1 //===- LegacyDivergenceAnalysis.cpp --------- Legacy Divergence Analysis 2 //Implementation -==// 3 // 4 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. 5 // See https://llvm.org/LICENSE.txt for license information. 6 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception 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/ADT/PostOrderIterator.h" 68 #include "llvm/Analysis/CFG.h" 69 #include "llvm/Analysis/DivergenceAnalysis.h" 70 #include "llvm/Analysis/LegacyDivergenceAnalysis.h" 71 #include "llvm/Analysis/Passes.h" 72 #include "llvm/Analysis/PostDominators.h" 73 #include "llvm/Analysis/TargetTransformInfo.h" 74 #include "llvm/IR/Dominators.h" 75 #include "llvm/IR/InstIterator.h" 76 #include "llvm/IR/Instructions.h" 77 #include "llvm/IR/Value.h" 78 #include "llvm/Support/Debug.h" 79 #include "llvm/Support/raw_ostream.h" 80 #include <vector> 81 using namespace llvm; 82 83 #define DEBUG_TYPE "divergence" 84 85 // transparently use the GPUDivergenceAnalysis 86 static cl::opt<bool> UseGPUDA("use-gpu-divergence-analysis", cl::init(false), 87 cl::Hidden, 88 cl::desc("turn the LegacyDivergenceAnalysis into " 89 "a wrapper for GPUDivergenceAnalysis")); 90 91 namespace { 92 93 class DivergencePropagator { 94 public: 95 DivergencePropagator(Function &F, TargetTransformInfo &TTI, DominatorTree &DT, 96 PostDominatorTree &PDT, DenseSet<const Value *> &DV, 97 DenseSet<const Use *> &DU) 98 : F(F), TTI(TTI), DT(DT), PDT(PDT), DV(DV), DU(DU) {} 99 void populateWithSourcesOfDivergence(); 100 void propagate(); 101 102 private: 103 // A helper function that explores data dependents of V. 104 void exploreDataDependency(Value *V); 105 // A helper function that explores sync dependents of TI. 106 void exploreSyncDependency(Instruction *TI); 107 // Computes the influence region from Start to End. This region includes all 108 // basic blocks on any simple path from Start to End. 109 void computeInfluenceRegion(BasicBlock *Start, BasicBlock *End, 110 DenseSet<BasicBlock *> &InfluenceRegion); 111 // Finds all users of I that are outside the influence region, and add these 112 // users to Worklist. 113 void findUsersOutsideInfluenceRegion( 114 Instruction &I, const DenseSet<BasicBlock *> &InfluenceRegion); 115 116 Function &F; 117 TargetTransformInfo &TTI; 118 DominatorTree &DT; 119 PostDominatorTree &PDT; 120 std::vector<Value *> Worklist; // Stack for DFS. 121 DenseSet<const Value *> &DV; // Stores all divergent values. 122 DenseSet<const Use *> &DU; // Stores divergent uses of possibly uniform 123 // values. 124 }; 125 126 void DivergencePropagator::populateWithSourcesOfDivergence() { 127 Worklist.clear(); 128 DV.clear(); 129 DU.clear(); 130 for (auto &I : instructions(F)) { 131 if (TTI.isSourceOfDivergence(&I)) { 132 Worklist.push_back(&I); 133 DV.insert(&I); 134 } 135 } 136 for (auto &Arg : F.args()) { 137 if (TTI.isSourceOfDivergence(&Arg)) { 138 Worklist.push_back(&Arg); 139 DV.insert(&Arg); 140 } 141 } 142 } 143 144 void DivergencePropagator::exploreSyncDependency(Instruction *TI) { 145 // Propagation rule 1: if branch TI is divergent, all PHINodes in TI's 146 // immediate post dominator are divergent. This rule handles if-then-else 147 // patterns. For example, 148 // 149 // if (tid < 5) 150 // a1 = 1; 151 // else 152 // a2 = 2; 153 // a = phi(a1, a2); // sync dependent on (tid < 5) 154 BasicBlock *ThisBB = TI->getParent(); 155 156 // Unreachable blocks may not be in the dominator tree. 157 if (!DT.isReachableFromEntry(ThisBB)) 158 return; 159 160 // If the function has no exit blocks or doesn't reach any exit blocks, the 161 // post dominator may be null. 162 DomTreeNode *ThisNode = PDT.getNode(ThisBB); 163 if (!ThisNode) 164 return; 165 166 BasicBlock *IPostDom = ThisNode->getIDom()->getBlock(); 167 if (IPostDom == nullptr) 168 return; 169 170 for (auto I = IPostDom->begin(); isa<PHINode>(I); ++I) { 171 // A PHINode is uniform if it returns the same value no matter which path is 172 // taken. 