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/Value.h"
75 #include "llvm/Support/Debug.h"
76 #include "llvm/Support/raw_ostream.h"
77 #include <vector>
78 using namespace llvm;
79
80 #define DEBUG_TYPE "divergence"
81
82 namespace {
83
84 class DivergencePropagator {
85 public:
DivergencePropagator(Function & F,TargetTransformInfo & TTI,DominatorTree & DT,PostDominatorTree & PDT,DenseSet<const Value * > & DV)86 DivergencePropagator(Function &F, TargetTransformInfo &TTI, DominatorTree &DT,
87 PostDominatorTree &PDT, DenseSet<const Value *> &DV)
88 : F(F), TTI(TTI), DT(DT), PDT(PDT), DV(DV) {}
89 void populateWithSourcesOfDivergence();
90 void propagate();
91
92 private:
93 // A helper function that explores data dependents of V.
94 void exploreDataDependency(Value *V);
95 // A helper function that explores sync dependents of TI.
96 void exploreSyncDependency(TerminatorInst *TI);
97 // Computes the influence region from Start to End. This region includes all
98 // basic blocks on any simple path from Start to End.
99 void computeInfluenceRegion(BasicBlock *Start, BasicBlock *End,
100 DenseSet<BasicBlock *> &InfluenceRegion);
101 // Finds all users of I that are outside the influence region, and add these
102 // users to Worklist.
103 void findUsersOutsideInfluenceRegion(
104 Instruction &I, const DenseSet<BasicBlock *> &InfluenceRegion);
105
106 Function &F;
107 TargetTransformInfo &TTI;
108 DominatorTree &DT;
109 PostDominatorTree &PDT;
110 std::vector<Value *> Worklist; // Stack for DFS.
111 DenseSet<const Value *> &DV; // Stores all divergent values.
112 };
113
populateWithSourcesOfDivergence()114 void DivergencePropagator::populateWithSourcesOfDivergence() {
115 Worklist.clear();
116 DV.clear();
117 for (auto &I : instructions(F)) {
118 if (TTI.isSourceOfDivergence(&I)) {
119 Worklist.push_back(&I);
120 DV.insert(&I);
121 }
122 }
123 for (auto &Arg : F.args()) {
124 if (TTI.isSourceOfDivergence(&Arg)) {
125 Worklist.push_back(&Arg);
126 DV.insert(&Arg);
127 }
128 }
129 }
130
exploreSyncDependency(TerminatorInst * TI)131 void DivergencePropagator::exploreSyncDependency(TerminatorInst *TI) {
132 // Propagation rule 1: if branch TI is divergent, all PHINodes in TI's
133 // immediate post dominator are divergent. This rule handles if-then-else
134 // patterns. For example,
135 //
136 // if (tid < 5)
137 // a1 = 1;
138 // else
139 // a2 = 2;
140 // a = phi(a1, a2); // sync dependent on (tid < 5)
141 BasicBlock *ThisBB = TI->getParent();
142
143 // Unreachable blocks may not be in the dominator tree.
144 if (!DT.isReachableFromEntry(ThisBB))
145 return;
146
147 // If the function has no exit blocks or doesn't reach any exit blocks, the
148 // post dominator may be null.
149 DomTreeNode *ThisNode = PDT.getNode(ThisBB);
150 if (!ThisNode)
151 return;
152
153 BasicBlock *IPostDom = ThisNode->getIDom()->getBlock();
154 if (IPostDom == nullptr)
155 return;
156
157 for (auto I = IPostDom->begin(); isa<PHINode>(I); ++I) {
158 // A PHINode is uniform if it returns the same value no matter which path is
159 // taken.
160 if (!cast<PHINode>(I)->hasConstantOrUndefValue() && DV.insert(&*I).second)
161 Worklist.push_back(&*I);
162 }
163
164 // Propagation rule 2: if a value defined in a loop is used outside, the user
165 // is sync dependent on the condition of the loop exits that dominate the
166 // user. For example,
167 //
168 // int i = 0;
169 // do {
170 // i++;
171 // if (foo(i)) ... // uniform
172 // } while (i < tid);
173 // if (bar(i)) ... // divergent
174 //
175 // A program may contain unstructured loops. Therefore, we cannot leverage
176 // LoopInfo, which only recognizes natural loops.
