[llvm] r237156 - Reimplement heuristic for estimating complete-unroll optimization effects.

Michael Zolotukhin mzolotukhin at apple.com
Wed May 20 23:20:30 PDT 2015


> On May 20, 2015, at 10:38 PM, Chandler Carruth <chandlerc at google.com> wrote:
> 
> If they cover the same different use cases, most notably the *specific* reason for using a percentage based threshold, that's what I was looking for.
Hi Chandler,

It is basically a single test, but it’s invoked with 4 different sets of thresholds:
1) Check that we unroll smallest loops (size < unroll-threshold) independently on the new heuristics - it’s basically a loop that we’d unroll even without the heuristic.
2) Check that we don’t unroll huge loops (size > absolute-unroll-threshold).
3) Check that we unroll mid-sized loops (unroll-threshold < size < absolute-unroll-threshold) for which we predict a certain part of instructions to be removed (percentage of predicted-to-be-removed instructions > min-percent-to-unroll).
4) Check that we don’t unroll mid-sized loops (unroll-threshold < size < absolute-unroll-threshold) for which we predict less than a certain part of instructions to be removed (percentage of predicted-to-be-removed instructions < min-percent-to-unroll).

Is it what you were looking for?

Thanks,
Michael

> 
> On Thu, May 14, 2015 at 5:16 PM Michael Zolotukhin <mzolotukhin at apple.com <mailto:mzolotukhin at apple.com>> wrote:
> Hi Chandler,
> 
> We agreed that I’ll follow-up on this with adding examples from our discussion as tests. However, the original tests (test/Transforms/LoopUnroll/full-unroll-heuristics.ll) are essentially covering the same cases. Did you mean some other tests, or these are sufficient?
> 
> Thanks,
> Michael
> 
> > On May 12, 2015, at 10:20 AM, Michael Zolotukhin <mzolotukhin at apple.com <mailto:mzolotukhin at apple.com>> wrote:
> >
> > Author: mzolotukhin
> > Date: Tue May 12 12:20:03 2015
> > New Revision: 237156
> >
> > URL: http://llvm.org/viewvc/llvm-project?rev=237156&view=rev <http://llvm.org/viewvc/llvm-project?rev=237156&view=rev>
> > Log:
> > Reimplement heuristic for estimating complete-unroll optimization effects.
> >
> > Summary:
> > This patch reimplements heuristic that tries to estimate optimization beneftis
> > from complete loop unrolling.
> >
> > In this patch I kept the minimal changes - e.g. I removed code handling
> > branches and folding compares. That's a promising area, but now there
> > are too many questions to discuss before we can enable it.
> >
> > Test Plan: Tests are included in the patch.
> >
> > Reviewers: hfinkel, chandlerc
> >
> > Subscribers: llvm-commits
> >
> > Differential Revision: http://reviews.llvm.org/D8816 <http://reviews.llvm.org/D8816>
> >
> > Added:
> >    llvm/trunk/test/Transforms/LoopUnroll/full-unroll-bad-geps.ll
> > Modified:
> >    llvm/trunk/lib/Transforms/Scalar/LoopUnrollPass.cpp
> >    llvm/trunk/test/Transforms/LoopUnroll/full-unroll-heuristics.ll
> >
> > Modified: llvm/trunk/lib/Transforms/Scalar/LoopUnrollPass.cpp
> > URL: http://llvm.org/viewvc/llvm-project/llvm/trunk/lib/Transforms/Scalar/LoopUnrollPass.cpp?rev=237156&r1=237155&r2=237156&view=diff <http://llvm.org/viewvc/llvm-project/llvm/trunk/lib/Transforms/Scalar/LoopUnrollPass.cpp?rev=237156&r1=237155&r2=237156&view=diff>
> > ==============================================================================
> > --- llvm/trunk/lib/Transforms/Scalar/LoopUnrollPass.cpp (original)
> > +++ llvm/trunk/lib/Transforms/Scalar/LoopUnrollPass.cpp Tue May 12 12:20:03 2015
> > @@ -186,33 +186,21 @@ namespace {
> >     void selectThresholds(const Loop *L, bool HasPragma,
> >                           const TargetTransformInfo::UnrollingPreferences &UP,
> >                           unsigned &Threshold, unsigned &PartialThreshold,
> > -                          unsigned NumberOfOptimizedInstructions) {
> > +                          unsigned &AbsoluteThreshold,
> > +                          unsigned &PercentOfOptimizedForCompleteUnroll) {
> >       // Determine the current unrolling threshold.  While this is
> >       // normally set from UnrollThreshold, it is overridden to a
> >       // smaller value if the current function is marked as
> >       // optimize-for-size, and the unroll threshold was not user
> >       // specified.
> >       Threshold = UserThreshold ? CurrentThreshold : UP.Threshold;
> > -
> > -      // If we are allowed to completely unroll if we can remove M% of
> > -      // instructions, and we know that with complete unrolling we'll be able
> > -      // to kill N instructions, then we can afford to completely unroll loops
> > -      // with unrolled size up to N*100/M.
