| //===- 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. |
| // The vectorizer uses the TargetTransformInfo analysis to estimate the costs |
| // of instructions in order to estimate the profitability of vectorization. |
| // |
| // The loop vectorizer combines consecutive loop iterations 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/EquivalenceClasses.h" |
| #include "llvm/ADT/Hashing.h" |
| #include "llvm/ADT/MapVector.h" |
| #include "llvm/ADT/SetVector.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/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/PatternMatch.h" |
| #include "llvm/Support/raw_ostream.h" |
| #include "llvm/Support/ValueHandle.h" |
| #include "llvm/Target/TargetLibraryInfo.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; |
| using namespace llvm::PatternMatch; |
| |
| 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 cl::opt<unsigned> |
| TinyTripCountVectorThreshold("vectorizer-min-trip-count", cl::init(16), |
| cl::Hidden, |
| cl::desc("Don't vectorize loops with a constant " |
| "trip count that is smaller than this " |
| "value.")); |
| |
| /// We don't unroll loops with a known constant trip count below this number. |
| static const unsigned TinyTripCountUnrollThreshold = 128; |
| |
| /// When performing memory disambiguation checks at runtime do not make more |
| /// than this number of comparisons. |
| static const unsigned RuntimeMemoryCheckThreshold = 8; |
| |
| /// Maximum simd width. |
| static const unsigned MaxVectorWidth = 64; |
| |
| /// Maximum vectorization unroll count. |
| static const unsigned MaxUnrollFactor = 16; |
| |
| /// The cost of a loop that is considered 'small' by the unroller. |
| static const unsigned SmallLoopCost = 20; |
| |
| 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, |
| const TargetLibraryInfo *TLI, unsigned VecWidth, |
| unsigned UnrollFactor) |
| : OrigLoop(OrigLoop), SE(SE), LI(LI), DT(DT), DL(DL), TLI(TLI), |
| 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(); |
| } |
| |
| virtual ~InnerLoopVectorizer() {} |
| |
| protected: |
| /// 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; |
| |
| // When we if-convert we need create edge masks. We have to cache values so |
| // that we don't end up with exponential recursion/IR. |
| typedef DenseMap<std::pair<BasicBlock*, BasicBlock*>, |
| VectorParts> EdgeMaskCache; |
| |
| /// Add code that checks at runtime if the accessed arrays overlap. |
| /// Returns the comparator value or NULL if no check is needed. |
| Instruction *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. |
| virtual void vectorizeLoop(LoopVectorizationLegality *Legal); |
| |
| /// \brief 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 fix the 'undef case'. |
| /// See PR14725. |
| void fixLCSSAPHIs(); |
| |
| /// 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); |
| |
| /// Vectorize a single PHINode in a block. This method handles the induction |
| /// variable canonicalization. It supports both VF = 1 for unrolled loops and |
| /// arbitrary length vectors. |
| void widenPHIInstruction(Instruction *PN, VectorParts &Entry, |
| LoopVectorizationLegality *Legal, |
| unsigned UF, unsigned VF, 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. |
| virtual void scalarizeInstruction(Instruction *Instr); |
| |
| /// Vectorize Load and Store instructions, |
| virtual void vectorizeMemoryInstruction(Instruction *Instr, |
| LoopVectorizationLegality *Legal); |
| |
| /// 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. |
| virtual 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. |
| virtual Value *getConsecutiveVector(Value* Val, int 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. |
| virtual 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) const { return MapStorage.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) { |
| VectorParts &Entry = MapStorage[Key]; |
| Entry.assign(UF, Val); |
| return Entry; |
| } |
| |
| ///\return A reference to the value that is stored at 'Key'. |
| VectorParts &get(Value *Key) { |