173 if (!cast<PHINode>(I)->hasConstantOrUndefValue() && DV.insert(&*I).second) 174 Worklist.push_back(&*I); 175 } 176 177 // Propagation rule 2: if a value defined in a loop is used outside, the user 178 // is sync dependent on the condition of the loop exits that dominate the 179 // user. For example, 180 // 181 // int i = 0; 182 // do { 183 // i++; 184 // if (foo(i)) ... // uniform 185 // } while (i < tid); 186 // if (bar(i)) ... // divergent 187 // 188 // A program may contain unstructured loops. Therefore, we cannot leverage 189 // LoopInfo, which only recognizes natural loops. 190 // 191 // The algorithm used here handles both natural and unstructured loops. Given 192 // a branch TI, we first compute its influence region, the union of all simple 193 // paths from TI to its immediate post dominator (IPostDom). Then, we search 194 // for all the values defined in the influence region but used outside. All 195 // these users are sync dependent on TI. 196 DenseSet<BasicBlock *> InfluenceRegion; 197 computeInfluenceRegion(ThisBB, IPostDom, InfluenceRegion); 198 // An insight that can speed up the search process is that all the in-region 199 // values that are used outside must dominate TI. Therefore, instead of 200 // searching every basic blocks in the influence region, we search all the 201 // dominators of TI until it is outside the influence region. 202 BasicBlock *InfluencedBB = ThisBB; 203 while (InfluenceRegion.count(InfluencedBB)) { 204 for (auto &I : *InfluencedBB) { 205 if (!DV.count(&I)) 206 findUsersOutsideInfluenceRegion(I, InfluenceRegion); 207 } 208 DomTreeNode *IDomNode = DT.getNode(InfluencedBB)->getIDom(); 209 if (IDomNode == nullptr) 210 break; 211 InfluencedBB = IDomNode->getBlock(); 212 } 213 } 214 215 void DivergencePropagator::findUsersOutsideInfluenceRegion( 216 Instruction &I, const DenseSet<BasicBlock *> &InfluenceRegion) { 217 for (Use &Use : I.uses()) { 218 Instruction *UserInst = cast<Instruction>(Use.getUser()); 219 if (!InfluenceRegion.count(UserInst->getParent())) { 220 DU.insert(&Use); 221 if (DV.insert(UserInst).second) 222 Worklist.push_back(UserInst); 223 } 224 } 225 } 226 227 // A helper function for computeInfluenceRegion that adds successors of "ThisBB" 228 // to the influence region. 229 static void 230 addSuccessorsToInfluenceRegion(BasicBlock *ThisBB, BasicBlock *End, 231 DenseSet<BasicBlock *> &InfluenceRegion, 232 std::vector<BasicBlock *> &InfluenceStack) { 233 for (BasicBlock *Succ : successors(ThisBB)) { 234 if (Succ != End && InfluenceRegion.insert(Succ).second) 235 InfluenceStack.push_back(Succ); 236 } 237 } 238 239 void DivergencePropagator::computeInfluenceRegion( 240 BasicBlock *Start, BasicBlock *End, 241 DenseSet<BasicBlock *> &InfluenceRegion) { 242 assert(PDT.properlyDominates(End, Start) && 243 "End does not properly dominate Start"); 244 245 // The influence region starts from the end of "Start" to the beginning of 246 // "End". Therefore, "Start" should not be in the region unless "Start" is in 247 // a loop that doesn't contain "End". 248 std::vector<BasicBlock *> InfluenceStack; 249 addSuccessorsToInfluenceRegion(Start, End, InfluenceRegion, InfluenceStack); 250 while (!InfluenceStack.empty()) { 251 BasicBlock *BB = InfluenceStack.back(); 252 InfluenceStack.pop_back(); 253 addSuccessorsToInfluenceRegion(BB, End, InfluenceRegion, InfluenceStack); 254 } 255 } 256 257 void DivergencePropagator::exploreDataDependency(Value *V) { 258 // Follow def-use chains of V. 259 for (User *U : V->users()) { 260 Instruction *UserInst = cast<Instruction>(U); 261 if (!TTI.isAlwaysUniform(U) && DV.insert(UserInst).second) 262 Worklist.push_back(UserInst); 263 } 264 } 265 266 void DivergencePropagator::propagate() { 267 // Traverse the dependency graph using DFS. 268 while (!Worklist.empty()) { 269 Value *V = Worklist.back(); 270 Worklist.pop_back(); 271 if (Instruction *I = dyn_cast<Instruction>(V)) { 272 // Terminators with less than two successors won't introduce sync 273 // dependency. Ignore them. 274 if (I->isTerminator() && I->getNumSuccessors() > 1) 275 exploreSyncDependency(I); 276 } 277 exploreDataDependency(V); 278 } 279 } 280 281 } // namespace 282 283 // Register this pass. 284 char LegacyDivergenceAnalysis::ID = 0; 285 INITIALIZE_PASS_BEGIN(LegacyDivergenceAnalysis, "divergence", 