> > -      // Adjust the threshold according to that:
> > -      unsigned PercentOfOptimizedForCompleteUnroll =
> > -          UserPercentOfOptimized ? CurrentMinPercentOfOptimized
> > -                                 : UP.MinPercentOfOptimized;
> > -      unsigned AbsoluteThreshold = UserAbsoluteThreshold
> > -                                       ? CurrentAbsoluteThreshold
> > -                                       : UP.AbsoluteThreshold;
> > -      if (PercentOfOptimizedForCompleteUnroll)
> > -        Threshold = std::max<unsigned>(Threshold,
> > -                                       NumberOfOptimizedInstructions * 100 /
> > -                                           PercentOfOptimizedForCompleteUnroll);
> > -      // But don't allow unrolling loops bigger than absolute threshold.
> > -      Threshold = std::min<unsigned>(Threshold, AbsoluteThreshold);
> > -
> >       PartialThreshold = UserThreshold ? CurrentThreshold : UP.PartialThreshold;
> > +      AbsoluteThreshold = UserAbsoluteThreshold ? CurrentAbsoluteThreshold
> > +                                                : UP.AbsoluteThreshold;
> > +      PercentOfOptimizedForCompleteUnroll = UserPercentOfOptimized
> > +                                                ? CurrentMinPercentOfOptimized
> > +                                                : UP.MinPercentOfOptimized;
> > +
> >       if (!UserThreshold &&
> >           L->getHeader()->getParent()->hasFnAttribute(
> >               Attribute::OptimizeForSize)) {
> > @@ -231,6 +219,10 @@ namespace {
> >               std::max<unsigned>(PartialThreshold, PragmaUnrollThreshold);
> >       }
> >     }
> > +    bool canUnrollCompletely(Loop *L, unsigned Threshold,
> > +                             unsigned AbsoluteThreshold, uint64_t UnrolledSize,
> > +                             unsigned NumberOfOptimizedInstructions,
> > +                             unsigned PercentOfOptimizedForCompleteUnroll);
> >   };
> > }
> >
> > @@ -253,57 +245,75 @@ Pass *llvm::createSimpleLoopUnrollPass()
> >   return llvm::createLoopUnrollPass(-1, -1, 0, 0);
> > }
> >
> > -static bool isLoadFromConstantInitializer(Value *V) {
> > -  if (GlobalVariable *GV = dyn_cast<GlobalVariable>(V))
> > -    if (GV->isConstant() && GV->hasDefinitiveInitializer())
> > -      return GV->getInitializer();
> > -  return false;
> > -}
> > -
> > namespace {
> > +/// \brief SCEV expressions visitor used for finding expressions that would
> > +/// become constants if the loop L is unrolled.
> > struct FindConstantPointers {
> > -  bool LoadCanBeConstantFolded;
> > +  /// \brief Shows whether the expression is ConstAddress+Constant or not.
> >   bool IndexIsConstant;
> > -  APInt Step;
> > -  APInt StartValue;
> > +
> > +  /// \brief Used for filtering out SCEV expressions with two or more AddRec
> > +  /// subexpressions.
> > +  ///
> > +  /// Used to filter out complicated SCEV expressions, having several AddRec
> > +  /// sub-expressions. We don't handle them, because unrolling one loop
> > +  /// would help to replace only one of these inductions with a constant, and
> > +  /// consequently, the expression would remain non-constant.
> > +  bool HaveSeenAR;
> > +
> > +  /// \brief If the SCEV expression becomes ConstAddress+Constant, this value
> > +  /// holds ConstAddress. Otherwise, it's nullptr.
> >   Value *BaseAddress;
> > +
> > +  /// \brief The loop, which we try to completely unroll.
> >   const Loop *L;
> > +
> >   ScalarEvolution &SE;
> > -  FindConstantPointers(const Loop *loop, ScalarEvolution &SE)
> > -      : LoadCanBeConstantFolded(true), IndexIsConstant(true), L(loop), SE(SE) {}
> >
> > +  FindConstantPointers(const Loop *L, ScalarEvolution &SE)
> > +      : IndexIsConstant(true), HaveSeenAR(false), BaseAddress(nullptr),
> > +        L(L), SE(SE) {}
> > +
> > +  /// Examine the given expression S and figure out, if it can be a part of an
> > +  /// expression, that could become a constant after the loop is unrolled.
> > +  /// The routine sets IndexIsConstant and HaveSeenAR according to the analysis
> > +  /// results.
> > +  /// \returns true if we need to examine subexpressions, and false otherwise.
> >   bool follow(const SCEV *S) {
> >     if (const SCEVUnknown *SC = dyn_cast<SCEVUnknown>(S)) {
> >       // We've reached the leaf node of SCEV, it's most probably just a
> > -      // variable. Now it's time to see if it corresponds to a global constant
> > -      // global (in which case we can eliminate the load), or not.
> > +      // variable.
> > +      // If it's the only one SCEV-subexpression, then it might be a base
> > +      // address of an index expression.
> > +      // If we've already recorded base address, then just give up on this SCEV
> > +      // - it's too complicated.
> > +      if (BaseAddress) {
> > +        IndexIsConstant = false;
> > +        return false;
> > +      }
> >       BaseAddress = SC->getValue();
> > -      LoadCanBeConstantFolded =
> > -          IndexIsConstant && isLoadFromConstantInitializer(BaseAddress);
> >       return false;
> >     }
> >     if (isa<SCEVConstant>(S))
> > -      return true;
> > +      return false;
> >     if (const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(S)) {
> >       // If the current SCEV expression is AddRec, and its loop isn't the loop
> >       // we are about to unroll, then we won't get a constant address after
> >       // unrolling, and thus, won't be able to eliminate the load.
