//===-- DependenceAnalysis.cpp - DA Implementation --------------*- C++ -*-===// // // The LLVM Compiler Infrastructure // // This file is distributed under the University of Illinois Open Source // License. See LICENSE.TXT for details. // //===----------------------------------------------------------------------===// // // DependenceAnalysis is an LLVM pass that analyses dependences between memory // accesses. Currently, it is an (incomplete) implementation of the approach // described in // // Practical Dependence Testing // Goff, Kennedy, Tseng // PLDI 1991 // // There's a single entry point that analyzes the dependence between a pair // of memory references in a function, returning either NULL, for no dependence, // or a more-or-less detailed description of the dependence between them. // // Currently, the implementation cannot propagate constraints between // coupled RDIV subscripts and lacks a multi-subscript MIV test. // Both of these are conservative weaknesses; // that is, not a source of correctness problems. // // The implementation depends on the GEP instruction to differentiate // subscripts. Since Clang linearizes some array subscripts, the dependence // analysis is using SCEV->delinearize to recover the representation of multiple // subscripts, and thus avoid the more expensive and less precise MIV tests. The // delinearization is controlled by the flag -da-delinearize. // // We should pay some careful attention to the possibility of integer overflow // in the implementation of the various tests. This could happen with Add, // Subtract, or Multiply, with both APInt's and SCEV's. // // Some non-linear subscript pairs can be handled by the GCD test // (and perhaps other tests). // Should explore how often these things occur. // // Finally, it seems like certain test cases expose weaknesses in the SCEV // simplification, especially in the handling of sign and zero extensions. // It could be useful to spend time exploring these. // // Please note that this is work in progress and the interface is subject to // change. // //===----------------------------------------------------------------------===// // // // In memory of Ken Kennedy, 1945 - 2007 // // // //===----------------------------------------------------------------------===// #include "llvm/Analysis/DependenceAnalysis.h" #include "llvm/ADT/Statistic.h" #include "llvm/Analysis/AliasAnalysis.h" #include "llvm/Analysis/LoopInfo.h" #include "llvm/Analysis/ScalarEvolution.h" #include "llvm/Analysis/ScalarEvolutionExpressions.h" #include "llvm/Analysis/ValueTracking.h" #include "llvm/IR/InstIterator.h" #include "llvm/IR/Operator.h" #include "llvm/Support/CommandLine.h" #include "llvm/Support/Debug.h" #include "llvm/Support/ErrorHandling.h" #include "llvm/Support/raw_ostream.h" using namespace llvm; #define DEBUG_TYPE "da" //===----------------------------------------------------------------------===// // statistics STATISTIC(TotalArrayPairs, "Array pairs tested"); STATISTIC(SeparableSubscriptPairs, "Separable subscript pairs"); STATISTIC(CoupledSubscriptPairs, "Coupled subscript pairs"); STATISTIC(NonlinearSubscriptPairs, "Nonlinear subscript pairs"); STATISTIC(ZIVapplications, "ZIV applications"); STATISTIC(ZIVindependence, "ZIV independence"); STATISTIC(StrongSIVapplications, "Strong SIV applications"); STATISTIC(StrongSIVsuccesses, "Strong SIV successes"); STATISTIC(StrongSIVindependence, "Strong SIV independence"); STATISTIC(WeakCrossingSIVapplications, "Weak-Crossing SIV applications"); STATISTIC(WeakCrossingSIVsuccesses, "Weak-Crossing SIV successes"); STATISTIC(WeakCrossingSIVindependence, "Weak-Crossing SIV independence"); STATISTIC(ExactSIVapplications, "Exact SIV applications"); STATISTIC(ExactSIVsuccesses, "Exact SIV successes"); STATISTIC(ExactSIVindependence, "Exact SIV independence"); STATISTIC(WeakZeroSIVapplications, "Weak-Zero SIV applications"); STATISTIC(WeakZeroSIVsuccesses, "Weak-Zero SIV successes"); STATISTIC(WeakZeroSIVindependence, "Weak-Zero SIV independence"); STATISTIC(ExactRDIVapplications, "Exact RDIV applications"); STATISTIC(ExactRDIVindependence, "Exact RDIV independence"); STATISTIC(SymbolicRDIVapplications, "Symbolic RDIV applications"); STATISTIC(SymbolicRDIVindependence, "Symbolic RDIV independence"); STATISTIC(DeltaApplications, "Delta applications"); STATISTIC(DeltaSuccesses, "Delta successes"); STATISTIC(DeltaIndependence, "Delta independence"); STATISTIC(DeltaPropagations, "Delta propagations"); STATISTIC(GCDapplications, "GCD applications"); STATISTIC(GCDsuccesses, "GCD successes"); STATISTIC(GCDindependence, "GCD independence"); STATISTIC(BanerjeeApplications, "Banerjee applications"); STATISTIC(BanerjeeIndependence, "Banerjee independence"); STATISTIC(BanerjeeSuccesses, "Banerjee successes"); static cl::opt Delinearize("da-delinearize", cl::init(false), cl::Hidden, cl::ZeroOrMore, cl::desc("Try to delinearize array references.")); //===----------------------------------------------------------------------===// // basics INITIALIZE_PASS_BEGIN(DependenceAnalysis, "da", "Dependence Analysis", true, true) INITIALIZE_PASS_DEPENDENCY(LoopInfo) INITIALIZE_PASS_DEPENDENCY(ScalarEvolution) INITIALIZE_AG_DEPENDENCY(AliasAnalysis) INITIALIZE_PASS_END(DependenceAnalysis, "da", "Dependence Analysis", true, true) char DependenceAnalysis::ID = 0; FunctionPass *llvm::createDependenceAnalysisPass() { return new DependenceAnalysis(); } bool DependenceAnalysis::runOnFunction(Function &F) { this->F = &F; AA = &getAnalysis(); SE = &getAnalysis(); LI = &getAnalysis(); return false; } void DependenceAnalysis::releaseMemory() { } void DependenceAnalysis::getAnalysisUsage(AnalysisUsage &AU) const { AU.setPreservesAll(); AU.addRequiredTransitive(); AU.addRequiredTransitive(); AU.addRequiredTransitive(); } // Used to test the dependence analyzer. // Looks through the function, noting loads and stores. // Calls depends() on every possible pair and prints out the result. // Ignores all other instructions. static void dumpExampleDependence(raw_ostream &OS, Function *F, DependenceAnalysis *DA) { for (inst_iterator SrcI = inst_begin(F), SrcE = inst_end(F); SrcI != SrcE; ++SrcI) { if (isa(*SrcI) || isa(*SrcI)) { for (inst_iterator DstI = SrcI, DstE = inst_end(F); DstI != DstE; ++DstI) { if (isa(*DstI) || isa(*DstI)) { OS << "da analyze - "; if (Dependence *D = DA->depends(&*SrcI, &*DstI, true)) { D->dump(OS); for (unsigned Level = 1; Level <= D->getLevels(); Level++) { if (D->isSplitable(Level)) { OS << "da analyze - split level = " << Level; OS << ", iteration = " << *DA->getSplitIteration(D, Level); OS << "!\n"; } } delete D; } else OS << "none!\n"; } } } } } void DependenceAnalysis::print(raw_ostream &OS, const Module*) const { dumpExampleDependence(OS, F, const_cast(this)); } //===----------------------------------------------------------------------===// // Dependence methods // Returns true if this is an input dependence. bool Dependence::isInput() const { return Src->mayReadFromMemory() && Dst->mayReadFromMemory(); } // Returns true if this is an output dependence. bool Dependence::isOutput() const { return Src->mayWriteToMemory() && Dst->mayWriteToMemory(); } // Returns true if this is an flow (aka true) dependence. bool Dependence::isFlow() const { return Src->mayWriteToMemory() && Dst->mayReadFromMemory(); } // Returns true if this is an anti dependence. bool Dependence::isAnti() const { return Src->mayReadFromMemory() && Dst->mayWriteToMemory(); } // Returns true if a particular level is scalar; that is, // if no subscript in the source or destination mention the induction // variable associated with the loop at this level. // Leave this out of line, so it will serve as a virtual method anchor bool Dependence::isScalar(unsigned level) const { return false; } //===----------------------------------------------------------------------===// // FullDependence methods FullDependence::FullDependence(Instruction *Source, Instruction *Destination, bool PossiblyLoopIndependent, unsigned CommonLevels) : Dependence(Source, Destination), Levels(CommonLevels), LoopIndependent(PossiblyLoopIndependent) { Consistent = true; DV = CommonLevels ? new DVEntry[CommonLevels] : nullptr; } // The rest are simple getters that hide the implementation. // getDirection - Returns the direction associated with a particular level. unsigned FullDependence::getDirection(unsigned Level) const { assert(0 < Level && Level <= Levels && "Level out of range"); return DV[Level - 1].Direction; } // Returns the distance (or NULL) associated with a particular level. const SCEV *FullDependence::getDistance(unsigned Level) const { assert(0 < Level && Level <= Levels && "Level out of range"); return DV[Level - 1].Distance; } // Returns true if a particular level is scalar; that is, // if no subscript in the source or destination mention the induction // variable associated with the loop at this level. bool FullDependence::isScalar(unsigned Level) const { assert(0 < Level && Level <= Levels && "Level out of range"); return DV[Level - 1].Scalar; } // Returns true if peeling the first iteration from this loop // will break this dependence. bool FullDependence::isPeelFirst(unsigned Level) const { assert(0 < Level && Level <= Levels && "Level out of range"); return DV[Level - 1].PeelFirst; } // Returns true if peeling the last iteration from this loop // will break this dependence. bool FullDependence::isPeelLast(unsigned Level) const { assert(0 < Level && Level <= Levels && "Level out of range"); return DV[Level - 1].PeelLast; } // Returns true if splitting this loop will break the dependence. bool FullDependence::isSplitable(unsigned Level) const { assert(0 < Level && Level <= Levels && "Level out of range"); return DV[Level - 1].Splitable; } //===----------------------------------------------------------------------===// // DependenceAnalysis::Constraint methods // If constraint is a point , returns X. // Otherwise assert. const SCEV *DependenceAnalysis::Constraint::getX() const { assert(Kind == Point && "Kind should be Point"); return A; } // If constraint is a point , returns Y. // Otherwise assert. const SCEV *DependenceAnalysis::Constraint::getY() const { assert(Kind == Point && "Kind should be Point"); return B; } // If constraint is a line AX + BY = C, returns A. // Otherwise assert. const SCEV *DependenceAnalysis::Constraint::getA() const { assert((Kind == Line || Kind == Distance) && "Kind should be Line (or Distance)"); return A; } // If constraint is a line AX + BY = C, returns B. // Otherwise assert. const SCEV *DependenceAnalysis::Constraint::getB() const { assert((Kind == Line || Kind == Distance) && "Kind should be Line (or Distance)"); return B; } // If constraint is a line AX + BY = C, returns C. // Otherwise assert. const SCEV *DependenceAnalysis::Constraint::getC() const { assert((Kind == Line || Kind == Distance) && "Kind should be Line (or Distance)"); return C; } // If constraint is a distance, returns D. // Otherwise assert. const SCEV *DependenceAnalysis::Constraint::getD() const { assert(Kind == Distance && "Kind should be Distance"); return SE->getNegativeSCEV(C); } // Returns the loop associated with this constraint. const Loop *DependenceAnalysis::Constraint::getAssociatedLoop() const { assert((Kind == Distance || Kind == Line || Kind == Point) && "Kind should be Distance, Line, or Point"); return AssociatedLoop; } void DependenceAnalysis::Constraint::setPoint(const SCEV *X, const SCEV *Y, const Loop *CurLoop) { Kind = Point; A = X; B = Y; AssociatedLoop = CurLoop; } void DependenceAnalysis::Constraint::setLine(const SCEV *AA, const SCEV *BB, const SCEV *CC, const Loop *CurLoop) { Kind = Line; A = AA; B = BB; C = CC; AssociatedLoop = CurLoop; } void DependenceAnalysis::Constraint::setDistance(const SCEV *D, const Loop *CurLoop) { Kind = Distance; A = SE->getConstant(D->getType(), 1); B = SE->getNegativeSCEV(A); C = SE->getNegativeSCEV(D); AssociatedLoop = CurLoop; } void DependenceAnalysis::Constraint::setEmpty() { Kind = Empty; } void DependenceAnalysis::Constraint::setAny(ScalarEvolution *NewSE) { SE = NewSE; Kind = Any; } // For debugging purposes. Dumps the constraint out to OS. void DependenceAnalysis::Constraint::dump(raw_ostream &OS) const { if (isEmpty()) OS << " Empty\n"; else if (isAny()) OS << " Any\n"; else if (isPoint()) OS << " Point is <" << *getX() << ", " << *getY() << ">\n"; else if (isDistance()) OS << " Distance is " << *getD() << " (" << *getA() << "*X + " << *getB() << "*Y = " << *getC() << ")\n"; else if (isLine()) OS << " Line is " << *getA() << "*X + " << *getB() << "*Y = " << *getC() << "\n"; else llvm_unreachable("unknown constraint type in Constraint::dump"); } // Updates X with the intersection // of the Constraints X and Y. Returns true if X has changed. // Corresponds to Figure 4 from the paper // // Practical Dependence Testing // Goff, Kennedy, Tseng // PLDI 1991 bool DependenceAnalysis::intersectConstraints(Constraint *X, const Constraint *Y) { ++DeltaApplications; DEBUG(dbgs() << "\tintersect constraints\n"); DEBUG(dbgs() << "\t X ="; X->dump(dbgs())); DEBUG(dbgs() << "\t Y ="; Y->dump(dbgs())); assert(!Y->isPoint() && "Y must not be a Point"); if (X->isAny()) { if (Y->isAny()) return false; *X = *Y; return true; } if (X->isEmpty()) return false; if (Y->isEmpty()) { X->setEmpty(); return true; } if (X->isDistance() && Y->isDistance()) { DEBUG(dbgs() << "\t intersect 2 distances\n"); if (isKnownPredicate(CmpInst::ICMP_EQ, X->getD(), Y->getD())) return false; if (isKnownPredicate(CmpInst::ICMP_NE, X->getD(), Y->getD())) { X->setEmpty(); ++DeltaSuccesses; return true; } // Hmmm, interesting situation. // I guess if either is constant, keep it and ignore the other. if (isa(Y->getD())) { *X = *Y; return true; } return false; } // At this point, the pseudo-code in Figure 4 of the paper // checks if (X->isPoint() && Y->isPoint()). // This case can't occur in our implementation, // since a Point can only arise as the result of intersecting // two Line constraints, and the right-hand value, Y, is never // the result of an intersection. assert(!(X->isPoint() && Y->isPoint()) && "We shouldn't ever see X->isPoint() && Y->isPoint()"); if (X->isLine() && Y->isLine()) { DEBUG(dbgs() << "\t intersect 2 lines\n"); const SCEV *Prod1 = SE->getMulExpr(X->getA(), Y->getB()); const SCEV *Prod2 = SE->getMulExpr(X->getB(), Y->getA()); if (isKnownPredicate(CmpInst::ICMP_EQ, Prod1, Prod2)) { // slopes are equal, so lines are parallel DEBUG(dbgs() << "\t\tsame slope\n"); Prod1 = SE->getMulExpr(X->getC(), Y->getB()); Prod2 = SE->getMulExpr(X->getB(), Y->getC()); if (isKnownPredicate(CmpInst::ICMP_EQ, Prod1, Prod2)) return false; if (isKnownPredicate(CmpInst::ICMP_NE, Prod1, Prod2)) { X->setEmpty(); ++DeltaSuccesses; return true; } return false; } if (isKnownPredicate(CmpInst::ICMP_NE, Prod1, Prod2)) { // slopes differ, so lines intersect DEBUG(dbgs() << "\t\tdifferent slopes\n"); const SCEV *C1B2 = SE->getMulExpr(X->getC(), Y->getB()); const SCEV *C1A2 = SE->getMulExpr(X->getC(), Y->getA()); const SCEV *C2B1 = SE->getMulExpr(Y->getC(), X->getB()); const SCEV *C2A1 = SE->getMulExpr(Y->getC(), X->getA()); const SCEV *A1B2 = SE->getMulExpr(X->getA(), Y->getB()); const SCEV *A2B1 = SE->getMulExpr(Y->getA(), X->getB()); const SCEVConstant *C1A2_C2A1 = dyn_cast(SE->getMinusSCEV(C1A2, C2A1)); const SCEVConstant *C1B2_C2B1 = dyn_cast(SE->getMinusSCEV(C1B2, C2B1)); const SCEVConstant *A1B2_A2B1 = dyn_cast(SE->getMinusSCEV(A1B2, A2B1)); const SCEVConstant *A2B1_A1B2 = dyn_cast(SE->getMinusSCEV(A2B1, A1B2)); if (!C1B2_C2B1 || !C1A2_C2A1 || !A1B2_A2B1 || !A2B1_A1B2) return false; APInt Xtop = C1B2_C2B1->getValue()->getValue(); APInt Xbot = A1B2_A2B1->getValue()->getValue(); APInt Ytop = C1A2_C2A1->getValue()->getValue(); APInt Ybot = A2B1_A1B2->getValue()->getValue(); DEBUG(dbgs() << "\t\tXtop = " << Xtop << "\n"); DEBUG(dbgs() << "\t\tXbot = " << Xbot << "\n"); DEBUG(dbgs() << "\t\tYtop = " << Ytop << "\n"); DEBUG(dbgs() << "\t\tYbot = " << Ybot << "\n"); APInt Xq = Xtop; // these need to be initialized, even APInt Xr = Xtop; // though they're just going to be overwritten APInt::sdivrem(Xtop, Xbot, Xq, Xr); APInt Yq = Ytop; APInt Yr = Ytop; APInt::sdivrem(Ytop, Ybot, Yq, Yr); if (Xr != 0 || Yr != 0) { X->setEmpty(); ++DeltaSuccesses; return true; } DEBUG(dbgs() << "\t\tX = " << Xq << ", Y = " << Yq << "\n"); if (Xq.slt(0) || Yq.slt(0)) { X->setEmpty(); ++DeltaSuccesses; return true; } if (const SCEVConstant *CUB = collectConstantUpperBound(X->getAssociatedLoop(), Prod1->getType())) { APInt UpperBound = CUB->getValue()->getValue(); DEBUG(dbgs() << "\t\tupper bound = " << UpperBound << "\n"); if (Xq.sgt(UpperBound) || Yq.sgt(UpperBound)) { X->setEmpty(); ++DeltaSuccesses; return true; } } X->setPoint(SE->getConstant(Xq), SE->getConstant(Yq), X->getAssociatedLoop()); ++DeltaSuccesses; return true; } return false; } // if (X->isLine() && Y->isPoint()) This case can't occur. assert(!