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Diffstat (limited to 'lib/Transforms/Vectorize/LoopVectorize.cpp')
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diff --git a/lib/Transforms/Vectorize/LoopVectorize.cpp b/lib/Transforms/Vectorize/LoopVectorize.cpp new file mode 100644 index 0000000..9c82cb8 --- /dev/null +++ b/lib/Transforms/Vectorize/LoopVectorize.cpp @@ -0,0 +1,3080 @@ +//===- LoopVectorize.cpp - A Loop Vectorizer ------------------------------===// +// +// The LLVM Compiler Infrastructure +// +// This file is distributed under the University of Illinois Open Source +// License. See LICENSE.TXT for details. +// +//===----------------------------------------------------------------------===// +// +// This is the LLVM loop vectorizer. This pass modifies 'vectorizable' loops +// and generates target-independent LLVM-IR. Legalization of the IR is done +// in the codegen. However, the vectorizes uses (will use) the codegen +// interfaces to generate IR that is likely to result in an optimal binary. +// +// The loop vectorizer combines consecutive loop iteration into a single +// 'wide' iteration. After this transformation the index is incremented +// by the SIMD vector width, and not by one. +// +// This pass has three parts: +// 1. The main loop pass that drives the different parts. +// 2. LoopVectorizationLegality - A unit that checks for the legality +// of the vectorization. +// 3. InnerLoopVectorizer - A unit that performs the actual +// widening of instructions. +// 4. LoopVectorizationCostModel - A unit that checks for the profitability +// of vectorization. It decides on the optimal vector width, which +// can be one, if vectorization is not profitable. +// +//===----------------------------------------------------------------------===// +// +// The reduction-variable vectorization is based on the paper: +// D. Nuzman and R. Henderson. Multi-platform Auto-vectorization. +// +// Variable uniformity checks are inspired by: +// Karrenberg, R. and Hack, S. Whole Function Vectorization. +// +// Other ideas/concepts are from: +// A. Zaks and D. Nuzman. Autovectorization in GCC-two years later. +// +// S. Maleki, Y. Gao, M. Garzaran, T. Wong and D. Padua. An Evaluation of +// Vectorizing Compilers. +// +//===----------------------------------------------------------------------===// + +#define LV_NAME "loop-vectorize" +#define DEBUG_TYPE LV_NAME + +#include "llvm/Transforms/Vectorize.h" +#include "llvm/ADT/DenseMap.h" +#include "llvm/ADT/MapVector.h" +#include "llvm/ADT/SmallPtrSet.h" +#include "llvm/ADT/SmallSet.h" +#include "llvm/ADT/SmallVector.h" +#include "llvm/ADT/StringExtras.h" +#include "llvm/Analysis/AliasAnalysis.h" +#include "llvm/Analysis/AliasSetTracker.h" +#include "llvm/Analysis/Dominators.h" +#include "llvm/Analysis/LoopInfo.h" +#include "llvm/Analysis/LoopIterator.h" +#include "llvm/Analysis/LoopPass.h" +#include "llvm/Analysis/ScalarEvolution.h" +#include "llvm/Analysis/ScalarEvolutionExpander.h" +#include "llvm/Analysis/ScalarEvolutionExpressions.h" +#include "llvm/Analysis/TargetTransformInfo.h" +#include "llvm/Analysis/ValueTracking.h" +#include "llvm/Analysis/Verifier.h" +#include "llvm/IR/Constants.h" +#include "llvm/IR/DataLayout.h" +#include "llvm/IR/DerivedTypes.h" +#include "llvm/IR/Function.h" +#include "llvm/IR/IRBuilder.h" +#include "llvm/IR/Instructions.h" +#include "llvm/IR/IntrinsicInst.h" +#include "llvm/IR/LLVMContext.h" +#include "llvm/IR/Module.h" +#include "llvm/IR/Type.h" +#include "llvm/IR/Value.h" +#include "llvm/Pass.h" +#include "llvm/Support/CommandLine.h" +#include "llvm/Support/Debug.h" +#include "llvm/Support/raw_ostream.h" +#include "llvm/Transforms/Scalar.h" +#include "llvm/Transforms/Utils/BasicBlockUtils.h" +#include "llvm/Transforms/Utils/Local.h" +#include <algorithm> +#include <map> + +using namespace llvm; + +static cl::opt<unsigned> +VectorizationFactor("force-vector-width", cl::init(0), cl::Hidden, + cl::desc("Sets the SIMD width. Zero is autoselect.")); + +static cl::opt<unsigned> +VectorizationUnroll("force-vector-unroll", cl::init(0), cl::Hidden, + cl::desc("Sets the vectorization unroll count. " + "Zero is autoselect.")); + +static cl::opt<bool> +EnableIfConversion("enable-if-conversion", cl::init(true), cl::Hidden, + cl::desc("Enable if-conversion during vectorization.")); + +/// We don't vectorize loops with a known constant trip count below this number. +static const unsigned TinyTripCountVectorThreshold = 16; + +/// We don't unroll loops with a known constant trip count below this number. +static const unsigned TinyTripCountUnrollThreshold = 128; + +/// We don't unroll loops that are larget than this threshold. +static const unsigned MaxLoopSizeThreshold = 32; + +/// When performing a runtime memory check, do not check more than this +/// number of pointers. Notice that the check is quadratic! +static const unsigned RuntimeMemoryCheckThreshold = 4; + +/// This is the highest vector width that we try to generate. +static const unsigned MaxVectorSize = 8; + +/// This is the highest Unroll Factor. +static const unsigned MaxUnrollSize = 4; + +namespace { + +// Forward declarations. +class LoopVectorizationLegality; +class LoopVectorizationCostModel; + +/// InnerLoopVectorizer vectorizes loops which contain only one basic +/// block to a specified vectorization factor (VF). +/// This class performs the widening of scalars into vectors, or multiple +/// scalars. This class also implements the following features: +/// * It inserts an epilogue loop for handling loops that don't have iteration +/// counts that are known to be a multiple of the vectorization factor. +/// * It handles the code generation for reduction variables. +/// * Scalarization (implementation using scalars) of un-vectorizable +/// instructions. +/// InnerLoopVectorizer does not perform any vectorization-legality +/// checks, and relies on the caller to check for the different legality +/// aspects. The InnerLoopVectorizer relies on the +/// LoopVectorizationLegality class to provide information about the induction +/// and reduction variables that were found to a given vectorization factor. +class InnerLoopVectorizer { +public: + InnerLoopVectorizer(Loop *OrigLoop, ScalarEvolution *SE, LoopInfo *LI, + DominatorTree *DT, DataLayout *DL, unsigned VecWidth, + unsigned UnrollFactor) + : OrigLoop(OrigLoop), SE(SE), LI(LI), DT(DT), DL(DL), VF(VecWidth), + UF(UnrollFactor), Builder(SE->getContext()), Induction(0), + OldInduction(0), WidenMap(UnrollFactor) {} + + // Perform the actual loop widening (vectorization). + void vectorize(LoopVectorizationLegality *Legal) { + // Create a new empty loop. Unlink the old loop and connect the new one. + createEmptyLoop(Legal); + // Widen each instruction in the old loop to a new one in the new loop. + // Use the Legality module to find the induction and reduction variables. + vectorizeLoop(Legal); + // Register the new loop and update the analysis passes. + updateAnalysis(); + } + +private: + /// A small list of PHINodes. + typedef SmallVector<PHINode*, 4> PhiVector; + /// When we unroll loops we have multiple vector values for each scalar. + /// This data structure holds the unrolled and vectorized values that + /// originated from one scalar instruction. + typedef SmallVector<Value*, 2> VectorParts; + + /// Add code that checks at runtime if the accessed arrays overlap. + /// Returns the comparator value or NULL if no check is needed. + Value *addRuntimeCheck(LoopVectorizationLegality *Legal, + Instruction *Loc); + /// Create an empty loop, based on the loop ranges of the old loop. + void createEmptyLoop(LoopVectorizationLegality *Legal); + /// Copy and widen the instructions from the old loop. + void vectorizeLoop(LoopVectorizationLegality *Legal); + + /// A helper function that computes the predicate of the block BB, assuming + /// that the header block of the loop is set to True. It returns the *entry* + /// mask for the block BB. + VectorParts createBlockInMask(BasicBlock *BB); + /// A helper function that computes the predicate of the edge between SRC + /// and DST. + VectorParts createEdgeMask(BasicBlock *Src, BasicBlock *Dst); + + /// A helper function to vectorize a single BB within the innermost loop. + void vectorizeBlockInLoop(LoopVectorizationLegality *Legal, BasicBlock *BB, + PhiVector *PV); + + /// Insert the new loop to the loop hierarchy and pass manager + /// and update the analysis passes. + void updateAnalysis(); + + /// This instruction is un-vectorizable. Implement it as a sequence + /// of scalars. + void scalarizeInstruction(Instruction *Instr); + + /// Create a broadcast instruction. This method generates a broadcast + /// instruction (shuffle) for loop invariant values and for the induction + /// value. If this is the induction variable then we extend it to N, N+1, ... + /// this is needed because each iteration in the loop corresponds to a SIMD + /// element. + Value *getBroadcastInstrs(Value *V); + + /// This function adds 0, 1, 2 ... to each vector element, starting at zero. + /// If Negate is set then negative numbers are added e.g. (0, -1, -2, ...). + /// The sequence starts at StartIndex. + Value *getConsecutiveVector(Value* Val, unsigned StartIdx, bool Negate); + + /// When we go over instructions in the basic block we rely on previous + /// values within the current basic block or on loop invariant values. + /// When we widen (vectorize) values we place them in the map. If the values + /// are not within the map, they have to be loop invariant, so we simply + /// broadcast them into a vector. + VectorParts &getVectorValue(Value *V); + + /// Generate a shuffle sequence that will reverse the vector Vec. + Value *reverseVector(Value *Vec); + + /// This is a helper class that holds the vectorizer state. It maps scalar + /// instructions to vector instructions. When the code is 'unrolled' then + /// then a single scalar value is mapped to multiple vector parts. The parts + /// are stored in the VectorPart type. + struct ValueMap { + /// C'tor. UnrollFactor controls the number of vectors ('parts') that + /// are mapped. + ValueMap(unsigned UnrollFactor) : UF(UnrollFactor) {} + + /// \return True if 'Key' is saved in the Value Map. + bool has(Value *Key) { return MapStoreage.count(Key); } + + /// Initializes a new entry in the map. Sets all of the vector parts to the + /// save value in 'Val'. + /// \return A reference to a vector with splat values. + VectorParts &splat(Value *Key, Value *Val) { + MapStoreage[Key].clear(); + MapStoreage[Key].append(UF, Val); + return MapStoreage[Key]; + } + + ///\return A reference to the value that is stored at 'Key'. + VectorParts &get(Value *Key) { + if (!has(Key)) + MapStoreage[Key].resize(UF); + return MapStoreage[Key]; + } + + /// The unroll factor. Each entry in the map stores this number of vector + /// elements. + unsigned UF; + + /// Map storage. We use std::map and not DenseMap because insertions to a + /// dense map invalidates its iterators. + std::map<Value*, VectorParts> MapStoreage; + }; + + /// The original loop. + Loop *OrigLoop; + /// Scev analysis to use. + ScalarEvolution *SE; + /// Loop Info. + LoopInfo *LI; + /// Dominator Tree. + DominatorTree *DT; + /// Data Layout. + DataLayout *DL; + /// The vectorization SIMD factor to use. Each vector will have this many + /// vector elements. + unsigned VF; + /// The vectorization unroll factor to use. Each scalar is vectorized to this + /// many different vector instructions. + unsigned UF; + + /// The builder that we use + IRBuilder<> Builder; + + // --- Vectorization state --- + + /// The vector-loop preheader. + BasicBlock *LoopVectorPreHeader; + /// The scalar-loop preheader. + BasicBlock *LoopScalarPreHeader; + /// Middle Block between the vector and the scalar. + BasicBlock *LoopMiddleBlock; + ///The ExitBlock of the scalar loop. + BasicBlock *LoopExitBlock; + ///The vector loop body. + BasicBlock *LoopVectorBody; + ///The scalar loop body. + BasicBlock *LoopScalarBody; + ///The first bypass block. + BasicBlock *LoopBypassBlock; + + /// The new Induction variable which was added to the new block. + PHINode *Induction; + /// The induction variable of the old basic block. + PHINode *OldInduction; + /// Maps scalars to widened vectors. + ValueMap WidenMap; +}; + +/// LoopVectorizationLegality checks if it is legal to vectorize a loop, and +/// to what vectorization factor. +/// This class does not look at the profitability of vectorization, only the +/// legality. This class has two main kinds of checks: +/// * Memory checks - The code in canVectorizeMemory checks if vectorization +/// will change the order of memory accesses in a way that will change the +/// correctness of the program. +/// * Scalars checks - The code in canVectorizeInstrs and canVectorizeMemory +/// checks for a number of different conditions, such as the availability of a +/// single induction variable, that all types are supported and vectorize-able, +/// etc. This code reflects the capabilities of InnerLoopVectorizer. +/// This class is also used by InnerLoopVectorizer for identifying +/// induction variable and the different reduction variables. +class LoopVectorizationLegality { +public: + LoopVectorizationLegality(Loop *L, ScalarEvolution *SE, DataLayout *DL, + DominatorTree *DT) + : TheLoop(L), SE(SE), DL(DL), DT(DT), Induction(0) {} + + /// This enum represents the kinds of reductions that we support. + enum ReductionKind { + RK_NoReduction, ///< Not a reduction. + RK_IntegerAdd, ///< Sum of integers. + RK_IntegerMult, ///< Product of integers. + RK_IntegerOr, ///< Bitwise or logical OR of numbers. + RK_IntegerAnd, ///< Bitwise or logical AND of numbers. + RK_IntegerXor, ///< Bitwise