//===- BranchProbabilityInfo.cpp - Branch Probability Analysis ------------===// // // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. // See https://llvm.org/LICENSE.txt for license information. // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception // //===----------------------------------------------------------------------===// // // Loops should be simplified before this analysis. // //===----------------------------------------------------------------------===// #include "llvm/Analysis/BranchProbabilityInfo.h" #include "llvm/ADT/PostOrderIterator.h" #include "llvm/ADT/SCCIterator.h" #include "llvm/ADT/STLExtras.h" #include "llvm/ADT/SmallVector.h" #include "llvm/Analysis/LoopInfo.h" #include "llvm/Analysis/PostDominators.h" #include "llvm/Analysis/TargetLibraryInfo.h" #include "llvm/IR/Attributes.h" #include "llvm/IR/BasicBlock.h" #include "llvm/IR/CFG.h" #include "llvm/IR/Constants.h" #include "llvm/IR/Dominators.h" #include "llvm/IR/Function.h" #include "llvm/IR/InstrTypes.h" #include "llvm/IR/Instruction.h" #include "llvm/IR/Instructions.h" #include "llvm/IR/LLVMContext.h" #include "llvm/IR/Metadata.h" #include "llvm/IR/PassManager.h" #include "llvm/IR/Type.h" #include "llvm/IR/Value.h" #include "llvm/InitializePasses.h" #include "llvm/Pass.h" #include "llvm/Support/BranchProbability.h" #include "llvm/Support/Casting.h" #include "llvm/Support/CommandLine.h" #include "llvm/Support/Debug.h" #include "llvm/Support/raw_ostream.h" #include #include #include #include using namespace llvm; #define DEBUG_TYPE "branch-prob" static cl::opt PrintBranchProb( "print-bpi", cl::init(false), cl::Hidden, cl::desc("Print the branch probability info.")); cl::opt PrintBranchProbFuncName( "print-bpi-func-name", cl::Hidden, cl::desc("The option to specify the name of the function " "whose branch probability info is printed.")); INITIALIZE_PASS_BEGIN(BranchProbabilityInfoWrapperPass, "branch-prob", "Branch Probability Analysis", false, true) INITIALIZE_PASS_DEPENDENCY(LoopInfoWrapperPass) INITIALIZE_PASS_DEPENDENCY(TargetLibraryInfoWrapperPass) INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass) INITIALIZE_PASS_DEPENDENCY(PostDominatorTreeWrapperPass) INITIALIZE_PASS_END(BranchProbabilityInfoWrapperPass, "branch-prob", "Branch Probability Analysis", false, true) BranchProbabilityInfoWrapperPass::BranchProbabilityInfoWrapperPass() : FunctionPass(ID) { initializeBranchProbabilityInfoWrapperPassPass( *PassRegistry::getPassRegistry()); } char BranchProbabilityInfoWrapperPass::ID = 0; // Weights are for internal use only. They are used by heuristics to help to // estimate edges' probability. Example: // // Using "Loop Branch Heuristics" we predict weights of edges for the // block BB2. // ... // | // V // BB1<-+ // | | // | | (Weight = 124) // V | // BB2--+ // | // | (Weight = 4) // V // BB3 // // Probability of the edge BB2->BB1 = 124 / (124 + 4) = 0.96875 // Probability of the edge BB2->BB3 = 4 / (124 + 4) = 0.03125 static const uint32_t LBH_TAKEN_WEIGHT = 124; static const uint32_t LBH_NONTAKEN_WEIGHT = 4; /// Unreachable-terminating branch taken probability. /// /// This is the probability for a branch being taken to a block that terminates /// (eventually) in unreachable. These are predicted as unlikely as possible. /// All reachable probability will proportionally share the remaining part. static const BranchProbability UR_TAKEN_PROB = BranchProbability::getRaw(1); static const uint32_t PH_TAKEN_WEIGHT = 20; static const uint32_t PH_NONTAKEN_WEIGHT = 12; static const uint32_t ZH_TAKEN_WEIGHT = 20; static const uint32_t ZH_NONTAKEN_WEIGHT = 12; static const uint32_t FPH_TAKEN_WEIGHT = 20; static const uint32_t FPH_NONTAKEN_WEIGHT = 12; /// This is the probability for an ordered floating point comparison. static const uint32_t FPH_ORD_WEIGHT = 1024 * 1024 - 1; /// This is the probability for an unordered floating point comparison, it means /// one or two of the operands are NaN. Usually it is used to test for an /// exceptional case, so the result is unlikely. static const uint32_t FPH_UNO_WEIGHT = 1; /// Set of dedicated "absolute" execution weights for a block. These weights are /// meaningful relative to each other and their derivatives only. enum class BlockExecWeight : std::uint32_t { /// Special weight used for cases with exact zero probability. ZERO = 0x0, /// Minimal possible non zero weight. LOWEST_NON_ZERO = 0x1, /// Weight to an 'unreachable' block. UNREACHABLE = ZERO, /// Weight to a block containing non returning call. NORETURN = LOWEST_NON_ZERO, /// Weight to 'unwind' block of an invoke instruction. UNWIND = LOWEST_NON_ZERO, /// Weight to a 'cold' block. Cold blocks are the ones containing calls marked /// with attribute 'cold'. COLD = 0xffff, /// Default weight is used in cases when there is no dedicated execution /// weight set. It is not propagated through the domination line either. DEFAULT = 0xfffff }; BranchProbabilityInfo::SccInfo::SccInfo(const Function &F) { // Record SCC numbers of blocks in the CFG to identify irreducible loops. // FIXME: We could only calculate this if the CFG is known to be irreducible // (perhaps cache this info in LoopInfo if we can easily calculate it there?). int SccNum = 0; for (scc_iterator It = scc_begin(&F); !It.isAtEnd(); ++It, ++SccNum) { // Ignore single-block SCCs since they either aren't loops or LoopInfo will // catch them. const std::vector &Scc = *It; if (Scc.size() == 1) continue; LLVM_DEBUG(dbgs() << "BPI: SCC " << SccNum << ":"); for (const auto *BB : Scc) { LLVM_DEBUG(dbgs() << " " << BB->getName()); SccNums[BB] = SccNum; calculateSccBlockType(BB, SccNum); } LLVM_DEBUG(dbgs() << "\n"); } } int BranchProbabilityInfo::SccInfo::getSCCNum(const BasicBlock *BB) const { auto SccIt = SccNums.find(BB); if (SccIt == SccNums.end()) return -1; return SccIt->second; } void BranchProbabilityInfo::SccInfo::getSccEnterBlocks( int SccNum, SmallVectorImpl &Enters) const { for (auto MapIt : SccBlocks[SccNum]) { const auto *BB = MapIt.first; if (isSCCHeader(BB, SccNum)) for (const auto *Pred : predecessors(BB)) if (getSCCNum(Pred) != SccNum) Enters.push_back(const_cast(BB)); } } void BranchProbabilityInfo::SccInfo::getSccExitBlocks( int SccNum, SmallVectorImpl &Exits) const { for (auto MapIt : SccBlocks[SccNum]) { const auto *BB = MapIt.first; if (isSCCExitingBlock(BB, SccNum)) for (const auto *Succ : successors(BB)) if (getSCCNum(Succ) != SccNum) Exits.push_back(const_cast(BB)); } } uint32_t BranchProbabilityInfo::SccInfo::getSccBlockType(const BasicBlock *BB, int SccNum) const { assert(getSCCNum(BB) == SccNum); assert(SccBlocks.size() > static_cast(SccNum) && "Unknown SCC"); const auto &SccBlockTypes = SccBlocks[SccNum]; auto It = SccBlockTypes.find(BB); if (It != SccBlockTypes.end()) { return It->second; } return Inner; } void BranchProbabilityInfo::SccInfo::calculateSccBlockType(const BasicBlock *BB, int SccNum) { assert(getSCCNum(BB) == SccNum); uint32_t BlockType = Inner; if (llvm::any_of(predecessors(BB), [&](const BasicBlock *Pred) { // Consider any block that is an entry point to the SCC as // a header. return getSCCNum(Pred) != SccNum; })) BlockType |= Header; if (llvm::any_of(successors(BB), [&](const BasicBlock *Succ) { return getSCCNum(Succ) != SccNum; })) BlockType |= Exiting; // Lazily compute the set of headers for a given SCC and cache the results // in the SccHeaderMap. if (SccBlocks.size() <= static_cast(SccNum)) SccBlocks.resize(SccNum + 1); auto &SccBlockTypes = SccBlocks[SccNum]; if (BlockType != Inner) { bool IsInserted; std::tie(std::ignore, IsInserted) = SccBlockTypes.insert(std::make_pair(BB, BlockType)); assert(IsInserted && "Duplicated block in SCC"); } } BranchProbabilityInfo::LoopBlock::LoopBlock(const BasicBlock *BB, const LoopInfo &LI, const SccInfo &SccI) : BB(BB) { LD.first = LI.getLoopFor(BB); if (!LD.first) { LD.second = SccI.getSCCNum(BB); } } bool BranchProbabilityInfo::isLoopEnteringEdge(const LoopEdge &Edge) const { const auto &SrcBlock = Edge.first; const auto &DstBlock = Edge.second; return (DstBlock.getLoop() && !DstBlock.getLoop()->contains(SrcBlock.getLoop())) || // Assume that SCCs can't be nested. (DstBlock.getSccNum() != -1 && SrcBlock.getSccNum() != DstBlock.getSccNum()); } bool BranchProbabilityInfo::isLoopExitingEdge(const LoopEdge &Edge) const { return isLoopEnteringEdge({Edge.second, Edge.first}); } bool BranchProbabilityInfo::isLoopEnteringExitingEdge( const LoopEdge &Edge) const { return isLoopEnteringEdge(Edge) || isLoopExitingEdge(Edge); } bool BranchProbabilityInfo::isLoopBackEdge(const LoopEdge &Edge) const { const auto &SrcBlock = Edge.first; const auto &DstBlock = Edge.second; return SrcBlock.belongsToSameLoop(DstBlock) && ((DstBlock.getLoop() && DstBlock.getLoop()->getHeader() == DstBlock.getBlock()) || (DstBlock.getSccNum() != -1 && SccI->isSCCHeader(DstBlock.getBlock(), DstBlock.getSccNum()))); } void BranchProbabilityInfo::getLoopEnterBlocks( const LoopBlock &LB, SmallVectorImpl &Enters) const { if (LB.getLoop()) { auto *Header = LB.getLoop()->getHeader(); Enters.append(pred_begin(Header), pred_end(Header)); } else { assert(LB.getSccNum() != -1 && "LB doesn't belong to any loop?"); SccI->getSccEnterBlocks(LB.getSccNum(), Enters); } } void BranchProbabilityInfo::getLoopExitBlocks( const LoopBlock &LB, SmallVectorImpl &Exits) const { if (LB.getLoop()) { LB.getLoop()->getExitBlocks(Exits); } else { assert(LB.getSccNum() != -1 && "LB doesn't belong to any loop?"); SccI->getSccExitBlocks(LB.getSccNum(), Exits); } } // Propagate existing explicit probabilities from either profile data or // 'expect' intrinsic processing. Examine metadata against unreachable // heuristic. The probability of the edge coming to unreachable block is // set to min of metadata and unreachable heuristic. bool BranchProbabilityInfo::calcMetadataWeights(const BasicBlock *BB) { const Instruction *TI = BB->getTerminator(); assert(TI->getNumSuccessors() > 1 && "expected more than one successor!"); if (!(isa(TI) || isa(TI) || isa(TI) || isa(TI))) return false; MDNode *WeightsNode = TI->getMetadata(LLVMContext::MD_prof); if (!WeightsNode) return false; // Check that the number of successors is manageable. assert(TI->getNumSuccessors() < UINT32_MAX && "Too many successors"); // Ensure there are weights for all of the successors. Note that the first // operand to the metadata node is a name, not a weight. if (WeightsNode->getNumOperands() != TI->getNumSuccessors() + 1) return false; // Build up the final weights that will be used in a temporary buffer. // Compute the sum of all weights to later decide whether they need to // be scaled to fit in 32 bits. uint64_t WeightSum = 0; SmallVector Weights; SmallVector UnreachableIdxs; SmallVector ReachableIdxs; Weights.reserve(TI->getNumSuccessors()); for (unsigned I = 1, E = WeightsNode->getNumOperands(); I != E; ++I) { ConstantInt *Weight = mdconst::dyn_extract(WeightsNode->getOperand(I)); if (!Weight) return false; assert(Weight->getValue().getActiveBits() <= 