(X->isLine() && Y->isPoint()) && "This case should never occur"); if (X->isPoint() && Y->isLine()) { DEBUG(dbgs() << "\t intersect Point and Line\n"); const SCEV *A1X1 = SE->getMulExpr(Y->getA(), X->getX()); const SCEV *B1Y1 = SE->getMulExpr(Y->getB(), X->getY()); const SCEV *Sum = SE->getAddExpr(A1X1, B1Y1); if (isKnownPredicate(CmpInst::ICMP_EQ, Sum, Y->getC())) return false; if (isKnownPredicate(CmpInst::ICMP_NE, Sum, Y->getC())) { X->setEmpty(); ++DeltaSuccesses; return true; } return false; } llvm_unreachable("shouldn't reach the end of Constraint intersection"); return false; } //===----------------------------------------------------------------------===// // DependenceAnalysis methods // For debugging purposes. Dumps a dependence to OS. void Dependence::dump(raw_ostream &OS) const { bool Splitable = false; if (isConfused()) OS << "confused"; else { if (isConsistent()) OS << "consistent "; if (isFlow()) OS << "flow"; else if (isOutput()) OS << "output"; else if (isAnti()) OS << "anti"; else if (isInput()) OS << "input"; unsigned Levels = getLevels(); OS << " ["; for (unsigned II = 1; II <= Levels; ++II) { if (isSplitable(II)) Splitable = true; if (isPeelFirst(II)) OS << 'p'; const SCEV *Distance = getDistance(II); if (Distance) OS << *Distance; else if (isScalar(II)) OS << "S"; else { unsigned Direction = getDirection(II); if (Direction == DVEntry::ALL) OS << "*"; else { if (Direction & DVEntry::LT) OS << "<"; if (Direction & DVEntry::EQ) OS << "="; if (Direction & DVEntry::GT) OS << ">"; } } if (isPeelLast(II)) OS << 'p'; if (II < Levels) OS << " "; } if (isLoopIndependent()) OS << "|<"; OS << "]"; if (Splitable) OS << " splitable"; } OS << "!\n"; } static AliasAnalysis::AliasResult underlyingObjectsAlias(AliasAnalysis *AA, const Value *A, const Value *B) { const Value *AObj = GetUnderlyingObject(A); const Value *BObj = GetUnderlyingObject(B); return AA->alias(AObj, AA->getTypeStoreSize(AObj->getType()), BObj, AA->getTypeStoreSize(BObj->getType())); } // Returns true if the load or store can be analyzed. Atomic and volatile // operations have properties which this analysis does not understand. static bool isLoadOrStore(const Instruction *I) { if (const LoadInst *LI = dyn_cast(I)) return LI->isUnordered(); else if (const StoreInst *SI = dyn_cast(I)) return SI->isUnordered(); return false; } static Value *getPointerOperand(Instruction *I) { if (LoadInst *LI = dyn_cast(I)) return LI->getPointerOperand(); if (StoreInst *SI = dyn_cast(I)) return SI->getPointerOperand(); llvm_unreachable("Value is not load or store instruction"); return nullptr; } // Examines the loop nesting of the Src and Dst // instructions and establishes their shared loops. Sets the variables // CommonLevels, SrcLevels, and MaxLevels. // The source and destination instructions needn't be contained in the same // loop. The routine establishNestingLevels finds the level of most deeply // nested loop that contains them both, CommonLevels. An instruction that's // not contained in a loop is at level = 0. MaxLevels is equal to the level // of the source plus the level of the destination, minus CommonLevels. // This lets us allocate vectors MaxLevels in length, with room for every // distinct loop referenced in both the source and destination subscripts. // The variable SrcLevels is the nesting depth of the source instruction. // It's used to help calculate distinct loops referenced by the destination. // Here's the map from loops to levels: // 0 - unused // 1 - outermost common loop // ... - other common loops // CommonLevels - innermost common loop // ... - loops containing Src but not Dst // SrcLevels - innermost loop containing Src but not Dst // ... - loops containing Dst but not Src // MaxLevels - innermost loops containing Dst but not Src // Consider the follow code fragment: // for (a = ...) { // for (b = ...) { // for (c = ...) { // for (d = ...) { // A[] = ...; // } // } // for (e = ...) { // for (f = ...) { // for (g = ...) { // ... = A[]; // } // } // } // } // } // If we're looking at the possibility of a dependence between the store // to A (the Src) and the load from A (the Dst), we'll note that they // have 2 loops in common, so CommonLevels will equal 2 and the direction // vector for Result will have 2 entries. SrcLevels = 4 and MaxLevels = 7. // A map from loop names to loop numbers would look like // a - 1 // b - 2 = CommonLevels // c - 3 // d - 4 = SrcLevels // e - 5 // f - 6 // g - 7 = MaxLevels void DependenceAnalysis::establishNestingLevels(const Instruction *Src, const Instruction *Dst) { const BasicBlock *SrcBlock = Src->getParent(); const BasicBlock *DstBlock = Dst->getParent(); unsigned SrcLevel = LI->getLoopDepth(SrcBlock); unsigned DstLevel = LI->getLoopDepth(DstBlock); const Loop *SrcLoop = LI->getLoopFor(SrcBlock); const Loop *DstLoop = LI->getLoopFor(DstBlock); SrcLevels = SrcLevel; MaxLevels = SrcLevel + DstLevel; while (SrcLevel > DstLevel) { SrcLoop = SrcLoop->getParentLoop(); SrcLevel--; } while (DstLevel > SrcLevel) { DstLoop = DstLoop->getParentLoop(); DstLevel--; } while (SrcLoop != DstLoop) { SrcLoop = SrcLoop->getParentLoop(); DstLoop = DstLoop->getParentLoop(); SrcLevel--; } CommonLevels = SrcLevel; MaxLevels -= CommonLevels; } // Given one of the loops containing the source, return // its level index in our numbering scheme. unsigned DependenceAnalysis::mapSrcLoop(const Loop *SrcLoop) const { return SrcLoop->getLoopDepth(); } // Given one of the loops containing the destination, // return its level index in our numbering scheme. unsigned DependenceAnalysis::mapDstLoop(const Loop *DstLoop) const { unsigned D = DstLoop->getLoopDepth(); if (D > CommonLevels) return D - CommonLevels + SrcLevels; else return D; } // Returns true if Expression is loop invariant in LoopNest. bool DependenceAnalysis::isLoopInvariant(const SCEV *Expression, const Loop *LoopNest) const { if (!LoopNest) return true; return SE->isLoopInvariant(Expression, LoopNest) && isLoopInvariant(Expression, LoopNest->getParentLoop()); } // Finds the set of loops from the LoopNest that // have a level <= CommonLevels and are referred to by the SCEV Expression. void DependenceAnalysis::collectCommonLoops(const SCEV *Expression, const Loop *LoopNest, SmallBitVector &Loops) const { while (LoopNest) { unsigned Level = LoopNest->getLoopDepth(); if (Level <= CommonLevels && !SE->isLoopInvariant(Expression, LoopNest)) Loops.set(Level); LoopNest = LoopNest->getParentLoop(); } } // removeMatchingExtensions - Examines a subscript pair. // If the source and destination are identically sign (or zero) // extended, it strips off the extension in an effect to simplify // the actual analysis. void DependenceAnalysis::removeMatchingExtensions(Subscript *Pair) { const SCEV *Src = Pair->Src; const SCEV *Dst = Pair->Dst; if ((isa(Src) && isa(Dst)) || (isa(Src) && isa(Dst))) { const SCEVCastExpr *SrcCast = cast(Src); const SCEVCastExpr *DstCast = cast(Dst); if (SrcCast->getType() == DstCast->getType()) { Pair->Src = SrcCast->getOperand(); Pair->Dst = DstCast->getOperand(); } } } // Examine the scev and return true iff it's linear. // Collect any loops mentioned in the set of "Loops". bool DependenceAnalysis::checkSrcSubscript(const SCEV *Src, const Loop *LoopNest, SmallBitVector &Loops) { const SCEVAddRecExpr *AddRec = dyn_cast(Src); if (!AddRec) return isLoopInvariant(Src, LoopNest); const SCEV *Start = AddRec->getStart(); const SCEV *Step = AddRec->getStepRecurrence(*SE); if (!isLoopInvariant(Step, LoopNest)) return false; Loops.set(mapSrcLoop(AddRec->getLoop())); return checkSrcSubscript(Start, LoopNest, Loops); } // Examine the scev and return true iff it's linear. // Collect any loops mentioned in the set of "Loops". bool DependenceAnalysis::checkDstSubscript(const SCEV *Dst, const Loop *LoopNest, SmallBitVector &Loops) { const SCEVAddRecExpr *AddRec = dyn_cast(Dst); if (!AddRec) return isLoopInvariant(Dst, LoopNest); const SCEV *Start = AddRec->getStart(); const SCEV *Step = AddRec->getStepRecurrence(*SE); if (!isLoopInvariant(Step, LoopNest)) return false; Loops.set(mapDstLoop(AddRec->getLoop())); return checkDstSubscript(Start, LoopNest, Loops); } // Examines the subscript pair (the Src and Dst SCEVs) // and classifies it as either ZIV, SIV, RDIV, MIV, or Nonlinear. // Collects the associated loops in a set. DependenceAnalysis::Subscript::ClassificationKind DependenceAnalysis::classifyPair(const SCEV *Src, const Loop *SrcLoopNest, const SCEV *Dst, const Loop *DstLoopNest, SmallBitVector &Loops) { SmallBitVector SrcLoops(MaxLevels + 1); SmallBitVector DstLoops(MaxLevels + 1); if (!checkSrcSubscript(Src, SrcLoopNest, SrcLoops)) return Subscript::NonLinear; if (!checkDstSubscript(Dst, DstLoopNest, DstLoops)) return Subscript::NonLinear; Loops = SrcLoops; Loops |= DstLoops; unsigned N = Loops.count(); if (N == 0) return Subscript::ZIV; if (N == 1) return Subscript::SIV; if (N == 2 && (SrcLoops.count() == 0 || DstLoops.count() == 0 || (SrcLoops.count() == 1 && DstLoops.count() == 1))) return Subscript::RDIV; return Subscript::MIV; } // A wrapper around SCEV::isKnownPredicate. // Looks for cases where we're interested in comparing for equality. // If both X and Y have been identically sign or zero extended, // it strips off the (confusing) extensions before invoking // SCEV::isKnownPredicate. Perhaps, someday, the ScalarEvolution package // will be similarly updated. // // If SCEV::isKnownPredicate can't prove the predicate, // we try simple subtraction, which seems to help in some cases // involving symbolics. bool DependenceAnalysis::isKnownPredicate(ICmpInst::Predicate Pred, const SCEV *X, const SCEV *Y) const { if (Pred == CmpInst::ICMP_EQ || Pred == CmpInst::ICMP_NE) { if ((isa(X) && isa(Y)) || (isa(X) && isa(Y))) { const SCEVCastExpr *CX = cast(X); const SCEVCastExpr *CY = cast(Y); const SCEV *Xop = CX->getOperand(); const SCEV *Yop = CY->getOperand(); if (Xop->getType() == Yop->getType()) { X = Xop; Y = Yop; } } } if (SE->isKnownPredicate(Pred, X, Y)) return true; // If SE->isKnownPredicate can't prove the condition, // we try the brute-force approach of subtracting // and testing the difference. // By testing with SE->isKnownPredicate first, we avoid // the possibility of overflow when the arguments are constants. const SCEV *Delta = SE->getMinusSCEV(X, Y); switch (Pred) { case CmpInst::ICMP_EQ: return Delta->isZero(); case CmpInst::ICMP_NE: return SE->isKnownNonZero(Delta); case CmpInst::ICMP_SGE: return SE->isKnownNonNegative(Delta); case CmpInst::ICMP_SLE: return SE->isKnownNonPositive(Delta); case CmpInst::ICMP_SGT: return SE->isKnownPositive(Delta); case CmpInst::ICMP_SLT: return SE->isKnownNegative(Delta); default: llvm_unreachable("unexpected predicate in isKnownPredicate"); } } // All subscripts are all the same type. // Loop bound may be smaller (e.g., a char). // Should zero extend loop bound, since it's always >= 0. // This routine collects upper bound and extends if needed. // Return null if no bound available. const SCEV *DependenceAnalysis::collectUpperBound(const Loop *L, Type *T) const { if (SE->hasLoopInvariantBackedgeTakenCount(L)) { const SCEV *UB = SE->getBackedgeTakenCount(L); return SE->getNoopOrZeroExtend(UB, T); } return nullptr; } // Calls collectUpperBound(), then attempts to cast it to SCEVConstant. // If the cast fails, returns NULL. const SCEVConstant *DependenceAnalysis::collectConstantUpperBound(const Loop *L, Type *T ) const { if (const SCEV *UB = collectUpperBound(L, T)) return dyn_cast(UB); return nullptr; } // testZIV - // When we have a pair of subscripts of the form [c1] and [c2], // where c1 and c2 are both loop invariant, we attack it using // the ZIV test. Basically, we test by comparing the two values, // but there are actually three possible results: // 1) the values are equal, so there's a dependence // 2) the values are different, so there's no dependence // 3) the values might be equal, so we have to assume a dependence. // // Return true if dependence disproved. bool DependenceAnalysis::testZIV(const SCEV *Src, const SCEV *Dst, FullDependence &Result) const { DEBUG(dbgs() << " src = " << *Src << "\n"); DEBUG(dbgs() << " dst = " << *Dst << "\n"); ++ZIVapplications; if (isKnownPredicate(CmpInst::ICMP_EQ, Src, Dst)) { DEBUG(dbgs() << " provably dependent\n"); return false; // provably dependent } if (isKnownPredicate(CmpInst::ICMP_NE, Src, Dst)) { DEBUG(dbgs() << " provably independent\n"); ++ZIVindependence; return true; // provably independent } DEBUG(dbgs() << " possibly dependent\n"); Result.Consistent = false; return false; // possibly dependent } // strongSIVtest - // From the paper, Practical Dependence Testing, Section 4.2.1 // // When we have a pair of subscripts of the form [c1 + a*i] and [c2 + a*i], // where i is an induction variable, c1 and c2 are loop invariant, // and a is a constant, we can solve it exactly using the Strong SIV test. // // Can prove independence. Failing that, can compute distance (and direction). // In the presence of symbolic terms, we can sometimes make progress. // // If there's a dependence, // // c1 + a*i = c2 + a*i' // // The dependence distance is // // d = i' - i = (c1 - c2)/a // // A dependence only exists if d is an integer and abs(d) <= U, where U is the // loop's upper bound. If a dependence exists, the dependence direction is // defined as // // { < if d > 0 // direction = { = if d = 0 // { > if d < 0 // // Return true if dependence disproved. bool DependenceAnalysis::strongSIVtest(const SCEV *Coeff, const SCEV *SrcConst, const SCEV *DstConst, const Loop *CurLoop, unsigned Level, FullDependence &Result, Constraint &NewConstraint) const { DEBUG(dbgs() << "\tStrong SIV test\n"); DEBUG(dbgs() << "\t Coeff = " << *Coeff); DEBUG(dbgs() << ", " << *Coeff->getType() << "\n"); DEBUG(dbgs() << "\t SrcConst = " << *SrcConst); DEBUG(dbgs() << ", " << *SrcConst->getType() << "\n"); DEBUG(dbgs() << "\t DstConst = " << *DstConst); DEBUG(dbgs() << ", " << *DstConst->getType() << "\n"); ++StrongSIVapplications; assert(0 < Level && Level <= CommonLevels && "level out of range"); Level--; const SCEV *Delta = SE->getMinusSCEV(SrcConst, DstConst); DEBUG(dbgs() << "\t Delta = " << *Delta); DEBUG(dbgs() << ", " << *Delta->getType() << "\n"); // check that |Delta| < iteration count if (const SCEV *UpperBound = collectUpperBound(CurLoop, Delta->getType())) { DEBUG(dbgs() << "\t