> > -      if (AR->getLoop() != L)
> > -        return IndexIsConstant = false;
> > -      // If the step isn't constant, we won't get constant addresses in unrolled
> > -      // version. Bail out.
> > -      if (const SCEVConstant *StepSE =
> > -              dyn_cast<SCEVConstant>(AR->getStepRecurrence(SE)))
> > -        Step = StepSE->getValue()->getValue();
> > -      else
> > -        return IndexIsConstant = false;
> > -
> > -      return IndexIsConstant;
> > +      if (AR->getLoop() != L) {
> > +        IndexIsConstant = false;
> > +        return false;
> > +      }
> > +      // We don't handle multiple AddRecs here, so give up in this case.
> > +      if (HaveSeenAR) {
> > +        IndexIsConstant = false;
> > +        return false;
> > +      }
> > +      HaveSeenAR = true;
> >     }
> > -    // If Result is true, continue traversal.
> > -    // Otherwise, we have found something that prevents us from (possible) load
> > -    // elimination.
> > -    return IndexIsConstant;
> > +
> > +    // Continue traversal.
> > +    return true;
> >   }
> >   bool isDone() const { return !IndexIsConstant; }
> > };
> > @@ -328,27 +338,54 @@ class UnrollAnalyzer : public InstVisito
> >   typedef InstVisitor<UnrollAnalyzer, bool> Base;
> >   friend class InstVisitor<UnrollAnalyzer, bool>;
> >
> > +  struct SCEVGEPDescriptor {
> > +    Value *BaseAddr;
> > +    APInt Start;
> > +    APInt Step;
> > +  };
> > +
> > +  /// \brief The loop we're going to analyze.
> >   const Loop *L;
> > +
> > +  /// \brief TripCount of the given loop.
> >   unsigned TripCount;
> > +
> >   ScalarEvolution &SE;
> > +
> >   const TargetTransformInfo &TTI;
> >
> > +  // While we walk the loop instructions, we we build up and maintain a mapping
> > +  // of simplified values specific to this iteration.  The idea is to propagate
> > +  // any special information we have about loads that can be replaced with
> > +  // constants after complete unrolling, and account for likely simplifications
> > +  // post-unrolling.
> >   DenseMap<Value *, Constant *> SimplifiedValues;
> > -  DenseMap<LoadInst *, Value *> LoadBaseAddresses;
> > -  SmallPtrSet<Instruction *, 32> CountedInstructions;
> >
> > -  /// \brief Count the number of optimized instructions.
> > -  unsigned NumberOfOptimizedInstructions;
> > +  // To avoid requesting SCEV info on every iteration, request it once, and
> > +  // for each value that would become ConstAddress+Constant after loop
> > +  // unrolling, save the corresponding data.
> > +  SmallDenseMap<Value *, SCEVGEPDescriptor> SCEVCache;
> > +
> > +  /// \brief Number of currently simulated iteration.
> > +  ///
> > +  /// If an expression is ConstAddress+Constant, then the Constant is
> > +  /// Start + Iteration*Step, where Start and Step could be obtained from
> > +  /// SCEVCache.
> > +  unsigned Iteration;
> > +
> > +  /// \brief Upper threshold for complete unrolling.
> > +  unsigned MaxUnrolledLoopSize;
> >
> > -  // Provide base case for our instruction visit.
> > +  /// Base case for the instruction visitor.
> >   bool visitInstruction(Instruction &I) { return false; };
> > -  // TODO: We should also visit ICmp, FCmp, GetElementPtr, Trunc, ZExt, SExt,
> > -  // FPTrunc, FPExt, FPToUI, FPToSI, UIToFP, SIToFP, BitCast, Select,
> > -  // ExtractElement, InsertElement, ShuffleVector, ExtractValue, InsertValue.
> > -  //
> > -  // Probaly it's worth to hoist the code for estimating the simplifications
> > -  // effects to a separate class, since we have a very similar code in
> > -  // InlineCost already.
> > +
> > +  /// TODO: Add visitors for other instruction types, e.g. ZExt, SExt.
> > +
> > +  /// Try to simplify binary operator I.
> > +  ///
> > +  /// TODO: Probaly it's worth to hoist the code for estimating the
> > +  /// simplifications effects to a separate class, since we have a very similar
> > +  /// code in InlineCost already.
> >   bool visitBinaryOperator(BinaryOperator &I) {
> >     Value *LHS = I.getOperand(0), *RHS = I.getOperand(1);
> >     if (!isa<Constant>(LHS))
> > @@ -365,7 +402,7 @@ class UnrollAnalyzer : public InstVisito
> >     else
> >       SimpleV = SimplifyBinOp(I.getOpcode(), LHS, RHS, DL);
> >
> > -    if (SimpleV && CountedInstructions.insert(&I).second)
> > +    if (SimpleV)
> >       NumberOfOptimizedInstructions += TTI.getUserCost(&I);
> >
> >     if (Constant *C = dyn_cast_or_null<Constant>(SimpleV)) {
> > @@ -375,207 +412,172 @@ class UnrollAnalyzer : public InstVisito
> >     return false;
> >   }
> >
> > -  Constant *computeLoadValue(LoadInst *LI, unsigned Iteration) {
> > -    if (!LI)
> > -      return nullptr;
> > -    Value *BaseAddr = LoadBaseAddresses[LI];
> > -    if (!BaseAddr)
> > -      return nullptr;
> > -
> > -    auto GV = dyn_cast<GlobalVariable>(BaseAddr);
> > -    if (!GV)
> > -      return nullptr;
> > +  /// Try to fold load I.