32 && "Too many bits for uint32_t"); Weights.push_back(Weight->getZExtValue()); WeightSum += Weights.back(); const LoopBlock SrcLoopBB = getLoopBlock(BB); const LoopBlock DstLoopBB = getLoopBlock(TI->getSuccessor(I - 1)); auto EstimatedWeight = getEstimatedEdgeWeight({SrcLoopBB, DstLoopBB}); if (EstimatedWeight && EstimatedWeight.getValue() <= static_cast(BlockExecWeight::UNREACHABLE)) UnreachableIdxs.push_back(I - 1); else ReachableIdxs.push_back(I - 1); } assert(Weights.size() == TI->getNumSuccessors() && "Checked above"); // If the sum of weights does not fit in 32 bits, scale every weight down // accordingly. uint64_t ScalingFactor = (WeightSum > UINT32_MAX) ? WeightSum / UINT32_MAX + 1 : 1; if (ScalingFactor > 1) { WeightSum = 0; for (unsigned I = 0, E = TI->getNumSuccessors(); I != E; ++I) { Weights[I] /= ScalingFactor; WeightSum += Weights[I]; } } assert(WeightSum <= UINT32_MAX && "Expected weights to scale down to 32 bits"); if (WeightSum == 0 || ReachableIdxs.size() == 0) { for (unsigned I = 0, E = TI->getNumSuccessors(); I != E; ++I) Weights[I] = 1; WeightSum = TI->getNumSuccessors(); } // Set the probability. SmallVector BP; for (unsigned I = 0, E = TI->getNumSuccessors(); I != E; ++I) BP.push_back({ Weights[I], static_cast(WeightSum) }); // Examine the metadata against unreachable heuristic. // If the unreachable heuristic is more strong then we use it for this edge. if (UnreachableIdxs.size() == 0 || ReachableIdxs.size() == 0) { setEdgeProbability(BB, BP); return true; } auto UnreachableProb = UR_TAKEN_PROB; for (auto I : UnreachableIdxs) if (UnreachableProb < BP[I]) { BP[I] = UnreachableProb; } // Sum of all edge probabilities must be 1.0. If we modified the probability // of some edges then we must distribute the introduced difference over the // reachable blocks. // // Proportional distribution: the relation between probabilities of the // reachable edges is kept unchanged. That is for any reachable edges i and j: // newBP[i] / newBP[j] == oldBP[i] / oldBP[j] => // newBP[i] / oldBP[i] == newBP[j] / oldBP[j] == K // Where K is independent of i,j. // newBP[i] == oldBP[i] * K // We need to find K. // Make sum of all reachables of the left and right parts: // sum_of_reachable(newBP) == K * sum_of_reachable(oldBP) // Sum of newBP must be equal to 1.0: // sum_of_reachable(newBP) + sum_of_unreachable(newBP) == 1.0 => // sum_of_reachable(newBP) = 1.0 - sum_of_unreachable(newBP) // Where sum_of_unreachable(newBP) is what has been just changed. // Finally: // K == sum_of_reachable(newBP) / sum_of_reachable(oldBP) => // K == (1.0 - sum_of_unreachable(newBP)) / sum_of_reachable(oldBP) BranchProbability NewUnreachableSum = BranchProbability::getZero(); for (auto I : UnreachableIdxs) NewUnreachableSum += BP[I]; BranchProbability NewReachableSum = BranchProbability::getOne() - NewUnreachableSum; BranchProbability OldReachableSum = BranchProbability::getZero(); for (auto I : ReachableIdxs) OldReachableSum += BP[I]; if (OldReachableSum != NewReachableSum) { // Anything to dsitribute? if (OldReachableSum.isZero()) { // If all oldBP[i] are zeroes then the proportional distribution results // in all zero probabilities and the error stays big. In this case we // evenly spread NewReachableSum over the reachable edges. BranchProbability PerEdge = NewReachableSum / ReachableIdxs.size(); for (auto I : ReachableIdxs) BP[I] = PerEdge; } else { for (auto I : ReachableIdxs) { // We use uint64_t to avoid double rounding error of the following // calculation: BP[i] = BP[i] * NewReachableSum / OldReachableSum // The formula is taken from the private constructor // BranchProbability(uint32_t Numerator, uint32_t Denominator) uint64_t Mul = static_cast(NewReachableSum.getNumerator()) * BP[I].getNumerator(); uint32_t Div = static_cast( divideNearest(Mul, OldReachableSum.getNumerator())); BP[I] = BranchProbability::getRaw(Div); } } } setEdgeProbability(BB, BP); return true; } // Calculate Edge Weights using "Pointer Heuristics". Predict a comparison // between two pointer or pointer and NULL will fail. bool BranchProbabilityInfo::calcPointerHeuristics(const BasicBlock *BB) { const BranchInst *BI = dyn_cast(BB->getTerminator()); if (!BI || !BI->isConditional()) return false; Value *Cond = BI->getCondition(); ICmpInst *CI = dyn_cast(Cond); if (!CI || !CI->isEquality()) return false; Value *LHS = CI->getOperand(0); if (!LHS->getType()->isPointerTy()) return false; assert(CI->getOperand(1)->getType()->isPointerTy()); BranchProbability TakenProb(PH_TAKEN_WEIGHT, PH_TAKEN_WEIGHT + PH_NONTAKEN_WEIGHT); BranchProbability UntakenProb(PH_NONTAKEN_WEIGHT, PH_TAKEN_WEIGHT + PH_NONTAKEN_WEIGHT); // p != 0 -> isProb = true // p == 0 -> isProb = false // p != q -> isProb = true // p == q -> isProb = false; bool isProb = CI->getPredicate() == ICmpInst::ICMP_NE; if (!isProb) std::swap(TakenProb, UntakenProb); setEdgeProbability( BB, SmallVector({TakenProb, UntakenProb})); return true; } // Compute the unlikely successors to the block BB in the loop L, specifically // those that are unlikely because this is a loop, and add them to the // UnlikelyBlocks set. static void computeUnlikelySuccessors(const BasicBlock *BB, Loop *L, SmallPtrSetImpl &UnlikelyBlocks) { // Sometimes in a loop we have a branch whose condition is made false by // taking it. This is typically something like // int n = 0; // while (...) { // if (++n >= MAX) { // n = 0; // } // } // In this sort of situation taking the branch means that at the very least it // won't be taken again in the next iteration of the loop, so we should // consider it less likely than a typical branch. // // We detect this by looking back through the graph of PHI nodes that sets the // value that the condition depends on, and seeing if we can reach a successor // block which can be determined to make the condition false. // // FIXME: We currently consider unlikely blocks to be half as likely as other // blocks, but if we consider the example above the likelyhood is actually // 1/MAX. We could therefore be more precise in how unlikely we consider // blocks to be, but it would require more careful examination of the form // of the comparison expression. const BranchInst *BI = dyn_cast(BB->getTerminator()); if (!BI || !BI->isConditional()) return; // Check if the branch is based on an instruction compared with a constant CmpInst *CI = dyn_cast(BI->getCondition()); if (!CI || !isa(CI->getOperand(0)) || !isa(CI->getOperand(1))) return; // Either the instruction must be a PHI, or a chain of operations involving // constants that ends in a PHI which we can then collapse into a single value // if the PHI value is known. Instruction *CmpLHS = dyn_cast(CI->getOperand(0)); PHINode *CmpPHI = dyn_cast(CmpLHS); Constant *CmpConst = dyn_cast(CI->getOperand(1)); // Collect the instructions until we hit a PHI SmallVector InstChain; while (!CmpPHI && CmpLHS && isa(CmpLHS) && isa(CmpLHS->getOperand(1))) { // Stop if the chain extends outside of the loop if (!L->contains(CmpLHS)) return; InstChain.push_back(cast(CmpLHS)); CmpLHS = dyn_cast(CmpLHS->getOperand(0)); if (CmpLHS) CmpPHI = dyn_cast(CmpLHS); } if (!CmpPHI || !L->contains(CmpPHI)) return; // Trace the phi node to find all values that come from successors of BB SmallPtrSet VisitedInsts; SmallVector WorkList; WorkList.push_back(CmpPHI); VisitedInsts.insert(CmpPHI); while (!WorkList.empty()) { PHINode *P = WorkList.pop_back_val(); for (BasicBlock *B : P->blocks()) { // Skip blocks that aren't part of the loop if (!L->contains(B)) continue; Value *V = P->getIncomingValueForBlock(B); // If the source is a PHI add it to the work list if we haven't // already visited it. if (PHINode *PN = dyn_cast(V)) { if (VisitedInsts.insert(PN).second) WorkList.push_back(PN); continue; } // If this incoming value is a constant and B is a successor of BB, then // we can constant-evaluate the compare to see if it makes the branch be // taken or not. Constant *CmpLHSConst = dyn_cast(V); if (!CmpLHSConst || !llvm::is_contained(successors(BB), B)) continue; // First collapse InstChain for (Instruction *I : llvm::reverse(InstChain)) { CmpLHSConst = ConstantExpr::get(I->getOpcode(), CmpLHSConst, cast(I->getOperand(1)), true); if (!CmpLHSConst) break; } if (!CmpLHSConst) continue; // Now constant-evaluate the compare Constant *Result = ConstantExpr::getCompare(CI->getPredicate(), CmpLHSConst, CmpConst, true); // If the result means we don't branch to the block then that block is // unlikely. if (Result && ((Result->isZeroValue() && B == BI->getSuccessor(0)) || (Result->isOneValue() && B == BI->getSuccessor(1)))) UnlikelyBlocks.insert(B); } } } Optional BranchProbabilityInfo::getEstimatedBlockWeight(const BasicBlock *BB) const { auto WeightIt = EstimatedBlockWeight.find(BB); if (WeightIt == EstimatedBlockWeight.end()) return None; return WeightIt->second; } Optional BranchProbabilityInfo::getEstimatedLoopWeight(const LoopData &L) const { auto WeightIt = EstimatedLoopWeight.find(L); if (WeightIt == EstimatedLoopWeight.end()) return None; return WeightIt->second; } Optional BranchProbabilityInfo::getEstimatedEdgeWeight(const LoopEdge &Edge) const { // For edges entering a loop take weight of a loop rather than an individual // block in the loop. return isLoopEnteringEdge(Edge) ? getEstimatedLoopWeight(Edge.second.getLoopData()) : getEstimatedBlockWeight(Edge.second.getBlock()); } template Optional BranchProbabilityInfo::getMaxEstimatedEdgeWeight( const LoopBlock &SrcLoopBB, iterator_range Successors) const { SmallVector Weights; Optional MaxWeight; for (const BasicBlock *DstBB : Successors) { const LoopBlock DstLoopBB = getLoopBlock(DstBB); auto Weight = getEstimatedEdgeWeight({SrcLoopBB, DstLoopBB}); if (!Weight) return None; if (!MaxWeight || MaxWeight.getValue() < Weight.getValue()) MaxWeight = Weight; } return MaxWeight; } // Updates \p LoopBB's weight and returns true. If \p LoopBB has already // an associated weight it is unchanged and false is returned. // // Please note by the algorithm the weight is not expected to change once set // thus 'false' status is used to track visited blocks. bool BranchProbabilityInfo::updateEstimatedBlockWeight( LoopBlock &LoopBB, uint32_t BBWeight, SmallVectorImpl &BlockWorkList, SmallVectorImpl &LoopWorkList) { BasicBlock *BB = LoopBB.getBlock(); // In general, weight is assigned to a block when it has final value and // can't/shouldn't be changed. However, there are cases when a block // inherently has several (possibly "contradicting") weights. For example, // "unwind" block may also contain "cold" call. In that case the first // set weight is favored and all consequent weights are ignored. if (!EstimatedBlockWeight.insert({BB, BBWeight}).second) return false; for (BasicBlock *PredBlock : predecessors(BB)) { LoopBlock PredLoop = getLoopBlock(PredBlock); // Add affected block/loop to a working list. if (isLoopExitingEdge({PredLoop, LoopBB})) { if (!EstimatedLoopWeight.count(PredLoop.getLoopData())) LoopWorkList.push_back(PredLoop); } else