| VectorParts &Entry = MapStorage[Key]; |
| if (Entry.empty()) |
| Entry.resize(UF); |
| assert(Entry.size() == UF); |
| return Entry; |
| } |
| |
| private: |
| /// 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> MapStorage; |
| }; |
| |
| /// The original loop. |
| Loop *OrigLoop; |
| /// Scev analysis to use. |
| ScalarEvolution *SE; |
| /// Loop Info. |
| LoopInfo *LI; |
| /// Dominator Tree. |
| DominatorTree *DT; |
| /// Data Layout. |
| DataLayout *DL; |
| /// Target Library Info. |
| const TargetLibraryInfo *TLI; |
| |
| /// The vectorization SIMD factor to use. Each vector will have this many |
| /// vector elements. |
| unsigned VF; |
| |
| protected: |
| /// 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; |
| /// A list of all bypass blocks. The first block is the entry of the loop. |
| SmallVector<BasicBlock *, 4> LoopBypassBlocks; |
| |
| /// The new Induction variable which was added to the new block. |
| PHINode *Induction; |
| /// The induction variable of the old basic block. |
| PHINode *OldInduction; |
| /// Holds the extended (to the widest induction type) start index. |
| Value *ExtendedIdx; |
| /// Maps scalars to widened vectors. |
| ValueMap WidenMap; |
| EdgeMaskCache MaskCache; |
| }; |
| |
| class InnerLoopUnroller : public InnerLoopVectorizer { |
| public: |
| InnerLoopUnroller(Loop *OrigLoop, ScalarEvolution *SE, LoopInfo *LI, |
| DominatorTree *DT, DataLayout *DL, |
| const TargetLibraryInfo *TLI, unsigned UnrollFactor) : |
| InnerLoopVectorizer(OrigLoop, SE, LI, DT, DL, TLI, 1, UnrollFactor) { } |
| |
| private: |
| virtual void scalarizeInstruction(Instruction *Instr); |
| virtual void vectorizeMemoryInstruction(Instruction *Instr, |
| LoopVectorizationLegality *Legal); |
| virtual Value *getBroadcastInstrs(Value *V); |
| virtual Value *getConsecutiveVector(Value* Val, int StartIdx, bool Negate); |
| virtual Value *reverseVector(Value *Vec); |
| }; |
| |
| /// \brief Look for a meaningful debug location on the instruction or it's |
| /// operands. |
| static Instruction *getDebugLocFromInstOrOperands(Instruction *I) { |
| if (!I) |
| return I; |
| |
| DebugLoc Empty; |
| if (I->getDebugLoc() != Empty) |
| return I; |
| |
| for (User::op_iterator OI = I->op_begin(), OE = I->op_end(); OI != OE; ++OI) { |
| if (Instruction *OpInst = dyn_cast<Instruction>(*OI)) |
| if (OpInst->getDebugLoc() != Empty) |
| return OpInst; |
| } |
| |
| return I; |
| } |
| |
| /// \brief Set the debug location in the builder using the debug location in the |
| /// instruction. |
| static void setDebugLocFromInst(IRBuilder<> &B, const Value *Ptr) { |
| if (const Instruction *Inst = dyn_cast_or_null<Instruction>(Ptr)) |
| B.SetCurrentDebugLocation(Inst->getDebugLoc()); |
| else |
| B.SetCurrentDebugLocation(DebugLoc()); |
| } |
| |
| /// 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, TargetLibraryInfo *TLI) |
| : TheLoop(L), SE(SE), DL(DL), DT(DT), TLI(TLI), |
| Induction(0), WidestIndTy(0), HasFunNoNaNAttr(false), |
| MaxSafeDepDistBytes(-1U) {} |
| |
| /// 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_IntegerMinMax, ///< Min/max implemented in terms of select(cmp()). |
| RK_FloatAdd, ///< Sum of floats. |
| RK_FloatMult, ///< Product of floats. |
| RK_FloatMinMax ///< Min/max implemented in terms of select(cmp()). |
| }; |
| |
| /// 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 var. Step = sizeof(elem). |
| IK_ReversePtrInduction ///< Reverse ptr indvar. Step = - sizeof(elem). |
| }; |
| |
| // This enum represents the kind of minmax reduction. |
| enum MinMaxReductionKind { |
| MRK_Invalid, |
| MRK_UIntMin, |
| MRK_UIntMax, |
| MRK_SIntMin, |
| MRK_SIntMax, |
| MRK_FloatMin, |
| MRK_FloatMax |
| }; |
| |
| /// This struct holds information about reduction variables. |
| struct ReductionDescriptor { |
| ReductionDescriptor() : StartValue(0), LoopExitInstr(0), |
| Kind(RK_NoReduction), MinMaxKind(MRK_Invalid) {} |
| |
| ReductionDescriptor(Value *Start, Instruction *Exit, ReductionKind K, |
| MinMaxReductionKind MK) |
| : StartValue(Start), LoopExitInstr(Exit), Kind(K), MinMaxKind(MK) {} |