> > +  bool visitLoad(LoadInst &I) {
> > +    Value *AddrOp = I.getPointerOperand();
> > +    if (!isa<Constant>(AddrOp))
> > +      if (Constant *SimplifiedAddrOp = SimplifiedValues.lookup(AddrOp))
> > +        AddrOp = SimplifiedAddrOp;
> > +
> > +    auto It = SCEVCache.find(AddrOp);
> > +    if (It == SCEVCache.end())
> > +      return false;
> > +    SCEVGEPDescriptor GEPDesc = It->second;
> > +
> > +    auto GV = dyn_cast<GlobalVariable>(GEPDesc.BaseAddr);
> > +    // We're only interested in loads that can be completely folded to a
> > +    // constant.
> > +    if (!GV || !GV->hasInitializer())
> > +      return false;
> >
> >     ConstantDataSequential *CDS =
> >         dyn_cast<ConstantDataSequential>(GV->getInitializer());
> >     if (!CDS)
> > -      return nullptr;
> > -
> > -    const SCEV *BaseAddrSE = SE.getSCEV(BaseAddr);
> > -    const SCEV *S = SE.getSCEV(LI->getPointerOperand());
> > -    const SCEV *OffSE = SE.getMinusSCEV(S, BaseAddrSE);
> > -
> > -    APInt StepC, StartC;
> > -    const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(OffSE);
> > -    if (!AR)
> > -      return nullptr;
> > -
> > -    if (const SCEVConstant *StepSE =
> > -            dyn_cast<SCEVConstant>(AR->getStepRecurrence(SE)))
> > -      StepC = StepSE->getValue()->getValue();
> > -    else
> > -      return nullptr;
> > -
> > -    if (const SCEVConstant *StartSE = dyn_cast<SCEVConstant>(AR->getStart()))
> > -      StartC = StartSE->getValue()->getValue();
> > -    else
> > -      return nullptr;
> > +      return false;
> >
> > +    // Check possible overflow.
> > +    if (GEPDesc.Start.getActiveBits() > 32 || GEPDesc.Step.getActiveBits() > 32)
> > +      return false;
> >     unsigned ElemSize = CDS->getElementType()->getPrimitiveSizeInBits() / 8U;
> > -    unsigned Start = StartC.getLimitedValue();
> > -    unsigned Step = StepC.getLimitedValue();
> > -
> > -    unsigned Index = (Start + Step * Iteration) / ElemSize;
> > -    if (Index >= CDS->getNumElements())
> > -      return nullptr;
> > +    uint64_t Index = (GEPDesc.Start.getLimitedValue() +
> > +                      GEPDesc.Step.getLimitedValue() * Iteration) /
> > +                     ElemSize;
> > +    if (Index >= CDS->getNumElements()) {
> > +      // FIXME: For now we conservatively ignore out of bound accesses, but
> > +      // we're allowed to perform the optimization in this case.
> > +      return false;
> > +    }
> >
> >     Constant *CV = CDS->getElementAsConstant(Index);
> > +    assert(CV && "Constant expected.");
> > +    SimplifiedValues[&I] = CV;
> >
> > -    return CV;
> > +    NumberOfOptimizedInstructions += TTI.getUserCost(&I);
> > +    return true;
> >   }
> >
> > -public:
> > -  UnrollAnalyzer(const Loop *L, unsigned TripCount, ScalarEvolution &SE,
> > -                 const TargetTransformInfo &TTI)
> > -      : L(L), TripCount(TripCount), SE(SE), TTI(TTI),
> > -        NumberOfOptimizedInstructions(0) {}
> > -
> > -  // Visit all loads the loop L, and for those that, after complete loop
> > -  // unrolling, would have a constant address and it will point to a known
> > -  // constant initializer, record its base address for future use.  It is used
> > -  // when we estimate number of potentially simplified instructions.
> > -  void findConstFoldableLoads() {
> > +  /// Visit all GEPs in the loop and find those which after complete loop
> > +  /// unrolling would become a constant, or BaseAddress+Constant.
> > +  ///
> > +  /// Such GEPs could allow to evaluate a load to a constant later - for now we
> > +  /// just store the corresponding BaseAddress and StartValue with StepValue in
> > +  /// the SCEVCache.
> > +  void cacheSCEVResults() {
> >     for (auto BB : L->getBlocks()) {
> > -      for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E; ++I) {
> > -        if (LoadInst *LI = dyn_cast<LoadInst>(I)) {
> > -          if (!LI->isSimple())
> > -            continue;
> > -          Value *AddrOp = LI->getPointerOperand();
> > -          const SCEV *S = SE.getSCEV(AddrOp);
> > +      for (Instruction &I : *BB) {
> > +        if (GetElementPtrInst *GEP = dyn_cast<GetElementPtrInst>(&I)) {
> > +          Value *V = cast<Value>(GEP);
> > +          if (!SE.isSCEVable(V->getType()))
> > +              continue;
> > +          const SCEV *S = SE.getSCEV(V);
> > +          // FIXME: Hoist the initialization out of the loop.
> >           FindConstantPointers Visitor(L, SE);
> >           SCEVTraversal<FindConstantPointers> T(Visitor);
> > +          // Try to find (BaseAddress+Step+Offset) tuple.
