llvm-6502/lib/Transforms/Scalar/SampleProfile.cpp
Alexander Kornienko cd52a7a381 Revert r240137 (Fixed/added namespace ending comments using clang-tidy. NFC)
Apparently, the style needs to be agreed upon first.


git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@240390 91177308-0d34-0410-b5e6-96231b3b80d8
2015-06-23 09:49:53 +00:00

778 lines
29 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/Transforms/Scalar.h"
#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/raw_ostream.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<BasicBlock *, unsigned> BlockWeightMap;
typedef DenseMap<BasicBlock *, BasicBlock *> EquivalenceClassMap;
typedef std::pair<BasicBlock *, BasicBlock *> Edge;
typedef DenseMap<Edge, unsigned> EdgeWeightMap;
typedef DenseMap<BasicBlock *, SmallVector<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 FunctionPass {
public:
// Class identification, replacement for typeinfo
static char ID;
SampleProfileLoader(StringRef Name = SampleProfileFile)
: FunctionPass(ID), DT(nullptr), PDT(nullptr), LI(nullptr), Ctx(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 runOnFunction(Function &F) override;
void getAnalysisUsage(AnalysisUsage &AU) const override {
AU.setPreservesCFG();
AU.addRequired<LoopInfoWrapperPass>();
AU.addRequired<DominatorTreeWrapperPass>();
AU.addRequired<PostDominatorTree>();
}
protected:
unsigned getFunctionLoc(Function &F);
bool emitAnnotations(Function &F);
unsigned getInstWeight(Instruction &I);
unsigned getBlockWeight(BasicBlock *BB);
void printEdgeWeight(raw_ostream &OS, Edge E);
void printBlockWeight(raw_ostream &OS, BasicBlock *BB);
void printBlockEquivalence(raw_ostream &OS, 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);
/// \brief Line number for the function header. Used to compute absolute
/// line numbers from the relative line numbers found in the profile.
unsigned HeaderLineno;
/// \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<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.
DominatorTree *DT;
PostDominatorTree *PDT;
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 LLVM context holding the debug data we need.
LLVMContext *Ctx;
/// \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,
BasicBlock *BB) {
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, BasicBlock *BB) {
OS << "weight[" << BB->getName() << "]: " << BlockWeights[BB] << "\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 profiled weight of I.
unsigned SampleProfileLoader::getInstWeight(Instruction &Inst) {
DebugLoc DLoc = Inst.getDebugLoc();
if (!DLoc)
return 0;
unsigned Lineno = DLoc.getLine();
if (Lineno < HeaderLineno)
return 0;
const DILocation *DIL = DLoc;
int LOffset = Lineno - HeaderLineno;
unsigned Discriminator = DIL->getDiscriminator();
unsigned Weight = Samples->samplesAt(LOffset, Discriminator);
DEBUG(dbgs() << " " << Lineno << "." << Discriminator << ":" << Inst
<< " (line offset: " << LOffset << "." << Discriminator
<< " - weight: " << Weight << ")\n");
return Weight;
}
/// \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. The weight of \p BB is computed and cached in
/// the BlockWeights map.
///
/// \param BB The basic block to query.
///
/// \returns The computed weight of BB.
unsigned SampleProfileLoader::getBlockWeight(BasicBlock *BB) {
// If we've computed BB's weight before, return it.
std::pair<BlockWeightMap::iterator, bool> Entry =
BlockWeights.insert(std::make_pair(BB, 0));
if (!Entry.second)
return Entry.first->second;
// Otherwise, compute and cache BB's weight.
unsigned Weight = 0;
for (auto &I : BB->getInstList()) {
unsigned InstWeight = getInstWeight(I);
if (InstWeight > Weight)
Weight = InstWeight;
}
Entry.first->second = Weight;
return Weight;
}
/// \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 (auto &BB : F) {
unsigned Weight = getBlockWeight(&BB);
Changed |= (Weight > 0);
DEBUG(printBlockWeight(dbgs(), &BB));
}
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) {
for (auto *BB2 : Descendants) {
bool IsDomParent = DomTree->dominates(BB2, BB1);
bool IsInSameLoop = LI->getLoopFor(BB1) == LI->getLoopFor(BB2);
if (BB1 != BB2 && VisitedBlocks.insert(BB2).second && IsDomParent &&
IsInSameLoop) {
EquivalenceClass[BB2] = BB1;
// 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.
unsigned &BB1Weight = BlockWeights[BB1];
unsigned &BB2Weight = BlockWeights[BB2];
BB1Weight = std::max(BB1Weight, BB2Weight);
}
}
}
/// \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->DT);
// Repeat the same logic for all the blocks post-dominated by BB1.
// We are looking for every basic block BB2 such that:
//
// 1- BB1 post-dominates BB2.
// 2- BB2 dominates BB1.
// 3- BB1 and BB2 are in the same loop nest.
//
// If all those conditions hold, BB2's equivalence class is BB1.
DominatedBBs.clear();
PDT->getDescendants(BB1, DominatedBBs);
findEquivalencesFor(BB1, DominatedBBs, DT);
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) {
BasicBlock *BB = &BI;
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 (auto &BI : F) {
BasicBlock *BB = &BI;
// 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[BB];
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(BB).second)
Changed = true;
} else if (NumUnknownEdges == 1 && VisitedBlocks.count(BB)) {
// 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(BB)) {
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;
}
/// \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;
// Initialize invariants used during computation and propagation.
HeaderLineno = getFunctionLoc(F);
if (HeaderLineno == 0)
return false;
DEBUG(dbgs() << "Line number for the first instruction in " << F.getName()
<< ": " << HeaderLineno << "\n");
// Compute basic block weights.
Changed |= computeBlockWeights(F);
if (Changed) {
// 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(DominatorTreeWrapperPass)
INITIALIZE_PASS_DEPENDENCY(PostDominatorTree)
INITIALIZE_PASS_DEPENDENCY(LoopInfoWrapperPass)
INITIALIZE_PASS_DEPENDENCY(AddDiscriminators)
INITIALIZE_PASS_END(SampleProfileLoader, "sample-profile",
"Sample Profile loader", false, false)
bool SampleProfileLoader::doInitialization(Module &M) {
auto ReaderOrErr = SampleProfileReader::create(Filename, M.getContext());
if (std::error_code EC = ReaderOrErr.getError()) {
std::string Msg = "Could not open profile: " + EC.message();
M.getContext().diagnose(DiagnosticInfoSampleProfile(Filename.data(), Msg));
return false;
}
Reader = std::move(ReaderOrErr.get());
ProfileIsValid = (Reader->read() == sampleprof_error::success);
return true;
}
FunctionPass *llvm::createSampleProfileLoaderPass() {
return new SampleProfileLoader(SampleProfileFile);
}
FunctionPass *llvm::createSampleProfileLoaderPass(StringRef Name) {
return new SampleProfileLoader(Name);
}
bool SampleProfileLoader::runOnFunction(Function &F) {
if (!ProfileIsValid)
return false;
DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree();
PDT = &getAnalysis<PostDominatorTree>();
LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo();
Ctx = &F.getParent()->getContext();
Samples = Reader->getSamplesFor(F);
if (!Samples->empty())
return emitAnnotations(F);
return false;
}