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view lib/Analysis/DivergenceAnalysis.cpp @ 107:a03ddd01be7e
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author | Kaito Tokumori <e105711@ie.u-ryukyu.ac.jp> |
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date | Sun, 31 Jan 2016 17:34:49 +0900 |
parents | 7d135dc70f03 |
children | 1172e4bd9c6f |
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//===- DivergenceAnalysis.cpp --------- Divergence Analysis Implementation -==// // // The LLVM Compiler Infrastructure // // This file is distributed under the University of Illinois Open Source // License. See LICENSE.TXT for details. // //===----------------------------------------------------------------------===// // // This file implements divergence analysis which determines whether a branch // in a GPU program is divergent.It can help branch optimizations such as jump // threading and loop unswitching to make better decisions. // // GPU programs typically use the SIMD execution model, where multiple threads // in the same execution group have to execute in lock-step. Therefore, if the // code contains divergent branches (i.e., threads in a group do not agree on // which path of the branch to take), the group of threads has to execute all // the paths from that branch with different subsets of threads enabled until // they converge at the immediately post-dominating BB of the paths. // // Due to this execution model, some optimizations such as jump // threading and loop unswitching can be unfortunately harmful when performed on // divergent branches. Therefore, an analysis that computes which branches in a // GPU program are divergent can help the compiler to selectively run these // optimizations. // // This file defines divergence analysis which computes a conservative but // non-trivial approximation of all divergent branches in a GPU program. It // partially implements the approach described in // // Divergence Analysis // Sampaio, Souza, Collange, Pereira // TOPLAS '13 // // The divergence analysis identifies the sources of divergence (e.g., special // variables that hold the thread ID), and recursively marks variables that are // data or sync dependent on a source of divergence as divergent. // // While data dependency is a well-known concept, the notion of sync dependency // is worth more explanation. Sync dependence characterizes the control flow // aspect of the propagation of branch divergence. For example, // // %cond = icmp slt i32 %tid, 10 // br i1 %cond, label %then, label %else // then: // br label %merge // else: // br label %merge // merge: // %a = phi i32 [ 0, %then ], [ 1, %else ] // // Suppose %tid holds the thread ID. Although %a is not data dependent on %tid // because %tid is not on its use-def chains, %a is sync dependent on %tid // because the branch "br i1 %cond" depends on %tid and affects which value %a // is assigned to. // // The current implementation has the following limitations: // 1. intra-procedural. It conservatively considers the arguments of a // non-kernel-entry function and the return value of a function call as // divergent. // 2. memory as black box. It conservatively considers values loaded from // generic or local address as divergent. This can be improved by leveraging // pointer analysis. // //===----------------------------------------------------------------------===// #include "llvm/Analysis/DivergenceAnalysis.h" #include "llvm/Analysis/Passes.h" #include "llvm/Analysis/PostDominators.h" #include "llvm/Analysis/TargetTransformInfo.h" #include "llvm/IR/Dominators.h" #include "llvm/IR/InstIterator.h" #include "llvm/IR/Instructions.h" #include "llvm/IR/IntrinsicInst.h" #include "llvm/IR/Value.h" #include "llvm/Support/CommandLine.h" #include "llvm/Support/Debug.h" #include "llvm/Support/raw_ostream.h" #include "llvm/Transforms/Scalar.h" #include <vector> using namespace llvm; namespace { class DivergencePropagator { public: DivergencePropagator(Function &F, TargetTransformInfo &TTI, DominatorTree &DT, PostDominatorTree &PDT, DenseSet<const Value *> &DV) : F(F), TTI(TTI), DT(DT), PDT(PDT), DV(DV) {} void populateWithSourcesOfDivergence(); void propagate(); private: // A helper function that explores data dependents of V. void exploreDataDependency(Value *V); // A helper function that explores sync dependents of TI. void exploreSyncDependency(TerminatorInst *TI); // Computes the influence region from Start to End. This region includes all // basic blocks on any simple path from Start to End. void computeInfluenceRegion(BasicBlock *Start, BasicBlock *End, DenseSet<BasicBlock *> &InfluenceRegion); // Finds all users of I that are outside the influence region, and add these // users to Worklist. void findUsersOutsideInfluenceRegion( Instruction &I, const DenseSet<BasicBlock *> &InfluenceRegion); Function &F; TargetTransformInfo &TTI; DominatorTree &DT; PostDominatorTree &PDT; std::vector<Value *> Worklist; // Stack for DFS. DenseSet<const Value *> &DV; // Stores all divergent values. }; void DivergencePropagator::populateWithSourcesOfDivergence() { Worklist.clear(); DV.clear(); for (auto &I : instructions(F)) { if (TTI.isSourceOfDivergence(&I)) { Worklist.push_back(&I); DV.insert(&I); } } for (auto &Arg : F.args()) { if (TTI.isSourceOfDivergence(&Arg)) { Worklist.push_back(&Arg); DV.insert(&Arg); } } } void DivergencePropagator::exploreSyncDependency(TerminatorInst *TI) { // Propagation rule 1: if branch TI is divergent, all PHINodes in TI's // immediate post dominator are divergent. This rule handles if-then-else // patterns. For example, // // if (tid < 5) // a1 = 1; // else // a2 = 2; // a = phi(a1, a2); // sync dependent on (tid < 5) BasicBlock *ThisBB = TI->getParent(); BasicBlock *IPostDom = PDT.getNode(ThisBB)->getIDom()->getBlock(); if (IPostDom == nullptr) return; for (auto I = IPostDom->begin(); isa<PHINode>(I); ++I) { // A PHINode is uniform if it returns the same value no matter which path is // taken. if (!cast<PHINode>(I)->hasConstantValue() && DV.insert(&*I).second) Worklist.push_back(&*I); } // Propagation rule 2: if a value defined in a loop is used outside, the user // is sync dependent on the condition of the loop exits that dominate the // user. For example, // // int i = 0; // do { // i++; // if (foo(i)) ... // uniform // } while (i < tid); // if (bar(i)) ... // divergent // // A program may contain unstructured loops. Therefore, we cannot leverage // LoopInfo, which only recognizes natural loops. // // The algorithm used here handles both natural and unstructured loops. Given // a branch TI, we first compute its influence region, the union of all simple // paths from TI to its immediate post dominator (IPostDom). Then, we search // for all the values defined in the influence region but used outside. All // these users are sync dependent on TI. DenseSet<BasicBlock *> InfluenceRegion; computeInfluenceRegion(ThisBB, IPostDom, InfluenceRegion); // An insight that can speed up the search process is that all the in-region // values that are used outside must dominate TI. Therefore, instead of // searching every basic blocks in the influence region, we search all the // dominators of TI until it is outside the influence region. BasicBlock *InfluencedBB = ThisBB; while (InfluenceRegion.count(InfluencedBB)) { for (auto &I : *InfluencedBB) findUsersOutsideInfluenceRegion(I, InfluenceRegion); DomTreeNode *IDomNode = DT.getNode(InfluencedBB)->getIDom(); if (IDomNode == nullptr) break; InfluencedBB = IDomNode->getBlock(); } } void DivergencePropagator::findUsersOutsideInfluenceRegion( Instruction &I, const DenseSet<BasicBlock *> &InfluenceRegion) { for (User *U : I.users()) { Instruction *UserInst = cast<Instruction>(U); if (!InfluenceRegion.count(UserInst->getParent())) { if (DV.insert(UserInst).second) Worklist.push_back(UserInst); } } } // A helper function for computeInfluenceRegion that adds successors of "ThisBB" // to the influence region. static void addSuccessorsToInfluenceRegion(BasicBlock *ThisBB, BasicBlock *End, DenseSet<BasicBlock *> &InfluenceRegion, std::vector<BasicBlock *> &InfluenceStack) { for (BasicBlock *Succ : successors(ThisBB)) { if (Succ != End && InfluenceRegion.insert(Succ).second) InfluenceStack.push_back(Succ); } } void DivergencePropagator::computeInfluenceRegion( BasicBlock *Start, BasicBlock *End, DenseSet<BasicBlock *> &InfluenceRegion) { assert(PDT.properlyDominates(End, Start) && "End does not properly dominate Start"); // The influence region starts from the end of "Start" to the beginning of // "End". Therefore, "Start" should not be in the region unless "Start" is in // a loop that doesn't contain "End". std::vector<BasicBlock *> InfluenceStack; addSuccessorsToInfluenceRegion(Start, End, InfluenceRegion, InfluenceStack); while (!InfluenceStack.empty()) { BasicBlock *BB = InfluenceStack.back(); InfluenceStack.pop_back(); addSuccessorsToInfluenceRegion(BB, End, InfluenceRegion, InfluenceStack); } } void DivergencePropagator::exploreDataDependency(Value *V) { // Follow def-use chains of V. for (User *U : V->users()) { Instruction *UserInst = cast<Instruction>(U); if (DV.insert(UserInst).second) Worklist.push_back(UserInst); } } void DivergencePropagator::propagate() { // Traverse the dependency graph using DFS. while (!Worklist.empty()) { Value *V = Worklist.back(); Worklist.pop_back(); if (TerminatorInst *TI = dyn_cast<TerminatorInst>(V)) { // Terminators with less than two successors won't introduce sync // dependency. Ignore them. if (TI->getNumSuccessors() > 1) exploreSyncDependency(TI); } exploreDataDependency(V); } } } /// end namespace anonymous // Register this pass. char DivergenceAnalysis::ID = 0; INITIALIZE_PASS_BEGIN(DivergenceAnalysis, "divergence", "Divergence Analysis", false, true) INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass) INITIALIZE_PASS_DEPENDENCY(PostDominatorTree) INITIALIZE_PASS_END(DivergenceAnalysis, "divergence", "Divergence Analysis", false, true) FunctionPass *llvm::createDivergenceAnalysisPass() { return new DivergenceAnalysis(); } void DivergenceAnalysis::getAnalysisUsage(AnalysisUsage &AU) const { AU.addRequired<DominatorTreeWrapperPass>(); AU.addRequired<PostDominatorTree>(); AU.setPreservesAll(); } bool DivergenceAnalysis::runOnFunction(Function &F) { auto *TTIWP = getAnalysisIfAvailable<TargetTransformInfoWrapperPass>(); if (TTIWP == nullptr) return false; TargetTransformInfo &TTI = TTIWP->getTTI(F); // Fast path: if the target does not have branch divergence, we do not mark // any branch as divergent. if (!TTI.hasBranchDivergence()) return false; DivergentValues.clear(); DivergencePropagator DP(F, TTI, getAnalysis<DominatorTreeWrapperPass>().getDomTree(), getAnalysis<PostDominatorTree>(), DivergentValues); DP.populateWithSourcesOfDivergence(); DP.propagate(); return false; } void DivergenceAnalysis::print(raw_ostream &OS, const Module *) const { if (DivergentValues.empty()) return; const Value *FirstDivergentValue = *DivergentValues.begin(); const Function *F; if (const Argument *Arg = dyn_cast<Argument>(FirstDivergentValue)) { F = Arg->getParent(); } else if (const Instruction *I = dyn_cast<Instruction>(FirstDivergentValue)) { F = I->getParent()->getParent(); } else { llvm_unreachable("Only arguments and instructions can be divergent"); } // Dumps all divergent values in F, arguments and then instructions. for (auto &Arg : F->args()) { if (DivergentValues.count(&Arg)) OS << "DIVERGENT: " << Arg << "\n"; } // Iterate instructions using instructions() to ensure a deterministic order. for (auto &I : instructions(F)) { if (DivergentValues.count(&I)) OS << "DIVERGENT:" << I << "\n"; } }