UpperBound = " << *UpperBound); DEBUG(dbgs() << ", " << *UpperBound->getType() << "\n"); const SCEV *AbsDelta = SE->isKnownNonNegative(Delta) ? Delta : SE->getNegativeSCEV(Delta); const SCEV *AbsCoeff = SE->isKnownNonNegative(Coeff) ? Coeff : SE->getNegativeSCEV(Coeff); const SCEV *Product = SE->getMulExpr(UpperBound, AbsCoeff); if (isKnownPredicate(CmpInst::ICMP_SGT, AbsDelta, Product)) { // Distance greater than trip count - no dependence ++StrongSIVindependence; ++StrongSIVsuccesses; return true; } } // Can we compute distance? if (isa(Delta) && isa(Coeff)) { APInt ConstDelta = cast(Delta)->getValue()->getValue(); APInt ConstCoeff = cast(Coeff)->getValue()->getValue(); APInt Distance = ConstDelta; // these need to be initialized APInt Remainder = ConstDelta; APInt::sdivrem(ConstDelta, ConstCoeff, Distance, Remainder); DEBUG(dbgs() << "\t Distance = " << Distance << "\n"); DEBUG(dbgs() << "\t Remainder = " << Remainder << "\n"); // Make sure Coeff divides Delta exactly if (Remainder != 0) { // Coeff doesn't divide Distance, no dependence ++StrongSIVindependence; ++StrongSIVsuccesses; return true; } Result.DV[Level].Distance = SE->getConstant(Distance); NewConstraint.setDistance(SE->getConstant(Distance), CurLoop); if (Distance.sgt(0)) Result.DV[Level].Direction &= Dependence::DVEntry::LT; else if (Distance.slt(0)) Result.DV[Level].Direction &= Dependence::DVEntry::GT; else Result.DV[Level].Direction &= Dependence::DVEntry::EQ; ++StrongSIVsuccesses; } else if (Delta->isZero()) { // since 0/X == 0 Result.DV[Level].Distance = Delta; NewConstraint.setDistance(Delta, CurLoop); Result.DV[Level].Direction &= Dependence::DVEntry::EQ; ++StrongSIVsuccesses; } else { if (Coeff->isOne()) { DEBUG(dbgs() << "\t Distance = " << *Delta << "\n"); Result.DV[Level].Distance = Delta; // since X/1 == X NewConstraint.setDistance(Delta, CurLoop); } else { Result.Consistent = false; NewConstraint.setLine(Coeff, SE->getNegativeSCEV(Coeff), SE->getNegativeSCEV(Delta), CurLoop); } // maybe we can get a useful direction bool DeltaMaybeZero = !SE->isKnownNonZero(Delta); bool DeltaMaybePositive = !SE->isKnownNonPositive(Delta); bool DeltaMaybeNegative = !SE->isKnownNonNegative(Delta); bool CoeffMaybePositive = !SE->isKnownNonPositive(Coeff); bool CoeffMaybeNegative = !SE->isKnownNonNegative(Coeff); // The double negatives above are confusing. // It helps to read !SE->isKnownNonZero(Delta) // as "Delta might be Zero" unsigned NewDirection = Dependence::DVEntry::NONE; if ((DeltaMaybePositive && CoeffMaybePositive) || (DeltaMaybeNegative && CoeffMaybeNegative)) NewDirection = Dependence::DVEntry::LT; if (DeltaMaybeZero) NewDirection |= Dependence::DVEntry::EQ; if ((DeltaMaybeNegative && CoeffMaybePositive) || (DeltaMaybePositive && CoeffMaybeNegative)) NewDirection |= Dependence::DVEntry::GT; if (NewDirection < Result.DV[Level].Direction) ++StrongSIVsuccesses; Result.DV[Level].Direction &= NewDirection; } return false; } // weakCrossingSIVtest - // From the paper, Practical Dependence Testing, Section 4.2.2 // // When we have a pair of subscripts of the form [c1 + a*i] and [c2 - a*i], // where i is an induction variable, c1 and c2 are loop invariant, // and a is a constant, we can solve it exactly using the // Weak-Crossing SIV test. // // Given c1 + a*i = c2 - a*i', we can look for the intersection of // the two lines, where i = i', yielding // // c1 + a*i = c2 - a*i // 2a*i = c2 - c1 // i = (c2 - c1)/2a // // If i < 0, there is no dependence. // If i > upperbound, there is no dependence. // If i = 0 (i.e., if c1 = c2), there's a dependence with distance = 0. // If i = upperbound, there's a dependence with distance = 0. // If i is integral, there's a dependence (all directions). // If the non-integer part = 1/2, there's a dependence (<> directions). // Otherwise, there's no dependence. // // Can prove independence. Failing that, // can sometimes refine the directions. // Can determine iteration for splitting. // // Return true if dependence disproved. bool DependenceAnalysis::weakCrossingSIVtest(const SCEV *Coeff, const SCEV *SrcConst, const SCEV *DstConst, const Loop *CurLoop, unsigned Level, FullDependence &Result, Constraint &NewConstraint, const SCEV *&SplitIter) const { DEBUG(dbgs() << "\tWeak-Crossing SIV test\n"); DEBUG(dbgs() << "\t Coeff = " << *Coeff << "\n"); DEBUG(dbgs() << "\t SrcConst = " << *SrcConst << "\n"); DEBUG(dbgs() << "\t DstConst = " << *DstConst << "\n"); ++WeakCrossingSIVapplications; assert(0 < Level && Level <= CommonLevels && "Level out of range"); Level--; Result.Consistent = false; const SCEV *Delta = SE->getMinusSCEV(DstConst, SrcConst); DEBUG(dbgs() << "\t Delta = " << *Delta << "\n"); NewConstraint.setLine(Coeff, Coeff, Delta, CurLoop); if (Delta->isZero()) { Result.DV[Level].Direction &= unsigned(~Dependence::DVEntry::LT); Result.DV[Level].Direction &= unsigned(~Dependence::DVEntry::GT); ++WeakCrossingSIVsuccesses; if (!Result.DV[Level].Direction) { ++WeakCrossingSIVindependence; return true; } Result.DV[Level].Distance = Delta; // = 0 return false; } const SCEVConstant *ConstCoeff = dyn_cast(Coeff); if (!ConstCoeff) return false; Result.DV[Level].Splitable = true; if (SE->isKnownNegative(ConstCoeff)) { ConstCoeff = dyn_cast(SE->getNegativeSCEV(ConstCoeff)); assert(ConstCoeff && "dynamic cast of negative of ConstCoeff should yield constant"); Delta = SE->getNegativeSCEV(Delta); } assert(SE->isKnownPositive(ConstCoeff) && "ConstCoeff should be positive"); // compute SplitIter for use by DependenceAnalysis::getSplitIteration() SplitIter = SE->getUDivExpr(SE->getSMaxExpr(SE->getConstant(Delta->getType(), 0), Delta), SE->getMulExpr(SE->getConstant(Delta->getType(), 2), ConstCoeff)); DEBUG(dbgs() << "\t Split iter = " << *SplitIter << "\n"); const SCEVConstant *ConstDelta = dyn_cast(Delta); if (!ConstDelta) return false; // We're certain that ConstCoeff > 0; therefore, // if Delta < 0, then no dependence. DEBUG(dbgs() << "\t Delta = " << *Delta << "\n"); DEBUG(dbgs() << "\t ConstCoeff = " << *ConstCoeff << "\n"); if (SE->isKnownNegative(Delta)) { // No dependence, Delta < 0 ++WeakCrossingSIVindependence; ++WeakCrossingSIVsuccesses; return true; } // We're certain that Delta > 0 and ConstCoeff > 0. // Check Delta/(2*ConstCoeff) against upper loop bound if (const SCEV *UpperBound = collectUpperBound(CurLoop, Delta->getType())) { DEBUG(dbgs() << "\t UpperBound = " << *UpperBound << "\n"); const SCEV *ConstantTwo = SE->getConstant(UpperBound->getType(), 2); const SCEV *ML = SE->getMulExpr(SE->getMulExpr(ConstCoeff, UpperBound), ConstantTwo); DEBUG(dbgs() << "\t ML = " << *ML << "\n"); if (isKnownPredicate(CmpInst::ICMP_SGT, Delta, ML)) { // Delta too big, no dependence ++WeakCrossingSIVindependence; ++WeakCrossingSIVsuccesses; return true; } if (isKnownPredicate(CmpInst::ICMP_EQ, Delta, ML)) { // i = i' = UB Result.DV[Level].Direction &= unsigned(~Dependence::DVEntry::LT); Result.DV[Level].Direction &= unsigned(~Dependence::DVEntry::GT); ++WeakCrossingSIVsuccesses; if (!Result.DV[Level].Direction) { ++WeakCrossingSIVindependence; return true; } Result.DV[Level].Splitable = false; Result.DV[Level].Distance = SE->getConstant(Delta->getType(), 0); return false; } } // check that Coeff divides Delta APInt APDelta = ConstDelta->getValue()->getValue(); APInt APCoeff = ConstCoeff->getValue()->getValue(); APInt Distance = APDelta; // these need to be initialzed APInt Remainder = APDelta; APInt::sdivrem(APDelta, APCoeff, Distance, Remainder); DEBUG(dbgs() << "\t Remainder = " << Remainder << "\n"); if (Remainder != 0) { // Coeff doesn't divide Delta, no dependence ++WeakCrossingSIVindependence; ++WeakCrossingSIVsuccesses; return true; } DEBUG(dbgs() << "\t Distance = " << Distance << "\n"); // if 2*Coeff doesn't divide Delta, then the equal direction isn't possible APInt Two = APInt(Distance.getBitWidth(), 2, true); Remainder = Distance.srem(Two); DEBUG(dbgs() << "\t Remainder = " << Remainder << "\n"); if (Remainder != 0) { // Equal direction isn't possible Result.DV[Level].Direction &= unsigned(~Dependence::DVEntry::EQ); ++WeakCrossingSIVsuccesses; } return false; } // Kirch's algorithm, from // // Optimizing Supercompilers for Supercomputers // Michael Wolfe // MIT Press, 1989 // // Program 2.1, page 29. // Computes the GCD of AM and BM. // Also finds a solution to the equation ax - by = gcd(a, b). // Returns true if dependence disproved; i.e., gcd does not divide Delta. static bool findGCD(unsigned Bits, APInt AM, APInt BM, APInt Delta, APInt &G, APInt &X, APInt &Y) { APInt A0(Bits, 1, true), A1(Bits, 0, true); APInt B0(Bits, 0, true), B1(Bits, 1, true); APInt G0 = AM.abs(); APInt G1 = BM.abs(); APInt Q = G0; // these need to be initialized APInt R = G0; APInt::sdivrem(G0, G1, Q, R); while (R != 0) { APInt A2 = A0 - Q*A1; A0 = A1; A1 = A2; APInt B2 = B0 - Q*B1; B0 = B1; B1 = B2; G0 = G1; G1 = R; APInt::sdivrem(G0, G1, Q, R); } G = G1; DEBUG(dbgs() << "\t GCD = " << G << "\n"); X = AM.slt(0) ? -A1 : A1; Y = BM.slt(0) ? B1 : -B1; // make sure gcd divides Delta R = Delta.srem(G); if (R != 0) return true; // gcd doesn't divide Delta, no dependence Q = Delta.sdiv(G); X *= Q; Y *= Q; return false; } static APInt floorOfQuotient(APInt A, APInt B) { APInt Q = A; // these need to be initialized APInt R = A; APInt::sdivrem(A, B, Q, R); if (R == 0) return Q; if ((A.sgt(0) && B.sgt(0)) || (A.slt(0) && B.slt(0))) return Q; else return Q - 1; } static APInt ceilingOfQuotient(APInt A, APInt B) { APInt Q = A; // these need to be initialized APInt R = A; APInt::sdivrem(A, B, Q, R); if (R == 0) return Q; if ((A.sgt(0) && B.sgt(0)) || (A.slt(0) && B.slt(0))) return Q + 1; else return Q; } static APInt maxAPInt(APInt A, APInt B) { return A.sgt(B) ? A : B; } static APInt minAPInt(APInt A, APInt B) { return A.slt(B) ? A : B; } // exactSIVtest - // When we have a pair of subscripts of the form [c1 + a1*i] and [c2 + a2*i], // where i is an induction variable, c1 and c2 are loop invariant, and a1 // and a2 are constant, we can solve it exactly using an algorithm developed // by Banerjee and Wolfe. See Section 2.5.3 in // // Optimizing Supercompilers for Supercomputers // Michael Wolfe // MIT Press, 1989 // // It's slower than the specialized tests (strong SIV, weak-zero SIV, etc), // so use them if possible. They're also a bit better with symbolics and, // in the case of the strong SIV test, can compute Distances. // // Return true if dependence disproved. bool DependenceAnalysis::exactSIVtest(const SCEV *SrcCoeff, const SCEV *DstCoeff, const SCEV *SrcConst, const SCEV *DstConst, const Loop *CurLoop, unsigned Level, FullDependence &Result, Constraint &NewConstraint) const { DEBUG(dbgs() << "\tExact SIV test\n"); DEBUG(dbgs() << "\t SrcCoeff = " << *SrcCoeff << " = AM\n"); DEBUG(dbgs() << "\t DstCoeff = " << *DstCoeff << " = BM\n"); DEBUG(dbgs() << "\t SrcConst = " << *SrcConst << "\n"); DEBUG(dbgs() << "\t DstConst = " << *DstConst << "\n"); ++ExactSIVapplications; assert(0 < Level && Level <= CommonLevels && "Level out of range"); Level--; Result.Consistent = false; const SCEV *Delta = SE->getMinusSCEV(DstConst, SrcConst); DEBUG(dbgs() << "\t Delta = " << *Delta << "\n"); NewConstraint.setLine(SrcCoeff, SE->getNegativeSCEV(DstCoeff), Delta, CurLoop); const SCEVConstant *ConstDelta = dyn_cast(Delta); const SCEVConstant *ConstSrcCoeff = dyn_cast(SrcCoeff); const SCEVConstant *ConstDstCoeff = dyn_cast(DstCoeff); if (!ConstDelta || !ConstSrcCoeff || !ConstDstCoeff) return false; // find gcd APInt G, X, Y; APInt AM = ConstSrcCoeff->getValue()->getValue(); APInt BM = ConstDstCoeff->getValue()->getValue(); unsigned Bits = AM.getBitWidth(); if (findGCD(Bits, AM, BM, ConstDelta->getValue()->getValue(), G, X, Y)) { // gcd doesn't divide Delta, no dependence ++ExactSIVindependence; ++ExactSIVsuccesses; return true; } DEBUG(dbgs() << "\t X = " << X << ", Y = " << Y << "\n"); // since SCEV construction normalizes, LM = 0 APInt UM(Bits, 1, true); bool UMvalid = false; // UM is perhaps unavailable, let's check if (const SCEVConstant *CUB = collectConstantUpperBound(CurLoop, Delta->getType())) { UM = CUB->getValue()->getValue(); DEBUG(dbgs() << "\t UM = " << UM << "\n"); UMvalid = true; } APInt TU(APInt::getSignedMaxValue(Bits)); APInt TL(APInt::getSignedMinValue(Bits)); // test(BM/G, LM-X) and test(-BM/G, X-UM) APInt TMUL = BM.sdiv(G); if (TMUL.sgt(0)) { TL = maxAPInt(TL, ceilingOfQuotient(-X, TMUL)); DEBUG(dbgs() << "\t TL = " << TL << "\n"); if (UMvalid) { TU = minAPInt(TU, floorOfQuotient(UM - X, TMUL)); DEBUG(dbgs() << "\t TU = " << TU << "\n"); } } else { TU = minAPInt(TU, floorOfQuotient(-X, TMUL)); DEBUG(dbgs() << "\t TU = " << TU << "\n"); if (UMvalid) { TL = maxAPInt(TL, ceilingOfQuotient(UM - X, TMUL)); DEBUG(dbgs() << "\t TL = " << TL << "\n"); } } // test(AM/G, LM-Y) and test(-AM/G, Y-UM) TMUL = AM.sdiv(G); if (TMUL.sgt(0)) { TL = maxAPInt(TL, ceilingOfQuotient(-Y, TMUL)); DEBUG(dbgs() << "\t TL = " << TL << "\n"); if (UMvalid) { TU = minAPInt(TU, floorOfQuotient(UM - Y, TMUL)); DEBUG(dbgs() << "\t TU = " << TU << "\n"); } } else { TU = minAPInt(TU, floorOfQuotient(-Y, TMUL)); DEBUG(dbgs() << "\t TU = " << TU << "\n"); if (UMvalid) { TL = maxAPInt(TL, ceilingOfQuotient(UM - Y, TMUL)); DEBUG(dbgs() << "\t TL = " << TL << "\n"); } } if (TL.sgt(TU)) { ++ExactSIVindependence; ++ExactSIVsuccesses; return true; } // explore directions unsigned NewDirection = Dependence::DVEntry::NONE; // less than APInt SaveTU(TU); // save these APInt SaveTL(TL); DEBUG(dbgs() << "\t exploring LT direction\n"); TMUL = AM - BM; if (TMUL.sgt(0)) { TL = maxAPInt(TL, ceilingOfQuotient(X - Y + 1, TMUL)); DEBUG(dbgs() << "\t\t TL = " << TL << "\n"); } else { TU = minAPInt(TU, floorOfQuotient(X - Y + 1, TMUL)); DEBUG(dbgs() << "\t\t TU = " << TU << "\n"); } if (TL.sle(TU)) { NewDirection |= Dependence::DVEntry::LT; ++ExactSIVsuccesses; } // equal TU = SaveTU; // restore TL = SaveTL; DEBUG(dbgs() << "\t exploring EQ direction\n"); if (TMUL.sgt(0)) { TL = maxAPInt(TL, ceilingOfQuotient(X - Y, TMUL)); DEBUG(dbgs() << "\t\t TL = " << TL << "\n"); } else { TU = minAPInt(TU, floorOfQuotient(X - Y, TMUL)); DEBUG(dbgs() << "\t\t TU = " << TU << "\n"); } TMUL = BM - AM; if (TMUL.sgt(0)) { TL = maxAPInt(TL, ceilingOfQuotient(Y - X, TMUL)); DEBUG(dbgs() << "\t\t TL = " << TL << "\n"); } else { TU = minAPInt(TU, floorOfQuotient(Y - X, TMUL)); DEBUG(dbgs() << "\t\t TU = " << TU << "\n"); } if (TL.sle(TU)) { NewDirection |= Dependence::DVEntry::EQ; ++ExactSIVsuccesses; } // greater than TU = SaveTU; // restore TL = SaveTL; DEBUG(dbgs() << "\t exploring GT direction\n"); if (TMUL.sgt(0)) { TL = maxAPInt(TL, ceilingOfQuotient(Y - X + 1, TMUL)); DEBUG(dbgs() << "\t\t TL = " << TL << "\n"); } else { TU = minAPInt(TU, floorOfQuotient(Y - X + 1, TMUL)); DEBUG(dbgs() << "\t\t TU = " << TU << "\n"); } if (TL.sle(TU)) { NewDirection |= Dependence::DVEntry::GT; ++ExactSIVsuccesses; } // finished Result.DV[Level].Direction &= NewDirection; if (Result.DV[Level].Direction == Dependence::DVEntry::NONE) ++ExactSIVindependence; return Result.DV[Level].Direction == Dependence::DVEntry::NONE; } // Return true if the divisor evenly divides the dividend. static bool isRemainderZero(const SCEVConstant *Dividend, const SCEVConstant *Divisor) { APInt ConstDividend = Dividend->getValue()->getValue(); APInt ConstDivisor = Divisor->getValue()->getValue(); return ConstDividend.srem(ConstDivisor) == 0; } // weakZeroSrcSIVtest - // From the paper, Practical Dependence Testing, Section 4.2.2 // // When we have a pair of subscripts of the form [c1] and [c2 + a*i], // where i is an induction variable, c1 and c2 are loop invariant, // and