or logical XOR of numbers. + RK_FloatAdd, ///< Sum of floats. + RK_FloatMult ///< Product of floats. + }; + + /// This enum represents the kinds of inductions that we support. + enum InductionKind { + IK_NoInduction, ///< Not an induction variable. + IK_IntInduction, ///< Integer induction variable. Step = 1. + IK_ReverseIntInduction, ///< Reverse int induction variable. Step = -1. + IK_PtrInduction ///< Pointer induction variable. Step = sizeof(elem). + }; + + /// This POD struct holds information about reduction variables. + struct ReductionDescriptor { + ReductionDescriptor() : StartValue(0), LoopExitInstr(0), + Kind(RK_NoReduction) {} + + ReductionDescriptor(Value *Start, Instruction *Exit, ReductionKind K) + : StartValue(Start), LoopExitInstr(Exit), Kind(K) {} + + // The starting value of the reduction. + // It does not have to be zero! + Value *StartValue; + // The instruction who's value is used outside the loop. + Instruction *LoopExitInstr; + // The kind of the reduction. + ReductionKind Kind; + }; + + // This POD struct holds information about the memory runtime legality + // check that a group of pointers do not overlap. + struct RuntimePointerCheck { + RuntimePointerCheck() : Need(false) {} + + /// Reset the state of the pointer runtime information. + void reset() { + Need = false; + Pointers.clear(); + Starts.clear(); + Ends.clear(); + } + + /// Insert a pointer and calculate the start and end SCEVs. + void insert(ScalarEvolution *SE, Loop *Lp, Value *Ptr); + + /// This flag indicates if we need to add the runtime check. + bool Need; + /// Holds the pointers that we need to check. + SmallVector<Value*, 2> Pointers; + /// Holds the pointer value at the beginning of the loop. + SmallVector<const SCEV*, 2> Starts; + /// Holds the pointer value at the end of the loop. + SmallVector<const SCEV*, 2> Ends; + }; + + /// A POD for saving information about induction variables. + struct InductionInfo { + InductionInfo(Value *Start, InductionKind K) : StartValue(Start), IK(K) {} + InductionInfo() : StartValue(0), IK(IK_NoInduction) {} + /// Start value. + Value *StartValue; + /// Induction kind. + InductionKind IK; + }; + + /// ReductionList contains the reduction descriptors for all + /// of the reductions that were found in the loop. + typedef DenseMap<PHINode*, ReductionDescriptor> ReductionList; + + /// InductionList saves induction variables and maps them to the + /// induction descriptor. + typedef MapVector<PHINode*, InductionInfo> InductionList; + + /// Returns true if it is legal to vectorize this loop. + /// This does not mean that it is profitable to vectorize this + /// loop, only that it is legal to do so. + bool canVectorize(); + + /// Returns the Induction variable. + PHINode *getInduction() { return Induction; } + + /// Returns the reduction variables found in the loop. + ReductionList *getReductionVars() { return &Reductions; } + + /// Returns the induction variables found in the loop. + InductionList *getInductionVars() { return &Inductions; } + + /// Returns True if V is an induction variable in this loop. + bool isInductionVariable(const Value *V); + + /// Return true if the block BB needs to be predicated in order for the loop + /// to be vectorized. + bool blockNeedsPredication(BasicBlock *BB); + + /// Check if this pointer is consecutive when vectorizing. This happens + /// when the last index of the GEP is the induction variable, or that the + /// pointer itself is an induction variable. + /// This check allows us to vectorize A[idx] into a wide load/store. + /// Returns: + /// 0 - Stride is unknown or non consecutive. + /// 1 - Address is consecutive. + /// -1 - Address is consecutive, and decreasing. + int isConsecutivePtr(Value *Ptr); + + /// Returns true if the value V is uniform within the loop. + bool isUniform(Value *V); + + /// Returns true if this instruction will remain scalar after vectorization. + bool isUniformAfterVectorization(Instruction* I) { return Uniforms.count(I); } + + /// Returns the information that we collected about runtime memory check. + RuntimePointerCheck *getRuntimePointerCheck() { return &PtrRtCheck; } +private: + /// Check if a single basic block loop is vectorizable. + /// At this point we know that this is a loop with a constant trip count + /// and we only need to check individual instructions. + bool canVectorizeInstrs(); + + /// When we vectorize loops we may change the order in which + /// we read and write from memory. This method checks if it is + /// legal to vectorize the code, considering only memory constrains. + /// Returns true if the loop is vectorizable + bool canVectorizeMemory(); + + /// Return true if we can vectorize this loop using the IF-conversion + /// transformation. + bool canVectorizeWithIfConvert(); + + /// Collect the variables that need to stay uniform after vectorization. + void collectLoopUniforms(); + + /// Return true if all of the instructions in the block can be speculatively + /// executed. + bool blockCanBePredicated(BasicBlock *BB); + + /// Returns True, if 'Phi' is the kind of reduction variable for type + /// 'Kind'. If this is a reduction variable, it adds it to ReductionList. + bool AddReductionVar(PHINode *Phi, ReductionKind Kind); + /// Returns true if the instruction I can be a reduction variable of type + /// 'Kind'. + bool isReductionInstr(Instruction *I, ReductionKind Kind); + /// Returns the induction kind of Phi. This function may return NoInduction + /// if the PHI is not an induction variable. + InductionKind isInductionVariable(PHINode *Phi); + /// Return true if can compute the address bounds of Ptr within the loop. + bool hasComputableBounds(Value *Ptr); + + /// The loop that we evaluate. + Loop *TheLoop; + /// Scev analysis. + ScalarEvolution *SE; + /// DataLayout analysis. + DataLayout *DL; + // Dominators. + DominatorTree *DT; + + // --- vectorization state --- // + + /// Holds the integer induction variable. This is the counter of the + /// loop. + PHINode *Induction; + /// Holds the reduction variables. + ReductionList Reductions; + /// Holds all of the induction variables that we found in the loop. + /// Notice that inductions don't need to start at zero and that induction + /// variables can be pointers. + InductionList Inductions; + + /// Allowed outside users. This holds the reduction + /// vars which can be accessed from outside the loop. + SmallPtrSet<Value*, 4> AllowedExit; + /// This set holds the variables which are known to be uniform after + /// vectorization. + SmallPtrSet<Instruction*, 4> Uniforms; + /// We need to check that all of the pointers in this list are disjoint + /// at runtime. + RuntimePointerCheck PtrRtCheck; +}; + +/// LoopVectorizationCostModel - estimates the expected speedups due to +/// vectorization. +/// In many cases vectorization is not profitable. This can happen because of +/// a number of reasons. In this class we mainly attempt to predict the +/// expected speedup/slowdowns due to the supported instruction set. We use the +/// TargetTransformInfo to query the different backends for the cost of +/// different operations. +class LoopVectorizationCostModel { +public: + LoopVectorizationCostModel(Loop *L, ScalarEvolution *SE, LoopInfo *LI, + LoopVectorizationLegality *Legal, + const TargetTransformInfo &TTI) + : TheLoop(L), SE(SE), LI(LI), Legal(Legal), TTI(TTI) {} + + /// \return The most profitable vectorization factor. + /// This method checks every power of two up to VF. If UserVF is not ZERO + /// then this vectorization factor will be selected if vectorization is + /// possible. + unsigned selectVectorizationFactor(bool OptForSize, unsigned UserVF); + + + /// \return The most profitable unroll factor. + /// If UserUF is non-zero then this method finds the best unroll-factor + /// based on register pressure and other parameters. + unsigned selectUnrollFactor(bool OptForSize, unsigned UserUF); + + /// \brief A struct that represents some properties of the register usage + /// of a loop. + struct RegisterUsage { + /// Holds the number of loop invariant values that are used in the loop. + unsigned LoopInvariantRegs; + /// Holds the maximum number of concurrent live intervals in the loop. + unsigned MaxLocalUsers; + /// Holds the number of instructions in the loop. + unsigned NumInstructions; + }; + + /// \return information about the register usage of the loop. + RegisterUsage calculateRegisterUsage(); + +private: + /// Returns the expected execution cost. The unit of the cost does + /// not matter because we use the 'cost' units to compare different + /// vector widths. The cost that is returned is *not* normalized by + /// the factor width. + unsigned expectedCost(unsigned VF); + + /// Returns the execution time cost of an instruction for a given vector + /// width. Vector width of one means scalar. + unsigned getInstructionCost(Instruction *I, unsigned VF); + + /// A helper function for converting Scalar types to vector types. + /// If the incoming type is void, we return void. If the VF is 1, we return + /// the scalar type. + static Type* ToVectorTy(Type *Scalar, unsigned VF); + + /// The loop that we evaluate. + Loop *TheLoop; + /// Scev analysis. + ScalarEvolution *SE; + /// Loop Info analysis. + LoopInfo *LI; + /// Vectorization legality. + LoopVectorizationLegality *Legal; + /// Vector target information. + const TargetTransformInfo &TTI; +}; + +/// The LoopVectorize Pass. +struct LoopVectorize : public LoopPass { + /// Pass identification, replacement for typeid + static char ID; + + explicit LoopVectorize() : LoopPass(ID) { + initializeLoopVectorizePass(*PassRegistry::getPassRegistry()); + } + + ScalarEvolution *SE; + DataLayout *DL; + LoopInfo *LI; + TargetTransformInfo *TTI; + DominatorTree *DT; + + virtual bool runOnLoop(Loop *L, LPPassManager &LPM) { + // We only vectorize innermost loops. + if (!L->empty()) + return false; + + SE = &getAnalysis<ScalarEvolution>(); + DL = getAnalysisIfAvailable<DataLayout>(); + LI = &getAnalysis<LoopInfo>(); + TTI = &getAnalysis<TargetTransformInfo>(); + DT = &getAnalysis<DominatorTree>(); + + DEBUG(dbgs() << "LV: Checking a loop in \"" << + L->getHeader()->getParent()->getName() << "\"\n"); + + // Check if it is legal to vectorize the loop. + LoopVectorizationLegality LVL(L, SE, DL, DT); + if (!LVL.canVectorize()) { + DEBUG(dbgs() << "LV: Not vectorizing.\n"); + return false; + } + + // Use the cost model. + LoopVectorizationCostModel CM(L, SE, LI, &LVL, *TTI); + + // Check the function attribues to find out if this function should be + // optimized for size. + Function *F = L->getHeader()->getParent(); + Attribute::AttrKind SzAttr = Attribute::OptimizeForSize; + Attribute::AttrKind FlAttr = Attribute::NoImplicitFloat; + unsigned FnIndex = AttributeSet::FunctionIndex; + bool OptForSize = F->getAttributes().hasAttribute(FnIndex, SzAttr); + bool NoFloat = F->getAttributes().hasAttribute(FnIndex, FlAttr); + + if (NoFloat) { + DEBUG(dbgs() << "LV: Can't vectorize when the NoImplicitFloat" + "attribute is used.\n"); + return false; + } + + unsigned VF = CM.selectVectorizationFactor(OptForSize, VectorizationFactor); + unsigned UF = CM.selectUnrollFactor(OptForSize, VectorizationUnroll); + + if (VF == 1) { + DEBUG(dbgs() << "LV: Vectorization is possible but not beneficial.\n"); + return false; + } + + DEBUG(dbgs() << "LV: Found a vectorizable loop ("<< VF << ") in "<< + F->getParent()->getModuleIdentifier()<<"\n"); + DEBUG(dbgs() << "LV: Unroll Factor is " << UF << "\n"); + + // If we decided that it is *legal* to vectorizer the loop then do it. + InnerLoopVectorizer LB(L, SE, LI, DT, DL, VF, UF); + LB.vectorize(&LVL); + + DEBUG(verifyFunction(*L->getHeader()->getParent())); + return true; + } + + virtual void getAnalysisUsage(AnalysisUsage &AU) const { + LoopPass::getAnalysisUsage(AU); + AU.addRequiredID(LoopSimplifyID); + AU.addRequiredID(LCSSAID); + AU.addRequired<DominatorTree>(); + AU.addRequired<LoopInfo>(); + AU.addRequired<ScalarEvolution>(); + AU.addRequired<TargetTransformInfo>(); + AU.addPreserved<LoopInfo>(); + AU.addPreserved<DominatorTree>(); + } + +}; + +} // end anonymous namespace + +//===----------------------------------------------------------------------===// +// Implementation of LoopVectorizationLegality, InnerLoopVectorizer and +// LoopVectorizationCostModel. +//===----------------------------------------------------------------------===// + +void +LoopVectorizationLegality::RuntimePointerCheck::insert(ScalarEvolution *SE, + Loop *Lp, Value *Ptr) { + const SCEV *Sc = SE->getSCEV(Ptr); + const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(Sc); + assert(AR && "Invalid addrec expression"); + const SCEV *Ex = SE->getExitCount(Lp, Lp->getLoopLatch()); + const SCEV *ScEnd = AR->evaluateAtIteration(Ex, *SE); + Pointers.push_back(Ptr); + Starts.push_back(AR->getStart()); + Ends.push_back(ScEnd); +} + +Value *InnerLoopVectorizer::getBroadcastInstrs(Value *V) { + // Save the current insertion location. + Instruction *Loc = Builder.GetInsertPoint(); + + // We need to place the broadcast of invariant variables outside the loop. + Instruction *Instr = dyn_cast<Instruction>(V); + bool NewInstr = (Instr && Instr->getParent() == LoopVectorBody); + bool Invariant = OrigLoop->isLoopInvariant(V) && !NewInstr; + + // Place the code for broadcasting invariant variables in the new preheader. + if (Invariant) + Builder.SetInsertPoint(LoopVectorPreHeader->getTerminator()); + + // Broadcast the scalar into all locations in the vector. + Value *Shuf = Builder.CreateVectorSplat(VF, V, "broadcast"); + + // Restore the builder insertion point. + if (Invariant) + Builder.SetInsertPoint(Loc); + + return Shuf; +} + +Value *InnerLoopVectorizer::getConsecutiveVector(Value* Val, unsigned StartIdx, + bool Negate) { + assert(Val->getType()->isVectorTy() && "Must be a vector"); + assert(Val->getType()->getScalarType()->isIntegerTy() && + "Elem must be an integer"); + // Create the types. + Type *ITy = Val->getType()->getScalarType(); + VectorType *Ty = cast<VectorType>(Val->getType()); + int VLen = Ty->getNumElements(); + SmallVector<Constant*, 8> Indices; + + // Create a vector of consecutive numbers from zero to VF. + for (int i = 0; i < VLen; ++i) { + int Idx = Negate ? (-i): i; + Indices.push_back(ConstantInt::get(ITy, StartIdx + Idx)); + } + + // Add the consecutive indices to the vector value. + Constant *Cv = ConstantVector::get(Indices); + assert(Cv->getType() == Val->getType() && "Invalid consecutive vec"); + return Builder.CreateAdd(Val, Cv, "induction"); +} + +int LoopVectorizationLegality::isConsecutivePtr(Value *Ptr) { + assert(Ptr->getType()->isPointerTy() && "Unexpected non ptr"); + + // If this value is a pointer induction variable we know it is consecutive. + PHINode *Phi = dyn_cast_or_null<PHINode>(Ptr); + if (Phi && Inductions.count(Phi)) { + InductionInfo II = Inductions[Phi]; + if (IK_PtrInduction == II.IK) + return 1; + } + + GetElementPtrInst *Gep = dyn_cast_or_null<GetElementPtrInst>(Ptr); + if (!Gep) + return 0; + + unsigned NumOperands = Gep->getNumOperands(); + Value *LastIndex = Gep->getOperand(NumOperands - 1); + + // Check that all of the gep indices are uniform except for the last. + for (unsigned i = 0; i < NumOperands - 1; ++i) + if (!SE->isLoopInvariant(SE->getSCEV(Gep->getOperand(i)), TheLoop)) + return 0; + + // We can emit wide load/stores only if the last index is the induction + // variable. + const SCEV *Last = SE->getSCEV(LastIndex); + if (const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(Last)) { + const SCEV *Step = AR->getStepRecurrence(*SE); + + // The memory is consecutive because the last index is consecutive + // and all other indices are loop invariant. + if (Step->isOne()) + return 1; + if (Step->isAllOnesValue()) + return -1; + } + + return 0; +} + +bool LoopVectorizationLegality::isUniform(Value *V) { + return (SE->isLoopInvariant(SE->getSCEV(V), TheLoop)); +} + +InnerLoopVectorizer::VectorParts& +InnerLoopVectorizer::getVectorValue(Value *V) { + assert(V != Induction && "The new induction variable should not be used."); + assert(!V->getType()->isVectorTy() && "Can't widen a vector"); + + // If we have this scalar in the map, return it. + if (WidenMap.has(V)) + return WidenMap.get(V); + + // If this scalar is unknown, assume that it is a constant or that it is + // loop invariant. Broadcast V and save the value for future uses. + Value *B = getBroadcastInstrs(V); + WidenMap.splat(V, B); + return WidenMap.get(V); +} + +Value *InnerLoopVectorizer::reverseVector(Value *Vec) { + assert(Vec->getType()->isVectorTy() && "Invalid type"); + SmallVector<Constant*, 8> ShuffleMask; + for (unsigned i = 0; i < VF; ++i) + ShuffleMask.push_back(Builder.getInt32(VF - i - 1)); + + return Builder.CreateShuffleVector(Vec, UndefValue::get(Vec->getType()), + ConstantVector::get(ShuffleMask), + "reverse"); +} + +void InnerLoopVectorizer::scalarizeInstruction(Instruction *Instr) { + assert(!Instr->getType()->isAggregateType() && "Can't handle vectors"); + // Holds vector parameters or scalars, in case of uniform vals. + SmallVector<VectorParts, 4> Params; + + // Find all of the vectorized parameters. + for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) { + Value *SrcOp = Instr->getOperand(op); + + // If we are accessing the old induction variable, use the new one. + if (SrcOp == OldInduction) { + Params.push_back(getVectorValue(SrcOp)); + continue; + } + + // Try using previously calculated values. + Instruction *SrcInst = dyn_cast<Instruction>(SrcOp); + + // If the src is an instruction that appeared earlier in the basic block + // then it should already be vectorized. + if (SrcInst && OrigLoop->contains(SrcInst)) { + assert(WidenMap.has(SrcInst) && "Source operand is unavailable"); + // The parameter is a vector value from earlier. + Params.push_back(WidenMap.get(SrcInst)); + } else { + // The parameter is a scalar from outside the loop. Maybe even a constant. + VectorParts Scalars; + Scalars.append(UF, SrcOp); + Params.push_back(Scalars); + } + } + + assert(Params.size() == Instr->getNumOperands() && + "Invalid number of operands"); + + // Does this instruction return a value ? + bool IsVoidRetTy = Instr->getType()->isVoidTy(); + + Value *UndefVec = IsVoidRetTy ? 0 : + UndefValue::get(VectorType::get(Instr->getType(), VF)); + // Create a new entry in the WidenMap and initialize it to Undef or Null. + VectorParts &VecResults = WidenMap.splat(Instr, UndefVec); + + // For each scalar that we create: + for (unsigned Width = 0; Width < VF; ++Width) { + // For each vector unroll 'part': + for (unsigned Part = 0; Part < UF; ++Part) { + Instruction *Cloned = Instr->clone(); + if (!IsVoidRetTy) + Cloned->setName(Instr->getName() + ".cloned"); + // Replace the operands of the cloned instrucions with extracted scalars. + for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) { + Value *Op = Params[op][Part]; + // Param is a vector. Need to extract the right lane. + if (Op->getType()->isVectorTy()) + Op = Builder.CreateExtractElement(Op, Builder.getInt32(Width)); + Cloned->setOperand(op, Op); + } + + // Place the cloned scalar in the new loop. + Builder.Insert(Cloned); + + // If the original scalar returns a value we need to place it in a vector + // so that future users will be able to use it. + if (!IsVoidRetTy) + VecResults[Part] = Builder.CreateInsertElement(VecResults[Part], Cloned, + Builder.getInt32(Width)); + } + } +} + +Value* +InnerLoopVectorizer::addRuntimeCheck(LoopVectorizationLegality *Legal, + Instruction *Loc) { + LoopVectorizationLegality::RuntimePointerCheck *PtrRtCheck = + Legal->getRuntimePointerCheck(); + + if (!PtrRtCheck->Need) + return NULL; + + Value *MemoryRuntimeCheck = 0; + unsigned NumPointers = PtrRtCheck->Pointers.size(); + SmallVector<Value* , 2> Starts; + SmallVector<Value* , 2> Ends; + + SCEVExpander Exp(*SE, "induction"); + + // Use this type for pointer arithmetic. + Type* PtrArithTy = Type::getInt8PtrTy(Loc->getContext(), 0); + + for (unsigned i = 0; i < NumPointers; ++i) { + Value *Ptr = PtrRtCheck->Pointers[i]; + const SCEV *Sc = SE->getSCEV(Ptr); + + if (SE->isLoopInvariant(Sc, OrigLoop)) { + DEBUG(dbgs() << "LV: Adding RT check for a loop invariant ptr:" << + *Ptr <<"\n"); + Starts.push_back(Ptr); + Ends.push_back(Ptr); + } else { + DEBUG(dbgs() << "LV: Adding RT check for range:" << *Ptr <<"\n"); + + Value *Start = Exp.expandCodeFor(PtrRtCheck->Starts[i], PtrArithTy, Loc); + Value *End = Exp.expandCodeFor(PtrRtCheck->Ends[i], PtrArithTy, Loc); + Starts.push_back(Start); + Ends.push_back(End); + } + } + + for (unsigned i = 0; i < NumPointers; ++i) { + for (unsigned j = i+1; j < NumPointers; ++j) { + Instruction::CastOps Op = Instruction::BitCast; + Value *Start0 = CastInst::Create(Op, Starts[i], PtrArithTy, "bc", Loc); + Value *Start1 = CastInst::Create(Op, Starts[j], PtrArithTy, "bc", Loc); + Value *End0 = CastInst::Create(Op, Ends[i], PtrArithTy, "bc", Loc); + Value *End1 = CastInst::Create(Op, Ends[j], PtrArithTy, "bc", Loc); + + Value *Cmp0 = CmpInst::Create(Instruction::ICmp, CmpInst::ICMP_ULE, + Start0, End1, "bound0", Loc); + Value *Cmp1 = CmpInst::Create(Instruction::ICmp, CmpInst::ICMP_ULE, + Start1, End0, "bound1", Loc); + Value *IsConflict = BinaryOperator::Create(Instruction::And, Cmp0, Cmp1, + "found.conflict", Loc); + if (MemoryRuntimeCheck) + MemoryRuntimeCheck = BinaryOperator::Create(Instruction::Or, + MemoryRuntimeCheck, + IsConflict, + "conflict.rdx", Loc); + else + MemoryRuntimeCheck = IsConflict; + + } + } + + return MemoryRuntimeCheck; +} + +void +InnerLoopVectorizer::createEmptyLoop(LoopVectorizationLegality *Legal) { + /* + In this function we generate a new loop. The new loop will contain + the vectorized instructions while the old loop will continue to run the + scalar remainder. + + [ ] <-- vector loop bypass. + / | + / v + | [ ] <-- vector pre header. + | | + | v + | [ ] \ + | [ ]_| <-- vector loop. + | | + \ v + >[ ] <--- middle-block. + / | + / v + | [ ] <--- new preheader. + | | + | v + | [ ] \ + | [ ]_| <-- old scalar loop to handle remainder. + \ | + \ v + >[ ] <-- exit block. + ... + */ + + BasicBlock *OldBasicBlock = OrigLoop->getHeader(); + BasicBlock *BypassBlock = OrigLoop->getLoopPreheader(); + BasicBlock *ExitBlock = OrigLoop->getExitBlock(); + assert(ExitBlock && "Must have an exit block"); + + // Some loops have a single integer induction variable, while other loops + // don't. One example is c++ iterators that often have multiple pointer + // induction variables. In the code below we also support a case where we + // don't have a single induction variable. + OldInduction = Legal->getInduction(); + Type *IdxTy = OldInduction ? OldInduction->getType() : + DL->getIntPtrType(SE->getContext()); + + // Find the loop boundaries. + const SCEV *ExitCount = SE->getExitCount(OrigLoop, OrigLoop->getLoopLatch()); + assert(ExitCount != SE->getCouldNotCompute() && "Invalid loop count"); + + // Get the total trip count from the count by adding 1. + ExitCount = SE->getAddExpr(ExitCount, + SE->getConstant(ExitCount->getType(), 1)); + + // Expand the trip count and place the new instructions in the preheader. + // Notice that the pre-header does not change, only the loop body. + SCEVExpander Exp(*SE, "induction"); + + // Count holds the overall loop count (N). + Value *Count = Exp.expandCodeFor(ExitCount, ExitCount->getType(), + BypassBlock->getTerminator()); + + // The loop index does not have to start at Zero. Find the original start + // value from the induction PHI node. If we don't have an induction variable + // then we know that it starts at zero. + Value *StartIdx = OldInduction ? + OldInduction->getIncomingValueForBlock(BypassBlock): + ConstantInt::get(IdxTy, 0); + + assert(BypassBlock && "Invalid loop structure"); + + // Generate the code that checks in runtime if arrays overlap. + Value *MemoryRuntimeCheck = addRuntimeCheck(Legal, + BypassBlock->getTerminator()); + + // Split the single block loop into the two loop structure described above. + BasicBlock *VectorPH = + BypassBlock->splitBasicBlock(BypassBlock->getTerminator(), "vector.ph"); + BasicBlock *VecBody = + VectorPH->splitBasicBlock(VectorPH->getTerminator(), "vector.body"); + BasicBlock *MiddleBlock = + VecBody->splitBasicBlock(VecBody->getTerminator(), "middle.block"); + BasicBlock *ScalarPH = + MiddleBlock->splitBasicBlock(MiddleBlock->getTerminator(), "scalar.ph"); + + // This is the location in which we add all of the logic for bypassing + // the new vector loop. + Instruction *Loc = BypassBlock->getTerminator(); + + // Use this IR builder to create the loop instructions (Phi, Br, Cmp) + // inside the loop. + Builder.SetInsertPoint(VecBody->getFirstInsertionPt()); + + // Generate the induction variable. + Induction = Builder.CreatePHI(IdxTy, 2, "index"); + // The loop step is equal to the vectorization factor (num of SIMD elements) + // times the unroll factor (num of SIMD instructions). + Constant *Step = ConstantInt::get(IdxTy, VF * UF); + + // We may need to extend the index in case there is a type mismatch. + // We know that the count starts at zero and does not overflow. + if (Count->getType() != IdxTy) { + // The exit count can be of pointer type. Convert it to the correct + // integer type. + if (ExitCount->getType()->isPointerTy()) + Count = CastInst::CreatePointerCast(Count, IdxTy, "ptrcnt.to.int", Loc); + else + Count = CastInst::CreateZExtOrBitCast(Count, IdxTy, "zext.cnt", Loc); + } + + // Add the start index to the loop count to get the new end index. + Value *IdxEnd = BinaryOperator::CreateAdd(Count, StartIdx, "end.idx", Loc); + + // Now we need to generate the expression for N - (N % VF), which is + // the part that the vectorized body will execute. + Value *R = BinaryOperator::CreateURem(Count, Step, "n.mod.vf", Loc); + Value *CountRoundDown = BinaryOperator::CreateSub(Count, R, "n.vec", Loc); + Value *IdxEndRoundDown = BinaryOperator::CreateAdd(CountRoundDown, StartIdx, + "end.idx.rnd.down", Loc); + + // Now, compare the new count to zero. If it is zero skip the vector loop and + // jump to the scalar loop. + Value *Cmp = CmpInst::Create(Instruction::ICmp, CmpInst::ICMP_EQ, + IdxEndRoundDown, + StartIdx, + "cmp.zero", Loc); + + // If we are using memory runtime checks, include them in. + if (MemoryRuntimeCheck) + Cmp = BinaryOperator::Create(Instruction::Or, Cmp, MemoryRuntimeCheck, + "CntOrMem", Loc); + + BranchInst::Create(MiddleBlock, VectorPH, Cmp, Loc); + // Remove the old terminator. + Loc->eraseFromParent(); + + // We are going to resume the execution of the scalar loop. + // Go over all of the induction variables that we found and fix the + // PHIs that are left in the scalar version of the loop. + // The starting values of PHI nodes depend on the counter of the last + // iteration in the vectorized loop. + // If we come from a bypass edge then we need to start from the original + // start value. + + // This variable saves the new starting index for the scalar loop. + PHINode *ResumeIndex = 0; + LoopVectorizationLegality::InductionList::iterator I, E; + LoopVectorizationLegality::InductionList *List = Legal->getInductionVars(); + for (I = List->begin(), E = List->end(); I != E; ++I) { + PHINode *OrigPhi = I->first; + LoopVectorizationLegality::InductionInfo II = I->second; + PHINode *ResumeVal = PHINode::Create(OrigPhi->getType(), 2, "resume.val", + MiddleBlock->getTerminator()); + Value *EndValue = 0; + switch (II.IK) { + case LoopVectorizationLegality::IK_NoInduction: + llvm_unreachable("Unknown induction"); + case LoopVectorizationLegality::IK_IntInduction: { + // Handle the integer induction counter: + assert(OrigPhi->getType()->isIntegerTy() && "Invalid type"); + assert(OrigPhi == OldInduction && "Unknown integer PHI"); + // We know what the end value is. + EndValue = IdxEndRoundDown; + // We also know which PHI node holds it. + ResumeIndex = ResumeVal; + break; + } + case LoopVectorizationLegality::IK_ReverseIntInduction: { + // Convert the CountRoundDown variable to the PHI size. + unsigned CRDSize = CountRoundDown->getType()->getScalarSizeInBits(); + unsigned IISize = II.StartValue->getType()->getScalarSizeInBits(); + Value *CRD = CountRoundDown; + if (CRDSize > IISize) + CRD = CastInst::Create(Instruction::Trunc, CountRoundDown, + II.StartValue->getType(), + "tr.crd", BypassBlock->getTerminator()); + else if (CRDSize < IISize) + CRD = CastInst::Create(Instruction::SExt, CountRoundDown, + II.StartValue->getType(), + "sext.crd", BypassBlock->getTerminator()); + // Handle reverse integer induction counter: + EndValue = BinaryOperator::CreateSub(II.StartValue, CRD, "rev.ind.end", + BypassBlock->getTerminator()); + break; + } + case LoopVectorizationLegality::IK_PtrInduction: { + // For pointer induction variables, calculate the offset using + // the end index. + EndValue = GetElementPtrInst::Create(II.StartValue, CountRoundDown, + "ptr.ind.end", + BypassBlock->getTerminator()); + break; + } + }// end of case + + // The new PHI merges the original incoming value, in case of a bypass, + // or the value at the end of the vectorized loop. + ResumeVal->addIncoming(II.StartValue, BypassBlock); + ResumeVal->addIncoming(EndValue, VecBody); + + // Fix the scalar body counter (PHI node). + unsigned BlockIdx = OrigPhi->getBasicBlockIndex(ScalarPH); + OrigPhi->setIncomingValue(BlockIdx, ResumeVal); + } + + // If we are generating a new induction variable then we also need to + // generate the code that calculates the exit value. This value is not + // simply the end of the counter because we may skip the vectorized body + // in case of a runtime check. + if (!OldInduction){ + assert(!ResumeIndex && "Unexpected resume value found"); + ResumeIndex = PHINode::Create(IdxTy, 2, "new.indc.resume.val", + MiddleBlock->getTerminator()); + ResumeIndex->addIncoming(StartIdx, BypassBlock); + ResumeIndex->addIncoming(IdxEndRoundDown, VecBody); + } + + // Make sure that we found the index where scalar loop needs to continue. + assert(ResumeIndex && ResumeIndex->getType()->isIntegerTy() && + "Invalid resume Index"); + + // Add a check in the middle block to see if we have completed + // all of the iterations in the first vector loop. + // If (N - N%VF) == N, then we *don't* need to run the remainder. + Value *CmpN = CmpInst::Create(Instruction::ICmp, CmpInst::ICMP_EQ, IdxEnd, + ResumeIndex, "cmp.n", + MiddleBlock->getTerminator()); + + BranchInst::Create(ExitBlock, ScalarPH, CmpN, MiddleBlock->getTerminator()); + // Remove the old terminator. + MiddleBlock->getTerminator()->eraseFromParent(); + + // Create i+1 and fill the PHINode. + Value *NextIdx = Builder.CreateAdd(Induction, Step, "index.next"); + Induction->addIncoming(StartIdx, VectorPH); + Induction->addIncoming(NextIdx, VecBody); + // Create the compare. + Value *ICmp = Builder.CreateICmpEQ(NextIdx, IdxEndRoundDown); + Builder.CreateCondBr(ICmp, MiddleBlock, VecBody); + + // Now we have two terminators. Remove the old one from the block. + VecBody->getTerminator()->eraseFromParent(); + + // Get ready to start creating new instructions into the vectorized body. + Builder.SetInsertPoint(VecBody->getFirstInsertionPt()); + + // Create and register the new vector loop. + Loop* Lp = new Loop(); + Loop *ParentLoop = OrigLoop->getParentLoop(); + + // Insert the new loop into the loop nest and register the new basic blocks. + if (ParentLoop) { + ParentLoop->addChildLoop(Lp); + ParentLoop->addBasicBlockToLoop(ScalarPH, LI->getBase()); + ParentLoop->addBasicBlockToLoop(VectorPH, LI->getBase()); + ParentLoop->addBasicBlockToLoop(MiddleBlock, LI->getBase()); + } else { + LI->addTopLevelLoop(Lp); + } + + Lp->addBasicBlockToLoop(VecBody, LI->getBase()); + + // Save the state. + LoopVectorPreHeader = VectorPH; + LoopScalarPreHeader = ScalarPH; + LoopMiddleBlock = MiddleBlock; + LoopExitBlock = ExitBlock; + LoopVectorBody = VecBody; + LoopScalarBody = OldBasicBlock; + LoopBypassBlock = BypassBlock; +} + +/// This function returns the identity element (or neutral element) for +/// the operation K. +static Constant* +getReductionIdentity(LoopVectorizationLegality::ReductionKind K, Type *Tp) { + switch (K) { + case LoopVectorizationLegality:: RK_IntegerXor: + case LoopVectorizationLegality:: RK_IntegerAdd: + case LoopVectorizationLegality:: RK_IntegerOr: + // Adding, Xoring, Oring zero to a number does not change it. + return ConstantInt::get(Tp, 0); + case LoopVectorizationLegality:: RK_IntegerMult: + // Multiplying a number by 1 does not change it. + return ConstantInt::get(Tp, 1); + case LoopVectorizationLegality:: RK_IntegerAnd: + // AND-ing a number with an all-1 value does not change it. + return ConstantInt::get(Tp, -1, true); + case LoopVectorizationLegality:: RK_FloatMult: + // Multiplying a number by 1 does not change it. + return ConstantFP::get(Tp, 1.0L); + case LoopVectorizationLegality:: RK_FloatAdd: + // Adding zero to a number does not change it. + return ConstantFP::get(Tp, 0.0L); + default: + llvm_unreachable("Unknown reduction kind"); + } +} + +static bool +isTriviallyVectorizableIntrinsic(Instruction *Inst) { + IntrinsicInst *II = dyn_cast<IntrinsicInst>(Inst); + if (!II) + return false; + switch (II->getIntrinsicID()) { + case Intrinsic::sqrt: + case Intrinsic::sin: + case Intrinsic::cos: + case Intrinsic::exp: + case Intrinsic::exp2: + case Intrinsic::log: + case Intrinsic::log10: + case Intrinsic::log2: + case Intrinsic::fabs: + case Intrinsic::floor: + case Intrinsic::ceil: + case Intrinsic::trunc: + case Intrinsic::rint: + case Intrinsic::nearbyint: + case Intrinsic::pow: + case Intrinsic::fma: + case Intrinsic::fmuladd: + return true; + default: + return false; + } + return false; +} + +/// This function translates the reduction kind to an LLVM binary operator. +static Instruction::BinaryOps +getReductionBinOp(LoopVectorizationLegality::ReductionKind Kind) { + switch (Kind) { + case LoopVectorizationLegality::RK_IntegerAdd: + return Instruction::Add; + case LoopVectorizationLegality::RK_IntegerMult: + return Instruction::Mul; + case LoopVectorizationLegality::RK_IntegerOr: + return Instruction::Or; + case LoopVectorizationLegality::RK_IntegerAnd: + return Instruction::And; + case LoopVectorizationLegality::RK_IntegerXor: + return Instruction::Xor; + case LoopVectorizationLegality::RK_FloatMult: + return Instruction::FMul; + case LoopVectorizationLegality::RK_FloatAdd: + return Instruction::FAdd; + default: + llvm_unreachable("Unknown reduction operation"); + } +} + +void +InnerLoopVectorizer::vectorizeLoop(LoopVectorizationLegality *Legal) { + //===------------------------------------------------===// + // + // Notice: any optimization or new instruction that go + // into the code below should be also be implemented in + // the cost-model. + // + //===------------------------------------------------===// + BasicBlock &BB = *OrigLoop->getHeader(); + Constant *Zero = + ConstantInt::get(IntegerType::getInt32Ty(BB.getContext()), 0); + + // In order to support reduction variables we need to be able to vectorize + // Phi nodes. Phi nodes have cycles, so we need to vectorize them in two + // stages. First, we create a new vector PHI node with no incoming edges. + // We use this value when we vectorize all of the instructions that use the + // PHI. Next, after all of the instructions in the block are complete we + // add the new incoming edges to the PHI. At this point all of the + // instructions in the basic block are vectorized, so we can use them to + // construct the PHI. + PhiVector RdxPHIsToFix; + + // Scan the loop in a topological order to ensure that defs are vectorized + // before users. + LoopBlocksDFS DFS(OrigLoop); + DFS.perform(LI); + + // Vectorize all of the blocks in the original loop. + for (LoopBlocksDFS::RPOIterator bb = DFS.beginRPO(), + be = DFS.endRPO(); bb != be; ++bb) + vectorizeBlockInLoop(Legal, *bb, &RdxPHIsToFix); + + // At this point every instruction in the original loop is widened to + // a vector form. We are almost done. Now, we need to fix the PHI nodes + // that we vectorized. The PHI nodes are currently empty because we did + // not want to introduce cycles. Notice that the remaining PHI nodes + // that we need to fix are reduction variables. + + // Create the 'reduced' values for each of the induction vars. + // The reduced values are the vector values that we scalarize and combine + // after the loop is finished. + for (PhiVector::iterator it = RdxPHIsToFix.begin(), e = RdxPHIsToFix.end(); + it != e; ++it) { + PHINode *RdxPhi = *it; + assert(RdxPhi && "Unable to recover vectorized PHI"); + + // Find the reduction variable descriptor. + assert(Legal->getReductionVars()->count(RdxPhi) && + "Unable to find the reduction variable"); + LoopVectorizationLegality::ReductionDescriptor RdxDesc = + (*Legal->getReductionVars())[RdxPhi]; + + // We need to generate a reduction vector from the incoming scalar. + // To do so, we need to generate the 'identity' vector and overide + // one of the elements with the incoming scalar reduction. We need + // to do it in the vector-loop preheader. + Builder.SetInsertPoint(LoopBypassBlock->getTerminator()); + + // This is the vector-clone of the value that leaves the loop. + VectorParts &VectorExit = getVectorValue(RdxDesc.LoopExitInstr); + Type *VecTy = VectorExit[0]->getType(); + + // Find the reduction identity variable. Zero for addition, or, xor, + // one for multiplication, -1 for And. + Constant *Iden = getReductionIdentity(RdxDesc.Kind, VecTy->getScalarType()); + Constant *Identity = ConstantVector::getSplat(VF, Iden); + + // This vector is the Identity vector where the first element is the + // incoming scalar reduction. + Value *VectorStart = Builder.CreateInsertElement(Identity, + RdxDesc.StartValue, Zero); + + // Fix the vector-loop phi. + // We created the induction variable so we know that the + // preheader is the first entry. + BasicBlock *VecPreheader = Induction->getIncomingBlock(0); + + // Reductions do not have to start at zero. They can start with + // any loop invariant values. + VectorParts &VecRdxPhi = WidenMap.get(RdxPhi); + BasicBlock *Latch = OrigLoop->getLoopLatch(); + Value *LoopVal = RdxPhi->getIncomingValueForBlock(Latch); + VectorParts &Val = getVectorValue(LoopVal); + for (unsigned part = 0; part < UF; ++part) { + // Make sure to add the reduction stat value only to the + // first unroll part. + Value *StartVal = (part == 0) ? VectorStart : Identity; + cast<PHINode>(VecRdxPhi[part])->addIncoming(StartVal, VecPreheader); + cast<PHINode>(VecRdxPhi[part])->addIncoming(Val[part], LoopVectorBody); + } + + // Before each round, move the insertion point right between + // the PHIs and the values we are going to write. + // This allows us to write both PHINodes and the extractelement + // instructions. + Builder.SetInsertPoint(LoopMiddleBlock->getFirstInsertionPt()); + + VectorParts RdxParts; + for (unsigned part = 0; part < UF; ++part) { + // This PHINode contains the vectorized reduction variable, or + // the initial value vector, if we bypass the vector loop. + VectorParts &RdxExitVal = getVectorValue(RdxDesc.LoopExitInstr); + PHINode *NewPhi = Builder.CreatePHI(VecTy, 2, "rdx.vec.exit.phi"); + Value *StartVal = (part == 0) ? VectorStart : Identity; + NewPhi->addIncoming(StartVal, LoopBypassBlock); + NewPhi->addIncoming(RdxExitVal[part], LoopVectorBody); + RdxParts.push_back(NewPhi); + } + + // Reduce all of the unrolled parts into a single vector. + Value *ReducedPartRdx = RdxParts[0]; + for (unsigned part = 1; part < UF; ++part) { + Instruction::BinaryOps Op = getReductionBinOp(RdxDesc.Kind); + ReducedPartRdx = Builder.CreateBinOp(Op, RdxParts[part], ReducedPartRdx, + "bin.rdx"); + } + + // VF is a power of 2 so we can emit the reduction using log2(VF) shuffles + // and vector ops, reducing the set of values being computed by half each + // round. + assert(isPowerOf2_32(VF) && + "Reduction emission only supported for pow2 vectors!"); + Value *TmpVec = ReducedPartRdx; + SmallVector<Constant*, 32> ShuffleMask(VF, 0); + for (unsigned i = VF; i != 1; i >>= 1) { + // Move the upper half of the vector to the lower half. + for (unsigned j = 0; j != i/2; ++j) + ShuffleMask[j] = Builder.getInt32(i/2 + j); + + // Fill the rest of the mask with undef. + std::fill(&ShuffleMask[i/2], ShuffleMask.end(), + UndefValue::get(Builder.getInt32Ty())); + + Value *Shuf = + Builder.CreateShuffleVector(TmpVec, + UndefValue::get(TmpVec->getType()), + ConstantVector::get(ShuffleMask), + "rdx.shuf"); + + Instruction::BinaryOps Op = getReductionBinOp(RdxDesc.Kind); + TmpVec = Builder.CreateBinOp(Op, TmpVec, Shuf, "bin.rdx"); + } + + // The result is in the first element of the vector. + Value *Scalar0 = Builder.CreateExtractElement(TmpVec, Builder.getInt32(0)); + + // Now, we need to fix the users of the reduction variable + // inside and outside of the scalar remainder loop. + // We know that the loop is in LCSSA form. We need to update the + // PHI nodes in the exit blocks. + for (BasicBlock::iterator LEI = LoopExitBlock->begin(), + LEE = LoopExitBlock->end(); LEI != LEE; ++LEI) { + PHINode *LCSSAPhi = dyn_cast<PHINode>(LEI); + if (!LCSSAPhi) continue; + + // All PHINodes need to have a single entry edge, or two if + // we already fixed them. + assert(LCSSAPhi->getNumIncomingValues() < 3 && "Invalid LCSSA PHI"); + + // We found our reduction value exit-PHI. Update it with the + // incoming bypass edge. + if (LCSSAPhi->getIncomingValue(0) == RdxDesc.LoopExitInstr) { + // Add an edge coming from the bypass. + LCSSAPhi->addIncoming(Scalar0, LoopMiddleBlock); + break; + } + }// end of the LCSSA phi scan. + + // Fix the scalar loop reduction variable with the incoming reduction sum + // from the vector body and from the backedge value. + int IncomingEdgeBlockIdx = + (RdxPhi)->getBasicBlockIndex(OrigLoop->getLoopLatch()); + assert(IncomingEdgeBlockIdx >= 0 && "Invalid block index"); + // Pick the other block. + int SelfEdgeBlockIdx = (IncomingEdgeBlockIdx ? 