> > +          // If succeeded, save it to the cache - it might help in folding
> > +          // loads.
> >           T.visitAll(S);
> > -          if (Visitor.IndexIsConstant && Visitor.LoadCanBeConstantFolded) {
> > -            LoadBaseAddresses[LI] = Visitor.BaseAddress;
> > -          }
> > +          if (!Visitor.IndexIsConstant || !Visitor.BaseAddress)
> > +            continue;
> > +
> > +          const SCEV *BaseAddrSE = SE.getSCEV(Visitor.BaseAddress);
> > +          if (BaseAddrSE->getType() != S->getType())
> > +            continue;
> > +          const SCEV *OffSE = SE.getMinusSCEV(S, BaseAddrSE);
> > +          const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(OffSE);
> > +
> > +          if (!AR)
> > +            continue;
> > +
> > +          const SCEVConstant *StepSE =
> > +              dyn_cast<SCEVConstant>(AR->getStepRecurrence(SE));
> > +          const SCEVConstant *StartSE = dyn_cast<SCEVConstant>(AR->getStart());
> > +          if (!StepSE || !StartSE)
> > +            continue;
> > +
> > +          SCEVCache[V] = {Visitor.BaseAddress, StartSE->getValue()->getValue(),
> > +                          StepSE->getValue()->getValue()};
> >         }
> >       }
> >     }
> >   }
> >
> > -  // Given a list of loads that could be constant-folded (LoadBaseAddresses),
> > -  // estimate number of optimized instructions after substituting the concrete
> > -  // values for the given Iteration. Also track how many instructions become
> > -  // dead through this process.
> > -  unsigned estimateNumberOfOptimizedInstructions(unsigned Iteration) {
> > -    // We keep a set vector for the worklist so that we don't wast space in the
> > -    // worklist queuing up the same instruction repeatedly. This can happen due
> > -    // to multiple operands being the same instruction or due to the same
> > -    // instruction being an operand of lots of things that end up dead or
> > -    // simplified.
> > -    SmallSetVector<Instruction *, 8> Worklist;
> > -
> > -    // Clear the simplified values and counts for this iteration.
> > -    SimplifiedValues.clear();
> > -    CountedInstructions.clear();
> > -    NumberOfOptimizedInstructions = 0;
> > -
> > -    // We start by adding all loads to the worklist.
> > -    for (auto &LoadDescr : LoadBaseAddresses) {
> > -      LoadInst *LI = LoadDescr.first;
> > -      SimplifiedValues[LI] = computeLoadValue(LI, Iteration);
> > -      if (CountedInstructions.insert(LI).second)
> > -        NumberOfOptimizedInstructions += TTI.getUserCost(LI);
> > +public:
> > +  UnrollAnalyzer(const Loop *L, unsigned TripCount, ScalarEvolution &SE,
> > +                 const TargetTransformInfo &TTI, unsigned MaxUnrolledLoopSize)
> > +      : L(L), TripCount(TripCount), SE(SE), TTI(TTI),
> > +        MaxUnrolledLoopSize(MaxUnrolledLoopSize),
> > +        NumberOfOptimizedInstructions(0), UnrolledLoopSize(0) {}
> >
> > -      for (User *U : LI->users())
> > -        Worklist.insert(cast<Instruction>(U));
> > -    }
> > +  /// \brief Count the number of optimized instructions.
> > +  unsigned NumberOfOptimizedInstructions;
> >
> > -    // And then we try to simplify every user of every instruction from the
> > -    // worklist. If we do simplify a user, add it to the worklist to process
> > -    // its users as well.
> > -    while (!Worklist.empty()) {
> > -      Instruction *I = Worklist.pop_back_val();
> > -      if (!L->contains(I))
> > -        continue;
> > -      if (!visit(I))
> > -        continue;
> > -      for (User *U : I->users())
> > -        Worklist.insert(cast<Instruction>(U));
> > -    }
> > +  /// \brief Count the total number of instructions.
> > +  unsigned UnrolledLoopSize;
> >
> > -    // Now that we know the potentially simplifed instructions, estimate number
> > -    // of instructions that would become dead if we do perform the
> > -    // simplification.
> > -
> > -    // The dead instructions are held in a separate set. This is used to
> > -    // prevent us from re-examining instructions and make sure we only count
> > -    // the benifit once. The worklist's internal set handles insertion
> > -    // deduplication.
> > -    SmallPtrSet<Instruction *, 16> DeadInstructions;
> > -
> > -    // Lambda to enque operands onto the worklist.
> > -    auto EnqueueOperands = [&](Instruction &I) {
> > -      for (auto *Op : I.operand_values())
> > -        if (auto *OpI = dyn_cast<Instruction>(Op))
> > -          if (!OpI->use_empty())
> > -            Worklist.insert(OpI);
> > -    };
> > -
> > -    // Start by initializing worklist with simplified instructions.
> > -    for (auto &FoldedKeyValue : SimplifiedValues)
> > -      if (auto *FoldedInst = dyn_cast<Instruction>(FoldedKeyValue.first)) {
> > -        DeadInstructions.insert(FoldedInst);
> > -
> > -        // Add each instruction operand of this dead instruction to the
> > -        // worklist.
> > -        EnqueueOperands(*FoldedInst);
> > -      }
> > +  /// \brief Figure out if the loop is worth full unrolling.