a is a constant, we can solve it exactly using the // Weak-Zero SIV test. // // Given // // c1 = c2 + a*i // // we get // // (c1 - c2)/a = i // // If i is not an integer, there's no dependence. // If i < 0 or > UB, there's no dependence. // If i = 0, the direction is <= and peeling the // 1st iteration will break the dependence. // If i = UB, the direction is >= and peeling the // last iteration will break the dependence. // Otherwise, the direction is *. // // Can prove independence. Failing that, we can sometimes refine // the directions. Can sometimes show that first or last // iteration carries all the dependences (so worth peeling). // // (see also weakZeroDstSIVtest) // // Return true if dependence disproved. bool DependenceAnalysis::weakZeroSrcSIVtest(const SCEV *DstCoeff, const SCEV *SrcConst, const SCEV *DstConst, const Loop *CurLoop, unsigned Level, FullDependence &Result, Constraint &NewConstraint) const { // For the WeakSIV test, it's possible the loop isn't common to // the Src and Dst loops. If it isn't, then there's no need to // record a direction. DEBUG(dbgs() << "\tWeak-Zero (src) SIV test\n"); DEBUG(dbgs() << "\t DstCoeff = " << *DstCoeff << "\n"); DEBUG(dbgs() << "\t SrcConst = " << *SrcConst << "\n"); DEBUG(dbgs() << "\t DstConst = " << *DstConst << "\n"); ++WeakZeroSIVapplications; assert(0 < Level && Level <= MaxLevels && "Level out of range"); Level--; Result.Consistent = false; const SCEV *Delta = SE->getMinusSCEV(SrcConst, DstConst); NewConstraint.setLine(SE->getConstant(Delta->getType(), 0), DstCoeff, Delta, CurLoop); DEBUG(dbgs() << "\t Delta = " << *Delta << "\n"); if (isKnownPredicate(CmpInst::ICMP_EQ, SrcConst, DstConst)) { if (Level < CommonLevels) { Result.DV[Level].Direction &= Dependence::DVEntry::LE; Result.DV[Level].PeelFirst = true; ++WeakZeroSIVsuccesses; } return false; // dependences caused by first iteration } const SCEVConstant *ConstCoeff = dyn_cast(DstCoeff); if (!ConstCoeff) return false; const SCEV *AbsCoeff = SE->isKnownNegative(ConstCoeff) ? SE->getNegativeSCEV(ConstCoeff) : ConstCoeff; const SCEV *NewDelta = SE->isKnownNegative(ConstCoeff) ? SE->getNegativeSCEV(Delta) : Delta; // check that Delta/SrcCoeff < iteration count // really check NewDelta < count*AbsCoeff if (const SCEV *UpperBound = collectUpperBound(CurLoop, Delta->getType())) { DEBUG(dbgs() << "\t UpperBound = " << *UpperBound << "\n"); const SCEV *Product = SE->getMulExpr(AbsCoeff, UpperBound); if (isKnownPredicate(CmpInst::ICMP_SGT, NewDelta, Product)) { ++WeakZeroSIVindependence; ++WeakZeroSIVsuccesses; return true; } if (isKnownPredicate(CmpInst::ICMP_EQ, NewDelta, Product)) { // dependences caused by last iteration if (Level < CommonLevels) { Result.DV[Level].Direction &= Dependence::DVEntry::GE; Result.DV[Level].PeelLast = true; ++WeakZeroSIVsuccesses; } return false; } } // check that Delta/SrcCoeff >= 0 // really check that NewDelta >= 0 if (SE->isKnownNegative(NewDelta)) { // No dependence, newDelta < 0 ++WeakZeroSIVindependence; ++WeakZeroSIVsuccesses; return true; } // if SrcCoeff doesn't divide Delta, then no dependence if (isa(Delta) && !isRemainderZero(cast(Delta), ConstCoeff)) { ++WeakZeroSIVindependence; ++WeakZeroSIVsuccesses; return true; } return false; } // weakZeroDstSIVtest - // From the paper, Practical Dependence Testing, Section 4.2.2 // // When we have a pair of subscripts of the form [c1 + a*i] and [c2], // where i is an induction variable, c1 and c2 are loop invariant, // and a is a constant, we can solve it exactly using the // Weak-Zero SIV test. // // Given // // c1 + a*i = c2 // // we get // // i = (c2 - c1)/a // // If i is not an integer, there's no dependence. // If i < 0 or > UB, there's no dependence. // If i = 0, the direction is <= and peeling the // 1st iteration will break the dependence. // If i = UB, the direction is >= and peeling the // last iteration will break the dependence. // Otherwise, the direction is *. // // Can prove independence. Failing that, we can sometimes refine // the directions. Can sometimes show that first or last // iteration carries all the dependences (so worth peeling). // // (see also weakZeroSrcSIVtest) // // Return true if dependence disproved. bool DependenceAnalysis::weakZeroDstSIVtest(const SCEV *SrcCoeff, const SCEV *SrcConst, const SCEV *DstConst, const Loop *CurLoop, unsigned Level, FullDependence &Result, Constraint &NewConstraint) const { // For the WeakSIV test, it's possible the loop isn't common to the // Src and Dst loops. If it isn't, then there's no need to record a direction. DEBUG(dbgs() << "\tWeak-Zero (dst) SIV test\n"); DEBUG(dbgs() << "\t SrcCoeff = " << *SrcCoeff << "\n"); DEBUG(dbgs() << "\t SrcConst = " << *SrcConst << "\n"); DEBUG(dbgs() << "\t DstConst = " << *DstConst << "\n"); ++WeakZeroSIVapplications; assert(0 < Level && Level <= SrcLevels && "Level out of range"); Level--; Result.Consistent = false; const SCEV *Delta = SE->getMinusSCEV(DstConst, SrcConst); NewConstraint.setLine(SrcCoeff, SE->getConstant(Delta->getType(), 0), Delta, CurLoop); DEBUG(dbgs() << "\t Delta = " << *Delta << "\n"); if (isKnownPredicate(CmpInst::ICMP_EQ, DstConst, SrcConst)) { if (Level < CommonLevels) { Result.DV[Level].Direction &= Dependence::DVEntry::LE; Result.DV[Level].PeelFirst = true; ++WeakZeroSIVsuccesses; } return false; // dependences caused by first iteration } const SCEVConstant *ConstCoeff = dyn_cast(SrcCoeff); if (!ConstCoeff) return false; const SCEV *AbsCoeff = SE->isKnownNegative(ConstCoeff) ? SE->getNegativeSCEV(ConstCoeff) : ConstCoeff; const SCEV *NewDelta = SE->isKnownNegative(ConstCoeff) ? SE->getNegativeSCEV(Delta) : Delta; // check that Delta/SrcCoeff < iteration count // really check NewDelta < count*AbsCoeff if (const SCEV *UpperBound = collectUpperBound(CurLoop, Delta->getType())) { DEBUG(dbgs() << "\t UpperBound = " << *UpperBound << "\n"); const SCEV *Product = SE->getMulExpr(AbsCoeff, UpperBound); if (isKnownPredicate(CmpInst::ICMP_SGT, NewDelta, Product)) { ++WeakZeroSIVindependence; ++WeakZeroSIVsuccesses; return true; } if (isKnownPredicate(CmpInst::ICMP_EQ, NewDelta, Product)) { // dependences caused by last iteration if (Level < CommonLevels) { Result.DV[Level].Direction &= Dependence::DVEntry::GE; Result.DV[Level].PeelLast = true; ++WeakZeroSIVsuccesses; } return false; } } // check that Delta/SrcCoeff >= 0 // really check that NewDelta >= 0 if (SE->isKnownNegative(NewDelta)) { // No dependence, newDelta < 0 ++WeakZeroSIVindependence; ++WeakZeroSIVsuccesses; return true; } // if SrcCoeff doesn't divide Delta, then no dependence if (isa(Delta) && !isRemainderZero(cast(Delta), ConstCoeff)) { ++WeakZeroSIVindependence; ++WeakZeroSIVsuccesses; return true; } return false; } // exactRDIVtest - Tests the RDIV subscript pair for dependence. // Things of the form [c1 + a*i] and [c2 + b*j], // where i and j are induction variable, c1 and c2 are loop invariant, // and a and b are constants. // Returns true if any possible dependence is disproved. // Marks the result as inconsistent. // Works in some cases that symbolicRDIVtest doesn't, and vice versa. bool DependenceAnalysis::exactRDIVtest(const SCEV *SrcCoeff, const SCEV *DstCoeff, const SCEV *SrcConst, const SCEV *DstConst, const Loop *SrcLoop, const Loop *DstLoop, FullDependence &Result) const { DEBUG(dbgs() << "\tExact RDIV test\n"); DEBUG(dbgs() << "\t SrcCoeff = " << *SrcCoeff << " = AM\n"); DEBUG(dbgs() << "\t DstCoeff = " << *DstCoeff << " = BM\n"); DEBUG(dbgs() << "\t SrcConst = " << *SrcConst << "\n"); DEBUG(dbgs() << "\t DstConst = " << *DstConst << "\n"); ++ExactRDIVapplications; Result.Consistent = false; const SCEV *Delta = SE->getMinusSCEV(DstConst, SrcConst); DEBUG(dbgs() << "\t Delta = " << *Delta << "\n"); const SCEVConstant *ConstDelta = dyn_cast(Delta); const SCEVConstant *ConstSrcCoeff = dyn_cast(SrcCoeff); const SCEVConstant *ConstDstCoeff = dyn_cast(DstCoeff); if (!ConstDelta || !ConstSrcCoeff || !ConstDstCoeff) return false; // find gcd APInt G, X, Y; APInt AM = ConstSrcCoeff->getValue()->getValue(); APInt BM = ConstDstCoeff->getValue()->getValue(); unsigned Bits = AM.getBitWidth(); if (findGCD(Bits, AM, BM, ConstDelta->getValue()->getValue(), G, X, Y)) { // gcd doesn't divide Delta, no dependence ++ExactRDIVindependence; return true; } DEBUG(dbgs() << "\t X = " << X << ", Y = " << Y << "\n"); // since SCEV construction seems to normalize, LM = 0 APInt SrcUM(Bits, 1, true); bool SrcUMvalid = false; // SrcUM is perhaps unavailable, let's check if (const SCEVConstant *UpperBound = collectConstantUpperBound(SrcLoop, Delta->getType())) { SrcUM = UpperBound->getValue()->getValue(); DEBUG(dbgs() << "\t SrcUM = " << SrcUM << "\n"); SrcUMvalid = true; } APInt DstUM(Bits, 1, true); bool DstUMvalid = false; // UM is perhaps unavailable, let's check if (const SCEVConstant *UpperBound = collectConstantUpperBound(DstLoop, Delta->getType())) { DstUM = UpperBound->getValue()->getValue(); DEBUG(dbgs() << "\t DstUM = " << DstUM << "\n"); DstUMvalid = true; } APInt TU(APInt::getSignedMaxValue(Bits)); APInt TL(APInt::getSignedMinValue(Bits)); // test(BM/G, LM-X) and test(-BM/G, X-UM) APInt TMUL = BM.sdiv(G); if (TMUL.sgt(0)) { TL = maxAPInt(TL, ceilingOfQuotient(-X, TMUL)); DEBUG(dbgs() << "\t TL = " << TL << "\n"); if (SrcUMvalid) { TU = minAPInt(TU, floorOfQuotient(SrcUM - X, TMUL)); DEBUG(dbgs() << "\t TU = " << TU << "\n"); } } else { TU = minAPInt(TU, floorOfQuotient(-X, TMUL)); DEBUG(dbgs() << "\t TU = " << TU << "\n"); if (SrcUMvalid) { TL = maxAPInt(TL, ceilingOfQuotient(SrcUM - X, TMUL)); DEBUG(dbgs() << "\t TL = " << TL << "\n"); } } // test(AM/G, LM-Y) and test(-AM/G, Y-UM) TMUL = AM.sdiv(G); if (TMUL.sgt(0)) { TL = maxAPInt(TL, ceilingOfQuotient(-Y, TMUL)); DEBUG(dbgs() << "\t TL = " << TL << "\n"); if (DstUMvalid) { TU = minAPInt(TU, floorOfQuotient(DstUM - Y, TMUL)); DEBUG(dbgs() << "\t TU = " << TU << "\n"); } } else { TU = minAPInt(TU, floorOfQuotient(-Y, TMUL)); DEBUG(dbgs() << "\t TU = " << TU << "\n"); if (DstUMvalid) { TL = maxAPInt(TL, ceilingOfQuotient(DstUM - Y, TMUL)); DEBUG(dbgs() << "\t TL = " << TL << "\n"); } } if (TL.sgt(TU)) ++ExactRDIVindependence; return TL.sgt(TU); } // symbolicRDIVtest - // In Section 4.5 of the Practical Dependence Testing paper,the authors // introduce a special case of Banerjee's Inequalities (also called the // Extreme-Value Test) that can handle some of the SIV and RDIV cases, // particularly cases with symbolics. Since it's only able to disprove // dependence (not compute distances or directions), we'll use it as a // fall back for the other tests. // // When we have a pair of subscripts of the form [c1 + a1*i] and [c2 + a2*j] // where i and j are induction variables and c1 and c2 are loop invariants, // we can use the symbolic tests to disprove some dependences, serving as a // backup for the RDIV test. Note that i and j can be the same variable, // letting this test serve as a backup for the various SIV tests. // // For a dependence to exist, c1 + a1*i must equal c2 + a2*j for some // 0 <= i <= N1 and some 0 <= j <= N2, where N1 and N2 are the (normalized) // loop bounds for the i and j loops, respectively. So, ... // // c1 + a1*i = c2 + a2*j // a1*i - a2*j = c2 - c1 // // To test for a dependence, we compute c2 - c1 and make sure it's in the // range of the maximum and minimum possible values of a1*i - a2*j. // Considering the signs of a1 and a2, we have 4 possible cases: // // 1) If a1 >= 0 and a2 >= 0, then // a1*0 - a2*N2 <= c2 - c1 <= a1*N1 - a2*0 // -a2*N2 <= c2 - c1 <= a1*N1 // // 2) If a1 >= 0 and a2 <= 0, then // a1*0 - a2*0 <= c2 - c1 <= a1*N1 - a2*N2 // 0 <= c2 - c1 <= a1*N1 - a2*N2 // // 3) If a1 <= 0 and a2 >= 0, then // a1*N1 - a2*N2 <= c2 - c1 <= a1*0 - a2*0 // a1*N1 - a2*N2 <= c2 - c1 <= 0 // // 4) If a1 <= 0 and a2 <= 0, then // a1*N1 - a2*0 <= c2 - c1 <= a1*0 - a2*N2 // a1*N1 <= c2 - c1 <= -a2*N2 // // return true if dependence disproved bool DependenceAnalysis::symbolicRDIVtest(const SCEV *A1, const SCEV *A2, const SCEV *C1, const SCEV *C2, const Loop *Loop1, const Loop *Loop2) const { ++SymbolicRDIVapplications; DEBUG(dbgs() << "\ttry symbolic RDIV test\n"); DEBUG(dbgs() << "\t A1 = " << *A1); DEBUG(dbgs() << ", type = " << *A1->getType() << "\n"); DEBUG(dbgs() << "\t A2 = " << *A2 << "\n"); DEBUG(dbgs() << "\t C1 = " << *C1 << "\n"); DEBUG(dbgs() << "\t C2 = " << *C2 << "\n"); const SCEV *N1 = collectUpperBound(Loop1, A1->getType()); const SCEV *N2 = collectUpperBound(Loop2, A1->getType()); DEBUG(if (N1) dbgs() << "\t N1 = " << *N1 << "\n"); DEBUG(if (N2) dbgs() << "\t N2 = " << *N2 << "\n"); const SCEV *C2_C1 = SE->getMinusSCEV(C2, C1); const SCEV *C1_C2 = SE->getMinusSCEV(C1, C2); DEBUG(dbgs() << "\t C2 - C1 = " << *C2_C1 << "\n"); DEBUG(dbgs() << "\t C1 - C2 = " << *C1_C2 << "\n"); if (SE->isKnownNonNegative(A1)) { if (SE->isKnownNonNegative(A2)) { // A1 >= 0 && A2 >= 0 if (N1) { // make sure that c2 - c1 <= a1*N1 const SCEV *A1N1 = SE->getMulExpr(A1, N1); DEBUG(dbgs() << "\t A1*N1 = " << *A1N1 << "\n"); if (isKnownPredicate(CmpInst::ICMP_SGT, C2_C1, A1N1)) { ++SymbolicRDIVindependence; return true; } } if (N2) { // make sure that -a2*N2 <= c2 - c1, or a2*N2 >= c1 - c2 const SCEV *A2N2 = SE->getMulExpr(A2, N2); DEBUG(dbgs() << "\t A2*N2 = " << *A2N2 << "\n"); if (isKnownPredicate(CmpInst::ICMP_SLT, A2N2, C1_C2)) { ++SymbolicRDIVindependence; return true; } } } else if (SE->isKnownNonPositive(A2)) { // a1 >= 0 && a2 <= 0 if (N1 && N2) { // make sure that c2 - c1 <= a1*N1 - a2*N2 const SCEV *A1N1 = SE->getMulExpr(A1, N1); const SCEV *A2N2 = SE->getMulExpr(A2, N2); const SCEV *A1N1_A2N2 = SE->getMinusSCEV(A1N1, A2N2); DEBUG(dbgs() << "\t A1*N1 - A2*N2 = " << *A1N1_A2N2 << "\n"); if (isKnownPredicate(CmpInst::ICMP_SGT, C2_C1, A1N1_A2N2)) { ++SymbolicRDIVindependence; return true; } } // make sure that 0 <= c2 - c1 if (SE->isKnownNegative(C2_C1)) { ++SymbolicRDIVindependence; return true; } } } else if (SE->isKnownNonPositive(A1)) { if (SE->isKnownNonNegative(A2)) { // a1 <= 0 && a2 >= 0 if (N1 && N2) { // make sure that a1*N1 - a2*N2 <= c2 - c1 const SCEV *A1N1 = SE->getMulExpr(A1, N1); const SCEV *A2N2 = SE->getMulExpr(A2, N2); const SCEV *A1N1_A2N2 = SE->getMinusSCEV(A1N1, A2N2); DEBUG(dbgs() << "\t A1*N1 - A2*N2 = " << *A1N1_A2N2 << "\n"); if (isKnownPredicate(CmpInst::ICMP_SGT, A1N1_A2N2, C2_C1)) { ++SymbolicRDIVindependence; return true; } } // make sure that c2 - c1 <= 0 if (SE->isKnownPositive(C2_C1)) { ++SymbolicRDIVindependence; return true; } } else if (SE->isKnownNonPositive(A2)) { // a1 <= 0 && a2 <= 0 if (N1) { // make sure that a1*N1 <= c2 - c1 const SCEV *A1N1 = SE->getMulExpr(A1, N1); DEBUG(dbgs() << "\t A1*N1 = " << *A1N1 << "\n"); if (isKnownPredicate(CmpInst::ICMP_SGT, A1N1, C2_C1)) { ++SymbolicRDIVindependence; return true; } } if (N2) { // make sure that c2 - c1 <= -a2*N2, or c1 - c2 >= a2*N2 const SCEV *A2N2 = SE->getMulExpr(A2, N2); DEBUG(dbgs() << "\t A2*N2 = " << *A2N2 << "\n"); if (isKnownPredicate(CmpInst::ICMP_SLT, C1_C2, A2N2)) { ++SymbolicRDIVindependence; return true; } } } } return false; } // testSIV - // When we have a pair of subscripts of the form [c1 + a1*i] and [c2 - a2*i] // where i is an induction variable, c1 and c2 are loop invariant, and a1 and // a2 are constant, we attack it with an SIV test. While they can all be // solved with the Exact SIV test, it's worthwhile to use simpler tests when // they apply; they're cheaper and sometimes more precise. // // Return true if dependence disproved. bool DependenceAnalysis::testSIV(const SCEV *Src, const SCEV *Dst, unsigned &Level, FullDependence &Result, Constraint &NewConstraint, const SCEV *&SplitIter) const { DEBUG(dbgs() << " src = " << *Src << "\n"); DEBUG(dbgs() << " dst = " << *Dst << "\n"); const SCEVAddRecExpr *SrcAddRec = dyn_cast(Src); const SCEVAddRecExpr *DstAddRec = dyn_cast(Dst); if (SrcAddRec && DstAddRec) { const SCEV *SrcConst = SrcAddRec->getStart(); const SCEV *DstConst = DstAddRec->getStart(); const SCEV *SrcCoeff = SrcAddRec->getStepRecurrence(*SE); const SCEV *DstCoeff = DstAddRec->getStepRecurrence(*SE); const Loop *CurLoop = SrcAddRec->getLoop(); assert(CurLoop == DstAddRec->getLoop() && "both loops in SIV should be same"); Level = mapSrcLoop(CurLoop); bool disproven; if (SrcCoeff == DstCoeff) disproven = strongSIVtest(SrcCoeff, SrcConst, DstConst, CurLoop, Level, Result, NewConstraint); else if (SrcCoeff == SE->getNegativeSCEV(DstCoeff)) disproven = weakCrossingSIVtest(SrcCoeff, SrcConst, DstConst, CurLoop, Level, Result, NewConstraint, SplitIter); else disproven = exactSIVtest(SrcCoeff, DstCoeff, SrcConst, DstConst, CurLoop, Level, Result, NewConstraint); return disproven || gcdMIVtest(Src, Dst, Result) || symbolicRDIVtest(SrcCoeff, DstCoeff, SrcConst, DstConst, CurLoop, CurLoop); } if (SrcAddRec) { const SCEV *SrcConst = SrcAddRec->getStart(); const SCEV *SrcCoeff = SrcAddRec->getStepRecurrence(*SE); const SCEV *DstConst = Dst; const Loop *CurLoop = SrcAddRec->getLoop(); Level = mapSrcLoop(CurLoop); return weakZeroDstSIVtest(SrcCoeff, SrcConst, DstConst, CurLoop, Level, Result, NewConstraint) || gcdMIVtest(Src, Dst, Result); } if (DstAddRec) { const SCEV *DstConst = DstAddRec->getStart(); const SCEV *DstCoeff = DstAddRec->getStepRecurrence(*SE); const SCEV *SrcConst = Src; const Loop *CurLoop = DstAddRec->getLoop(); Level = mapDstLoop(CurLoop); return weakZeroSrcSIVtest(DstCoeff, SrcConst, DstConst, CurLoop, Level, Result, NewConstraint) || gcdMIVtest(Src, Dst, Result); } llvm_unreachable("SIV test expected at least one AddRec"); return false; } // testRDIV - // When we have a pair of subscripts of the form [c1 + a1*i] and [c2 + a2*j] // where i and j are induction variables, c1 and c2 are loop invariant, // and a1 and a2 are constant, we can solve it exactly with an easy adaptation // of the Exact SIV test, the Restricted Double Index Variable (RDIV) test. // It doesn't make sense to talk about distance or direction in this case, // so there's no point in making special versions of the Strong SIV test or // the Weak-crossing SIV test. // // With minor algebra, this test can also be used for things like // [c1 + a1*i + a2*j][c2]. // // Return true if dependence disproved. bool DependenceAnalysis::testRDIV(const SCEV *Src, const SCEV *Dst, FullDependence &Result) const { // we have 3 possible situations here: // 1) [a*i + b] and [c*j + d] // 2) [a*i + c*j + b] and [d] // 3) [b] and [a*i + c*j + d] // We need to find what we've got and get organized const SCEV *SrcConst, *DstConst; const SCEV *SrcCoeff, *DstCoeff; const Loop *SrcLoop, *DstLoop; DEBUG(dbgs() << " src = " << *Src << "\n"); DEBUG(dbgs() << " dst = " << *Dst << "\n"); const SCEVAddRecExpr *SrcAddRec = dyn_cast(Src); const SCEVAddRecExpr *DstAddRec = dyn_cast(Dst); if (SrcAddRec && DstAddRec) { SrcConst = SrcAddRec->getStart(); SrcCoeff = SrcAddRec->getStepRecurrence(*SE); SrcLoop = SrcAddRec->getLoop(); DstConst = DstAddRec->getStart(); DstCoeff = DstAddRec->getStepRecurrence(*SE); DstLoop = DstAddRec->getLoop(); } else if (SrcAddRec) { if (const SCEVAddRecExpr *tmpAddRec = dyn_cast(SrcAddRec->getStart())) { SrcConst = tmpAddRec->getStart(); SrcCoeff = tmpAddRec->getStepRecurrence(*SE); SrcLoop = tmpAddRec->getLoop(); DstConst = Dst; DstCoeff = SE->getNegativeSCEV(SrcAddRec->getStepRecurrence(*SE)); DstLoop = SrcAddRec->getLoop(); } else llvm_unreachable("RDIV reached by surprising SCEVs"); } else if (DstAddRec) { if (const SCEVAddRecExpr *tmpAddRec = dyn_cast(DstAddRec->getStart())) { DstConst = tmpAddRec->getStart(); DstCoeff = tmpAddRec->getStepRecurrence(*SE); DstLoop = tmpAddRec->getLoop(); SrcConst = Src; SrcCoeff = SE->getNegativeSCEV(DstAddRec->getStepRecurrence(*SE)); SrcLoop = DstAddRec->getLoop(); } else llvm_unreachable("RDIV reached by surprising SCEVs"); } else llvm_unreachable("RDIV expected at least one AddRec"); return exactRDIVtest(SrcCoeff, DstCoeff, SrcConst, DstConst, SrcLoop, DstLoop, Result) || gcdMIVtest(Src, Dst, Result) || symbolicRDIVtest(SrcCoeff, DstCoeff, SrcConst, DstConst, SrcLoop, DstLoop); } // Tests the single-subscript MIV pair (Src and Dst) for dependence. // Return true if dependence disproved. // Can sometimes refine direction vectors. bool DependenceAnalysis::testMIV(const SCEV *Src, const SCEV *Dst, const SmallBitVector &Loops, FullDependence &Result) const { DEBUG(dbgs() << " src = " << *Src << "\n"); DEBUG(dbgs() << " dst = " << *Dst << "\n"); Result.Consistent = false; return gcdMIVtest(Src, Dst, Result) || banerjeeMIVtest(Src, Dst, Loops, Result); } // Given a product, e.g., 10*X*Y, returns the first constant operand, // in this case 10. If there is no constant part, returns NULL. static const SCEVConstant *getConstantPart(const SCEVMulExpr *Product) { for (unsigned Op = 0, Ops = Product->getNumOperands(); Op < Ops; Op++) { if (const SCEVConstant *Constant = dyn_cast(Product->getOperand(Op))) return Constant; } return nullptr; } //===----------------------------------------------------------------------===// // gcdMIVtest - // Tests an MIV subscript pair for dependence. // Returns true if any possible dependence is disproved. // Marks the result as inconsistent. // Can sometimes disprove the equal direction for 1 or more loops, // as discussed in Michael Wolfe's book, // High Performance Compilers for Parallel Computing, page 235. // // We spend some effort (code!) to handle cases like // [10*i + 5*N*j + 15*M + 6], where i and j are induction variables, // but M and N are just loop-invariant variables. // This should help us handle linearized subscripts; // also makes this test a useful backup to the various SIV tests. // // It occurs to me that the presence of loop-invariant variables // changes the nature of the test from "greatest common divisor" // to "a common divisor". bool DependenceAnalysis::gcdMIVtest(const SCEV *Src, const SCEV *Dst, FullDependence &Result) const { DEBUG(dbgs() << "starting gcd\n"); ++GCDapplications; unsigned BitWidth = SE->getTypeSizeInBits(Src->getType()); APInt RunningGCD = APInt::getNullValue(BitWidth); // Examine Src coefficients. // Compute running GCD and record source constant. // Because we're looking for the constant at the end of the chain, // we can't quit the loop just because the GCD == 1. const SCEV *Coefficients = Src; while (const SCEVAddRecExpr *AddRec = dyn_cast(Coefficients)) { const SCEV *Coeff = AddRec->getStepRecurrence(*SE); const SCEVConstant *Constant = dyn_cast(Coeff); if (const SCEVMulExpr *Product = dyn_cast(Coeff)) // If the coefficient is the product of a constant and other stuff, // we can use the constant in the GCD computation. Constant = getConstantPart(Product); if (!Constant) return false; APInt ConstCoeff = Constant->getValue()->getValue(); RunningGCD = APIntOps::GreatestCommonDivisor(RunningGCD, ConstCoeff.abs()); Coefficients = AddRec->getStart(); } const SCEV *SrcConst = Coefficients; // Examine Dst coefficients. // Compute running GCD and record destination constant. // Because we're looking for the constant at the end of the chain, // we can't quit the loop just because the GCD == 1. Coefficients = Dst; while (const SCEVAddRecExpr *AddRec = dyn_cast(Coefficients)) { const SCEV *Coeff = AddRec->getStepRecurrence(*SE); const SCEVConstant *Constant = dyn_cast(Coeff); if (const SCEVMulExpr *Product = dyn_cast(Coeff)) // If the coefficient is the product of a constant and other stuff, // we can use the constant in the GCD computation. Constant = getConstantPart(Product); if (!Constant) return false; APInt ConstCoeff = Constant->getValue()->getValue(); RunningGCD = APIntOps::GreatestCommonDivisor(RunningGCD, ConstCoeff.abs()); Coefficients = AddRec->getStart(); } const SCEV *DstConst = Coefficients; APInt ExtraGCD = APInt::getNullValue(BitWidth); const SCEV *Delta = SE->getMinusSCEV(DstConst, SrcConst); DEBUG(dbgs() << " Delta = " << *Delta << "\n"); const SCEVConstant *Constant = dyn_cast(Delta); if (const SCEVAddExpr *Sum = dyn_cast(Delta)) { // If Delta is a sum of products, we may be able to make further progress. for (unsigned Op = 0, Ops = Sum->getNumOperands(); Op < Ops; Op++) { const SCEV *Operand = Sum->getOperand(Op); if (isa(Operand)) { assert(!Constant && "Surprised to find multiple constants"); Constant = cast(Operand); } else if (const SCEVMulExpr *Product = dyn_cast(Operand)) { // Search for constant operand to participate in GCD; // If none found; return false. const SCEVConstant *ConstOp = getConstantPart(Product); if (!ConstOp) return false; APInt ConstOpValue = ConstOp->getValue()->getValue(); ExtraGCD = APIntOps::GreatestCommonDivisor(ExtraGCD, ConstOpValue.abs()); } else return false; } } if (!Constant) return false; APInt ConstDelta = cast(Constant)->getValue()->getValue(); DEBUG(dbgs() << " ConstDelta = " << ConstDelta << "\n"); if (ConstDelta == 0) return false; RunningGCD = APIntOps::GreatestCommonDivisor(RunningGCD, ExtraGCD); DEBUG(dbgs() << " RunningGCD = " << RunningGCD << "\n"); APInt Remainder = ConstDelta.srem(RunningGCD); if (Remainder != 0) { ++GCDindependence; return true; } // Try to disprove equal directions. // For example, given a subscript pair [3*i + 2*j] and [i' + 2*j' - 1], // the code above can't disprove the dependence because the GCD = 1. // So we consider what happen if i = i' and what happens if j = j'. // If i = i', we can simplify the subscript to [2*i + 2*j] and [2*j' - 1], // which is infeasible, so we can disallow the = direction for the i level. // Setting j = j' doesn't help matters, so we end up with a direction vector // of [<>, *] // // Given A[5*i + 10*j*M + 9*M*N] and A[15*i + 20*j*M - 21*N*M + 5], // we need to remember that the constant part is 5 and the RunningGCD should // be initialized to ExtraGCD = 30. DEBUG(dbgs() << " ExtraGCD = " << ExtraGCD << '\n'); bool Improved = false; Coefficients = Src; while (const SCEVAddRecExpr *AddRec = dyn_cast(Coefficients)) { Coefficients = AddRec->getStart(); const Loop *CurLoop = AddRec->getLoop(); RunningGCD = ExtraGCD; const SCEV *SrcCoeff = AddRec->getStepRecurrence(*SE); const SCEV *DstCoeff = SE->getMinusSCEV(SrcCoeff, SrcCoeff); const SCEV *Inner = Src; while (RunningGCD != 1 && isa(Inner)) { AddRec = cast(Inner); const SCEV *Coeff = AddRec->getStepRecurrence(*SE); if (CurLoop == AddRec->getLoop()) ; // SrcCoeff == Coeff else { if (const SCEVMulExpr *Product = dyn_cast(Coeff)) // If the coefficient is the product of a constant and other stuff, // we can use the constant in the GCD computation. Constant = getConstantPart(Product); else Constant = cast(Coeff); APInt ConstCoeff = Constant->getValue()->getValue(); RunningGCD = APIntOps::GreatestCommonDivisor(RunningGCD, ConstCoeff.abs()); } Inner = AddRec->getStart(); } Inner = Dst; while (RunningGCD != 1 && isa(Inner)) { AddRec = cast(Inner); const SCEV *Coeff = AddRec->getStepRecurrence(*SE); if (CurLoop == AddRec->getLoop()) DstCoeff = Coeff; else { if (const SCEVMulExpr *Product = dyn_cast(Coeff)) // If the coefficient is the product of a constant and other stuff, // we can use the constant in the GCD computation. Constant = getConstantPart(Product); else Constant = cast(Coeff); APInt ConstCoeff = Constant->getValue()->getValue(); RunningGCD = APIntOps::GreatestCommonDivisor(RunningGCD, ConstCoeff.abs()); } Inner = AddRec->getStart(); } Delta = SE->getMinusSCEV(SrcCoeff, DstCoeff); if (const SCEVMulExpr *Product = dyn_cast(Delta)) // If the coefficient is the product of a constant and other stuff, // we can use the constant in the GCD computation. Constant = getConstantPart(Product); else if (isa(Delta)) Constant = cast(Delta); else { // The difference of the two coefficients might not be a product // or constant, in which case we give up on this direction. continue; } APInt ConstCoeff = Constant->getValue()->getValue(); RunningGCD = APIntOps::GreatestCommonDivisor(RunningGCD, ConstCoeff.abs()); DEBUG(dbgs() << "\tRunningGCD = " << RunningGCD << "\n"); if (RunningGCD != 0) { Remainder = ConstDelta.srem(RunningGCD); DEBUG(dbgs() << "\tRemainder = " << Remainder << "\n"); if (Remainder != 0) { unsigned Level = mapSrcLoop(CurLoop); Result.DV[Level - 1].Direction &= unsigned(~Dependence::DVEntry::EQ); Improved = true; } } } if (Improved) ++GCDsuccesses; DEBUG(dbgs() << "all done\n"); return false; } //===----------------------------------------------------------------------===// // banerjeeMIVtest - // Use Banerjee's Inequalities to test an MIV subscript pair. // (Wolfe, in the race-car book, calls this the Extreme Value Test.) // Generally follows the discussion in Section 2.5.2 of // // Optimizing Supercompilers for Supercomputers // Michael Wolfe // // The inequalities given on page 25 are simplified in that loops are // normalized so that the lower bound is always 0 and the stride is always 1. // For example, Wolfe gives // // LB^<_k = (A^-_k - B_k)^- (U_k - L_k - N_k) + (A_k - B_k)L_k - B_k N_k // // where A_k is the coefficient of the kth index in the source subscript, // B_k is the coefficient of the kth index in the destination subscript, // U_k is the upper bound of the kth index, L_k is the lower bound of the Kth // index, and N_k is the stride of the kth index. Since all loops are normalized // by the SCEV package, N_k = 1 and L_k = 0, allowing us to simplify the // equation to // // LB^<_k = (A^-_k - B_k)^- (U_k - 0 - 1) + (A_k - B_k)0 - B_k 1 // = (A^-_k - B_k)^- (U_k - 1) - B_k // // Similar simplifications are possible for the other equations. // // When we can't determine the number of iterations for a loop, // we use NULL as an indicator for the worst case, infinity. // When computing the upper bound, NULL denotes +inf; // for the lower bound, NULL denotes -inf. // // Return true if dependence disproved. bool DependenceAnalysis::banerjeeMIVtest(const SCEV *Src, const SCEV *Dst, const SmallBitVector &Loops, FullDependence &Result) const { DEBUG(dbgs() << "starting Banerjee\n"); ++BanerjeeApplications; DEBUG(dbgs() << " Src = " << *Src << '\n'); const SCEV *A0; CoefficientInfo *A = collectCoeffInfo(Src, true, A0); DEBUG(dbgs() << " Dst = " << *Dst << '\n'); const SCEV *B0; CoefficientInfo *B = collectCoeffInfo(Dst, false, B0); BoundInfo *Bound = new BoundInfo[MaxLevels + 1]; const SCEV *Delta = SE->getMinusSCEV(B0, A0); DEBUG(dbgs() << "\tDelta = " << *Delta << '\n'); // Compute bounds for all the * directions. DEBUG(dbgs() << "\tBounds[*]\n"); for (unsigned K = 1; K <= MaxLevels; ++K) { Bound[K].Iterations = A[K].Iterations ? A[K].Iterations : B[K].Iterations; Bound[K].Direction = Dependence::DVEntry::ALL; Bound[K].DirSet = Dependence::DVEntry::NONE; findBoundsALL(A, B, Bound, K); #ifndef NDEBUG DEBUG(dbgs() << "\t " << K << '\t'); if (Bound[K].Lower[Dependence::DVEntry::ALL]) DEBUG(dbgs() << *Bound[K].Lower[Dependence::DVEntry::ALL] << '\t'); else DEBUG(dbgs() << "-inf\t"); if (Bound[K].Upper[Dependence::DVEntry::ALL]) DEBUG(dbgs() << *Bound[K].Upper[Dependence::DVEntry::ALL] << '\n'); else DEBUG(dbgs() << "+inf\n"); #endif } // Test the *, *, *, ... case. bool Disproved = false; if (testBounds(Dependence::DVEntry::ALL, 0, Bound, Delta)) { // Explore the direction vector hierarchy. unsigned DepthExpanded = 0; unsigned NewDeps = exploreDirections(1, A, B, Bound, Loops, DepthExpanded, Delta); if (NewDeps > 0) { bool Improved = false; for (unsigned K = 1; K <= CommonLevels; ++K) { if (Loops[K]) { unsigned Old = Result.DV[K - 1].Direction; Result.DV[K - 1].Direction = Old & Bound[K].DirSet; Improved |= Old != Result.DV[K - 1].Direction; if (!Result.DV[K - 1].Direction) { Improved = false; Disproved = true; break; } } } if (Improved) ++BanerjeeSuccesses; } else { ++BanerjeeIndependence; Disproved = true; } } else { ++BanerjeeIndependence; Disproved = true; } delete [] Bound; delete [] A; delete [] B; return Disproved; } // Hierarchically expands the direction vector // search space, combining the directions of discovered dependences // in the DirSet field of Bound. Returns the number of distinct // dependences discovered. If the dependence is disproved, // it will return 0. unsigned DependenceAnalysis::exploreDirections(unsigned Level, CoefficientInfo *A, CoefficientInfo *B, BoundInfo *Bound, const SmallBitVector &Loops, unsigned &DepthExpanded, const SCEV *Delta) const { if (Level > CommonLevels) { // record result DEBUG(dbgs() << "\t["); for (unsigned K = 1; K <= CommonLevels; ++K) { if (Loops[K]) { Bound[K].DirSet |= Bound[K].Direction; #ifndef NDEBUG switch (Bound[K].Direction) { case Dependence::DVEntry::LT: DEBUG(dbgs() << " <"); break; case Dependence::DVEntry::EQ: DEBUG(dbgs() << " ="); break; case Dependence::DVEntry::GT: DEBUG(dbgs() << " >"); break; case Dependence::DVEntry::ALL: DEBUG(dbgs() << " *"); break; default: llvm_unreachable("unexpected Bound[K].Direction"); } #endif } } DEBUG(dbgs() << " ]\n"); return 1; } if (Loops[Level]) { if (Level > DepthExpanded) { DepthExpanded = Level; // compute bounds for <, =, > at current level findBoundsLT(A, B, Bound, Level); findBoundsGT(A, B, Bound, Level); findBoundsEQ(A, B, Bound, Level); #ifndef NDEBUG DEBUG(dbgs() << "\tBound for level = " << Level << '\n'); DEBUG(dbgs() << "\t <\t"); if (Bound[Level].Lower[Dependence::DVEntry::LT]) DEBUG(dbgs() << *Bound[Level].Lower[Dependence::DVEntry::LT] << '\t'); else DEBUG(dbgs() << "-inf\t"); if (Bound[Level].Upper[Dependence::DVEntry::LT]) DEBUG(dbgs() << *Bound[Level].Upper[Dependence::DVEntry::LT] << '\n'); else DEBUG(dbgs() << "+inf\n"); DEBUG(dbgs() << "\t =\t"); if (Bound[Level].Lower[Dependence::DVEntry::EQ]) DEBUG(dbgs() << *Bound[Level].Lower[Dependence::DVEntry::EQ] << '\t'); else DEBUG(dbgs() << "-inf\t"); if (Bound[Level].Upper[Dependence::DVEntry::EQ]) DEBUG(dbgs() << *Bound[Level].Upper[Dependence::DVEntry::EQ] << '\n'); else DEBUG(dbgs() << "+inf\n"); DEBUG(dbgs() << "\t >\t"); if (Bound[Level].Lower[Dependence::DVEntry::GT]) DEBUG(dbgs() << *Bound[Level].Lower[Dependence::DVEntry::GT] << '\t'); else DEBUG(dbgs() << "-inf\t"); if (Bound[Level].Upper[Dependence::DVEntry::GT]) DEBUG(dbgs() << *Bound[Level].Upper[Dependence::DVEntry::GT] << '\n'); else DEBUG(dbgs() << "+inf\n"); #endif } unsigned NewDeps = 0; // test bounds for <, *, *, ... if (testBounds(Dependence::DVEntry::LT, Level, Bound, Delta)) NewDeps += exploreDirections(Level + 1, A, B, Bound, Loops, DepthExpanded, Delta); // Test bounds for =, *, *, ... if (testBounds(Dependence::DVEntry::EQ, Level, Bound, Delta)) NewDeps += exploreDirections(Level + 1, A, B, Bound, Loops, DepthExpanded, Delta); // test bounds for >, *, *, ... if (testBounds(Dependence::DVEntry::GT, Level, Bound, Delta)) NewDeps += exploreDirections(Level + 1, A, B, Bound, Loops, DepthExpanded, Delta); Bound[Level].Direction = Dependence::DVEntry::ALL; return NewDeps; } else return exploreDirections(Level + 1, A, B, Bound, Loops, DepthExpanded, Delta); } // Returns true iff the current bounds are plausible. bool DependenceAnalysis::testBounds(unsigned char DirKind, unsigned Level, BoundInfo *Bound, const SCEV *Delta) const { Bound[Level].Direction = DirKind; if (const SCEV *LowerBound = getLowerBound(Bound)) if (isKnownPredicate(CmpInst::ICMP_SGT, LowerBound, Delta)) return false; if (const SCEV *UpperBound = getUpperBound(Bound)) if (isKnownPredicate(CmpInst::ICMP_SGT, Delta, UpperBound)) return false; return true; } // Computes the upper and lower bounds for level K // using the * direction. Records them in Bound. // Wolfe gives the equations // // LB^*_k = (A^-_k - B^+_k)(U_k - L_k) + (A_k - B_k)L_k // UB^*_k = (A^+_k - B^-_k)(U_k - L_k) + (A_k - B_k)L_k // // Since we normalize loops, we can simplify these equations to // // LB^*_k = (A^-_k - B^+_k)U_k // UB^*_k = (A^+_k - B^-_k)U_k // // We must be careful to handle the case where the upper bound is unknown. // Note that the lower bound is always <= 0 // and the upper bound is always >= 0. void DependenceAnalysis::findBoundsALL(CoefficientInfo *A, CoefficientInfo *B, BoundInfo *Bound, unsigned K) const { Bound[K].Lower[Dependence::DVEntry::ALL] = nullptr; // Default value = -infinity. Bound[K].Upper[Dependence::DVEntry::ALL] = nullptr; // Default value = +infinity. if (Bound[K].Iterations) { Bound[K].Lower[Dependence::DVEntry::ALL] = SE->getMulExpr(SE->getMinusSCEV(A[K].NegPart, B[K].PosPart), Bound[K].Iterations); Bound[K].Upper[Dependence::DVEntry::ALL] = SE->getMulExpr(SE->getMinusSCEV(A[K].PosPart, B[K].NegPart), Bound[K].Iterations); } else { // If the difference is 0, we won't need to know the number of iterations. if (isKnownPredicate(CmpInst::ICMP_EQ, A[K].NegPart, B[K].PosPart)) Bound[K].Lower[Dependence::DVEntry::ALL] = SE->getConstant(A[K].Coeff->getType(), 0); if (isKnownPredicate(CmpInst::ICMP_EQ, A[K].PosPart, B[K].NegPart)) Bound[K].Upper[Dependence::DVEntry::ALL] = SE->getConstant(A[K].Coeff->getType(), 0); } } // Computes the upper and lower bounds for level K // using the = direction. Records them in Bound. // Wolfe gives the equations // // LB^=_k = (A_k - B_k)^- (U_k - L_k) + (A_k - B_k)L_k // UB^=_k = (A_k - B_k)^+ (U_k - L_k) + (A_k - B_k)L_k // // Since we normalize loops, we can simplify these equations to // // LB^=_k = (A_k - B_k)^- U_k // UB^=_k = (A_k - B_k)^+ U_k // // We must be careful to handle the case where the upper bound is unknown. // Note that the lower bound is always <= 0 // and the upper bound is always >= 0. void DependenceAnalysis::findBoundsEQ(CoefficientInfo *A, CoefficientInfo *B, BoundInfo *Bound, unsigned K) const { Bound[K].Lower[Dependence::DVEntry::EQ] = nullptr; // Default value = -infinity. Bound[K].Upper[Dependence::DVEntry::EQ] = nullptr; // Default value = +infinity. if (Bound[K].Iterations) { const SCEV *Delta = SE->getMinusSCEV(A[K].Coeff, B[K].Coeff); const SCEV *NegativePart = getNegativePart(Delta); Bound[K].Lower[Dependence::DVEntry::EQ] = SE->getMulExpr(NegativePart, Bound[K].Iterations); const SCEV *PositivePart = getPositivePart(Delta); Bound[K].Upper[Dependence::DVEntry::EQ] = SE->getMulExpr(PositivePart, Bound[K].Iterations); } else { // If the positive/negative part of the difference is 0, // we won't need to know the number of iterations. const SCEV *Delta = SE->getMinusSCEV(A[K].Coeff, B[K].Coeff); const SCEV *NegativePart = getNegativePart(Delta); if (NegativePart->isZero()) Bound[K].Lower[Dependence::DVEntry::EQ] = NegativePart; // Zero const SCEV *PositivePart = getPositivePart(Delta); if (PositivePart->isZero()) Bound[K].Upper[Dependence::DVEntry::EQ] = PositivePart; // Zero } } // Computes the upper and lower bounds for level K // using the < direction. Records them in Bound. // Wolfe gives the equations // // LB^<_k = (A^-_k - B_k)^- (U_k - L_k - N_k) + (A_k - B_k)L_k - B_k N_k // UB^<_k = (A^+_k - B_k)^+ (U_k - L_k - N_k) + (A_k - B_k)L_k - B_k N_k // // Since we normalize loops, we can simplify these equations to // // LB^<_k = (A^-_k - B_k)^- (U_k - 1) - B_k // UB^<_k = (A^+_k - B_k)^+ (U_k - 1) - B_k // // We must be careful to handle the case where the upper bound is unknown. void DependenceAnalysis::findBoundsLT(CoefficientInfo *A, CoefficientInfo *B, BoundInfo *Bound, unsigned K) const { Bound[K].Lower[Dependence::DVEntry::LT] = nullptr; // Default value = -infinity. Bound[K].Upper[Dependence::DVEntry::LT] = nullptr; // Default value = +infinity. if (Bound[K].Iterations) { const SCEV *Iter_1 = SE->getMinusSCEV(Bound[K].Iterations, SE->getConstant(Bound[K].Iterations->getType(), 1)); const SCEV *NegPart = getNegativePart(SE->getMinusSCEV(A[K].NegPart, B[K].Coeff)); Bound[K].Lower[Dependence::DVEntry::LT] = SE->getMinusSCEV(SE->getMulExpr(NegPart, Iter_1), B[K].Coeff); const SCEV *PosPart = getPositivePart(SE->getMinusSCEV(A[K].PosPart, B[K].Coeff)); Bound[K].Upper[Dependence::DVEntry::LT] = SE->getMinusSCEV(SE->getMulExpr(PosPart, Iter_1), B[K].Coeff); } else { // If the positive/negative part of the difference is 0, // we won't need to know the number of iterations. const SCEV *NegPart = getNegativePart(SE->getMinusSCEV(A[K].NegPart, B[K].Coeff)); if (NegPart->isZero()) Bound[K].Lower[Dependence::DVEntry::LT] = SE->getNegativeSCEV(B[K].Coeff); const SCEV *PosPart = getPositivePart(SE->getMinusSCEV(A[K].PosPart, B[K].Coeff)); if (PosPart->isZero()) Bound[K].Upper[Dependence::DVEntry::LT] = SE->getNegativeSCEV(B[K].Coeff); } } // Computes the upper and lower bounds for level K // using the > direction. Records them in Bound. // Wolfe gives the equations // // LB^>_k = (A_k - B^+_k)^- (U_k - L_k - N_k) + (A_k - B_k)L_k + A_k N_k // UB^>_k = (A_k - B^-_k)^+ (U_k - L_k - N_k) + (A_k - B_k)L_k + A_k N_k // // Since we normalize loops, we can simplify these equations to // // LB^>_k = (A_k - B^+_k)^- (U_k - 1) + A_k // UB^>_k = (A_k - B^-_k)^+ (U_k - 1) + A_k // // We must be careful to handle the case where the upper bound is unknown. void DependenceAnalysis::findBoundsGT(CoefficientInfo *A, CoefficientInfo *B, BoundInfo *Bound, unsigned K) const { Bound[K].Lower[Dependence::DVEntry::GT] = nullptr; // Default value = -infinity. Bound[K].Upper[Dependence::DVEntry::GT] = nullptr; // Default value = +infinity. if (Bound[K].Iterations) { const SCEV *Iter_1 = SE->getMinusSCEV(Bound[K].Iterations, SE->getConstant(Bound[K].Iterations->getType(), 1)); const SCEV *NegPart = getNegativePart(SE->getMinusSCEV(A[K].Coeff, B[K].PosPart)); Bound[K].Lower[Dependence::DVEntry::GT] = SE->getAddExpr(SE->getMulExpr(NegPart, Iter_1), A[K].Coeff); const SCEV *PosPart = getPositivePart(SE->getMinusSCEV(A[K].Coeff, B[K].NegPart)); Bound[K].Upper[Dependence::DVEntry::GT] = SE->getAddExpr(SE->getMulExpr(PosPart, Iter_1), A[K].Coeff); } else { // If the positive/negative part of the difference is 0, // we won't need to know the number of iterations. const SCEV *NegPart = getNegativePart(SE->getMinusSCEV(A[K].Coeff, B[K].PosPart)); if (NegPart->isZero()) Bound[K].Lower[Dependence::DVEntry::GT] = A[K].Coeff; const SCEV *PosPart = getPositivePart(SE->getMinusSCEV(A[K].Coeff, B[K].NegPart)); if (PosPart->isZero()) Bound[K].Upper[Dependence::DVEntry::GT] = A[K].Coeff; } } // X^+ = max(X, 0) const SCEV *DependenceAnalysis::getPositivePart(const SCEV *X) const { return SE->getSMaxExpr(X, SE->getConstant(X->getType(), 0)); } // X^- = min(X, 0) const SCEV *DependenceAnalysis::getNegativePart(const SCEV *X) const { return SE->getSMinExpr(X, SE->getConstant(X->getType(), 0)); } // Walks through the subscript, // collecting each coefficient, the associated loop bounds, // and recording its positive and negative parts for later use. DependenceAnalysis::CoefficientInfo * DependenceAnalysis::collectCoeffInfo(const SCEV *Subscript, bool SrcFlag, const SCEV *&Constant) const { const SCEV *Zero = SE->getConstant(Subscript->getType(), 0); CoefficientInfo *CI = new CoefficientInfo[MaxLevels + 1]; for (unsigned K = 1; K <= MaxLevels; ++K) { CI[K].Coeff = Zero; CI[K].PosPart = Zero; CI[K].NegPart = Zero; CI[K].Iterations = nullptr; } while (const SCEVAddRecExpr *AddRec = dyn_cast(Subscript)) { const Loop *L = AddRec->getLoop(); unsigned K = SrcFlag ? mapSrcLoop(L) : mapDstLoop(L); CI[K].Coeff = AddRec->getStepRecurrence(*SE); CI[K].PosPart = getPositivePart(CI[K].Coeff); CI[K].NegPart = getNegativePart(CI[K].Coeff); CI[K].Iterations = collectUpperBound(L, Subscript->getType()); Subscript = AddRec->getStart(); } Constant = Subscript; #ifndef NDEBUG DEBUG(dbgs() << "\tCoefficient Info\n"); for (unsigned K = 1; K <= MaxLevels; ++K) { DEBUG(dbgs() << "\t " << K << "\t" << *CI[K].Coeff); DEBUG(dbgs() << "\tPos Part = "); DEBUG(dbgs() << *CI[K].PosPart); DEBUG(dbgs() << "\tNeg Part = "); DEBUG(dbgs() << *CI[K].NegPart); DEBUG(dbgs() << "\tUpper Bound = "); if (CI[K].Iterations) DEBUG(dbgs() << *CI[K].Iterations); else DEBUG(dbgs() << "+inf"); DEBUG(dbgs() << '\n'); } DEBUG(dbgs() << "\t Constant = " << *Subscript << '\n'); #endif return CI; } // Looks through all the bounds info and // computes the lower bound given the current direction settings // at each level. If the lower bound for any level is -inf, // the result is -inf. const SCEV *DependenceAnalysis::getLowerBound(BoundInfo *Bound) const { const SCEV *Sum = Bound[1].Lower[Bound[1].Direction]; for (unsigned K = 2; Sum && K <= MaxLevels; ++K) { if (Bound[K].Lower[Bound[K].Direction]) Sum = SE->getAddExpr(Sum, Bound[K].Lower[Bound[K].Direction]); else Sum = nullptr; } return Sum; } // Looks through all the bounds info and // computes the upper bound given the current direction settings // at each level. If the upper bound at any level is +inf, // the result is +inf. const SCEV *DependenceAnalysis::getUpperBound(BoundInfo *Bound) const { const SCEV *Sum = Bound[1].Upper[Bound[1].Direction]; for (unsigned K = 2; Sum && K <= MaxLevels; ++K) { if (Bound[K].Upper[Bound[K].Direction]) Sum = SE->getAddExpr(Sum, Bound[K].Upper[Bound[K].Direction]); else Sum = nullptr; } return Sum; } //===----------------------------------------------------------------------===// // Constraint manipulation for Delta test. // Given a linear SCEV, // return the coefficient (the step) // corresponding to the specified loop. // If there isn't one, return 0. // For example, given a*i + b*j + c*k, zeroing the coefficient // corresponding to the j loop would yield b. const SCEV *DependenceAnalysis::findCoefficient(const SCEV *Expr, const Loop *TargetLoop) const { const SCEVAddRecExpr *AddRec = dyn_cast(Expr); if (!AddRec) return SE->getConstant(Expr->getType(), 0); if (AddRec->getLoop() == TargetLoop) return AddRec->getStepRecurrence(*SE); return findCoefficient(AddRec->getStart(), TargetLoop); } // Given a linear SCEV, // return the SCEV given by zeroing out the coefficient // corresponding to the specified loop. // For example, given a*i + b*j + c*k, zeroing the coefficient // corresponding to the j loop would yield a*i + c*k. const SCEV *DependenceAnalysis::zeroCoefficient(const SCEV *Expr, const Loop *TargetLoop) const { const SCEVAddRecExpr *AddRec = dyn_cast(Expr); if (!AddRec) return Expr; // ignore if (AddRec->getLoop() == TargetLoop) return AddRec->getStart(); return SE->getAddRecExpr(zeroCoefficient(AddRec->getStart(), TargetLoop), AddRec->getStepRecurrence(*SE), AddRec->getLoop(), AddRec->getNoWrapFlags()); } // Given a linear SCEV Expr, // return the SCEV given by adding some Value to the // coefficient corresponding to the specified TargetLoop. // For example, given a*i + b*j + c*k, adding 1 to the coefficient // corresponding to the j loop would yield a*i + (b+1)*j + c*k. const SCEV *DependenceAnalysis::addToCoefficient(const SCEV *Expr, const Loop *TargetLoop, const SCEV *Value) const { const SCEVAddRecExpr *AddRec = dyn_cast(Expr); if (!AddRec) // create a new addRec return SE->getAddRecExpr(Expr, Value, TargetLoop, SCEV::FlagAnyWrap); // Worst case, with no info. if (AddRec->getLoop() == TargetLoop) { const SCEV *Sum = SE->getAddExpr(AddRec->getStepRecurrence(*SE), Value); if (Sum->isZero()) return AddRec->getStart(); return SE->getAddRecExpr(AddRec->getStart(), Sum, AddRec->getLoop(), AddRec->getNoWrapFlags()); } if (SE->isLoopInvariant(AddRec, TargetLoop)) return SE->getAddRecExpr(AddRec, Value, TargetLoop, SCEV::FlagAnyWrap); return