177 //
178 // The algorithm used here handles both natural and unstructured loops. Given
179 // a branch TI, we first compute its influence region, the union of all simple
180 // paths from TI to its immediate post dominator (IPostDom). Then, we search
181 // for all the values defined in the influence region but used outside. All
182 // these users are sync dependent on TI.
183 DenseSet<BasicBlock *> InfluenceRegion;
184 computeInfluenceRegion(ThisBB, IPostDom, InfluenceRegion);
185 // An insight that can speed up the search process is that all the in-region
186 // values that are used outside must dominate TI. Therefore, instead of
187 // searching every basic blocks in the influence region, we search all the
188 // dominators of TI until it is outside the influence region.
189 BasicBlock *InfluencedBB = ThisBB;
190 while (InfluenceRegion.count(InfluencedBB)) {
191 for (auto &I : *InfluencedBB)
192 findUsersOutsideInfluenceRegion(I, InfluenceRegion);
193 DomTreeNode *IDomNode = DT.getNode(InfluencedBB)->getIDom();
194 if (IDomNode == nullptr)
195 break;
196 InfluencedBB = IDomNode->getBlock();
197 }
198 }
199
findUsersOutsideInfluenceRegion(Instruction & I,const DenseSet<BasicBlock * > & InfluenceRegion)200 void DivergencePropagator::findUsersOutsideInfluenceRegion(
201 Instruction &I, const DenseSet<BasicBlock *> &InfluenceRegion) {
202 for (User *U : I.users()) {
203 Instruction *UserInst = cast<Instruction>(U);
204 if (!InfluenceRegion.count(UserInst->getParent())) {
205 if (DV.insert(UserInst).second)
206 Worklist.push_back(UserInst);
207 }
208 }
209 }
210
211 // A helper function for computeInfluenceRegion that adds successors of "ThisBB"
212 // to the influence region.
213 static void
addSuccessorsToInfluenceRegion(BasicBlock * ThisBB,BasicBlock * End,DenseSet<BasicBlock * > & InfluenceRegion,std::vector<BasicBlock * > & InfluenceStack)214 addSuccessorsToInfluenceRegion(BasicBlock *ThisBB, BasicBlock *End,
215 DenseSet<BasicBlock *> &InfluenceRegion,
216 std::vector<BasicBlock *> &InfluenceStack) {
217 for (BasicBlock *Succ : successors(ThisBB)) {
218 if (Succ != End && InfluenceRegion.insert(Succ).second)
219 InfluenceStack.push_back(Succ);
220 }
221 }
222
computeInfluenceRegion(BasicBlock * Start,BasicBlock * End,DenseSet<BasicBlock * > & InfluenceRegion)223 void DivergencePropagator::computeInfluenceRegion(
224 BasicBlock *Start, BasicBlock *End,
225 DenseSet<BasicBlock *> &InfluenceRegion) {
226 assert(PDT.properlyDominates(End, Start) &&
227 "End does not properly dominate Start");
228
229 // The influence region starts from the end of "Start" to the beginning of
230 // "End". Therefore, "Start" should not be in the region unless "Start" is in
231 // a loop that doesn't contain "End".
232 std::vector<BasicBlock *> InfluenceStack;
233 addSuccessorsToInfluenceRegion(Start, End, InfluenceRegion, InfluenceStack);
234 while (!InfluenceStack.empty()) {
235 BasicBlock *BB = InfluenceStack.back();
236 InfluenceStack.pop_back();
237 addSuccessorsToInfluenceRegion(BB, End, InfluenceRegion, InfluenceStack);
238 }
239 }
240
exploreDataDependency(Value * V)241 void DivergencePropagator::exploreDataDependency(Value *V) {
242 // Follow def-use chains of V.
243 for (User *U : V->users()) {
244 Instruction *UserInst = cast<Instruction>(U);
245 if (!TTI.isAlwaysUniform(U) && DV.insert(UserInst).second)
246 Worklist.push_back(UserInst);
247 }
248 }
249
propagate()250 void DivergencePropagator::propagate() {
251 // Traverse the dependency graph using DFS.