> > +  ///
> > +  /// Complete loop unrolling can make some loads constant, and we need to know
> > +  /// if that would expose any further optimization opportunities.  This routine
> > +  /// estimates this optimization.  It assigns computed number of instructions,
> > +  /// that potentially might be optimized away, to
> > +  /// NumberOfOptimizedInstructions, and total number of instructions to
> > +  /// UnrolledLoopSize (not counting blocks that won't be reached, if we were
> > +  /// able to compute the condition).
> > +  /// \returns false if we can't analyze the loop, or if we discovered that
> > +  /// unrolling won't give anything. Otherwise, returns true.
> > +  bool analyzeLoop() {
> > +    SmallSetVector<BasicBlock *, 16> BBWorklist;
> > +
> > +    // Don't simulate loops with a big or unknown tripcount
> > +    if (!UnrollMaxIterationsCountToAnalyze || !TripCount ||
> > +        TripCount > UnrollMaxIterationsCountToAnalyze)
> > +      return false;
> >
> > -    // If a definition of an insn is only used by simplified or dead
> > -    // instructions, it's also dead. Check defs of all instructions from the
> > -    // worklist.
> > -    while (!Worklist.empty()) {
> > -      Instruction *I = Worklist.pop_back_val();
> > -      if (!L->contains(I))
> > -        continue;
> > -      if (DeadInstructions.count(I))
> > -        continue;
> > -
> > -      if (std::all_of(I->user_begin(), I->user_end(), [&](User *U) {
> > -            return DeadInstructions.count(cast<Instruction>(U));
> > -          })) {
> > -        NumberOfOptimizedInstructions += TTI.getUserCost(I);
> > -        DeadInstructions.insert(I);
> > -        EnqueueOperands(*I);
> > +    // To avoid compute SCEV-expressions on every iteration, compute them once
> > +    // and store interesting to us in SCEVCache.
> > +    cacheSCEVResults();
> > +
> > +    // Simulate execution of each iteration of the loop counting instructions,
> > +    // which would be simplified.
> > +    // Since the same load will take different values on different iterations,
> > +    // we literally have to go through all loop's iterations.
> > +    for (Iteration = 0; Iteration < TripCount; ++Iteration) {
> > +      SimplifiedValues.clear();
> > +      BBWorklist.clear();
> > +      BBWorklist.insert(L->getHeader());
> > +      // Note that we *must not* cache the size, this loop grows the worklist.
> > +      for (unsigned Idx = 0; Idx != BBWorklist.size(); ++Idx) {
> > +        BasicBlock *BB = BBWorklist[Idx];
> > +
> > +        // Visit all instructions in the given basic block and try to simplify
> > +        // it.  We don't change the actual IR, just count optimization
> > +        // opportunities.
> > +        for (Instruction &I : *BB) {
> > +          UnrolledLoopSize += TTI.getUserCost(&I);
> > +          Base::visit(I);
> > +          // If unrolled body turns out to be too big, bail out.
> > +          if (UnrolledLoopSize - NumberOfOptimizedInstructions >
> > +              MaxUnrolledLoopSize)
> > +            return false;
> > +        }
> > +
> > +        // Add BB's successors to the worklist.
> > +        for (BasicBlock *Succ : successors(BB))
> > +          if (L->contains(Succ))
> > +            BBWorklist.insert(Succ);
> >       }
> > +
> > +      // If we found no optimization opportunities on the first iteration, we
> > +      // won't find them on later ones too.
> > +      if (!NumberOfOptimizedInstructions)
> > +        return false;
> >     }
> > -    return NumberOfOptimizedInstructions;
> > +    return true;
> >   }
> > };
> > } // namespace
> >
> > -// Complete loop unrolling can make some loads constant, and we need to know if
> > -// that would expose any further optimization opportunities.
> > -// This routine estimates this optimization effect and returns the number of
> > -// instructions, that potentially might be optimized away.
> > -static unsigned
> > -approximateNumberOfOptimizedInstructions(const Loop *L, ScalarEvolution &SE,
> > -                                         unsigned TripCount,
> > -                                         const TargetTransformInfo &TTI) {
> > -  if (!TripCount || !UnrollMaxIterationsCountToAnalyze)
> > -    return 0;
> > -
> > -  UnrollAnalyzer UA(L, TripCount, SE, TTI);
> > -  UA.findConstFoldableLoads();
> > -
> > -  // Estimate number of instructions, that could be simplified if we replace a
> > -  // load with the corresponding constant. Since the same load will take
> > -  // different values on different iterations, we have to go through all loop's
> > -  // iterations here. To limit ourselves here, we check only first N
> > -  // iterations, and then scale the found number, if necessary.
> > -  unsigned IterationsNumberForEstimate =
> > -      std::min<unsigned>(UnrollMaxIterationsCountToAnalyze, TripCount);
> > -  unsigned NumberOfOptimizedInstructions = 0;
> > -  for (unsigned i = 0; i < IterationsNumberForEstimate; ++i)
> > -    NumberOfOptimizedInstructions +=
> > -        UA.estimateNumberOfOptimizedInstructions(i);
> > -
> > -  NumberOfOptimizedInstructions *= TripCount / IterationsNumberForEstimate;
> > -
> > -  return NumberOfOptimizedInstructions;
> > -}
> > -
> > /// ApproximateLoopSize - Approximate the size of the loop.