SE->getAddRecExpr(addToCoefficient(AddRec->getStart(), TargetLoop, Value), AddRec->getStepRecurrence(*SE), AddRec->getLoop(), AddRec->getNoWrapFlags()); } // Review the constraints, looking for opportunities // to simplify a subscript pair (Src and Dst). // Return true if some simplification occurs. // If the simplification isn't exact (that is, if it is conservative // in terms of dependence), set consistent to false. // Corresponds to Figure 5 from the paper // // Practical Dependence Testing // Goff, Kennedy, Tseng // PLDI 1991 bool DependenceAnalysis::propagate(const SCEV *&Src, const SCEV *&Dst, SmallBitVector &Loops, SmallVectorImpl &Constraints, bool &Consistent) { bool Result = false; for (int LI = Loops.find_first(); LI >= 0; LI = Loops.find_next(LI)) { DEBUG(dbgs() << "\t Constraint[" << LI << "] is"); DEBUG(Constraints[LI].dump(dbgs())); if (Constraints[LI].isDistance()) Result |= propagateDistance(Src, Dst, Constraints[LI], Consistent); else if (Constraints[LI].isLine()) Result |= propagateLine(Src, Dst, Constraints[LI], Consistent); else if (Constraints[LI].isPoint()) Result |= propagatePoint(Src, Dst, Constraints[LI]); } return Result; } // Attempt to propagate a distance // constraint into a subscript pair (Src and Dst). // Return true if some simplification occurs. // If the simplification isn't exact (that is, if it is conservative // in terms of dependence), set consistent to false. bool DependenceAnalysis::propagateDistance(const SCEV *&Src, const SCEV *&Dst, Constraint &CurConstraint, bool &Consistent) { const Loop *CurLoop = CurConstraint.getAssociatedLoop(); DEBUG(dbgs() << "\t\tSrc is " << *Src << "\n"); const SCEV *A_K = findCoefficient(Src, CurLoop); if (A_K->isZero()) return false; const SCEV *DA_K = SE->getMulExpr(A_K, CurConstraint.getD()); Src = SE->getMinusSCEV(Src, DA_K); Src = zeroCoefficient(Src, CurLoop); DEBUG(dbgs() << "\t\tnew Src is " << *Src << "\n"); DEBUG(dbgs() << "\t\tDst is " << *Dst << "\n"); Dst = addToCoefficient(Dst, CurLoop, SE->getNegativeSCEV(A_K)); DEBUG(dbgs() << "\t\tnew Dst is " << *Dst << "\n"); if (!findCoefficient(Dst, CurLoop)->isZero()) Consistent = false; return true; } // Attempt to propagate a line // constraint into a subscript pair (Src and Dst). // Return true if some simplification occurs. // If the simplification isn't exact (that is, if it is conservative // in terms of dependence), set consistent to false. bool DependenceAnalysis::propagateLine(const SCEV *&Src, const SCEV *&Dst, Constraint &CurConstraint, bool &Consistent) { const Loop *CurLoop = CurConstraint.getAssociatedLoop(); const SCEV *A = CurConstraint.getA(); const SCEV *B = CurConstraint.getB(); const SCEV *C = CurConstraint.getC(); DEBUG(dbgs() << "\t\tA = " << *A << ", B = " << *B << ", C = " << *C << "\n"); DEBUG(dbgs() << "\t\tSrc = " << *Src << "\n"); DEBUG(dbgs() << "\t\tDst = " << *Dst << "\n"); if (A->isZero()) { const SCEVConstant *Bconst = dyn_cast(B); const SCEVConstant *Cconst = dyn_cast(C); if (!Bconst || !Cconst) return false; APInt Beta = Bconst->getValue()->getValue(); APInt Charlie = Cconst->getValue()->getValue(); APInt CdivB = Charlie.sdiv(Beta); assert(Charlie.srem(Beta) == 0 && "C should be evenly divisible by B"); const SCEV *AP_K = findCoefficient(Dst, CurLoop); // Src = SE->getAddExpr(Src, SE->getMulExpr(AP_K, SE->getConstant(CdivB))); Src = SE->getMinusSCEV(Src, SE->getMulExpr(AP_K, SE->getConstant(CdivB))); Dst = zeroCoefficient(Dst, CurLoop); if (!findCoefficient(Src, CurLoop)->isZero()) Consistent = false; } else if (B->isZero()) { const SCEVConstant *Aconst = dyn_cast(A); const SCEVConstant *Cconst = dyn_cast(C); if (!Aconst || !Cconst) return false; APInt Alpha = Aconst->getValue()->getValue(); APInt Charlie = Cconst->getValue()->getValue(); APInt CdivA = Charlie.sdiv(Alpha); assert(Charlie.srem(Alpha) == 0 && "C should be evenly divisible by A"); const SCEV *A_K = findCoefficient(Src, CurLoop); Src = SE->getAddExpr(Src, SE->getMulExpr(A_K, SE->getConstant(CdivA))); Src = zeroCoefficient(Src, CurLoop); if (!findCoefficient(Dst, CurLoop)->isZero()) Consistent = false; } else if (isKnownPredicate(CmpInst::ICMP_EQ, A, B)) { const SCEVConstant *Aconst = dyn_cast(A); const SCEVConstant *Cconst = dyn_cast(C); if (!Aconst || !Cconst) return false; APInt Alpha = Aconst->getValue()->getValue(); APInt Charlie = Cconst->getValue()->getValue(); APInt CdivA = Charlie.sdiv(Alpha); assert(Charlie.srem(Alpha) == 0 && "C should be evenly divisible by A"); const SCEV *A_K = findCoefficient(Src, CurLoop); Src = SE->getAddExpr(Src, SE->getMulExpr(A_K, SE->getConstant(CdivA))); Src = zeroCoefficient(Src, CurLoop); Dst = addToCoefficient(Dst, CurLoop, A_K); if (!findCoefficient(Dst, CurLoop)->isZero()) Consistent = false; } else { // paper is incorrect here, or perhaps just misleading const SCEV *A_K = findCoefficient(Src, CurLoop); Src = SE->getMulExpr(Src, A); Dst = SE->getMulExpr(Dst, A); Src = SE->getAddExpr(Src, SE->getMulExpr(A_K, C)); Src = zeroCoefficient(Src, CurLoop); Dst = addToCoefficient(Dst, CurLoop, SE->getMulExpr(A_K, B)); if (!findCoefficient(Dst, CurLoop)->isZero()) Consistent = false; } DEBUG(dbgs() << "\t\tnew Src = " << *Src << "\n"); DEBUG(dbgs() << "\t\tnew Dst = " << *Dst << "\n"); return true; } // Attempt to propagate a point // constraint into a subscript pair (Src and Dst). // Return true if some simplification occurs. bool DependenceAnalysis::propagatePoint(const SCEV *&Src, const SCEV *&Dst, Constraint &CurConstraint) { const Loop *CurLoop = CurConstraint.getAssociatedLoop(); const SCEV *A_K = findCoefficient(Src, CurLoop); const SCEV *AP_K = findCoefficient(Dst, CurLoop); const SCEV *XA_K = SE->getMulExpr(A_K, CurConstraint.getX()); const SCEV *YAP_K = SE->getMulExpr(AP_K, CurConstraint.getY()); DEBUG(dbgs() << "\t\tSrc is " << *Src << "\n"); Src = SE->getAddExpr(Src, SE->getMinusSCEV(XA_K, YAP_K)); Src = zeroCoefficient(Src, CurLoop); DEBUG(dbgs() << "\t\tnew Src is " << *Src << "\n"); DEBUG(dbgs() << "\t\tDst is " << *Dst << "\n"); Dst = zeroCoefficient(Dst, CurLoop); DEBUG(dbgs() << "\t\tnew Dst is " << *Dst << "\n"); return true; } // Update direction vector entry based on the current constraint. void DependenceAnalysis::updateDirection(Dependence::DVEntry &Level, const Constraint &CurConstraint ) const { DEBUG(dbgs() << "\tUpdate direction, constraint ="); DEBUG(CurConstraint.dump(dbgs())); if (CurConstraint.isAny()) ; // use defaults else if (CurConstraint.isDistance()) { // this one is consistent, the others aren't Level.Scalar = false; Level.Distance = CurConstraint.getD(); unsigned NewDirection = Dependence::DVEntry::NONE; if (!SE->isKnownNonZero(Level.Distance)) // if may be zero NewDirection = Dependence::DVEntry::EQ; if (!SE->isKnownNonPositive(Level.Distance)) // if may be positive NewDirection |= Dependence::DVEntry::LT; if (!SE->isKnownNonNegative(Level.Distance)) // if may be negative NewDirection |= Dependence::DVEntry::GT; Level.Direction &= NewDirection; } else if (CurConstraint.isLine()) { Level.Scalar = false; Level.Distance = nullptr; // direction should be accurate } else if (CurConstraint.isPoint()) { Level.Scalar = false; Level.Distance = nullptr; unsigned NewDirection = Dependence::DVEntry::NONE; if (!isKnownPredicate(CmpInst::ICMP_NE, CurConstraint.getY(), CurConstraint.getX())) // if X may be = Y NewDirection |= Dependence::DVEntry::EQ; if (!isKnownPredicate(CmpInst::ICMP_SLE, CurConstraint.getY(), CurConstraint.getX())) // if Y may be > X NewDirection |= Dependence::DVEntry::LT; if (!isKnownPredicate(CmpInst::ICMP_SGE, CurConstraint.getY(), CurConstraint.getX())) // if Y may be < X NewDirection |= Dependence::DVEntry::GT; Level.Direction &= NewDirection; } else llvm_unreachable("constraint has unexpected kind"); } /// Check if we can delinearize the subscripts. If the SCEVs representing the /// source and destination array references are recurrences on a nested loop, /// this function flattens the nested recurrences into separate recurrences /// for each loop level. bool DependenceAnalysis::tryDelinearize(const SCEV *SrcSCEV, const SCEV *DstSCEV, SmallVectorImpl &Pair, const SCEV *ElementSize) const { const SCEVUnknown *SrcBase = dyn_cast(SE->getPointerBase(SrcSCEV)); const SCEVUnknown *DstBase = dyn_cast(SE->getPointerBase(DstSCEV)); if (!SrcBase || !DstBase || SrcBase != DstBase) return false; SrcSCEV = SE->getMinusSCEV(SrcSCEV, SrcBase); DstSCEV = SE->getMinusSCEV(DstSCEV, DstBase); const SCEVAddRecExpr *SrcAR = dyn_cast(SrcSCEV); const SCEVAddRecExpr *DstAR = dyn_cast(DstSCEV); if (!SrcAR || !DstAR || !SrcAR->isAffine() || !DstAR->isAffine()) return false; // First step: collect parametric terms in both array references. SmallVector Terms; SrcAR->collectParametricTerms(*SE, Terms); DstAR->collectParametricTerms(*SE, Terms); // Second step: find subscript sizes. SmallVector Sizes; SE->findArrayDimensions(Terms, Sizes, ElementSize); // Third step: compute the access functions for each subscript. SmallVector SrcSubscripts, DstSubscripts; SrcAR->computeAccessFunctions(*SE, SrcSubscripts, Sizes); DstAR->computeAccessFunctions(*SE, DstSubscripts, Sizes); // Fail when there is only a subscript: that's a linearized access function. if (SrcSubscripts.size() < 2 || DstSubscripts.size() < 2 || SrcSubscripts.size() != DstSubscripts.size()) return false; int size = SrcSubscripts.size(); DEBUG({ dbgs() << "\nSrcSubscripts: "; for (int i = 0; i < size; i++) dbgs() << *SrcSubscripts[i]; dbgs() << "\nDstSubscripts: "; for (int i = 0; i < size; i++) dbgs() << *DstSubscripts[i]; }); // The delinearization transforms a single-subscript MIV dependence test into // a multi-subscript SIV dependence test that is easier to compute. So we // resize Pair to contain as many pairs of subscripts as the delinearization // has found, and then initialize the pairs following the delinearization. Pair.resize(size); for (int i = 0; i < size; ++i) { Pair[i].Src = SrcSubscripts[i]; Pair[i].Dst = DstSubscripts[i]; // FIXME: we should record the bounds SrcSizes[i] and DstSizes[i] that the // delinearization has found, and add these constraints to the dependence // check to avoid memory accesses overflow from one dimension into another. // This is related to the problem of determining the existence of data // dependences in array accesses using a different number of subscripts: in // C one can access an array A[100][100]; as A[0][9999], *A[9999], etc. } return true; } //===----------------------------------------------------------------------===// #ifndef NDEBUG // For debugging purposes, dump a small bit vector to dbgs(). static void dumpSmallBitVector(SmallBitVector &BV) { dbgs() << "{"; for (int VI = BV.find_first(); VI >= 0; VI = BV.find_next(VI)) { dbgs() << VI; if (BV.find_next(VI) >= 0) dbgs() << ' '; } dbgs() << "}\n"; } #endif // depends - // Returns NULL if there is no dependence. // Otherwise, return a Dependence with as many details as possible. // Corresponds to Section 3.1 in the paper // // Practical Dependence Testing // Goff, Kennedy, Tseng // PLDI 1991 // // Care is required to keep the routine below, getSplitIteration(), // up to date with respect to this routine. Dependence *DependenceAnalysis::depends(Instruction *Src, Instruction *Dst, bool PossiblyLoopIndependent) { if (Src == Dst) PossiblyLoopIndependent = false; if ((!Src->mayReadFromMemory() && !Src->mayWriteToMemory()) || (!Dst->mayReadFromMemory() && !Dst->mayWriteToMemory())) // if both instructions don't reference memory, there's no dependence return nullptr; if (!isLoadOrStore(Src) || !isLoadOrStore(Dst)) { // can only analyze simple loads and stores, i.e., no calls, invokes, etc. DEBUG(dbgs() << "can only handle simple loads and stores\n"); return new Dependence(Src, Dst); } Value *SrcPtr = getPointerOperand(Src); Value *DstPtr = getPointerOperand(Dst); switch (underlyingObjectsAlias(AA, DstPtr, SrcPtr)) { case AliasAnalysis::MayAlias: case AliasAnalysis::PartialAlias: // cannot analyse objects if we don't understand their aliasing. DEBUG(dbgs() << "can't analyze may or partial alias\n"); return new Dependence(Src, Dst); case AliasAnalysis::NoAlias: // If the objects noalias, they are distinct, accesses are independent. DEBUG(dbgs() << "no alias\n"); return nullptr; case AliasAnalysis::MustAlias: break; // The underlying objects alias; test accesses for dependence. } // establish loop nesting levels establishNestingLevels(Src, Dst); DEBUG(dbgs() << " common nesting levels = " << CommonLevels << "\n"); DEBUG(dbgs() << " maximum nesting levels = " << MaxLevels << "\n"); FullDependence Result(Src, Dst, PossiblyLoopIndependent, CommonLevels); ++TotalArrayPairs; // See if there are GEPs we can use. bool UsefulGEP = false; GEPOperator *SrcGEP = dyn_cast(SrcPtr); GEPOperator *DstGEP = dyn_cast(DstPtr); if (SrcGEP && DstGEP && SrcGEP->getPointerOperandType() == DstGEP->getPointerOperandType()) { const SCEV *SrcPtrSCEV = SE->getSCEV(SrcGEP->getPointerOperand()); const SCEV *DstPtrSCEV = SE->getSCEV(DstGEP->getPointerOperand()); DEBUG(dbgs() << " SrcPtrSCEV = " << *SrcPtrSCEV << "\n"); DEBUG(dbgs() << " DstPtrSCEV = " << *DstPtrSCEV << "\n"); UsefulGEP = isLoopInvariant(SrcPtrSCEV, LI->getLoopFor(Src->getParent())) && isLoopInvariant(DstPtrSCEV, LI->getLoopFor(Dst->getParent())); } unsigned Pairs = UsefulGEP ? SrcGEP->idx_end() - SrcGEP->idx_begin() : 1; SmallVector Pair(Pairs); if (UsefulGEP) { DEBUG(dbgs() << " using GEPs\n"); unsigned P = 0; for (GEPOperator::const_op_iterator SrcIdx = SrcGEP->idx_begin(), SrcEnd = SrcGEP->idx_end(), DstIdx = DstGEP->idx_begin(); SrcIdx != SrcEnd; ++SrcIdx, ++DstIdx, ++P) { Pair[P].Src = SE->getSCEV(*SrcIdx); Pair[P].Dst = SE->getSCEV(*DstIdx); } } else { DEBUG(dbgs() << " ignoring GEPs\n"); const SCEV *SrcSCEV = SE->getSCEV(SrcPtr); const SCEV *DstSCEV = SE->getSCEV(DstPtr); DEBUG(dbgs() << " SrcSCEV = " << *SrcSCEV << "\n"); DEBUG(dbgs() << " DstSCEV = " << *DstSCEV << "\n"); Pair[0].Src = SrcSCEV; Pair[0].Dst = DstSCEV; } if (Delinearize && Pairs == 1 && CommonLevels > 1 && tryDelinearize(Pair[0].Src, Pair[0].Dst, Pair, SE->getElementSize(Src))) { DEBUG(dbgs() << " delinerized GEP\n"); Pairs = Pair.size(); } for (unsigned P = 0; P < Pairs; ++P) { Pair[P].Loops.resize(MaxLevels + 1); Pair[P].GroupLoops.resize(MaxLevels + 1); Pair[P].Group.resize(Pairs); removeMatchingExtensions(&Pair[P]); Pair[P].Classification = classifyPair(Pair[P].Src, LI->getLoopFor(Src->getParent()), Pair[P].Dst, LI->getLoopFor(Dst->getParent()), Pair[P].Loops); Pair[P].GroupLoops = Pair[P].Loops; Pair[P].Group.set(P); DEBUG(dbgs() << " subscript " << P << "\n"); DEBUG(dbgs() << "\tsrc = " << *Pair[P].Src << "\n"); DEBUG(dbgs() << "\tdst = " << *Pair[P].Dst << "\n"); DEBUG(dbgs() << "\tclass = " << Pair[P].Classification << "\n"); DEBUG(dbgs() << "\tloops = "); DEBUG(dumpSmallBitVector(Pair[P].Loops)); } SmallBitVector Separable(Pairs); SmallBitVector Coupled(Pairs); // Partition subscripts into separable and minimally-coupled groups // Algorithm in paper is algorithmically better; // this may be faster in practice. Check someday. // // Here's an example of how it works. Consider this code: // // for (i = ...) { // for (j = ...) { // for (k = ...) { // for (l = ...) { // for (m = ...) { // A[i][j][k][m] = ...; // ... = A[0][j][l][i + j]; // } // } // } // } // } // // There are 4 subscripts here: // 0 [i] and [0] // 1 [j] and [j] // 2 [k] and [l] // 3 [m] and [i + j] // // We've already classified each subscript pair as ZIV, SIV, etc., // and collected all the loops mentioned by pair P in Pair[P].Loops. // In addition, we've initialized Pair[P].GroupLoops to Pair[P].Loops // and set Pair[P].Group = {P}. // // Src Dst Classification Loops GroupLoops Group // 0 [i] [0] SIV {1} {1} {0} // 1 [j] [j] SIV {2} {2} {1} // 2 [k] [l] RDIV {3,4} {3,4} {2} // 3 [m] [i + j] MIV {1,2,5} {1,2,5} {3} // // For each subscript SI 0 .. 