if (!EstimatedBlockWeight.count(PredBlock)) BlockWorkList.push_back(PredBlock); } return true; } // Starting from \p BB traverse through dominator blocks and assign \p BBWeight // to all such blocks that are post dominated by \BB. In other words to all // blocks that the one is executed if and only if another one is executed. // Importantly, we skip loops here for two reasons. First weights of blocks in // a loop should be scaled by trip count (yet possibly unknown). Second there is // no any value in doing that because that doesn't give any additional // information regarding distribution of probabilities inside the loop. // Exception is loop 'enter' and 'exit' edges that are handled in a special way // at calcEstimatedHeuristics. // // In addition, \p WorkList is populated with basic blocks if at leas one // successor has updated estimated weight. void BranchProbabilityInfo::propagateEstimatedBlockWeight( const LoopBlock &LoopBB, DominatorTree *DT, PostDominatorTree *PDT, uint32_t BBWeight, SmallVectorImpl &BlockWorkList, SmallVectorImpl &LoopWorkList) { const BasicBlock *BB = LoopBB.getBlock(); const auto *DTStartNode = DT->getNode(BB); const auto *PDTStartNode = PDT->getNode(BB); // TODO: Consider propagating weight down the domination line as well. for (const auto *DTNode = DTStartNode; DTNode != nullptr; DTNode = DTNode->getIDom()) { auto *DomBB = DTNode->getBlock(); // Consider blocks which lie on one 'line'. if (!PDT->dominates(PDTStartNode, PDT->getNode(DomBB))) // If BB doesn't post dominate DomBB it will not post dominate dominators // of DomBB as well. break; LoopBlock DomLoopBB = getLoopBlock(DomBB); const LoopEdge Edge{DomLoopBB, LoopBB}; // Don't propagate weight to blocks belonging to different loops. if (!isLoopEnteringExitingEdge(Edge)) { if (!updateEstimatedBlockWeight(DomLoopBB, BBWeight, BlockWorkList, LoopWorkList)) // If DomBB has weight set then all it's predecessors are already // processed (since we propagate weight up to the top of IR each time). break; } else if (isLoopExitingEdge(Edge)) { LoopWorkList.push_back(DomLoopBB); } } } Optional BranchProbabilityInfo::getInitialEstimatedBlockWeight( const BasicBlock *BB) { // Returns true if \p BB has call marked with "NoReturn" attribute. auto hasNoReturn = [&](const BasicBlock *BB) { for (const auto &I : reverse(*BB)) if (const CallInst *CI = dyn_cast(&I)) if (CI->hasFnAttr(Attribute::NoReturn)) return true; return false; }; // Important note regarding the order of checks. They are ordered by weight // from lowest to highest. Doing that allows to avoid "unstable" results // when several conditions heuristics can be applied simultaneously. if (isa(BB->getTerminator()) || // If this block is terminated by a call to // @llvm.experimental.deoptimize then treat it like an unreachable // since it is expected to practically never execute. // TODO: Should we actually treat as never returning call? BB->getTerminatingDeoptimizeCall()) return hasNoReturn(BB) ? static_cast(BlockExecWeight::NORETURN) : static_cast(BlockExecWeight::UNREACHABLE); // Check if the block is 'unwind' handler of some invoke instruction. for (const auto *Pred : predecessors(BB)) if (Pred) if (const auto *II = dyn_cast(Pred->getTerminator())) if (II->getUnwindDest() == BB) return static_cast(BlockExecWeight::UNWIND); // Check if the block contains 'cold' call. for (const auto &I : *BB) if (const CallInst *CI = dyn_cast(&I)) if (CI->hasFnAttr(Attribute::Cold)) return static_cast(BlockExecWeight::COLD); return None; } // Does RPO traversal over all blocks in \p F and assigns weights to // 'unreachable', 'noreturn', 'cold', 'unwind' blocks. In addition it does its // best to propagate the weight to up/down the IR. void BranchProbabilityInfo::computeEestimateBlockWeight( const Function &F, DominatorTree *DT, PostDominatorTree *PDT) { SmallVector BlockWorkList; SmallVector LoopWorkList; // By doing RPO we make sure that all predecessors already have weights // calculated before visiting theirs successors. ReversePostOrderTraversal RPOT(&F); for (const auto *BB : RPOT) if (auto BBWeight = getInitialEstimatedBlockWeight(BB)) // If we were able to find estimated weight for the block set it to this // block and propagate up the IR. propagateEstimatedBlockWeight(getLoopBlock(BB), DT, PDT, BBWeight.getValue(), BlockWorkList, LoopWorkList); // BlockWorklist/LoopWorkList contains blocks/loops with at least one // successor/exit having estimated weight. Try to propagate weight to such // blocks/loops from successors/exits. // Process loops and blocks. Order is not important. do { while (!LoopWorkList.empty()) { const LoopBlock LoopBB = LoopWorkList.pop_back_val(); if (EstimatedLoopWeight.count(LoopBB.getLoopData())) continue; SmallVector Exits; getLoopExitBlocks(LoopBB, Exits); auto LoopWeight = getMaxEstimatedEdgeWeight( LoopBB, make_range(Exits.begin(), Exits.end())); if (LoopWeight) { // If we never exit the loop then we can enter it once at maximum. if (LoopWeight <= static_cast(BlockExecWeight::UNREACHABLE)) LoopWeight = static_cast(BlockExecWeight::LOWEST_NON_ZERO); EstimatedLoopWeight.insert( {LoopBB.getLoopData(), LoopWeight.getValue()}); // Add all blocks entering the loop into working list. getLoopEnterBlocks(LoopBB, BlockWorkList); } } while (!BlockWorkList.empty()) { // We can reach here only if BlockWorkList is not empty. const BasicBlock *BB = BlockWorkList.pop_back_val(); if (EstimatedBlockWeight.count(BB)) continue; // We take maximum over