> > static unsigned ApproximateLoopSize(const Loop *L, unsigned &NumCalls,
> >                                     bool &NotDuplicatable,
> > @@ -679,6 +681,49 @@ static void SetLoopAlreadyUnrolled(Loop
> >   L->setLoopID(NewLoopID);
> > }
> >
> > +bool LoopUnroll::canUnrollCompletely(
> > +    Loop *L, unsigned Threshold, unsigned AbsoluteThreshold,
> > +    uint64_t UnrolledSize, unsigned NumberOfOptimizedInstructions,
> > +    unsigned PercentOfOptimizedForCompleteUnroll) {
> > +
> > +  if (Threshold == NoThreshold) {
> > +    DEBUG(dbgs() << "  Can fully unroll, because no threshold is set.\n");
> > +    return true;
> > +  }
> > +
> > +  if (UnrolledSize <= Threshold) {
> > +    DEBUG(dbgs() << "  Can fully unroll, because unrolled size: "
> > +                 << UnrolledSize << "<" << Threshold << "\n");
> > +    return true;
> > +  }
> > +
> > +  assert(UnrolledSize && "UnrolledSize can't be 0 at this point.");
> > +  unsigned PercentOfOptimizedInstructions =
> > +      (uint64_t)NumberOfOptimizedInstructions * 100ull / UnrolledSize;
> > +
> > +  if (UnrolledSize <= AbsoluteThreshold &&
> > +      PercentOfOptimizedInstructions >= PercentOfOptimizedForCompleteUnroll) {
> > +    DEBUG(dbgs() << "  Can fully unroll, because unrolling will help removing "
> > +                 << PercentOfOptimizedInstructions
> > +                 << "% instructions (threshold: "
> > +                 << PercentOfOptimizedForCompleteUnroll << "%)\n");
> > +    DEBUG(dbgs() << "  Unrolled size (" << UnrolledSize
> > +                 << ") is less than the threshold (" << AbsoluteThreshold
> > +                 << ").\n");
> > +    return true;
> > +  }
> > +
> > +  DEBUG(dbgs() << "  Too large to fully unroll:\n");
> > +  DEBUG(dbgs() << "    Unrolled size: " << UnrolledSize << "\n");
> > +  DEBUG(dbgs() << "    Estimated number of optimized instructions: "
> > +               << NumberOfOptimizedInstructions << "\n");
> > +  DEBUG(dbgs() << "    Absolute threshold: " << AbsoluteThreshold << "\n");
> > +  DEBUG(dbgs() << "    Minimum percent of removed instructions: "
> > +               << PercentOfOptimizedForCompleteUnroll << "\n");
> > +  DEBUG(dbgs() << "    Threshold for small loops: " << Threshold << "\n");
> > +  return false;
> > +}
> > +
> > unsigned LoopUnroll::selectUnrollCount(
> >     const Loop *L, unsigned TripCount, bool PragmaFullUnroll,
> >     unsigned PragmaCount, const TargetTransformInfo::UnrollingPreferences &UP,
> > @@ -785,27 +830,34 @@ bool LoopUnroll::runOnLoop(Loop *L, LPPa
> >     return false;
> >   }
> >
> > -  unsigned NumberOfOptimizedInstructions =
> > -      approximateNumberOfOptimizedInstructions(L, *SE, TripCount, TTI);
> > -  DEBUG(dbgs() << "  Complete unrolling could save: "
> > -               << NumberOfOptimizedInstructions << "\n");
> > -
> >   unsigned Threshold, PartialThreshold;
> > +  unsigned AbsoluteThreshold, PercentOfOptimizedForCompleteUnroll;
> >   selectThresholds(L, HasPragma, UP, Threshold, PartialThreshold,
> > -                   NumberOfOptimizedInstructions);
> > +                   AbsoluteThreshold, PercentOfOptimizedForCompleteUnroll);
> >
> >   // Given Count, TripCount and thresholds determine the type of
> >   // unrolling which is to be performed.
> >   enum { Full = 0, Partial = 1, Runtime = 2 };
> >   int Unrolling;
> >   if (TripCount && Count == TripCount) {
> > -    if (Threshold != NoThreshold && UnrolledSize > Threshold) {
> > -      DEBUG(dbgs() << "  Too large to fully unroll with count: " << Count
> > -                   << " because size: " << UnrolledSize << ">" << Threshold
> > -                   << "\n");
> > -      Unrolling = Partial;
> > -    } else {
> > +    Unrolling = Partial;
> > +    // If the loop is really small, we don't need to run an expensive analysis.
> > +    if (canUnrollCompletely(
> > +            L, Threshold, AbsoluteThreshold,
> > +            UnrolledSize, 0, 100)) {
> >       Unrolling = Full;
> > +    } else {
> > +      // The loop isn't that small, but we still can fully unroll it if that
> > +      // helps to remove a significant number of instructions.
> > +      // To check that, run additional analysis on the loop.