0 : 1); + (RdxPhi)->setIncomingValue(SelfEdgeBlockIdx, Scalar0); + (RdxPhi)->setIncomingValue(IncomingEdgeBlockIdx, RdxDesc.LoopExitInstr); + }// end of for each redux variable. + + // The Loop exit block may have single value PHI nodes where the incoming + // value is 'undef'. While vectorizing we only handled real values that + // were defined inside the loop. Here we handle the 'undef case'. + // See PR14725. + for (BasicBlock::iterator LEI = LoopExitBlock->begin(), + LEE = LoopExitBlock->end(); LEI != LEE; ++LEI) { + PHINode *LCSSAPhi = dyn_cast<PHINode>(LEI); + if (!LCSSAPhi) continue; + if (LCSSAPhi->getNumIncomingValues() == 1) + LCSSAPhi->addIncoming(UndefValue::get(LCSSAPhi->getType()), + LoopMiddleBlock); + } +} + +InnerLoopVectorizer::VectorParts +InnerLoopVectorizer::createEdgeMask(BasicBlock *Src, BasicBlock *Dst) { + assert(std::find(pred_begin(Dst), pred_end(Dst), Src) != pred_end(Dst) && + "Invalid edge"); + + VectorParts SrcMask = createBlockInMask(Src); + + // The terminator has to be a branch inst! + BranchInst *BI = dyn_cast<BranchInst>(Src->getTerminator()); + assert(BI && "Unexpected terminator found"); + + if (BI->isConditional()) { + VectorParts EdgeMask = getVectorValue(BI->getCondition()); + + if (BI->getSuccessor(0) != Dst) + for (unsigned part = 0; part < UF; ++part) + EdgeMask[part] = Builder.CreateNot(EdgeMask[part]); + + for (unsigned part = 0; part < UF; ++part) + EdgeMask[part] = Builder.CreateAnd(EdgeMask[part], SrcMask[part]); + return EdgeMask; + } + + return SrcMask; +} + +InnerLoopVectorizer::VectorParts +InnerLoopVectorizer::createBlockInMask(BasicBlock *BB) { + assert(OrigLoop->contains(BB) && "Block is not a part of a loop"); + + // Loop incoming mask is all-one. + if (OrigLoop->getHeader() == BB) { + Value *C = ConstantInt::get(IntegerType::getInt1Ty(BB->getContext()), 1); + return getVectorValue(C); + } + + // This is the block mask. We OR all incoming edges, and with zero. + Value *Zero = ConstantInt::get(IntegerType::getInt1Ty(BB->getContext()), 0); + VectorParts BlockMask = getVectorValue(Zero); + + // For each pred: + for (pred_iterator it = pred_begin(BB), e = pred_end(BB); it != e; ++it) { + VectorParts EM = createEdgeMask(*it, BB); + for (unsigned part = 0; part < UF; ++part) + BlockMask[part] = Builder.CreateOr(BlockMask[part], EM[part]); + } + + return BlockMask; +} + +void +InnerLoopVectorizer::vectorizeBlockInLoop(LoopVectorizationLegality *Legal, + BasicBlock *BB, PhiVector *PV) { + Constant *Zero = Builder.getInt32(0); + + // For each instruction in the old loop. + for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { + VectorParts &Entry = WidenMap.get(it); + switch (it->getOpcode()) { + case Instruction::Br: + // Nothing to do for PHIs and BR, since we already took care of the + // loop control flow instructions. + continue; + case Instruction::PHI:{ + PHINode* P = cast<PHINode>(it); + // Handle reduction variables: + if (Legal->getReductionVars()->count(P)) { + for (unsigned part = 0; part < UF; ++part) { + // This is phase one of vectorizing PHIs. + Type *VecTy = VectorType::get(it->getType(), VF); + Entry[part] = PHINode::Create(VecTy, 2, "vec.phi", + LoopVectorBody-> getFirstInsertionPt()); + } + PV->push_back(P); + continue; + } + + // Check for PHI nodes that are lowered to vector selects. + if (P->getParent() != OrigLoop->getHeader()) { + // We know that all PHIs in non header blocks are converted into + // selects, so we don't have to worry about the insertion order and we + // can just use the builder. + + // At this point we generate the predication tree. There may be + // duplications since this is a simple recursive scan, but future + // optimizations will clean it up. + VectorParts Cond = createEdgeMask(P->getIncomingBlock(0), + P->getParent()); + + for (unsigned part = 0; part < UF; ++part) { + VectorParts &In0 = getVectorValue(P->getIncomingValue(0)); + VectorParts &In1 = getVectorValue(P->getIncomingValue(1)); + Entry[part] = Builder.CreateSelect(Cond[part], In0[part], In1[part], + "predphi"); + } + continue; + } + + // This PHINode must be an induction variable. + // Make sure that we know about it. + assert(Legal->getInductionVars()->count(P) && + "Not an induction variable"); + + LoopVectorizationLegality::InductionInfo II = + Legal->getInductionVars()->lookup(P); + + switch (II.IK) { + case LoopVectorizationLegality::IK_NoInduction: + llvm_unreachable("Unknown induction"); + case LoopVectorizationLegality::IK_IntInduction: { + assert(P == OldInduction && "Unexpected PHI"); + Value *Broadcasted = getBroadcastInstrs(Induction); + // After broadcasting the induction variable we need to make the + // vector consecutive by adding 0, 1, 2 ... + for (unsigned part = 0; part < UF; ++part) + Entry[part] = getConsecutiveVector(Broadcasted, VF * part, false); + continue; + } + case LoopVectorizationLegality::IK_ReverseIntInduction: + case LoopVectorizationLegality::IK_PtrInduction: + // Handle reverse integer and pointer inductions. + Value *StartIdx = 0; + // If we have a single integer induction variable then use it. + // Otherwise, start counting at zero. + if (OldInduction) { + LoopVectorizationLegality::InductionInfo OldII = + Legal->getInductionVars()->lookup(OldInduction); + StartIdx = OldII.StartValue; + } else { + StartIdx = ConstantInt::get(Induction->getType(), 0); + } + // This is the normalized GEP that starts counting at zero. + Value *NormalizedIdx = Builder.CreateSub(Induction, StartIdx, + "normalized.idx"); + + // Handle the reverse integer induction variable case. + if (LoopVectorizationLegality::IK_ReverseIntInduction == II.IK) { + IntegerType *DstTy = cast<IntegerType>(II.StartValue->getType()); + Value *CNI = Builder.CreateSExtOrTrunc(NormalizedIdx, DstTy, + "resize.norm.idx"); + Value *ReverseInd = Builder.CreateSub(II.StartValue, CNI, + "reverse.idx"); + + // This is a new value so do not hoist it out. + Value *Broadcasted = getBroadcastInstrs(ReverseInd); + // After broadcasting the induction variable we need to make the + // vector consecutive by adding ... -3, -2, -1, 0. + for (unsigned part = 0; part < UF; ++part) + Entry[part] = getConsecutiveVector(Broadcasted, -VF * part, true); + continue; + } + + // Handle the pointer induction variable case. + assert(P->getType()->isPointerTy() && "Unexpected type."); + + // This is the vector of results. Notice that we don't generate + // vector geps because scalar geps result in better code. + for (unsigned part = 0; part < UF; ++part) { + Value *VecVal = UndefValue::get(VectorType::get(P->getType(), VF)); + for (unsigned int i = 0; i < VF; ++i) { + Constant *Idx = ConstantInt::get(Induction->getType(), + i + part * VF); + Value *GlobalIdx = Builder.CreateAdd(NormalizedIdx, Idx, + "gep.idx"); + Value *SclrGep = Builder.CreateGEP(II.StartValue, GlobalIdx, + "next.gep"); + VecVal = Builder.CreateInsertElement(VecVal, SclrGep, + Builder.getInt32(i), + "insert.gep"); + } + Entry[part] = VecVal; + } + continue; + } + + }// End of PHI. + + case Instruction::Add: + case Instruction::FAdd: + case Instruction::Sub: + case Instruction::FSub: + case Instruction::Mul: + case Instruction::FMul: + case Instruction::UDiv: + case Instruction::SDiv: + case Instruction::FDiv: + case Instruction::URem: + case Instruction::SRem: + case Instruction::FRem: + case Instruction::Shl: + case Instruction::LShr: + case Instruction::AShr: + case Instruction::And: + case Instruction::Or: + case Instruction::Xor: { + // Just widen binops. + BinaryOperator *BinOp = dyn_cast<BinaryOperator>(it); + VectorParts &A = getVectorValue(it->getOperand(0)); + VectorParts &B = getVectorValue(it->getOperand(1)); + + // Use this vector value for all users of the original instruction. + for (unsigned Part = 0; Part < UF; ++Part) { + Value *V = Builder.CreateBinOp(BinOp->getOpcode(), A[Part], B[Part]); + + // Update the NSW, NUW and Exact flags. + BinaryOperator *VecOp = cast<BinaryOperator>(V); + if (isa<OverflowingBinaryOperator>(BinOp)) { + VecOp->setHasNoSignedWrap(BinOp->hasNoSignedWrap()); + VecOp->setHasNoUnsignedWrap(BinOp->hasNoUnsignedWrap()); + } + if (isa<PossiblyExactOperator>(VecOp)) + VecOp->setIsExact(BinOp->isExact()); + + Entry[Part] = V; + } + break; + } + case Instruction::Select: { + // Widen selects. + // If the selector is loop invariant we can create a select + // instruction with a scalar condition. Otherwise, use vector-select. + bool InvariantCond = SE->isLoopInvariant(SE->getSCEV(it->getOperand(0)), + OrigLoop); + + // The condition can be loop invariant but still defined inside the + // loop. This means that we can't just use the original 'cond' value. + // We have to take the 'vectorized' value and pick the first lane. + // Instcombine will make this a no-op. + VectorParts &Cond = getVectorValue(it->getOperand(0)); + VectorParts &Op0 = getVectorValue(it->getOperand(1)); + VectorParts &Op1 = getVectorValue(it->getOperand(2)); + Value *ScalarCond = Builder.CreateExtractElement(Cond[0], + Builder.getInt32(0)); + for (unsigned Part = 0; Part < UF; ++Part) { + Entry[Part] = Builder.CreateSelect( + InvariantCond ? ScalarCond : Cond[Part], + Op0[Part], + Op1[Part]); + } + break; + } + + case Instruction::ICmp: + case Instruction::FCmp: { + // Widen compares. Generate vector compares. + bool FCmp = (it->getOpcode() == Instruction::FCmp); + CmpInst *Cmp = dyn_cast<CmpInst>(it); + VectorParts &A = getVectorValue(it->getOperand(0)); + VectorParts &B = getVectorValue(it->getOperand(1)); + for (unsigned Part = 0; Part < UF; ++Part) { + Value *C = 0; + if (FCmp) + C = Builder.CreateFCmp(Cmp->getPredicate(), A[Part], B[Part]); + else + C = Builder.CreateICmp(Cmp->getPredicate(), A[Part], B[Part]); + Entry[Part] = C; + } + break; + } + + case Instruction::Store: { + // Attempt to issue a wide store. + StoreInst *SI = dyn_cast<StoreInst>(it); + Type *StTy = VectorType::get(SI->getValueOperand()->getType(), VF); + Value *Ptr = SI->getPointerOperand(); + unsigned Alignment = SI->getAlignment(); + + assert(!Legal->isUniform(Ptr) && + "We do not allow storing to uniform addresses"); + + + int Stride = Legal->isConsecutivePtr(Ptr); + bool Reverse = Stride < 0; + if (Stride == 0) { + scalarizeInstruction(it); + break; + } + + // Handle consecutive stores. + + GetElementPtrInst *Gep = dyn_cast<GetElementPtrInst>(Ptr); + if (Gep) { + // The last index does not have to be the induction. It can be + // consecutive and be a function of the index. For example A[I+1]; + unsigned NumOperands = Gep->getNumOperands(); + + Value *LastGepOperand = Gep->getOperand(NumOperands - 1); + VectorParts &GEPParts = getVectorValue(LastGepOperand); + Value *LastIndex = GEPParts[0]; + LastIndex = Builder.CreateExtractElement(LastIndex, Zero); + + // Create the new GEP with the new induction variable. + GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone()); + Gep2->setOperand(NumOperands - 1, LastIndex); + Ptr = Builder.Insert(Gep2); + } else { + // Use the induction element ptr. + assert(isa<PHINode>(Ptr) && "Invalid induction ptr"); + VectorParts &PtrVal = getVectorValue(Ptr); + Ptr = Builder.CreateExtractElement(PtrVal[0], Zero); + } + + VectorParts &StoredVal = getVectorValue(SI->getValueOperand()); + for (unsigned Part = 0; Part < UF; ++Part) { + // Calculate the pointer for the specific unroll-part. + Value *PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(Part * VF)); + + if (Reverse) { + // If we store to reverse consecutive memory locations then we need + // to reverse the order of elements in the stored value. + StoredVal[Part] = reverseVector(StoredVal[Part]); + // If the address is consecutive but reversed, then the + // wide store needs to start at the last vector element. + PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(-Part * VF)); + PartPtr = Builder.CreateGEP(PartPtr, Builder.getInt32(1 - VF)); + } + + Value *VecPtr = Builder.CreateBitCast(PartPtr, StTy->getPointerTo()); + Builder.CreateStore(StoredVal[Part], VecPtr)->setAlignment(Alignment); + } + break; + } + case Instruction::Load: { + // Attempt to issue a wide load. + LoadInst *LI = dyn_cast<LoadInst>(it); + Type *RetTy = VectorType::get(LI->getType(), VF); + Value *Ptr = LI->getPointerOperand(); + unsigned Alignment = LI->getAlignment(); + + // If the pointer is loop invariant or if it is non consecutive, + // scalarize the load. + int Stride = Legal->isConsecutivePtr(Ptr); + bool Reverse = Stride < 0; + if (Legal->isUniform(Ptr) || Stride == 0) { + scalarizeInstruction(it); + break; + } + + GetElementPtrInst *Gep = dyn_cast<GetElementPtrInst>(Ptr); + if (Gep) { + // The last index does not have to be the induction. It can be + // consecutive and be a function of the index. For example A[I+1]; + unsigned NumOperands = Gep->getNumOperands(); + + Value *LastGepOperand = Gep->getOperand(NumOperands - 1); + VectorParts &GEPParts = getVectorValue(LastGepOperand); + Value *LastIndex = GEPParts[0]; + LastIndex = Builder.CreateExtractElement(LastIndex, Zero); + + // Create the new GEP with the new induction variable. + GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone()); + Gep2->setOperand(NumOperands - 1, LastIndex); + Ptr = Builder.Insert(Gep2); + } else { + // Use the induction element ptr. + assert(isa<PHINode>(Ptr) && "Invalid induction ptr"); + VectorParts &PtrVal = getVectorValue(Ptr); + Ptr = Builder.CreateExtractElement(PtrVal[0], Zero); + } + + for (unsigned Part = 0; Part < UF; ++Part) { + // Calculate the pointer for the specific unroll-part. + Value *PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(Part * VF)); + + if (Reverse) { + // If the address is consecutive but reversed, then the + // wide store needs to start at the last vector element. + PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(-Part * VF)); + PartPtr = Builder.CreateGEP(PartPtr, Builder.getInt32(1 - VF)); + } + + Value *VecPtr = Builder.CreateBitCast(PartPtr, RetTy->getPointerTo()); + Value *LI = Builder.CreateLoad(VecPtr, "wide.load"); + cast<LoadInst>(LI)->setAlignment(Alignment); + Entry[Part] = Reverse ? reverseVector(LI) : LI; + } + break; + } + case Instruction::ZExt: + case Instruction::SExt: + case Instruction::FPToUI: + case Instruction::FPToSI: + case Instruction::FPExt: + case Instruction::PtrToInt: + case Instruction::IntToPtr: + case Instruction::SIToFP: + case Instruction::UIToFP: + case Instruction::Trunc: + case Instruction::FPTrunc: + case Instruction::BitCast: { + CastInst *CI = dyn_cast<CastInst>(it); + /// Optimize the special case where the source is the induction + /// variable. Notice that we can only optimize the 'trunc' case + /// because: a. FP conversions lose precision, b. sext/zext may wrap, + /// c. other casts depend on pointer size. + if (CI->getOperand(0) == OldInduction && + it->getOpcode() == Instruction::Trunc) { + Value *ScalarCast = Builder.CreateCast(CI->getOpcode(), Induction, + CI->getType()); + Value *Broadcasted = getBroadcastInstrs(ScalarCast); + for (unsigned Part = 0; Part < UF; ++Part) + Entry[Part] = getConsecutiveVector(Broadcasted, VF * Part, false); + break; + } + /// Vectorize casts. + Type *DestTy = VectorType::get(CI->getType()->getScalarType(), VF); + + VectorParts &A = getVectorValue(it->getOperand(0)); + for (unsigned Part = 0; Part < UF; ++Part) + Entry[Part] = Builder.CreateCast(CI->getOpcode(), A[Part], DestTy); + break; + } + + case Instruction::Call: { + assert(isTriviallyVectorizableIntrinsic(it)); + Module *M = BB->getParent()->getParent(); + IntrinsicInst *II = cast<IntrinsicInst>(it); + Intrinsic::ID ID = II->getIntrinsicID(); + for (unsigned Part = 0; Part < UF; ++Part) { + SmallVector<Value*, 4> Args; + for (unsigned i = 0, ie = II->getNumArgOperands(); i != ie; ++i) { + VectorParts &Arg = getVectorValue(II->getArgOperand(i)); + Args.push_back(Arg[Part]); + } + Type *Tys[] = { VectorType::get(II->getType()->getScalarType(), VF) }; + Function *F = Intrinsic::getDeclaration(M, ID, Tys); + Entry[Part] = Builder.CreateCall(F, Args); + } + break; + } + + default: + // All other instructions are unsupported. Scalarize them. + scalarizeInstruction(it); + break; + }// end of switch. + }// end of for_each instr. +} + +void InnerLoopVectorizer::updateAnalysis() { + // Forget the original basic block. + SE->forgetLoop(OrigLoop); + + // Update the dominator tree information. + assert(DT->properlyDominates(LoopBypassBlock, LoopExitBlock) && + "Entry does not dominate exit."); + + DT->addNewBlock(LoopVectorPreHeader, LoopBypassBlock); + DT->addNewBlock(LoopVectorBody, LoopVectorPreHeader); + DT->addNewBlock(LoopMiddleBlock, LoopBypassBlock); + DT->addNewBlock(LoopScalarPreHeader, LoopMiddleBlock); + DT->changeImmediateDominator(LoopScalarBody, LoopScalarPreHeader); + DT->changeImmediateDominator(LoopExitBlock, LoopMiddleBlock); + + DEBUG(DT->verifyAnalysis()); +} + +bool LoopVectorizationLegality::canVectorizeWithIfConvert() { + if (!EnableIfConversion) + return false; + + assert(TheLoop->getNumBlocks() > 1 && "Single block loops are vectorizable"); + std::vector<BasicBlock*> &LoopBlocks = TheLoop->getBlocksVector(); + + // Collect the blocks that need predication. + for (unsigned i = 0, e = LoopBlocks.size(); i < e; ++i) { + BasicBlock *BB = LoopBlocks[i]; + + // We don't support switch statements inside loops. + if (!isa<BranchInst>(BB->getTerminator())) + return false; + + // We must have at most two predecessors because we need to convert + // all PHIs to selects. + unsigned Preds = std::distance(pred_begin(BB), pred_end(BB)); + if (Preds > 2) + return false; + + // We must be able to predicate all blocks that need to be predicated. + if (blockNeedsPredication(BB) && !blockCanBePredicated(BB)) + return false; + } + + // We can if-convert this loop. + return true; +} + +bool LoopVectorizationLegality::canVectorize() { + assert(TheLoop->getLoopPreheader() && "No preheader!!"); + + // We can only vectorize innermost loops. + if (TheLoop->getSubLoopsVector().size()) + return false; + + // We must have a single backedge. + if (TheLoop->getNumBackEdges() != 1) + return false; + + // We must have a single exiting block. + if (!TheLoop->getExitingBlock()) + return false; + + unsigned NumBlocks = TheLoop->getNumBlocks(); + + // Check if we can if-convert non single-bb loops. + if (NumBlocks != 1 && !canVectorizeWithIfConvert()) { + DEBUG(dbgs() << "LV: Can't if-convert the loop.\n"); + return false; + } + + // We need to have a loop header. + BasicBlock *Latch = TheLoop->getLoopLatch(); + DEBUG(dbgs() << "LV: Found a loop: " << + TheLoop->getHeader()->getName() << "\n"); + + // ScalarEvolution needs to be able to find the exit count. + const SCEV *ExitCount = SE->getExitCount(TheLoop, Latch); + if (ExitCount == SE->getCouldNotCompute()) { + DEBUG(dbgs() << "LV: SCEV could not compute the loop exit count.\n"); + return false; + } + + // Do not loop-vectorize loops with a tiny trip count. + unsigned TC = SE->getSmallConstantTripCount(TheLoop, Latch); + if (TC > 0u && TC < TinyTripCountVectorThreshold) { + DEBUG(dbgs() << "LV: Found a loop with a very small trip count. " << + "This loop is not worth vectorizing.\n"); + return false; + } + + // Check if we can vectorize the instructions and CFG in this loop. + if (!canVectorizeInstrs()) { + DEBUG(dbgs() << "LV: Can't vectorize the instructions or CFG\n"); + return false; + } + + // Go over each instruction and look at memory deps. + if (!canVectorizeMemory()) { + DEBUG(dbgs() << "LV: Can't vectorize due to memory conflicts\n"); + return false; + } + + // Collect all of the variables that remain uniform after vectorization. + collectLoopUniforms(); + + DEBUG(dbgs() << "LV: We can vectorize this loop" << + (PtrRtCheck.Need ? " (with a runtime bound check)" : "") + <<"!\n"); + + // Okay! We can vectorize. At this point we don't have any other mem analysis + // which may limit our maximum vectorization factor, so just return true with + // no restrictions. + return true; +} + +bool LoopVectorizationLegality::canVectorizeInstrs() { + BasicBlock *PreHeader = TheLoop->getLoopPreheader(); + BasicBlock *Header = TheLoop->getHeader(); + + // For each block in the loop. + for (Loop::block_iterator bb = TheLoop->block_begin(), + be = TheLoop->block_end(); bb != be; ++bb) { + + // Scan the instructions in the block and look for hazards. + for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e; + ++it) { + + if (PHINode *Phi = dyn_cast<PHINode>(it)) { + // This should not happen because the loop should be normalized. + if (Phi->getNumIncomingValues() != 2) { + DEBUG(dbgs() << "LV: Found an invalid PHI.\n"); + return false; + } + + // Check that this PHI type is allowed. + if (!Phi->getType()->isIntegerTy() && + !Phi->getType()->isFloatingPointTy() && + !Phi->getType()->isPointerTy()) { + DEBUG(dbgs() << "LV: Found an non-int non-pointer PHI.\n"); + return false; + } + + // If this PHINode is not in the header block, then we know that we + // can convert it to select during if-conversion. No need to check if + // the PHIs in this block are induction or reduction variables. + if (*bb != Header) + continue; + + // This is the value coming from the preheader. + Value *StartValue = Phi->getIncomingValueForBlock(PreHeader); + // Check if this is an induction variable. + InductionKind IK = isInductionVariable(Phi); + + if (IK_NoInduction != IK) { + // Int inductions are special because we only allow one IV. + if (IK == IK_IntInduction) { + if (Induction) { + DEBUG(dbgs() << "LV: Found too many inductions."<< *Phi <<"\n"); + return false; + } + Induction = Phi; + } + + DEBUG(dbgs() << "LV: Found an induction variable.\n"); + Inductions[Phi] = InductionInfo(StartValue, IK); + continue; + } + + if (AddReductionVar(Phi, RK_IntegerAdd)) { + DEBUG(dbgs() << "LV: Found an ADD reduction PHI."<< *Phi <<"\n"); + continue; + } + if (AddReductionVar(Phi, RK_IntegerMult)) { + DEBUG(dbgs() << "LV: Found a MUL reduction PHI."<< *Phi <<"\n"); + continue; + } + if (AddReductionVar(Phi, RK_IntegerOr)) { + DEBUG(dbgs() << "LV: Found an OR reduction PHI."<< *Phi <<"\n"); + continue; + } + if (AddReductionVar(Phi, RK_IntegerAnd)) { + DEBUG(dbgs() << "LV: Found an AND reduction PHI."<< *Phi <<"\n"); + continue; + } + if (AddReductionVar(Phi, RK_IntegerXor)) { + DEBUG(dbgs() << "LV: Found a XOR reduction PHI."<< *Phi <<"\n"); + continue; + } + if (AddReductionVar(Phi, RK_FloatMult)) { + DEBUG(dbgs() << "LV: Found an FMult reduction PHI."<< *Phi <<"\n"); + continue; + } + if (AddReductionVar(Phi, RK_FloatAdd)) { + DEBUG(dbgs() << "LV: Found an FAdd reduction PHI."<< *Phi <<"\n"); + continue; + } + + DEBUG(dbgs() << "LV: Found an unidentified PHI."<< *Phi <<"\n"); + return false; + }// end of PHI handling + + // We still don't handle functions. + CallInst *CI = dyn_cast<CallInst>(it); + if (CI && !isTriviallyVectorizableIntrinsic(it)) { + DEBUG(dbgs() << "LV: Found a call site.\n"); + return false; + } + + // Check that the instruction return type is vectorizable. + if (!VectorType::isValidElementType(it->getType()) && + !it->getType()->isVoidTy()) { + DEBUG(dbgs() << "LV: Found unvectorizable type." << "\n"); + return false; + } + + // Check that the stored type is vectorizable. + if (StoreInst *ST = dyn_cast<StoreInst>(it)) { + Type *T = ST->getValueOperand()->getType(); + if (!VectorType::isValidElementType(T)) + return false; + } + + // Reduction instructions are allowed to have exit users. + // All other instructions must not have external users. + if (!AllowedExit.count(it)) + //Check that all of the users of the loop are inside the BB. + for (Value::use_iterator I = it->use_begin(), E = it->use_end(); + I != E; ++I) { + Instruction *U = cast<Instruction>(*I); + // This user may be a reduction exit value. + if (!TheLoop->contains(U)) { + DEBUG(dbgs() << "LV: Found an outside user for : "<< *U << "\n"); + return false; + } + } + } // next instr. + + } + + if (!Induction) { + DEBUG(dbgs() << "LV: Did not find one integer induction var.\n"); + assert(getInductionVars()->size() && "No induction variables"); + } + + return true; +} + +void LoopVectorizationLegality::collectLoopUniforms() { + // We now know that the loop is vectorizable! + // Collect variables that will remain uniform after vectorization. + std::vector<Value*> Worklist; + BasicBlock *Latch = TheLoop->getLoopLatch(); + + // Start with the conditional branch and walk up the block. + Worklist.push_back(Latch->getTerminator()->getOperand(0)); + + while (Worklist.size()) { + Instruction *I = dyn_cast<Instruction>(Worklist.back()); + Worklist.pop_back(); + + // Look at instructions inside this loop. + // Stop when reaching PHI nodes. + // TODO: we need to follow values all over the loop, not only in this block. + if (!I || !TheLoop->contains(I) || isa<PHINode>(I)) + continue; + + // This is a known uniform. + Uniforms.insert(I); + + // Insert all operands. + for (int i = 0, Op = I->getNumOperands(); i < Op; ++i) { + Worklist.push_back(I->getOperand(i)); + } + } +} + +bool LoopVectorizationLegality::canVectorizeMemory() { + typedef SmallVector<Value*, 16> ValueVector; + typedef SmallPtrSet<Value*, 16> ValueSet; + // Holds the Load and Store *instructions*. + ValueVector Loads; + ValueVector Stores; + PtrRtCheck.Pointers.clear(); + PtrRtCheck.Need = false; + + // For each block. + for (Loop::block_iterator bb = TheLoop->block_begin(), + be = TheLoop->block_end(); bb != be; ++bb) { + + // Scan the BB and collect legal loads and stores. + for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e; + ++it) { + + // If this is a load, save it. If this instruction can read from memory + // but is not a load, then we quit. Notice that we don't handle function + // calls that read or write. + if (it->mayReadFromMemory()) { + LoadInst *Ld = dyn_cast<LoadInst>(it); + if (!Ld) return false; + if (!Ld->isSimple()) { + DEBUG(dbgs() << "LV: Found a non-simple load.\n"); + return false; + } + Loads.push_back(Ld); + continue; + } + + // Save 'store' instructions. Abort if other instructions write to memory. + if (it->mayWriteToMemory()) { + StoreInst *St = dyn_cast<StoreInst>(it); + if (!St) return false; + if (!St->isSimple()) { + DEBUG(dbgs() << "LV: Found a non-simple store.\n"); + return false; + } + Stores.push_back(St); + } + } // next instr. + } // next block. + + // Now we have two lists that hold the loads and the stores. + // Next, we find the pointers that they use. + + // Check if we see any stores. If there are no stores, then we don't + // care if the pointers are *restrict*. + if (!Stores.size()) { + DEBUG(dbgs() << "LV: Found a read-only loop!