a
/// propagation heuristic. Propagation proceeds in 3 phases:
///
/// 1- Assignment of block weights. All the basic blocks in the function
/// are initial assigned the same weight as their most frequently
/// executed instruction.
///
/// 2- Creation of equivalence classes. Since samples may be missing from
/// blocks, we can fill in the gaps by setting the weights of all the
/// blocks in the same equivalence class to the same weight. To compute
/// the concept of equivalence, we use dominance and loop information.
/// Two blocks B1 and B2 are in the same equivalence class if B1
/// dominates B2, B2 post-dominates B1 and both are in the same loop.
///
/// 3- Propagation of block weights into edges. This uses a simple
/// propagation heuristic. The following rules are applied to every
/// block BB in the CFG:
///
/// - If BB has a single predecessor/successor, then the weight
/// of that edge is the weight of the block.
///
/// - If all the edges are known except one, and the weight of the
/// block is already known, the weight of the unknown edge will
/// be the weight of the block minus the sum of all the known
/// edges. If the sum of all the known edges is larger than BB's weight,
/// we set the unknown edge weight to zero.
///
/// - If there is a self-referential edge, and the weight of the block is
/// known, the weight for that edge is set to the weight of the block
/// minus the weight of the other incoming edges to that block (if
/// known).
///
/// Since this propagation is not guaranteed to finalize for every CFG, we
/// only allow it to proceed for a limited number of iterations (controlled
/// by -sample-profile-max-propagate-iterations).
///
/// FIXME: Try to replace this propagation heuristic with a scheme
/// that is guaranteed to finalize. A work-list approach similar to
/// the standard value propagation algorithm used by SSA-CCP might
/// work here.
///
/// Once all the branch weights are computed, we emit the MD_prof
/// metadata on BB using the computed values for each of its branches.
///
/// \param F The function to query.
///
/// \returns true if \p F was modified. Returns false, otherwise.
bool SampleProfileLoader::emitAnnotations(Function &F) {
bool Changed = false;
if (getFunctionLoc(F) == 0)
return false;
DEBUG(dbgs() << "Line number for the first instruction in " << F.getName()
<< ": " << getFunctionLoc(F) << "\n");
Changed |= inlineHotFunctions(F);
// Compute basic block weights.
Changed |= computeBlockWeights(F);
if (Changed) {
// Compute dominance and loop info needed for propagation.
computeDominanceAndLoopInfo(F);
// Find equivalence classes.
findEquivalenceClasses(F);
// Propagate weights to all edges.
propagateWeights(F);
}
return Changed;
}
char SampleProfileLoader::ID = 0;
INITIALIZE_PASS_BEGIN(SampleProfileLoader, "sample-profile",
"Sample Profile loader", false, false)
INITIALIZE_PASS_DEPENDENCY(AddDiscriminators)
INITIALIZE_PASS_END(SampleProfileLoader, "sample-profile",
"Sample Profile loader", false, false)
bool SampleProfileLoader::doInitialization(Module &M) {
auto &Ctx = M.getContext();
auto ReaderOrErr = SampleProfileReader::create(Filename, Ctx);
if (std::error_code EC = ReaderOrErr.getError()) {
std::string Msg = "Could not open profile: " + EC.message();
Ctx.diagnose(DiagnosticInfoSampleProfile(Filename.data(), Msg));
return false;
}
Reader = std::move(ReaderOrErr.get());
ProfileIsValid = (Reader->read() == sampleprof_error::success);
return true;
}
ModulePass *llvm::createSampleProfileLoaderPass() {
return new SampleProfileLoader(SampleProfileFile);
}
ModulePass *llvm::createSampleProfileLoaderPass(StringRef Name) {
return new SampleProfileLoader(Name);
}
bool SampleProfileLoader::runOnModule(Module &M) {
bool retval = false;
for (auto &F : M)
if (!F.isDeclaration())
retval |= runOnFunction(F);
return retval;
}
bool SampleProfileLoader::runOnFunction(Function &F) {
if (!ProfileIsValid)
return false;
Samples = Reader->getSamplesFor(F);
if (!Samples->empty())
return emitAnnotations(F);
return false;
}