> > +      UnrollAnalyzer UA(L, TripCount, *SE, TTI, AbsoluteThreshold);
> > +      if (UA.analyzeLoop() &&
> > +          canUnrollCompletely(L, Threshold, AbsoluteThreshold,
> > +                              UA.UnrolledLoopSize,
> > +                              UA.NumberOfOptimizedInstructions,
> > +                              PercentOfOptimizedForCompleteUnroll)) {
> > +        Unrolling = Full;
> > +      }
> >     }
> >   } else if (TripCount && Count < TripCount) {
> >     Unrolling = Partial;
> >
> > Added: llvm/trunk/test/Transforms/LoopUnroll/full-unroll-bad-geps.ll
> > URL: http://llvm.org/viewvc/llvm-project/llvm/trunk/test/Transforms/LoopUnroll/full-unroll-bad-geps.ll?rev=237156&view=auto <http://llvm.org/viewvc/llvm-project/llvm/trunk/test/Transforms/LoopUnroll/full-unroll-bad-geps.ll?rev=237156&view=auto>
> > ==============================================================================
> > --- llvm/trunk/test/Transforms/LoopUnroll/full-unroll-bad-geps.ll (added)
> > +++ llvm/trunk/test/Transforms/LoopUnroll/full-unroll-bad-geps.ll Tue May 12 12:20:03 2015
> > @@ -0,0 +1,34 @@
> > +; Check that we don't crash on corner cases.
> > +; RUN: opt < %s -S -loop-unroll -unroll-max-iteration-count-to-analyze=1000 -unroll-absolute-threshold=10  -unroll-threshold=10  -unroll-percent-of-optimized-for-complete-unroll=20 -o /dev/null
> > +target datalayout = "e-m:o-i64:64-f80:128-n8:16:32:64-S128"
> > +
> > +define void @foo1() {
> > +entry:
> > +  br label %for.body
> > +
> > +for.body:
> > +  %phi = phi i64 [ 0, %entry ], [ %inc, %for.body ]
> > +  %idx = zext i32 undef to i64
> > +  %add.ptr = getelementptr inbounds i64, i64* null, i64 %idx
> > +  %inc = add nuw nsw i64 %phi, 1
> > +  %cmp = icmp ult i64 %inc, 999
> > +  br i1 %cmp, label %for.body, label %for.exit
> > +
> > +for.exit:
> > +  ret void
> > +}
> > +
> > +define void @foo2() {
> > +entry:
> > +  br label %for.body
> > +
> > +for.body:
> > +  %phi = phi i64 [ 0, %entry ], [ %inc, %for.body ]
> > +  %x = getelementptr i32, <4 x i32*> undef, <4 x i32> <i32 1, i32 1, i32 1, i32 1>
> > +  %inc = add nuw nsw i64 %phi, 1
> > +  %cmp = icmp ult i64 %inc, 999
> > +  br i1 %cmp, label %for.body, label %for.exit
> > +
> > +for.exit:
> > +  ret void
> > +}
> >
> > Modified: llvm/trunk/test/Transforms/LoopUnroll/full-unroll-heuristics.ll
> > URL: http://llvm.org/viewvc/llvm-project/llvm/trunk/test/Transforms/LoopUnroll/full-unroll-heuristics.ll?rev=237156&r1=237155&r2=237156&view=diff <http://llvm.org/viewvc/llvm-project/llvm/trunk/test/Transforms/LoopUnroll/full-unroll-heuristics.ll?rev=237156&r1=237155&r2=237156&view=diff>
> > ==============================================================================
> > --- llvm/trunk/test/Transforms/LoopUnroll/full-unroll-heuristics.ll (original)
> > +++ llvm/trunk/test/Transforms/LoopUnroll/full-unroll-heuristics.ll Tue May 12 12:20:03 2015
> > @@ -17,8 +17,8 @@
> > ; optimizations to remove ~55% of the instructions, the loop body size is 9,
> > ; and unrolled size is 65.
> >
> > -; RUN: opt < %s -S -loop-unroll -unroll-max-iteration-count-to-analyze=1000 -unroll-absolute-threshold=10  -unroll-threshold=10  -unroll-percent-of-optimized-for-complete-unroll=30 | FileCheck %s -check-prefix=TEST1
> > -; RUN: opt < %s -S -loop-unroll -unroll-max-iteration-count-to-analyze=1000 -unroll-absolute-threshold=100 -unroll-threshold=10  -unroll-percent-of-optimized-for-complete-unroll=30 | FileCheck %s -check-prefix=TEST2
> > +; RUN: opt < %s -S -loop-unroll -unroll-max-iteration-count-to-analyze=1000 -unroll-absolute-threshold=10  -unroll-threshold=10  -unroll-percent-of-optimized-for-complete-unroll=20 | FileCheck %s -check-prefix=TEST1
> > +; RUN: opt < %s -S -loop-unroll -unroll-max-iteration-count-to-analyze=1000 -unroll-absolute-threshold=100 -unroll-threshold=10  -unroll-percent-of-optimized-for-complete-unroll=20 | FileCheck %s -check-prefix=TEST2
> > ; RUN: opt < %s -S -loop-unroll -unroll-max-iteration-count-to-analyze=1000 -unroll-absolute-threshold=100 -unroll-threshold=10  -unroll-percent-of-optimized-for-complete-unroll=80 | FileCheck %s -check-prefix=TEST3
> > ; RUN: opt < %s -S -loop-unroll -unroll-max-iteration-count-to-analyze=1000 -unroll-absolute-threshold=100 -unroll-threshold=100 -unroll-percent-of-optimized-for-complete-unroll=80 | FileCheck %s -check-prefix=TEST4
> >
> >
> >
> > _______________________________________________
> > llvm-commits mailing list
> > llvm-commits at cs.uiuc.edu <mailto:llvm-commits at cs.uiuc.edu>
> > http://lists.cs.uiuc.edu/mailman/listinfo/llvm-commits <http://lists.cs.uiuc.edu/mailman/listinfo/llvm-commits>
> 

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