\n"); + return true; + } + + // Holds the read and read-write *pointers* that we find. + ValueVector Reads; + ValueVector ReadWrites; + + // Holds the analyzed pointers. We don't want to call GetUnderlyingObjects + // multiple times on the same object. If the ptr is accessed twice, once + // for read and once for write, it will only appear once (on the write + // list). This is okay, since we are going to check for conflicts between + // writes and between reads and writes, but not between reads and reads. + ValueSet Seen; + + ValueVector::iterator I, IE; + for (I = Stores.begin(), IE = Stores.end(); I != IE; ++I) { + StoreInst *ST = cast<StoreInst>(*I); + Value* Ptr = ST->getPointerOperand(); + + if (isUniform(Ptr)) { + DEBUG(dbgs() << "LV: We don't allow storing to uniform addresses\n"); + return false; + } + + // If we did *not* see this pointer before, insert it to + // the read-write list. At this phase it is only a 'write' list. + if (Seen.insert(Ptr)) + ReadWrites.push_back(Ptr); + } + + for (I = Loads.begin(), IE = Loads.end(); I != IE; ++I) { + LoadInst *LD = cast<LoadInst>(*I); + Value* Ptr = LD->getPointerOperand(); + // If we did *not* see this pointer before, insert it to the + // read list. If we *did* see it before, then it is already in + // the read-write list. This allows us to vectorize expressions + // such as A[i] += x; Because the address of A[i] is a read-write + // pointer. This only works if the index of A[i] is consecutive. + // If the address of i is unknown (for example A[B[i]]) then we may + // read a few words, modify, and write a few words, and some of the + // words may be written to the same address. + if (Seen.insert(Ptr) || 0 == isConsecutivePtr(Ptr)) + Reads.push_back(Ptr); + } + + // If we write (or read-write) to a single destination and there are no + // other reads in this loop then is it safe to vectorize. + if (ReadWrites.size() == 1 && Reads.size() == 0) { + DEBUG(dbgs() << "LV: Found a write-only loop!\n"); + return true; + } + + // Find pointers with computable bounds. We are going to use this information + // to place a runtime bound check. + bool CanDoRT = true; + for (I = ReadWrites.begin(), IE = ReadWrites.end(); I != IE; ++I) + if (hasComputableBounds(*I)) { + PtrRtCheck.insert(SE, TheLoop, *I); + DEBUG(dbgs() << "LV: Found a runtime check ptr:" << **I <<"\n"); + } else { + CanDoRT = false; + break; + } + for (I = Reads.begin(), IE = Reads.end(); I != IE; ++I) + if (hasComputableBounds(*I)) { + PtrRtCheck.insert(SE, TheLoop, *I); + DEBUG(dbgs() << "LV: Found a runtime check ptr:" << **I <<"\n"); + } else { + CanDoRT = false; + break; + } + + // Check that we did not collect too many pointers or found a + // unsizeable pointer. + if (!CanDoRT || PtrRtCheck.Pointers.size() > RuntimeMemoryCheckThreshold) { + PtrRtCheck.reset(); + CanDoRT = false; + } + + if (CanDoRT) { + DEBUG(dbgs() << "LV: We can perform a memory runtime check if needed.\n"); + } + + bool NeedRTCheck = false; + + // Now that the pointers are in two lists (Reads and ReadWrites), we + // can check that there are no conflicts between each of the writes and + // between the writes to the reads. + ValueSet WriteObjects; + ValueVector TempObjects; + + // Check that the read-writes do not conflict with other read-write + // pointers. + bool AllWritesIdentified = true; + for (I = ReadWrites.begin(), IE = ReadWrites.end(); I != IE; ++I) { + GetUnderlyingObjects(*I, TempObjects, DL); + for (ValueVector::iterator it=TempObjects.begin(), e=TempObjects.end(); + it != e; ++it) { + if (!isIdentifiedObject(*it)) { + DEBUG(dbgs() << "LV: Found an unidentified write ptr:"<< **it <<"\n"); + NeedRTCheck = true; + AllWritesIdentified = false; + } + if (!WriteObjects.insert(*it)) { + DEBUG(dbgs() << "LV: Found a possible write-write reorder:" + << **it <<"\n"); + return false; + } + } + TempObjects.clear(); + } + + /// Check that the reads don't conflict with the read-writes. + for (I = Reads.begin(), IE = Reads.end(); I != IE; ++I) { + GetUnderlyingObjects(*I, TempObjects, DL); + for (ValueVector::iterator it=TempObjects.begin(), e=TempObjects.end(); + it != e; ++it) { + // If all of the writes are identified then we don't care if the read + // pointer is identified or not. + if (!AllWritesIdentified && !isIdentifiedObject(*it)) { + DEBUG(dbgs() << "LV: Found an unidentified read ptr:"<< **it <<"\n"); + NeedRTCheck = true; + } + if (WriteObjects.count(*it)) { + DEBUG(dbgs() << "LV: Found a possible read/write reorder:" + << **it <<"\n"); + return false; + } + } + TempObjects.clear(); + } + + PtrRtCheck.Need = NeedRTCheck; + if (NeedRTCheck && !CanDoRT) { + DEBUG(dbgs() << "LV: We can't vectorize because we can't find " << + "the array bounds.\n"); + PtrRtCheck.reset(); + return false; + } + + DEBUG(dbgs() << "LV: We "<< (NeedRTCheck ? "" : "don't") << + " need a runtime memory check.\n"); + return true; +} + +bool LoopVectorizationLegality::AddReductionVar(PHINode *Phi, + ReductionKind Kind) { + if (Phi->getNumIncomingValues() != 2) + return false; + + // Reduction variables are only found in the loop header block. + if (Phi->getParent() != TheLoop->getHeader()) + return false; + + // Obtain the reduction start value from the value that comes from the loop + // preheader. + Value *RdxStart = Phi->getIncomingValueForBlock(TheLoop->getLoopPreheader()); + + // ExitInstruction is the single value which is used outside the loop. + // We only allow for a single reduction value to be used outside the loop. + // This includes users of the reduction, variables (which form a cycle + // which ends in the phi node). + Instruction *ExitInstruction = 0; + // Indicates that we found a binary operation in our scan. + bool FoundBinOp = false; + + // Iter is our iterator. We start with the PHI node and scan for all of the + // users of this instruction. All users must be instructions that can be + // used as reduction variables (such as ADD). We may have a single + // out-of-block user. The cycle must end with the original PHI. + Instruction *Iter = Phi; + while (true) { + // If the instruction has no users then this is a broken + // chain and can't be a reduction variable. + if (Iter->use_empty()) + return false; + + // Did we find a user inside this loop already ? + bool FoundInBlockUser = false; + // Did we reach the initial PHI node already ? + bool FoundStartPHI = false; + + // Is this a bin op ? + FoundBinOp |= !isa<PHINode>(Iter); + + // For each of the *users* of iter. + for (Value::use_iterator it = Iter->use_begin(), e = Iter->use_end(); + it != e; ++it) { + Instruction *U = cast<Instruction>(*it); + // We already know that the PHI is a user. + if (U == Phi) { + FoundStartPHI = true; + continue; + } + + // Check if we found the exit user. + BasicBlock *Parent = U->getParent(); + if (!TheLoop->contains(Parent)) { + // Exit if you find multiple outside users. + if (ExitInstruction != 0) + return false; + ExitInstruction = Iter; + } + + // We allow in-loop PHINodes which are not the original reduction PHI + // node. If this PHI is the only user of Iter (happens in IF w/ no ELSE + // structure) then don't skip this PHI. + if (isa<PHINode>(Iter) && isa<PHINode>(U) && + U->getParent() != TheLoop->getHeader() && + TheLoop->contains(U) && + Iter->getNumUses() > 1) + continue; + + // We can't have multiple inside users. + if (FoundInBlockUser) + return false; + FoundInBlockUser = true; + + // Any reduction instr must be of one of the allowed kinds. + if (!isReductionInstr(U, Kind)) + return false; + + // Reductions of instructions such as Div, and Sub is only + // possible if the LHS is the reduction variable. + if (!U->isCommutative() && !isa<PHINode>(U) && U->getOperand(0) != Iter) + return false; + + Iter = U; + } + + // We found a reduction var if we have reached the original + // phi node and we only have a single instruction with out-of-loop + // users. + if (FoundStartPHI) { + // This instruction is allowed to have out-of-loop users. + AllowedExit.insert(ExitInstruction); + + // Save the description of this reduction variable. + ReductionDescriptor RD(RdxStart, ExitInstruction, Kind); + Reductions[Phi] = RD; + // We've ended the cycle. This is a reduction variable if we have an + // outside user and it has a binary op. + return FoundBinOp && ExitInstruction; + } + } +} + +bool +LoopVectorizationLegality::isReductionInstr(Instruction *I, + ReductionKind Kind) { + bool FP = I->getType()->isFloatingPointTy(); + bool FastMath = (FP && I->isCommutative() && I->isAssociative()); + + switch (I->getOpcode()) { + default: + return false; + case Instruction::PHI: + if (FP && (Kind != RK_FloatMult && Kind != RK_FloatAdd)) + return false; + // possibly. + return true; + case Instruction::Sub: + case Instruction::Add: + return Kind == RK_IntegerAdd; + case Instruction::SDiv: + case Instruction::UDiv: + case Instruction::Mul: + return Kind == RK_IntegerMult; + case Instruction::And: + return Kind == RK_IntegerAnd; + case Instruction::Or: + return Kind == RK_IntegerOr; + case Instruction::Xor: + return Kind == RK_IntegerXor; + case Instruction::FMul: + return Kind == RK_FloatMult && FastMath; + case Instruction::FAdd: + return Kind == RK_FloatAdd && FastMath; + } +} + +LoopVectorizationLegality::InductionKind +LoopVectorizationLegality::isInductionVariable(PHINode *Phi) { + Type *PhiTy = Phi->getType(); + // We only handle integer and pointer inductions variables. + if (!PhiTy->isIntegerTy() && !PhiTy->isPointerTy()) + return IK_NoInduction; + + // Check that the PHI is consecutive and starts at zero. + const SCEV *PhiScev = SE->getSCEV(Phi); + const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PhiScev); + if (!AR) { + DEBUG(dbgs() << "LV: PHI is not a poly recurrence.\n"); + return IK_NoInduction; + } + const SCEV *Step = AR->getStepRecurrence(*SE); + + // Integer inductions need to have a stride of one. + if (PhiTy->isIntegerTy()) { + if (Step->isOne()) + return IK_IntInduction; + if (Step->isAllOnesValue()) + return IK_ReverseIntInduction; + return IK_NoInduction; + } + + // Calculate the pointer stride and check if it is consecutive. + const SCEVConstant *C = dyn_cast<SCEVConstant>(Step); + if (!C) + return IK_NoInduction; + + assert(PhiTy->isPointerTy() && "The PHI must be a pointer"); + uint64_t Size = DL->getTypeAllocSize(PhiTy->getPointerElementType()); + if (C->getValue()->equalsInt(Size)) + return IK_PtrInduction; + + return IK_NoInduction; +} + +bool LoopVectorizationLegality::isInductionVariable(const Value *V) { + Value *In0 = const_cast<Value*>(V); + PHINode *PN = dyn_cast_or_null<PHINode>(In0); + if (!PN) + return false; + + return Inductions.count(PN); +} + +bool LoopVectorizationLegality::blockNeedsPredication(BasicBlock *BB) { + assert(TheLoop->contains(BB) && "Unknown block used"); + + // Blocks that do not dominate the latch need predication. + BasicBlock* Latch = TheLoop->getLoopLatch(); + return !DT->dominates(BB, Latch); +} + +bool LoopVectorizationLegality::blockCanBePredicated(BasicBlock *BB) { + for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { + // We don't predicate loads/stores at the moment. + if (it->mayReadFromMemory() || it->mayWriteToMemory() || it->mayThrow()) + return false; + + // The instructions below can trap. + switch (it->getOpcode()) { + default: continue; + case Instruction::UDiv: + case Instruction::SDiv: + case Instruction::URem: + case Instruction::SRem: + return false; + } + } + + return true; +} + +bool LoopVectorizationLegality::hasComputableBounds(Value *Ptr) { + const SCEV *PhiScev = SE->getSCEV(Ptr); + const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PhiScev); + if (!AR) + return false; + + return AR->isAffine(); +} + +unsigned +LoopVectorizationCostModel::selectVectorizationFactor(bool OptForSize, + unsigned UserVF) { + if (OptForSize && Legal->getRuntimePointerCheck()->Need) { + DEBUG(dbgs() << "LV: Aborting. Runtime ptr check is required in Os.\n"); + return 1; + } + + // Find the trip count. + unsigned TC = SE->getSmallConstantTripCount(TheLoop, TheLoop->getLoopLatch()); + DEBUG(dbgs() << "LV: Found trip count:"<<TC<<"\n"); + + unsigned VF = MaxVectorSize; + + // If we optimize the program for size, avoid creating the tail loop. + if (OptForSize) { + // If we are unable to calculate the trip count then don't try to vectorize. + if (TC < 2) { + DEBUG(dbgs() << "LV: Aborting. A tail loop is required in Os.\n"); + return 1; + } + + // Find the maximum SIMD width that can fit within the trip count. + VF = TC % MaxVectorSize; + + if (VF == 0) + VF = MaxVectorSize; + + // If the trip count that we found modulo the vectorization factor is not + // zero then we require a tail. + if (VF < 2) { + DEBUG(dbgs() << "LV: Aborting. A tail loop is required in Os.\n"); + return 1; + } + } + + if (UserVF != 0) { + assert(isPowerOf2_32(UserVF) && "VF needs to be a power of two"); + DEBUG(dbgs() << "LV: Using user VF "<<UserVF<<".\n"); + + return UserVF; + } + + float Cost = expectedCost(1); + unsigned Width = 1; + DEBUG(dbgs() << "LV: Scalar loop costs: "<< (int)Cost << ".\n"); + for (unsigned i=2; i <= VF; i*=2) { + // Notice that the vector loop needs to be executed less times, so + // we need to divide the cost of the vector loops by the width of + // the vector elements. + float VectorCost = expectedCost(i) / (float)i; + DEBUG(dbgs() << "LV: Vector loop of width "<< i << " costs: " << + (int)VectorCost << ".\n"); + if (VectorCost < Cost) { + Cost = VectorCost; + Width = i; + } + } + + DEBUG(dbgs() << "LV: Selecting VF = : "<< Width << ".