all weights of successors. In other words we take // weight of "hot" path. In theory we can probably find a better function // which gives higher accuracy results (comparing to "maximum") but I // can't // think of any right now. And I doubt it will make any difference in // practice. const LoopBlock LoopBB = getLoopBlock(BB); auto MaxWeight = getMaxEstimatedEdgeWeight(LoopBB, successors(BB)); if (MaxWeight) propagateEstimatedBlockWeight(LoopBB, DT, PDT, MaxWeight.getValue(), BlockWorkList, LoopWorkList); } } while (!BlockWorkList.empty() || !LoopWorkList.empty()); } // Calculate edge probabilities based on block's estimated weight. // Note that gathered weights were not scaled for loops. Thus edges entering // and exiting loops requires special processing. bool BranchProbabilityInfo::calcEstimatedHeuristics(const BasicBlock *BB) { assert(BB->getTerminator()->getNumSuccessors() > 1 && "expected more than one successor!"); const LoopBlock LoopBB = getLoopBlock(BB); SmallPtrSet UnlikelyBlocks; uint32_t TC = LBH_TAKEN_WEIGHT / LBH_NONTAKEN_WEIGHT; if (LoopBB.getLoop()) computeUnlikelySuccessors(BB, LoopBB.getLoop(), UnlikelyBlocks); // Changed to 'true' if at least one successor has estimated weight. bool FoundEstimatedWeight = false; SmallVector SuccWeights; uint64_t TotalWeight = 0; // Go over all successors of BB and put their weights into SuccWeights. for (const BasicBlock *SuccBB : successors(BB)) { Optional Weight; const LoopBlock SuccLoopBB = getLoopBlock(SuccBB); const LoopEdge Edge{LoopBB, SuccLoopBB}; Weight = getEstimatedEdgeWeight(Edge); if (isLoopExitingEdge(Edge) && // Avoid adjustment of ZERO weight since it should remain unchanged. Weight != static_cast(BlockExecWeight::ZERO)) { // Scale down loop exiting weight by trip count. Weight = std::max( static_cast(BlockExecWeight::LOWEST_NON_ZERO), Weight.getValueOr(static_cast(BlockExecWeight::DEFAULT)) / TC); } bool IsUnlikelyEdge = LoopBB.getLoop() && UnlikelyBlocks.contains(SuccBB); if (IsUnlikelyEdge && // Avoid adjustment of ZERO weight since it should remain unchanged. Weight != static_cast(BlockExecWeight::ZERO)) { // 'Unlikely' blocks have twice lower weight. Weight = std::max( static_cast(BlockExecWeight::LOWEST_NON_ZERO), Weight.getValueOr(static_cast(BlockExecWeight::DEFAULT)) / 2); } if (Weight) FoundEstimatedWeight = true; auto WeightVal = Weight.getValueOr(static_cast(BlockExecWeight::DEFAULT)); TotalWeight += WeightVal; SuccWeights.push_back(WeightVal); } // If non of blocks have estimated weight bail out. // If TotalWeight is 0 that means weight of each successor is 0 as well and // equally likely. Bail out early to not deal with devision by zero. if (!FoundEstimatedWeight || TotalWeight == 0) return false; assert(SuccWeights.size() == succ_size(BB) && "Missed successor?"); const unsigned SuccCount = SuccWeights.size(); // If the sum of weights does not fit in 32 bits, scale every weight down // accordingly. if (TotalWeight > UINT32_MAX) { uint64_t ScalingFactor = TotalWeight / UINT32_MAX + 1; TotalWeight = 0; for (unsigned Idx = 0; Idx < SuccCount; ++Idx) { SuccWeights[Idx] /= ScalingFactor; if (SuccWeights[Idx] == static_cast(BlockExecWeight::ZERO)) SuccWeights[Idx] = static_cast(BlockExecWeight::LOWEST_NON_ZERO); TotalWeight += SuccWeights[Idx]; } assert(TotalWeight <= UINT32_MAX && "Total weight overflows"); } // Finally set probabilities to edges according to estimated block weights. SmallVector EdgeProbabilities( SuccCount, BranchProbability::getUnknown()); for (unsigned Idx = 0; Idx < SuccCount; ++Idx) { EdgeProbabilities[Idx] = BranchProbability(SuccWeights[Idx], (uint32_t)TotalWeight); } setEdgeProbability(BB, EdgeProbabilities); return true; } bool BranchProbabilityInfo::calcZeroHeuristics(const BasicBlock *BB, const TargetLibraryInfo *TLI) { const BranchInst *BI = dyn_cast(BB->getTerminator()); if (!BI || !BI->isConditional()) return false; Value *Cond = BI->getCondition(); ICmpInst *CI = dyn_cast(Cond); if (!CI) return false; auto GetConstantInt = [](Value *V) { if (auto *I = dyn_cast(V)) return dyn_cast(I->getOperand(0)); return dyn_cast(V); }; Value *RHS = CI->getOperand(1); ConstantInt *CV = GetConstantInt(RHS); if (!CV) return false; // If the LHS is the result of AND'ing a value with a single bit bitmask, // we don't have information about probabilities. if (Instruction *LHS = dyn_cast(CI->getOperand(0))) if (LHS->getOpcode() == Instruction::And) if (ConstantInt *AndRHS = GetConstantInt(LHS->getOperand(1))) if (AndRHS->getValue().isPowerOf2()) return false; // Check if the LHS is the return value of a library function LibFunc Func = NumLibFuncs; if (TLI) if (CallInst *Call = dyn_cast(CI->getOperand(0))) if (Function *CalledFn = Call->getCalledFunction()) TLI->getLibFunc(*CalledFn, Func); bool isProb; if (Func == LibFunc_strcasecmp || Func == LibFunc_strcmp || Func == LibFunc_strncasecmp || Func == LibFunc_strncmp || Func == LibFunc_memcmp || Func == LibFunc_bcmp) { // strcmp and similar functions return zero, negative, or positive, if the // first string is equal, less, or greater than the second. We consider it // likely that the strings are not equal, so a comparison with zero is // probably false, but also a comparison with any other number is also // probably false given that what exactly is returned for nonzero values is // not specified. Any kind of comparison other than equality we know // nothing about. switch (CI->getPredicate()) { case CmpInst::ICMP_EQ: isProb = false; break; case CmpInst::ICMP_NE: isProb = true; break; default: return false; } } else if (CV->isZero()) { switch (CI->getPredicate()) { case CmpInst::ICMP_EQ: // X == 0 -> Unlikely isProb = false; break; case CmpInst::ICMP_NE: // X != 0 -> Likely isProb = true; break; case CmpInst::ICMP_SLT: // X < 0 -> Unlikely isProb = false; break; case CmpInst::ICMP_SGT: // X > 0 -> Likely isProb = true; break; default: return false; } } else if (CV->isOne() && CI->getPredicate() == CmpInst::ICMP_SLT) { // InstCombine canonicalizes X <= 0 into X < 1. // X <= 0 -> Unlikely isProb = false; } else if (CV->isMinusOne()) { switch (CI->getPredicate()) { case CmpInst::ICMP_EQ: // X == -1 -> Unlikely isProb = false; break; case CmpInst::ICMP_NE: // X != -1 -> Likely isProb = true; break; case CmpInst::ICMP_SGT: // InstCombine canonicalizes X >= 0 into X > -1. // X >= 0 -> Likely isProb = true; break; default: return false; } } else { return false; } BranchProbability TakenProb(ZH_TAKEN_WEIGHT, ZH_TAKEN_WEIGHT + ZH_NONTAKEN_WEIGHT); BranchProbability UntakenProb(ZH_NONTAKEN_WEIGHT, ZH_TAKEN_WEIGHT + ZH_NONTAKEN_WEIGHT); if (!isProb) std::swap(TakenProb, UntakenProb); setEdgeProbability( BB, SmallVector({TakenProb, UntakenProb})); return true; } bool BranchProbabilityInfo::calcFloatingPointHeuristics(const BasicBlock *BB) { const BranchInst *BI = dyn_cast(BB->getTerminator()); if (!BI || !BI->isConditional()) return false; Value *Cond = BI->getCondition(); FCmpInst *FCmp = dyn_cast(Cond); if (!FCmp) return false; uint32_t TakenWeight = FPH_TAKEN_WEIGHT; uint32_t NontakenWeight = FPH_NONTAKEN_WEIGHT; bool isProb; if (FCmp->isEquality()) { // f1 == f2 -> Unlikely // f1 != f2 -> Likely isProb = !FCmp->isTrueWhenEqual(); } else if (FCmp->getPredicate() == FCmpInst::FCMP_ORD) { // !isnan -> Likely isProb = true; TakenWeight = FPH_ORD_WEIGHT; NontakenWeight = FPH_UNO_WEIGHT; } else if (FCmp->getPredicate() == FCmpInst::FCMP_UNO) { // isnan -> Unlikely isProb = false; TakenWeight = FPH_ORD_WEIGHT; NontakenWeight = FPH_UNO_WEIGHT; } else { return false; } BranchProbability TakenProb(TakenWeight, TakenWeight + NontakenWeight); BranchProbability UntakenProb(NontakenWeight, TakenWeight + NontakenWeight); if (!isProb) std::swap(TakenProb, UntakenProb); setEdgeProbability( BB, SmallVector({TakenProb, UntakenProb})); return true; } void BranchProbabilityInfo::releaseMemory() { Probs.clear(); Handles.clear(); } bool BranchProbabilityInfo::invalidate(Function &, const PreservedAnalyses &PA, FunctionAnalysisManager::Invalidator &) { // Check whether the analysis, all analyses on functions, or the function's // CFG have been preserved. auto PAC = PA.getChecker(); return !(PAC.preserved() || PAC.preservedSet>() || PAC.preservedSet()); } void BranchProbabilityInfo::print(raw_ostream &OS) const { OS << "---- Branch Probabilities ----\n"; // We print the probabilities from the last function the analysis ran over, // or the function it is currently running over. assert(LastF && "Cannot print prior to running over a function"); for (const auto &BI : *LastF) { for (const BasicBlock *Succ : successors(&BI)) printEdgeProbability(OS << " ", &BI, Succ); } } bool BranchProbabilityInfo:: isEdgeHot(const BasicBlock *Src, const BasicBlock *Dst) const { // Hot probability is at least 4/5 = 80% // FIXME: Compare against a static "hot" BranchProbability. return getEdgeProbability(Src, Dst) > BranchProbability(4, 5); } /// Get the raw edge probability for the edge. If can't find it, return a /// default probability 1/N where N is the number of successors. Here an edge is /// specified using PredBlock and an /// index to the successors. BranchProbability BranchProbabilityInfo::getEdgeProbability(const BasicBlock *Src, unsigned IndexInSuccessors) const { auto I = Probs.find(std::make_pair(Src, IndexInSuccessors)); assert((Probs.end() == Probs.find(std::make_pair(Src, 0))) == (Probs.end() == I) && "Probability for I-th successor must always be defined along with the " "probability for the first successor"); if (I != Probs.end()) return I->second; return {1, static_cast(succ_size(Src))}; } BranchProbability BranchProbabilityInfo::getEdgeProbability(const BasicBlock *Src, const_succ_iterator Dst) const { return getEdgeProbability(Src, Dst.getSuccessorIndex()); } /// Get the raw edge probability calculated for the block pair. This returns the /// sum of all raw edge probabilities from Src to Dst. BranchProbability BranchProbabilityInfo::getEdgeProbability(const BasicBlock *Src, const BasicBlock *Dst) const { if (!Probs.count(std::make_pair(Src, 0))) return BranchProbability(llvm::count(successors(Src), Dst), succ_size(Src)); auto Prob = BranchProbability::getZero(); for (const_succ_iterator I = succ_begin(Src), E = succ_end(Src); I != E; ++I) if (*I == Dst) Prob += Probs.find(std::make_pair(Src, I.getSuccessorIndex()))->second; return Prob; } /// Set the edge probability for all edges at once. void BranchProbabilityInfo::setEdgeProbability( const BasicBlock *Src, const SmallVectorImpl &Probs) { assert(Src->getTerminator()->getNumSuccessors() == Probs.size()); eraseBlock(Src); // Erase stale data if any. if (Probs.size() == 0) return; // Nothing to set. Handles.insert(BasicBlockCallbackVH(Src, this)); uint64_t TotalNumerator = 0; for (unsigned SuccIdx = 0; SuccIdx < Probs.size(); ++SuccIdx) { this->Probs[std::make_pair(Src, SuccIdx)] = Probs[SuccIdx]; LLVM_DEBUG(dbgs() << "set edge " << Src->getName() << " -> " << SuccIdx << " successor probability to " << Probs[SuccIdx] << "\n"); TotalNumerator += Probs[SuccIdx].getNumerator(); } // Because of rounding errors the total probability cannot be checked to be // 1.0 exactly. That is TotalNumerator == BranchProbability::getDenominator. // Instead, every single probability in Probs must be as accurate as possible. // This results in error 1/denominator at most, thus the total absolute error // should be within Probs.size / BranchProbability::getDenominator. assert(TotalNumerator <= BranchProbability::getDenominator() + Probs.size()); assert(TotalNumerator >= BranchProbability::getDenominator() - Probs.size()); (void)TotalNumerator; } void BranchProbabilityInfo::copyEdgeProbabilities(BasicBlock *Src, BasicBlock *Dst) { eraseBlock(Dst); // Erase stale data if any. unsigned NumSuccessors = Src->getTerminator()->getNumSuccessors(); assert(NumSuccessors == Dst->getTerminator()->getNumSuccessors()); if (NumSuccessors == 0) return; // Nothing to set. if (this->Probs.find(std::make_pair(Src, 0)) == this->Probs.end()) return; // No probability is set for edges from Src. Keep the same for Dst. Handles.insert(BasicBlockCallbackVH(Dst, this)); for (unsigned SuccIdx = 0; SuccIdx < NumSuccessors; ++SuccIdx) { auto Prob = this->Probs[std::make_pair(Src, SuccIdx)]; this->Probs[std::make_pair(Dst, SuccIdx)] = Prob; LLVM_DEBUG(dbgs() << "set edge " << Dst->getName() << " -> " << SuccIdx << " successor probability to " << Prob << "\n"); } } raw_ostream & BranchProbabilityInfo::printEdgeProbability(raw_ostream &OS, const BasicBlock *Src, const BasicBlock *Dst) const { const BranchProbability Prob = getEdgeProbability(Src, Dst); OS << "edge " << Src->getName() << " -> " << Dst->getName() << " probability is " << Prob << (isEdgeHot(Src, Dst) ? " [HOT edge]\n" : "\n"); return OS; } void BranchProbabilityInfo::eraseBlock(const BasicBlock *BB) { LLVM_DEBUG(dbgs() << "eraseBlock " << BB->getName() << "\n"); // Note that we cannot use successors of BB because the terminator of BB may // have changed when eraseBlock is called as a BasicBlockCallbackVH callback. // Instead we remove prob data for the block by iterating successors by their // indices from 0 till the last which exists. There could not be prob data for // a pair (BB, N) if there is no data for (BB, N-1) because the data is always // set for all successors from 0 to M at once by the method // setEdgeProbability(). Handles.erase(BasicBlockCallbackVH(BB, this)); for (unsigned I = 0;; ++I) { auto MapI = Probs.find(std::make_pair(BB, I)); if (MapI == Probs.end()) { assert(Probs.count(std::make_pair(BB, I + 1)) == 0 && "Must be no more successors"); return; } Probs.erase(MapI); } } void BranchProbabilityInfo::calculate(const Function &F, const LoopInfo &LoopI, const TargetLibraryInfo *TLI, DominatorTree *DT, PostDominatorTree *PDT) { LLVM_DEBUG(dbgs() << "---- Branch Probability Info : " << F.getName() << " ----\n\n"); LastF = &F; // Store the last function we ran on for printing. LI = &LoopI; SccI = std::make_unique(F); assert(EstimatedBlockWeight.empty()); assert(EstimatedLoopWeight.empty()); std::unique_ptr DTPtr; std::unique_ptr PDTPtr; if (!DT) { DTPtr = std::make_unique(const_cast(F)); DT = DTPtr.get(); } if (!PDT) { PDTPtr = std::make_unique(const_cast(F)); PDT = PDTPtr.get(); } computeEestimateBlockWeight(F, DT, PDT); // Walk the basic blocks in post-order so that we can build up state about // the successors of a block iteratively. for (auto BB : post_order(&F.getEntryBlock())) { LLVM_DEBUG(dbgs() << "Computing probabilities for " << BB->getName() << "\n"); // If there is no at least two successors, no sense to set probability. if (BB->getTerminator()->getNumSuccessors() < 2) continue; if (calcMetadataWeights(BB)) continue; if (calcEstimatedHeuristics(BB)) continue; if (calcPointerHeuristics(BB)) continue; if (calcZeroHeuristics(BB, TLI)) continue; if (calcFloatingPointHeuristics(BB)) continue; } EstimatedLoopWeight.clear(); EstimatedBlockWeight.clear(); SccI.reset(); if (PrintBranchProb && (PrintBranchProbFuncName.empty() || F.getName().equals(PrintBranchProbFuncName))) { print(dbgs()); } } void BranchProbabilityInfoWrapperPass::getAnalysisUsage( AnalysisUsage &AU) const { // We require DT so it's available when LI is available. The LI updating code // asserts that DT is also present so if we don't make sure that we have DT // here, that assert will trigger. AU.addRequired(); AU.addRequired(); AU.addRequired(); AU.addRequired(); AU.addRequired(); AU.setPreservesAll(); } bool BranchProbabilityInfoWrapperPass::runOnFunction(Function &F) { const LoopInfo &LI = getAnalysis().getLoopInfo(); const TargetLibraryInfo &TLI = getAnalysis().getTLI(F); DominatorTree &DT = getAnalysis().getDomTree(); PostDominatorTree &PDT = getAnalysis().getPostDomTree(); BPI.calculate(F, LI, &TLI, &DT, &PDT); return false; } void BranchProbabilityInfoWrapperPass::releaseMemory() { BPI.releaseMemory(); } void BranchProbabilityInfoWrapperPass::print(raw_ostream &OS, const Module *) const { BPI.print(OS); } AnalysisKey BranchProbabilityAnalysis::Key; BranchProbabilityInfo BranchProbabilityAnalysis::run(Function &F, FunctionAnalysisManager &AM) { BranchProbabilityInfo BPI; BPI.calculate(F, AM.getResult(F), &AM.getResult(F), &AM.getResult(F), &AM.getResult(F)); return BPI; } PreservedAnalyses BranchProbabilityPrinterPass::run(Function &F, FunctionAnalysisManager &AM) { OS << "Printing analysis results of BPI for function " << "'" << F.getName() << "':" << "\n"; AM.getResult(F).print(OS); return PreservedAnalyses::all(); }