1 //===- DivergenceAnalysis.cpp --------- Divergence Analysis Implementation -==// 2 // 3 // The LLVM Compiler Infrastructure 4 // 5 // This file is distributed under the University of Illinois Open Source 6 // License. See LICENSE.TXT for details. 7 // 8 //===----------------------------------------------------------------------===// 9 // 10 // This file implements divergence analysis which determines whether a branch 11 // in a GPU program is divergent.It can help branch optimizations such as jump 12 // threading and loop unswitching to make better decisions. 13 // 14 // GPU programs typically use the SIMD execution model, where multiple threads 15 // in the same execution group have to execute in lock-step. Therefore, if the 16 // code contains divergent branches (i.e., threads in a group do not agree on 17 // which path of the branch to take), the group of threads has to execute all 18 // the paths from that branch with different subsets of threads enabled until 19 // they converge at the immediately post-dominating BB of the paths. 20 // 21 // Due to this execution model, some optimizations such as jump 22 // threading and loop unswitching can be unfortunately harmful when performed on 23 // divergent branches. Therefore, an analysis that computes which branches in a 24 // GPU program are divergent can help the compiler to selectively run these 25 // optimizations. 26 // 27 // This file defines divergence analysis which computes a conservative but 28 // non-trivial approximation of all divergent branches in a GPU program. It 29 // partially implements the approach described in 30 // 31 // Divergence Analysis 32 // Sampaio, Souza, Collange, Pereira 33 // TOPLAS '13 34 // 35 // The divergence analysis identifies the sources of divergence (e.g., special 36 // variables that hold the thread ID), and recursively marks variables that are 37 // data or sync dependent on a source of divergence as divergent. 38 // 39 // While data dependency is a well-known concept, the notion of sync dependency 40 // is worth more explanation. Sync dependence characterizes the control flow 41 // aspect of the propagation of branch divergence. For example, 42 // 43 // %cond = icmp slt i32 %tid, 10 44 // br i1 %cond, label %then, label %else 45 // then: 46 // br label %merge 47 // else: 48 // br label %merge 49 // merge: 50 // %a = phi i32 [ 0, %then ], [ 1, %else ] 51 // 52 // Suppose %tid holds the thread ID. Although %a is not data dependent on %tid 53 // because %tid is not on its use-def chains, %a is sync dependent on %tid 54 // because the branch "br i1 %cond" depends on %tid and affects which value %a 55 // is assigned to. 56 // 57 // The current implementation has the following limitations: 58 // 1. intra-procedural. It conservatively considers the arguments of a 59 // non-kernel-entry function and the return value of a function call as 60 // divergent. 61 // 2. memory as black box. It conservatively considers values loaded from 62 // generic or local address as divergent. This can be improved by leveraging 63 // pointer analysis. 64 // 65 //===----------------------------------------------------------------------===// 66 67 #include "llvm/Analysis/DivergenceAnalysis.h" 68 #include "llvm/Analysis/Passes.h" 69 #include "llvm/Analysis/PostDominators.h" 70 #include "llvm/Analysis/TargetTransformInfo.h" 71 #include "llvm/IR/Dominators.h" 72 #include "llvm/IR/InstIterator.h" 73 #include "llvm/IR/Instructions.h" 74 #include "llvm/IR/IntrinsicInst.h" 75 #include "llvm/IR/Value.h" 76 #include "llvm/Support/CommandLine.h" 77 #include "llvm/Support/Debug.h" 78 #include "llvm/Support/raw_ostream.h" 79 #include "llvm/Transforms/Scalar.h" 80 #include <vector> 81 using namespace llvm; 82 83 namespace { 84 85 class DivergencePropagator { 86 public: 87 DivergencePropagator(Function &F, TargetTransformInfo &TTI, DominatorTree &DT, 88 PostDominatorTree &PDT, DenseSet<const Value *> &DV) 89 : F(F), TTI(TTI), DT(DT), PDT(PDT), DV(DV) {} 90 void populateWithSourcesOfDivergence(); 91 void propagate(); 92 93 private: 94 // A helper function that explores data dependents of V. 95 void exploreDataDependency(Value *V); 96 // A helper function that explores sync dependents of TI. 97 void exploreSyncDependency(TerminatorInst *TI); 98 // Computes the influence region from Start to End. This region includes all 99 // basic blocks on any path from Start to End. 100 void computeInfluenceRegion(BasicBlock *Start, BasicBlock *End, 101 DenseSet<BasicBlock *> &InfluenceRegion); 102 // Finds all users of I that are outside the influence region, and add these 103 // users to Worklist. 104 void findUsersOutsideInfluenceRegion( 105 Instruction &I, const DenseSet<BasicBlock *> &InfluenceRegion); 106 107 Function &F; 108 TargetTransformInfo &TTI; 109 DominatorTree &DT; 110 PostDominatorTree &PDT; 111 std::vector<Value *> Worklist; // Stack for DFS. 112 DenseSet<const Value *> &DV; // Stores all divergent values. 113 }; 114 115 void DivergencePropagator::populateWithSourcesOfDivergence() { 116 Worklist.clear(); 117 DV.clear(); 118 for (auto &I : instructions(F)) { 119 if (TTI.isSourceOfDivergence(&I)) { 120 Worklist.push_back(&I); 121 DV.insert(&I); 122 } 123 } 124 for (auto &Arg : F.args()) { 125 if (TTI.isSourceOfDivergence(&Arg)) { 126 Worklist.push_back(&Arg); 127 DV.insert(&Arg); 128 } 129 } 130 } 131 132 void DivergencePropagator::exploreSyncDependency(TerminatorInst *TI) { 133 // Propagation rule 1: if branch TI is divergent, all PHINodes in TI's 134 // immediate post dominator are divergent. This rule handles if-then-else 135 // patterns. For example, 136 // 137 // if (tid < 5) 138 // a1 = 1; 139 // else 140 // a2 = 2; 141 // a = phi(a1, a2); // sync dependent on (tid < 5) 142 BasicBlock *ThisBB = TI->getParent(); 143 BasicBlock *IPostDom = PDT.getNode(ThisBB)->getIDom()->getBlock(); 144 if (IPostDom == nullptr) 145 return; 146 147 for (auto I = IPostDom->begin(); isa<PHINode>(I); ++I) { 148 // A PHINode is uniform if it returns the same value no matter which path is 149 // taken. 150 if (!cast<PHINode>(I)->hasConstantValue() && DV.insert(I).second) 151 Worklist.push_back(I); 152 } 153 154 // Propagation rule 2: if a value defined in a loop is used outside, the user 155 // is sync dependent on the condition of the loop exits that dominate the 156 // user. For example, 157 // 158 // int i = 0; 159 // do { 160 // i++; 161 // if (foo(i)) ... // uniform 162 // } while (i < tid); 163 // if (bar(i)) ... // divergent 164 // 165 // A program may contain unstructured loops. Therefore, we cannot leverage 166 // LoopInfo, which only recognizes natural loops. 167 // 168 // The algorithm used here handles both natural and unstructured loops. Given 169 // a branch TI, we first compute its influence region, the union of all simple 170 // paths from TI to its immediate post dominator (IPostDom). Then, we search 171 // for all the values defined in the influence region but used outside. All 172 // these users are sync dependent on TI. 173 DenseSet<BasicBlock *> InfluenceRegion; 174 computeInfluenceRegion(ThisBB, IPostDom, InfluenceRegion); 175 // An insight that can speed up the search process is that all the in-region 176 // values that are used outside must dominate TI. Therefore, instead of 177 // searching every basic blocks in the influence region, we search all the 178 // dominators of TI until it is outside the influence region. 