286 "Legacy Divergence Analysis", false, true) 287 INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass) 288 INITIALIZE_PASS_DEPENDENCY(PostDominatorTreeWrapperPass) 289 INITIALIZE_PASS_DEPENDENCY(LoopInfoWrapperPass) 290 INITIALIZE_PASS_END(LegacyDivergenceAnalysis, "divergence", 291 "Legacy Divergence Analysis", false, true) 292 293 FunctionPass *llvm::createLegacyDivergenceAnalysisPass() { 294 return new LegacyDivergenceAnalysis(); 295 } 296 297 void LegacyDivergenceAnalysis::getAnalysisUsage(AnalysisUsage &AU) const { 298 AU.addRequired<DominatorTreeWrapperPass>(); 299 AU.addRequired<PostDominatorTreeWrapperPass>(); 300 if (UseGPUDA) 301 AU.addRequired<LoopInfoWrapperPass>(); 302 AU.setPreservesAll(); 303 } 304 305 bool LegacyDivergenceAnalysis::shouldUseGPUDivergenceAnalysis( 306 const Function &F) const { 307 if (!UseGPUDA) 308 return false; 309 310 // GPUDivergenceAnalysis requires a reducible CFG. 311 auto &LI = getAnalysis<LoopInfoWrapperPass>().getLoopInfo(); 312 using RPOTraversal = ReversePostOrderTraversal<const Function *>; 313 RPOTraversal FuncRPOT(&F); 314 return !containsIrreducibleCFG<const BasicBlock *, const RPOTraversal, 315 const LoopInfo>(FuncRPOT, LI); 316 } 317 318 bool LegacyDivergenceAnalysis::runOnFunction(Function &F) { 319 auto *TTIWP = getAnalysisIfAvailable<TargetTransformInfoWrapperPass>(); 320 if (TTIWP == nullptr) 321 return false; 322 323 TargetTransformInfo &TTI = TTIWP->getTTI(F); 324 // Fast path: if the target does not have branch divergence, we do not mark 325 // any branch as divergent. 326 if (!TTI.hasBranchDivergence()) 327 return false; 328 329 DivergentValues.clear(); 330 DivergentUses.clear(); 331 gpuDA = nullptr; 332 333 auto &DT = getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 334 auto &PDT = getAnalysis<PostDominatorTreeWrapperPass>().getPostDomTree(); 335 336 if (shouldUseGPUDivergenceAnalysis(F)) { 337 // run the new GPU divergence analysis 338 auto &LI = getAnalysis<LoopInfoWrapperPass>().getLoopInfo(); 339 gpuDA = std::make_unique<GPUDivergenceAnalysis>(F, DT, PDT, LI, TTI); 340 341 } else { 342 // run LLVM's existing DivergenceAnalysis 343 DivergencePropagator DP(F, TTI, DT, PDT, DivergentValues, DivergentUses); 344 DP.populateWithSourcesOfDivergence(); 345 DP.propagate(); 346 } 347 348 LLVM_DEBUG(dbgs() << "\nAfter divergence analysis on " << F.getName() 349 << ":\n"; 350 print(dbgs(), F.getParent())); 351 352 return false; 353 } 354 355 bool LegacyDivergenceAnalysis::isDivergent(const Value *V) const { 356 if (gpuDA) { 357 return gpuDA->isDivergent(*V); 358 } 359 return DivergentValues.count(V); 360 } 361 362 bool LegacyDivergenceAnalysis::isDivergentUse(const Use *U) const { 363 if (gpuDA) { 364 return gpuDA->isDivergentUse(*U); 365 } 366 return DivergentValues.count(U->get()) || DivergentUses.count(U); 367 } 368 369 void LegacyDivergenceAnalysis::print(raw_ostream &OS, const Module *) const { 370 if ((!gpuDA || !gpuDA->hasDivergence()) && DivergentValues.empty()) 371 return; 372 373 const Function *F = nullptr; 374 if (!DivergentValues.empty()) { 375 const Value *FirstDivergentValue = *DivergentValues.begin(); 376 if (const Argument *Arg = dyn_cast<Argument>(FirstDivergentValue)) { 377 F = Arg->getParent(); 378 } else if (const Instruction *I = 379 dyn_cast<Instruction>(FirstDivergentValue)) { 380 F = I->getParent()->getParent(); 381 } else { 382 llvm_unreachable("Only arguments and instructions can be divergent"); 383 } 384 } else if (gpuDA) { 385 F = &gpuDA->getFunction(); 386 } 387 if (!F) 388 return; 389 390 // Dumps all divergent values in F, arguments and then instructions. 391 for (auto &Arg : F->args()) { 392 OS << (isDivergent(&Arg) ? "DIVERGENT: " : " "); 393 OS << Arg << "\n"; 394 } 395 // Iterate instructions using instructions() to ensure a deterministic order. 396 for (auto BI = F->begin(), BE = F->end(); BI != BE; ++BI) { 397 auto &BB = *BI; 398 OS << "\n " << BB.getName() << ":\n"; 399 for (auto &I : BB.instructionsWithoutDebug()) { 400 OS << (isDivergent(&I) ? "DIVERGENT: " : " "); 401 OS << I << "\n"; 402 } 403 } 404 OS << "\n"; 405 } 406