\n"); + return Width; +} + +unsigned +LoopVectorizationCostModel::selectUnrollFactor(bool OptForSize, + unsigned UserUF) { + // Use the user preference, unless 'auto' is selected. + if (UserUF != 0) + return UserUF; + + // When we optimize for size we don't unroll. + if (OptForSize) + return 1; + + // Do not unroll loops with a relatively small trip count. + unsigned TC = SE->getSmallConstantTripCount(TheLoop, + TheLoop->getLoopLatch()); + if (TC > 1 && TC < TinyTripCountUnrollThreshold) + return 1; + + unsigned TargetVectorRegisters = TTI.getNumberOfRegisters(true); + DEBUG(dbgs() << "LV: The target has " << TargetVectorRegisters << + " vector registers\n"); + + LoopVectorizationCostModel::RegisterUsage R = calculateRegisterUsage(); + // We divide by these constants so assume that we have at least one + // instruction that uses at least one register. + R.MaxLocalUsers = std::max(R.MaxLocalUsers, 1U); + R.NumInstructions = std::max(R.NumInstructions, 1U); + + // We calculate the unroll factor using the following formula. + // Subtract the number of loop invariants from the number of available + // registers. These registers are used by all of the unrolled instances. + // Next, divide the remaining registers by the number of registers that is + // required by the loop, in order to estimate how many parallel instances + // fit without causing spills. + unsigned UF = (TargetVectorRegisters - R.LoopInvariantRegs) / R.MaxLocalUsers; + + // We don't want to unroll the loops to the point where they do not fit into + // the decoded cache. Assume that we only allow 32 IR instructions. + UF = std::min(UF, (MaxLoopSizeThreshold / R.NumInstructions)); + + // Clamp the unroll factor ranges to reasonable factors. + if (UF > MaxUnrollSize) + UF = MaxUnrollSize; + else if (UF < 1) + UF = 1; + + return UF; +} + +LoopVectorizationCostModel::RegisterUsage +LoopVectorizationCostModel::calculateRegisterUsage() { + // This function calculates the register usage by measuring the highest number + // of values that are alive at a single location. Obviously, this is a very + // rough estimation. We scan the loop in a topological order in order and + // assign a number to each instruction. We use RPO to ensure that defs are + // met before their users. We assume that each instruction that has in-loop + // users starts an interval. We record every time that an in-loop value is + // used, so we have a list of the first and last occurrences of each + // instruction. Next, we transpose this data structure into a multi map that + // holds the list of intervals that *end* at a specific location. This multi + // map allows us to perform a linear search. We scan the instructions linearly + // and record each time that a new interval starts, by placing it in a set. + // If we find this value in the multi-map then we remove it from the set. + // The max register usage is the maximum size of the set. + // We also search for instructions that are defined outside the loop, but are + // used inside the loop. We need this number separately from the max-interval + // usage number because when we unroll, loop-invariant values do not take + // more register. + LoopBlocksDFS DFS(TheLoop); + DFS.perform(LI); + + RegisterUsage R; + R.NumInstructions = 0; + + // Each 'key' in the map opens a new interval. The values + // of the map are the index of the 'last seen' usage of the + // instruction that is the key. + typedef DenseMap<Instruction*, unsigned> IntervalMap; + // Maps instruction to its index. + DenseMap<unsigned, Instruction*> IdxToInstr; + // Marks the end of each interval. + IntervalMap EndPoint; + // Saves the list of instruction indices that are used in the loop. + SmallSet<Instruction*, 8> Ends; + // Saves the list of values that are used in the loop but are + // defined outside the loop, such as arguments and constants. + SmallPtrSet<Value*, 8> LoopInvariants; + + unsigned Index = 0; + for (LoopBlocksDFS::RPOIterator bb = DFS.beginRPO(), + be = DFS.endRPO(); bb != be; ++bb) { + R.NumInstructions += (*bb)->size(); + for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e; + ++it) { + Instruction *I = it; + IdxToInstr[Index++] = I; + + // Save the end location of each USE. + for (unsigned i = 0; i < I->getNumOperands(); ++i) { + Value *U = I->getOperand(i); + Instruction *Instr = dyn_cast<Instruction>(U); + + // Ignore non-instruction values such as arguments, constants, etc. + if (!Instr) continue; + + // If this instruction is outside the loop then record it and continue. + if (!TheLoop->contains(Instr)) { + LoopInvariants.insert(Instr); + continue; + } + + // Overwrite previous end points. + EndPoint[Instr] = Index; + Ends.insert(Instr); + } + } + } + + // Saves the list of intervals that end with the index in 'key'. + typedef SmallVector<Instruction*, 2> InstrList; + DenseMap<unsigned, InstrList> TransposeEnds; + + // Transpose the EndPoints to a list of values that end at each index. + for (IntervalMap::iterator it = EndPoint.begin(), e = EndPoint.end(); + it != e; ++it) + TransposeEnds[it->second].push_back(it->first); + + SmallSet<Instruction*, 8> OpenIntervals; + unsigned MaxUsage = 0; + + + DEBUG(dbgs() << "LV(REG): Calculating max register usage:\n"); + for (unsigned int i = 0; i < Index; ++i) { + Instruction *I = IdxToInstr[i]; + // Ignore instructions that are never used within the loop. + if (!Ends.count(I)) continue; + + // Remove all of the instructions that end at this location. + InstrList &List = TransposeEnds[i]; + for (unsigned int j=0, e = List.size(); j < e; ++j) + OpenIntervals.erase(List[j]); + + // Count the number of live interals. + MaxUsage = std::max(MaxUsage, OpenIntervals.size()); + + DEBUG(dbgs() << "LV(REG): At #" << i << " Interval # " << + OpenIntervals.size() <<"\n"); + + // Add the current instruction to the list of open intervals. + OpenIntervals.insert(I); + } + + unsigned Invariant = LoopInvariants.size(); + DEBUG(dbgs() << "LV(REG): Found max usage: " << MaxUsage << " \n"); + DEBUG(dbgs() << "LV(REG): Found invariant usage: " << Invariant << " \n"); + DEBUG(dbgs() << "LV(REG): LoopSize: " << R.NumInstructions << " \n"); + + R.LoopInvariantRegs = Invariant; + R.MaxLocalUsers = MaxUsage; + return R; +} + +unsigned LoopVectorizationCostModel::expectedCost(unsigned VF) { + unsigned Cost = 0; + + // For each block. + for (Loop::block_iterator bb = TheLoop->block_begin(), + be = TheLoop->block_end(); bb != be; ++bb) { + unsigned BlockCost = 0; + BasicBlock *BB = *bb; + + // For each instruction in the old loop. + for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { + unsigned C = getInstructionCost(it, VF); + Cost += C; + DEBUG(dbgs() << "LV: Found an estimated cost of "<< C <<" for VF " << + VF << " For instruction: "<< *it << "\n"); + } + + // We assume that if-converted blocks have a 50% chance of being executed. + // When the code is scalar then some of the blocks are avoided due to CF. + // When the code is vectorized we execute all code paths. + if (Legal->blockNeedsPredication(*bb) && VF == 1) + BlockCost /= 2; + + Cost += BlockCost; + } + + return Cost; +} + +unsigned +LoopVectorizationCostModel::getInstructionCost(Instruction *I, unsigned VF) { + // If we know that this instruction will remain uniform, check the cost of + // the scalar version. + if (Legal->isUniformAfterVectorization(I)) + VF = 1; + + Type *RetTy = I->getType(); + Type *VectorTy = ToVectorTy(RetTy, VF); + + // TODO: We need to estimate the cost of intrinsic calls. + switch (I->getOpcode()) { + case Instruction::GetElementPtr: + // We mark this instruction as zero-cost because scalar GEPs are usually + // lowered to the intruction addressing mode. At the moment we don't + // generate vector geps. + return 0; + case Instruction::Br: { + return TTI.getCFInstrCost(I->getOpcode()); + } + case Instruction::PHI: + //TODO: IF-converted IFs become selects. + return 0; + case Instruction::Add: + case Instruction::FAdd: + case Instruction::Sub: + case Instruction::FSub: + case Instruction::Mul: + case Instruction::FMul: + case Instruction::UDiv: + case Instruction::SDiv: + case Instruction::FDiv: + case Instruction::URem: + case Instruction::SRem: + case Instruction::FRem: + case Instruction::Shl: + case Instruction::LShr: + case Instruction::AShr: + case Instruction::And: + case Instruction::Or: + case Instruction::Xor: + return TTI.getArithmeticInstrCost(I->getOpcode(), VectorTy); + case Instruction::Select: { + SelectInst *SI = cast<SelectInst>(I); + const SCEV *CondSCEV = SE->getSCEV(SI->getCondition()); + bool ScalarCond = (SE->isLoopInvariant(CondSCEV, TheLoop)); + Type *CondTy = SI->getCondition()->getType(); + if (ScalarCond) + CondTy = VectorType::get(CondTy, VF); + + return TTI.getCmpSelInstrCost(I->getOpcode(), VectorTy, CondTy); + } + case Instruction::ICmp: + case Instruction::FCmp: { + Type *ValTy = I->getOperand(0)->getType(); + VectorTy = ToVectorTy(ValTy, VF); + return TTI.getCmpSelInstrCost(I->getOpcode(), VectorTy); + } + case Instruction::Store: { + StoreInst *SI = cast<StoreInst>(I); + Type *ValTy = SI->getValueOperand()->getType(); + VectorTy = ToVectorTy(ValTy, VF); + + if (VF == 1) + return TTI.getMemoryOpCost(I->getOpcode(), VectorTy, + SI->getAlignment(), + SI->getPointerAddressSpace()); + + // Scalarized stores. + int Stride = Legal->isConsecutivePtr(SI->getPointerOperand()); + bool Reverse = Stride < 0; + if (0 == Stride) { + unsigned Cost = 0; + + // The cost of extracting from the value vector and pointer vector. + Type *PtrTy = ToVectorTy(I->getOperand(0)->getType(), VF); + for (unsigned i = 0; i < VF; ++i) { + Cost += TTI.getVectorInstrCost(Instruction::ExtractElement, VectorTy, + i); + Cost += TTI.getVectorInstrCost(Instruction::ExtractElement, PtrTy, i); + } + + // The cost of the scalar stores. + Cost += VF * TTI.getMemoryOpCost(I->getOpcode(), ValTy->getScalarType(), + SI->getAlignment(), + SI->getPointerAddressSpace()); + return Cost; + } + + // Wide stores. + unsigned Cost = TTI.getMemoryOpCost(I->getOpcode(), VectorTy, + SI->getAlignment(), + SI->getPointerAddressSpace()); + if (Reverse) + Cost += TTI.getShuffleCost(TargetTransformInfo::SK_Reverse, + VectorTy, 0); + return Cost; + } + case Instruction::Load: { + LoadInst *LI = cast<LoadInst>(I); + + if (VF == 1) + return TTI.getMemoryOpCost(I->getOpcode(), VectorTy, LI->getAlignment(), + LI->getPointerAddressSpace()); + + // Scalarized loads. + int Stride = Legal->isConsecutivePtr(LI->getPointerOperand()); + bool Reverse = Stride < 0; + if (0 == Stride) { + unsigned Cost = 0; + Type *PtrTy = ToVectorTy(I->getOperand(0)->getType(), VF); + + // The cost of extracting from the pointer vector. + for (unsigned i = 0; i < VF; ++i) + Cost += TTI.getVectorInstrCost(Instruction::ExtractElement, PtrTy, i); + + // The cost of inserting data to the result vector. + for (unsigned i = 0; i < VF; ++i) + Cost += TTI.getVectorInstrCost(Instruction::InsertElement, VectorTy, i); + + // The cost of the scalar stores. + Cost += VF * TTI.getMemoryOpCost(I->getOpcode(), RetTy->getScalarType(), + LI->getAlignment(), + LI->getPointerAddressSpace()); + return Cost; + } + + // Wide loads. + unsigned Cost = TTI.getMemoryOpCost(I->getOpcode(), VectorTy, + LI->getAlignment(), + LI->getPointerAddressSpace()); + if (Reverse) + Cost += TTI.getShuffleCost(TargetTransformInfo::SK_Reverse, VectorTy, 0); + return Cost; + } + case Instruction::ZExt: + case Instruction::SExt: + case Instruction::FPToUI: + case Instruction::FPToSI: + case Instruction::FPExt: + case Instruction::PtrToInt: + case Instruction::IntToPtr: + case Instruction::SIToFP: + case Instruction::UIToFP: + case Instruction::Trunc: + case Instruction::FPTrunc: + case Instruction::BitCast: { + // We optimize the truncation of induction variable. + // The cost of these is the same as the scalar operation. + if (I->getOpcode() == Instruction::Trunc && + Legal->isInductionVariable(I->getOperand(0))) + return TTI.getCastInstrCost(I->getOpcode(), I->getType(), + I->getOperand(0)->getType()); + + Type *SrcVecTy = ToVectorTy(I->getOperand(0)->getType(), VF); + return TTI.getCastInstrCost(I->getOpcode(), VectorTy, SrcVecTy); + } + case Instruction::Call: { + assert(isTriviallyVectorizableIntrinsic(I)); + IntrinsicInst *II = cast<IntrinsicInst>(I); + Type *RetTy = ToVectorTy(II->getType(), VF); + SmallVector<Type*, 4> Tys; + for (unsigned i = 0, ie = II->getNumArgOperands(); i != ie; ++i) + Tys.push_back(ToVectorTy(II->getArgOperand(i)->getType(), VF)); + return TTI.getIntrinsicInstrCost(II->getIntrinsicID(), RetTy, Tys); + } + default: { + // We are scalarizing the instruction. Return the cost of the scalar + // instruction, plus the cost of insert and extract into vector + // elements, times the vector width. + unsigned Cost = 0; + + if (!RetTy->isVoidTy() && VF != 1) { + unsigned InsCost = TTI.getVectorInstrCost(Instruction::InsertElement, + VectorTy); + unsigned ExtCost = TTI.getVectorInstrCost(Instruction::ExtractElement, + VectorTy); + + // The cost of inserting the results plus extracting each one of the + // operands. + Cost += VF * (InsCost + ExtCost * I->getNumOperands()); + } + + // The cost of executing VF copies of the scalar instruction. This opcode + // is unknown. Assume that it is the same as 'mul'. + Cost += VF * TTI.getArithmeticInstrCost(Instruction::Mul, VectorTy); + return Cost; + } + }// end of switch. +} + +Type* LoopVectorizationCostModel::ToVectorTy(Type *Scalar, unsigned VF) { + if (Scalar->isVoidTy() || VF == 1) + return Scalar; + return VectorType::get(Scalar, VF); +} + +char LoopVectorize::ID = 0; +static const char lv_name[] = "Loop Vectorization"; +INITIALIZE_PASS_BEGIN(LoopVectorize, LV_NAME, lv_name, false, false) +INITIALIZE_AG_DEPENDENCY(AliasAnalysis) +INITIALIZE_AG_DEPENDENCY(TargetTransformInfo) +INITIALIZE_PASS_DEPENDENCY(ScalarEvolution) +INITIALIZE_PASS_DEPENDENCY(LoopSimplify) +INITIALIZE_PASS_END(LoopVectorize, LV_NAME, lv_name, false, false) + +namespace llvm { + Pass *createLoopVectorizePass() { + return new LoopVectorize(); + } +} + + |