179 BasicBlock *InfluencedBB = ThisBB; 180 while (InfluenceRegion.count(InfluencedBB)) { 181 for (auto &I : *InfluencedBB) 182 findUsersOutsideInfluenceRegion(I, InfluenceRegion); 183 DomTreeNode *IDomNode = DT.getNode(InfluencedBB)->getIDom(); 184 if (IDomNode == nullptr) 185 break; 186 InfluencedBB = IDomNode->getBlock(); 187 } 188 } 189 190 void DivergencePropagator::findUsersOutsideInfluenceRegion( 191 Instruction &I, const DenseSet<BasicBlock *> &InfluenceRegion) { 192 for (User *U : I.users()) { 193 Instruction *UserInst = cast<Instruction>(U); 194 if (!InfluenceRegion.count(UserInst->getParent())) { 195 if (DV.insert(UserInst).second) 196 Worklist.push_back(UserInst); 197 } 198 } 199 } 200 201 void DivergencePropagator::computeInfluenceRegion( 202 BasicBlock *Start, BasicBlock *End, 203 DenseSet<BasicBlock *> &InfluenceRegion) { 204 assert(PDT.properlyDominates(End, Start) && 205 "End does not properly dominate Start"); 206 std::vector<BasicBlock *> InfluenceStack; 207 InfluenceStack.push_back(Start); 208 InfluenceRegion.insert(Start); 209 while (!InfluenceStack.empty()) { 210 BasicBlock *BB = InfluenceStack.back(); 211 InfluenceStack.pop_back(); 212 for (BasicBlock *Succ : successors(BB)) { 213 if (End != Succ && InfluenceRegion.insert(Succ).second) 214 InfluenceStack.push_back(Succ); 215 } 216 } 217 } 218 219 void DivergencePropagator::exploreDataDependency(Value *V) { 220 // Follow def-use chains of V. 221 for (User *U : V->users()) { 222 Instruction *UserInst = cast<Instruction>(U); 223 if (DV.insert(UserInst).second) 224 Worklist.push_back(UserInst); 225 } 226 } 227 228 void DivergencePropagator::propagate() { 229 // Traverse the dependency graph using DFS. 230 while (!Worklist.empty()) { 231 Value *V = Worklist.back(); 232 Worklist.pop_back(); 233 if (TerminatorInst *TI = dyn_cast<TerminatorInst>(V)) { 234 // Terminators with less than two successors won't introduce sync 235 // dependency. Ignore them. 236 if (TI->getNumSuccessors() > 1) 237 exploreSyncDependency(TI); 238 } 239 exploreDataDependency(V); 240 } 241 } 242 243 } /// end namespace anonymous 244 245 // Register this pass. 246 char DivergenceAnalysis::ID = 0; 247 INITIALIZE_PASS_BEGIN(DivergenceAnalysis, "divergence", "Divergence Analysis", 248 false, true) 249 INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass) 250 INITIALIZE_PASS_DEPENDENCY(PostDominatorTree) 251 INITIALIZE_PASS_END(DivergenceAnalysis, "divergence", "Divergence Analysis", 252 false, true) 253 254 FunctionPass *llvm::createDivergenceAnalysisPass() { 255 return new DivergenceAnalysis(); 256 } 257 258 void DivergenceAnalysis::getAnalysisUsage(AnalysisUsage &AU) const { 259 AU.addRequired<DominatorTreeWrapperPass>(); 260 AU.addRequired<PostDominatorTree>(); 261 AU.setPreservesAll(); 262 } 263 264 bool DivergenceAnalysis::runOnFunction(Function &F) { 265 auto *TTIWP = getAnalysisIfAvailable<TargetTransformInfoWrapperPass>(); 266 if (TTIWP == nullptr) 267 return false; 268 269 TargetTransformInfo &TTI = TTIWP->getTTI(F); 270 // Fast path: if the target does not have branch divergence, we do not mark 271 // any branch as divergent. 272 if (!TTI.hasBranchDivergence()) 273 return false; 274 275 DivergentValues.clear(); 276 DivergencePropagator DP(F, TTI, 277 getAnalysis<DominatorTreeWrapperPass>().getDomTree(), 278 getAnalysis<PostDominatorTree>(), DivergentValues); 279 DP.populateWithSourcesOfDivergence(); 280 DP.propagate(); 281 return false; 282 } 283 284 void DivergenceAnalysis::print(raw_ostream &OS, const Module *) const { 285 if (DivergentValues.empty()) 286 return; 287 const Value *FirstDivergentValue = *DivergentValues.begin(); 288 const Function *F; 289 if (const Argument *Arg = dyn_cast<Argument>(FirstDivergentValue)) { 290 F = Arg->getParent(); 291 } else if (const Instruction *I = 292 dyn_cast<Instruction>(FirstDivergentValue)) { 293 F = I->getParent()->getParent(); 294 } else { 295 llvm_unreachable("Only arguments and instructions can be divergent"); 296 } 297 298 // Dumps all divergent values in F, arguments and then instructions. 299 for (auto &Arg : F->args()) { 300 if (DivergentValues.count(&Arg)) 301 OS << "DIVERGENT: " << Arg << "\n"; 302 } 303 // Iterate instructions using instructions() to ensure a deterministic order. 304 for (auto &I : instructions(F)) { 305 if (DivergentValues.count(&I)) 306 OS << "DIVERGENT:" << I << "\n"; 307 } 308 } 309