3, we consider each remaining subscript, SJ. // So, 0 is compared against 1, 2, and 3; 1 is compared against 2 and 3, etc. // // We begin by comparing 0 and 1. The intersection of the GroupLoops is empty. // Next, 0 and 2. Again, the intersection of their GroupLoops is empty. // Next 0 and 3. The intersection of their GroupLoop = {1}, not empty, // so Pair[3].Group = {0,3} and Done = false (that is, 0 will not be added // to either Separable or Coupled). // // Next, we consider 1 and 2. The intersection of the GroupLoops is empty. // Next, 1 and 3. The intersectionof their GroupLoops = {2}, not empty, // so Pair[3].Group = {0, 1, 3} and Done = false. // // Next, we compare 2 against 3. The intersection of the GroupLoops is empty. // Since Done remains true, we add 2 to the set of Separable pairs. // // Finally, we consider 3. There's nothing to compare it with, // so Done remains true and we add it to the Coupled set. // Pair[3].Group = {0, 1, 3} and GroupLoops = {1, 2, 5}. // // In the end, we've got 1 separable subscript and 1 coupled group. for (unsigned SI = 0; SI < Pairs; ++SI) { if (Pair[SI].Classification == Subscript::NonLinear) { // ignore these, but collect loops for later ++NonlinearSubscriptPairs; collectCommonLoops(Pair[SI].Src, LI->getLoopFor(Src->getParent()), Pair[SI].Loops); collectCommonLoops(Pair[SI].Dst, LI->getLoopFor(Dst->getParent()), Pair[SI].Loops); Result.Consistent = false; } else if (Pair[SI].Classification == Subscript::ZIV) { // always separable Separable.set(SI); } else { // SIV, RDIV, or MIV, so check for coupled group bool Done = true; for (unsigned SJ = SI + 1; SJ < Pairs; ++SJ) { SmallBitVector Intersection = Pair[SI].GroupLoops; Intersection &= Pair[SJ].GroupLoops; if (Intersection.any()) { // accumulate set of all the loops in group Pair[SJ].GroupLoops |= Pair[SI].GroupLoops; // accumulate set of all subscripts in group Pair[SJ].Group |= Pair[SI].Group; Done = false; } } if (Done) { if (Pair[SI].Group.count() == 1) { Separable.set(SI); ++SeparableSubscriptPairs; } else { Coupled.set(SI); ++CoupledSubscriptPairs; } } } } DEBUG(dbgs() << " Separable = "); DEBUG(dumpSmallBitVector(Separable)); DEBUG(dbgs() << " Coupled = "); DEBUG(dumpSmallBitVector(Coupled)); Constraint NewConstraint; NewConstraint.setAny(SE); // test separable subscripts for (int SI = Separable.find_first(); SI >= 0; SI = Separable.find_next(SI)) { DEBUG(dbgs() << "testing subscript " << SI); switch (Pair[SI].Classification) { case Subscript::ZIV: DEBUG(dbgs() << ", ZIV\n"); if (testZIV(Pair[SI].Src, Pair[SI].Dst, Result)) return nullptr; break; case Subscript::SIV: { DEBUG(dbgs() << ", SIV\n"); unsigned Level; const SCEV *SplitIter = nullptr; if (testSIV(Pair[SI].Src, Pair[SI].Dst, Level, Result, NewConstraint, SplitIter)) return nullptr; break; } case Subscript::RDIV: DEBUG(dbgs() << ", RDIV\n"); if (testRDIV(Pair[SI].Src, Pair[SI].Dst, Result)) return nullptr; break; case Subscript::MIV: DEBUG(dbgs() << ", MIV\n"); if (testMIV(Pair[SI].Src, Pair[SI].Dst, Pair[SI].Loops, Result)) return nullptr; break; default: llvm_unreachable("subscript has unexpected classification"); } } if (Coupled.count()) { // test coupled subscript groups DEBUG(dbgs() << "starting on coupled subscripts\n"); DEBUG(dbgs() << "MaxLevels + 1 = " << MaxLevels + 1 << "\n"); SmallVector Constraints(MaxLevels + 1); for (unsigned II = 0; II <= MaxLevels; ++II) Constraints[II].setAny(SE); for (int SI = Coupled.find_first(); SI >= 0; SI = Coupled.find_next(SI)) { DEBUG(dbgs() << "testing subscript group " << SI << " { "); SmallBitVector Group(Pair[SI].Group); SmallBitVector Sivs(Pairs); SmallBitVector Mivs(Pairs); SmallBitVector ConstrainedLevels(MaxLevels + 1); for (int SJ = Group.find_first(); SJ >= 0; SJ = Group.find_next(SJ)) { DEBUG(dbgs() << SJ << " "); if (Pair[SJ].Classification == Subscript::SIV) Sivs.set(SJ); else Mivs.set(SJ); } DEBUG(dbgs() << "}\n"); while (Sivs.any()) { bool Changed = false; for (int SJ = Sivs.find_first(); SJ >= 0; SJ = Sivs.find_next(SJ)) { DEBUG(dbgs() << "testing subscript " << SJ << ", SIV\n"); // SJ is an SIV subscript that's part of the current coupled group unsigned Level; const SCEV *SplitIter = nullptr; DEBUG(dbgs() << "SIV\n"); if (testSIV(Pair[SJ].Src, Pair[SJ].Dst, Level, Result, NewConstraint, SplitIter)) return nullptr; ConstrainedLevels.set(Level); if (intersectConstraints(&Constraints[Level], &NewConstraint)) { if (Constraints[Level].isEmpty()) { ++DeltaIndependence; return nullptr; } Changed = true; } Sivs.reset(SJ); } if (Changed) { // propagate, possibly creating new SIVs and ZIVs DEBUG(dbgs() << " propagating\n"); DEBUG(dbgs() << "\tMivs = "); DEBUG(dumpSmallBitVector(Mivs)); for (int SJ = Mivs.find_first(); SJ >= 0; SJ = Mivs.find_next(SJ)) { // SJ is an MIV subscript that's part of the current coupled group DEBUG(dbgs() << "\tSJ = " << SJ << "\n"); if (propagate(Pair[SJ].Src, Pair[SJ].Dst, Pair[SJ].Loops, Constraints, Result.Consistent)) { DEBUG(dbgs() << "\t Changed\n"); ++DeltaPropagations; Pair[SJ].Classification = classifyPair(Pair[SJ].Src, LI->getLoopFor(Src->getParent()), Pair[SJ].Dst, LI->getLoopFor(Dst->getParent()), Pair[SJ].Loops); switch (Pair[SJ].Classification) { case Subscript::ZIV: DEBUG(dbgs() << "ZIV\n"); if (testZIV(Pair[SJ].Src, Pair[SJ].Dst, Result)) return nullptr; Mivs.reset(SJ); break; case Subscript::SIV: Sivs.set(SJ); Mivs.reset(SJ); break; case Subscript::RDIV: case Subscript::MIV: break; default: llvm_unreachable("bad subscript classification"); } } } } } // test & propagate remaining RDIVs for (int SJ = Mivs.find_first(); SJ >= 0; SJ = Mivs.find_next(SJ)) { if (Pair[SJ].Classification == Subscript::RDIV) { DEBUG(dbgs() << "RDIV test\n"); if (testRDIV(Pair[SJ].Src, Pair[SJ].Dst, Result)) return nullptr; // I don't yet understand how to propagate RDIV results Mivs.reset(SJ); } } // test remaining MIVs // This code is temporary. // Better to somehow test all remaining subscripts simultaneously. for (int SJ = Mivs.find_first(); SJ >= 0; SJ = Mivs.find_next(SJ)) { if (Pair[SJ].Classification == Subscript::MIV) { DEBUG(dbgs() << "MIV test\n"); if (testMIV(Pair[SJ].Src, Pair[SJ].Dst, Pair[SJ].Loops, Result)) return nullptr; } else llvm_unreachable("expected only MIV subscripts at this point"); } // update Result.DV from constraint vector DEBUG(dbgs() << " updating\n"); for (int SJ = ConstrainedLevels.find_first(); SJ >= 0; SJ = ConstrainedLevels.find_next(SJ)) { updateDirection(Result.DV[SJ - 1], Constraints[SJ]); if (Result.DV[SJ - 1].Direction == Dependence::DVEntry::NONE) return nullptr; } } } // Make sure the Scalar flags are set correctly. SmallBitVector CompleteLoops(MaxLevels + 1); for (unsigned SI = 0; SI < Pairs; ++SI) CompleteLoops |= Pair[SI].Loops; for (unsigned II = 1; II <= CommonLevels; ++II) if (CompleteLoops[II]) Result.DV[II - 1].Scalar = false; if (PossiblyLoopIndependent) { // Make sure the LoopIndependent flag is set correctly. // All directions must include equal, otherwise no // loop-independent dependence is possible. for (unsigned II = 1; II <= CommonLevels; ++II) { if (!(Result.getDirection(II) & Dependence::DVEntry::EQ)) { Result.LoopIndependent = false; break; } } } else { // On the other hand, if all directions are equal and there's no // loop-independent dependence possible, then no dependence exists. bool AllEqual = true; for (unsigned II = 1; II <= CommonLevels; ++II) { if (Result.getDirection(II) != Dependence::DVEntry::EQ) { AllEqual = false; break; } } if (AllEqual) return nullptr; } FullDependence *Final = new FullDependence(Result); Result.DV = nullptr; return Final; } //===----------------------------------------------------------------------===// // getSplitIteration - // Rather than spend rarely-used space recording the splitting iteration // during the Weak-Crossing SIV test, we re-compute it on demand. // The re-computation is basically a repeat of the entire dependence test, // though simplified since we know that the dependence exists. // It's tedious, since we must go through all propagations, etc. // // Care is required to keep this code up to date with respect to the routine // above, depends(). // // Generally, the dependence analyzer will be used to build // a dependence graph for a function (basically a map from instructions // to dependences). Looking for cycles in the graph shows us loops // that cannot be trivially vectorized/parallelized. // // We can try to improve the situation by examining all the dependences // that make up the cycle, looking for ones we can break. // Sometimes, peeling the first or last iteration of a loop will break // dependences, and we've got flags for those possibilities. // Sometimes, splitting a loop at some other iteration will do the trick, // and we've got a flag for that case. Rather than waste the space to // record the exact iteration (since we rarely know), we provide // a method that calculates the iteration. It's a drag that it must work // from scratch, but wonderful in that it's possible. // // Here's an example: // // for (i = 0; i < 10; i++) // A[i] = ... // ... = A[11 - i] // // There's a loop-carried flow dependence from the store to the load, // found by the weak-crossing SIV test. The dependence will have a flag, // indicating that the dependence can be broken by splitting the loop. // Calling getSplitIteration will return 5. // Splitting the loop breaks the dependence, like so: // // for (i = 0; i <= 5; i++) // A[i] = ... // ... = A[11 - i] // for (i = 6; i < 10; i++) // A[i] = ... // ... = A[11 - i] // // breaks the dependence and allows us to vectorize/parallelize // both loops. const SCEV *DependenceAnalysis::getSplitIteration(const Dependence *Dep, unsigned SplitLevel) { assert(Dep && "expected a pointer to a Dependence"); assert(Dep->isSplitable(SplitLevel) && "Dep should be splitable at SplitLevel"); Instruction *Src = Dep->getSrc(); Instruction *Dst = Dep->getDst(); assert(Src->mayReadFromMemory() || Src->mayWriteToMemory()); assert(Dst->mayReadFromMemory() || Dst->mayWriteToMemory()); assert(isLoadOrStore(Src)); assert(isLoadOrStore(Dst)); Value *SrcPtr = getPointerOperand(Src); Value *DstPtr = getPointerOperand(Dst); assert(underlyingObjectsAlias(AA, DstPtr, SrcPtr) == AliasAnalysis::MustAlias); // establish loop nesting levels establishNestingLevels(Src, Dst); FullDependence Result(Src, Dst, false, CommonLevels); // See if there are GEPs we can use. bool UsefulGEP = false; GEPOperator *SrcGEP = dyn_cast(SrcPtr); GEPOperator *DstGEP = dyn_cast(DstPtr); if (SrcGEP && DstGEP && SrcGEP->getPointerOperandType() == DstGEP->getPointerOperandType()) { const SCEV *SrcPtrSCEV = SE->getSCEV(SrcGEP->getPointerOperand()); const SCEV *DstPtrSCEV = SE->getSCEV(DstGEP->getPointerOperand()); UsefulGEP = isLoopInvariant(SrcPtrSCEV, LI->getLoopFor(Src->getParent())) && isLoopInvariant(DstPtrSCEV, LI->getLoopFor(Dst->getParent())); } unsigned Pairs = UsefulGEP ? SrcGEP->idx_end() - SrcGEP->idx_begin() : 1; SmallVector Pair(Pairs); if (UsefulGEP) { unsigned P = 0; for (GEPOperator::const_op_iterator SrcIdx = SrcGEP->idx_begin(), SrcEnd = SrcGEP->idx_end(), DstIdx = DstGEP->idx_begin(); SrcIdx != SrcEnd; ++SrcIdx, ++DstIdx, ++P) { Pair[P].Src = SE->getSCEV(*SrcIdx); Pair[P].Dst = SE->getSCEV(*DstIdx); } } else { const SCEV *SrcSCEV = SE->getSCEV(SrcPtr); const SCEV *DstSCEV = SE->getSCEV(DstPtr); Pair[0].Src = SrcSCEV; Pair[0].Dst = DstSCEV; } if (Delinearize && Pairs == 1 && CommonLevels > 1 && tryDelinearize(Pair[0].Src, Pair[0].Dst, Pair, SE->getElementSize(Src))) { DEBUG(dbgs() << " delinerized GEP\n"); Pairs = Pair.size(); } for (unsigned P = 0; P < Pairs; ++P) { Pair[P].Loops.resize(MaxLevels + 1); Pair[P].GroupLoops.resize(MaxLevels + 1); Pair[P].Group.resize(Pairs); removeMatchingExtensions(&Pair[P]); Pair[P].Classification = classifyPair(Pair[P].Src, LI->getLoopFor(Src->getParent()), Pair[P].Dst, LI->getLoopFor(Dst->getParent()), Pair[P].Loops); Pair[P].GroupLoops = Pair[P].Loops; Pair[P].Group.set(P); } SmallBitVector Separable(Pairs); SmallBitVector Coupled(Pairs); // partition subscripts into separable and minimally-coupled groups for (unsigned SI = 0; SI < Pairs; ++SI) { if (Pair[SI].Classification == Subscript::NonLinear) { // ignore these, but collect loops for later collectCommonLoops(Pair[SI].Src, LI->getLoopFor(Src->getParent()), Pair[SI].Loops); collectCommonLoops(Pair[SI].Dst, LI->getLoopFor(Dst->getParent()), Pair[SI].Loops); Result.Consistent = false; } else if (Pair[SI].Classification == Subscript::ZIV) Separable.set(SI); else { // SIV, RDIV, or MIV, so check for coupled group bool Done = true; for (unsigned SJ = SI + 1; SJ < Pairs; ++SJ) { SmallBitVector Intersection = Pair[SI].GroupLoops; Intersection &= Pair[SJ].GroupLoops; if (Intersection.any()) { // accumulate set of all the loops in group Pair[SJ].GroupLoops |= Pair[SI].GroupLoops; // accumulate set of all subscripts in group Pair[SJ].Group |= Pair[SI].Group; Done = false; } } if (Done) { if (Pair[SI].Group.count() == 1) Separable.set(SI); else Coupled.set(SI); } } } Constraint NewConstraint; NewConstraint.setAny(SE); // test separable subscripts for (int SI = Separable.find_first(); SI >= 0; SI = Separable.find_next(SI)) { switch (Pair[SI].Classification) { case Subscript::SIV: { unsigned Level; const SCEV *SplitIter = nullptr; (void) testSIV(Pair[SI].Src, Pair[SI].Dst, Level, Result, NewConstraint, SplitIter); if (Level == SplitLevel) { assert(SplitIter != nullptr); return SplitIter; } break; } case Subscript::ZIV: case Subscript::RDIV: case Subscript::MIV: break; default: llvm_unreachable("subscript has unexpected classification"); } } if (Coupled.count()) { // test coupled subscript groups SmallVector Constraints(MaxLevels + 1); for (unsigned II = 0; II <= MaxLevels; ++II) Constraints[II].setAny(SE); for (int SI = Coupled.find_first(); SI >= 0; SI = Coupled.find_next(SI)) { SmallBitVector Group(Pair[SI].Group); SmallBitVector Sivs(Pairs); SmallBitVector Mivs(Pairs); SmallBitVector ConstrainedLevels(MaxLevels + 1); for (int SJ = Group.find_first(); SJ >= 0; SJ = Group.find_next(SJ)) { if (Pair[SJ].Classification == Subscript::SIV) Sivs.set(SJ); else Mivs.set(SJ); } while (Sivs.any()) { bool Changed = false; for (int SJ = Sivs.find_first(); SJ >= 0; SJ = Sivs.find_next(SJ)) { // SJ is an SIV subscript that's part of the current coupled group unsigned Level; const SCEV *SplitIter = nullptr; (void) testSIV(Pair[SJ].Src, Pair[SJ].Dst, Level, Result, NewConstraint, SplitIter); if (Level == SplitLevel && SplitIter) return SplitIter; ConstrainedLevels.set(Level); if (intersectConstraints(&Constraints[Level], &NewConstraint)) Changed = true; Sivs.reset(SJ); } if (Changed) { // propagate, possibly creating new SIVs and ZIVs for (int SJ = Mivs.find_first(); SJ >= 0; SJ = Mivs.find_next(SJ)) { // SJ is an MIV subscript that's part of the current coupled group if (propagate(Pair[SJ].Src, Pair[SJ].Dst, Pair[SJ].Loops, Constraints, Result.Consistent)) { Pair[SJ].Classification = classifyPair(Pair[SJ].Src, LI->getLoopFor(Src->getParent()), Pair[SJ].Dst, LI->getLoopFor(Dst->getParent()), Pair[SJ].Loops); switch (Pair[SJ].Classification) { case Subscript::ZIV: Mivs.reset(SJ); break; case Subscript::SIV: Sivs.set(SJ); Mivs.reset(SJ); break; case Subscript::RDIV: case Subscript::MIV: break; default: llvm_unreachable("bad subscript classification"); } } } } } } } llvm_unreachable("somehow reached end of routine"); return nullptr; }