252 while (!Worklist.empty()) {
253 Value *V = Worklist.back();
254 Worklist.pop_back();
255 if (TerminatorInst *TI = dyn_cast<TerminatorInst>(V)) {
256 // Terminators with less than two successors won't introduce sync
257 // dependency. Ignore them.
258 if (TI->getNumSuccessors() > 1)
259 exploreSyncDependency(TI);
260 }
261 exploreDataDependency(V);
262 }
263 }
264
265 } /// end namespace anonymous
266
267 // Register this pass.
268 char DivergenceAnalysis::ID = 0;
269 INITIALIZE_PASS_BEGIN(DivergenceAnalysis, "divergence", "Divergence Analysis",
270 false, true)
INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass)271 INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass)
272 INITIALIZE_PASS_DEPENDENCY(PostDominatorTreeWrapperPass)
273 INITIALIZE_PASS_END(DivergenceAnalysis, "divergence", "Divergence Analysis",
274 false, true)
275
276 FunctionPass *llvm::createDivergenceAnalysisPass() {
277 return new DivergenceAnalysis();
278 }
279
getAnalysisUsage(AnalysisUsage & AU) const280 void DivergenceAnalysis::getAnalysisUsage(AnalysisUsage &AU) const {
281 AU.addRequired<DominatorTreeWrapperPass>();
282 AU.addRequired<PostDominatorTreeWrapperPass>();
283 AU.setPreservesAll();
284 }
285
runOnFunction(Function & F)286 bool DivergenceAnalysis::runOnFunction(Function &F) {
287 auto *TTIWP = getAnalysisIfAvailable<TargetTransformInfoWrapperPass>();
288 if (TTIWP == nullptr)
289 return false;
290
291 TargetTransformInfo &TTI = TTIWP->getTTI(F);
292 // Fast path: if the target does not have branch divergence, we do not mark
293 // any branch as divergent.
294 if (!TTI.hasBranchDivergence())
295 return false;
296
297 DivergentValues.clear();
298 auto &PDT = getAnalysis<PostDominatorTreeWrapperPass>().getPostDomTree();
299 DivergencePropagator DP(F, TTI,
300 getAnalysis<DominatorTreeWrapperPass>().getDomTree(),
301 PDT, DivergentValues);
302 DP.populateWithSourcesOfDivergence();
303 DP.propagate();
304 LLVM_DEBUG(
305 dbgs() << "\nAfter divergence analysis on " << F.getName() << ":\n";
306 print(dbgs(), F.getParent())
307 );
308 return false;
309 }
310
print(raw_ostream & OS,const Module *) const311 void DivergenceAnalysis::print(raw_ostream &OS, const Module *) const {
312 if (DivergentValues.empty())
313 return;
314 const Value *FirstDivergentValue = *DivergentValues.begin();
315 const Function *F;
316 if (const Argument *Arg = dyn_cast<Argument>(FirstDivergentValue)) {
317 F = Arg->getParent();
318 } else if (const Instruction *I =
319 dyn_cast<Instruction>(FirstDivergentValue)) {
320 F = I->getParent()->getParent();
321 } else {
322 llvm_unreachable("Only arguments and instructions can be divergent");
323 }
324
325 // Dumps all divergent values in F, arguments and then instructions.
326 for (auto &Arg : F->args()) {
327 OS << (DivergentValues.count(&Arg) ? "DIVERGENT: " : " ");
328 OS << Arg << "\n";
329 }
330 // Iterate instructions using instructions() to ensure a deterministic order.
331 for (auto BI = F->begin(), BE = F->end(); BI != BE; ++BI) {
332 auto &BB = *BI;
333 OS << "\n " << BB.getName() << ":\n";
334 for (auto &I : BB.instructionsWithoutDebug()) {
335 OS << (DivergentValues.count(&I) ? "DIVERGENT: " : " ");
336 OS << I << "\n";
337 }
338 }
339 OS << "\n";
340 }
341