| |
| // The starting value of the reduction. |
| // It does not have to be zero! |
| TrackingVH<Value> StartValue; |
| // The instruction who's value is used outside the loop. |
| Instruction *LoopExitInstr; |
| // The kind of the reduction. |
| ReductionKind Kind; |
| // If this a min/max reduction the kind of reduction. |
| MinMaxReductionKind MinMaxKind; |
| }; |
| |
| /// This POD struct holds information about a potential reduction operation. |
| struct ReductionInstDesc { |
| ReductionInstDesc(bool IsRedux, Instruction *I) : |
| IsReduction(IsRedux), PatternLastInst(I), MinMaxKind(MRK_Invalid) {} |
| |
| ReductionInstDesc(Instruction *I, MinMaxReductionKind K) : |
| IsReduction(true), PatternLastInst(I), MinMaxKind(K) {} |
| |
| // Is this instruction a reduction candidate. |
| bool IsReduction; |
| // The last instruction in a min/max pattern (select of the select(icmp()) |
| // pattern), or the current reduction instruction otherwise. |
| Instruction *PatternLastInst; |
| // If this is a min/max pattern the comparison predicate. |
| MinMaxReductionKind MinMaxKind; |
| }; |
| |
| /// This 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(); |
| IsWritePtr.clear(); |
| DependencySetId.clear(); |
| } |
| |
| /// Insert a pointer and calculate the start and end SCEVs. |
| void insert(ScalarEvolution *SE, Loop *Lp, Value *Ptr, bool WritePtr, |
| unsigned DepSetId); |
| |
| /// This flag indicates if we need to add the runtime check. |
| bool Need; |
| /// Holds the pointers that we need to check. |
| SmallVector<TrackingVH<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; |
| /// Holds the information if this pointer is used for writing to memory. |
| SmallVector<bool, 2> IsWritePtr; |
| /// Holds the id of the set of pointers that could be dependent because of a |
| /// shared underlying object. |
| SmallVector<unsigned, 2> DependencySetId; |
| }; |
| |
| /// A struct 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. |
| TrackingVH<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 the widest induction type. |
| Type *getWidestInductionType() { return WidestIndTy; } |
| |
| /// 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; } |
| |
| /// This function returns the identity element (or neutral element) for |
| /// the operation K. |
| static Constant *getReductionIdentity(ReductionKind K, Type *Tp); |
| |
| unsigned getMaxSafeDepDistBytes() { return MaxSafeDepDistBytes; } |
| |
| 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. \p SafePtrs is a list of addresses that are known to be legal |
| /// and we know that we can read from them without segfault. |
| bool blockCanBePredicated(BasicBlock *BB, SmallPtrSet<Value *, 8>& SafePtrs); |
| |
| /// 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 a struct describing if the instruction 'I' can be a reduction |
| /// variable of type 'Kind'. If the reduction is a min/max pattern of |
| /// select(icmp()) this function advances the instruction pointer 'I' from the |
| /// compare instruction to the select instruction and stores this pointer in |
| /// 'PatternLastInst' member of the returned struct. |
| ReductionInstDesc isReductionInstr(Instruction *I, ReductionKind Kind, |
| ReductionInstDesc &Desc); |
| /// Returns true if the instruction is a Select(ICmp(X, Y), X, Y) instruction |
| /// pattern corresponding to a min(X, Y) or max(X, Y). |
| static ReductionInstDesc isMinMaxSelectCmpPattern(Instruction *I, |
| ReductionInstDesc &Prev); |
| /// Returns the induction kind of Phi. This function may return NoInduction |
| /// if the PHI is not an induction variable. |
| InductionKind isInductionVariable(PHINode *Phi); |
| |
| /// The loop that we evaluate. |
| Loop *TheLoop; |
| /// Scev analysis. |
| ScalarEvolution *SE; |
| /// DataLayout analysis. |
| DataLayout *DL; |
| /// Dominators. |
| DominatorTree *DT; |
| /// Target Library Info. |
| TargetLibraryInfo *TLI; |
| |
| // --- 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; |
| /// Holds the widest induction type encountered. |
| Type *WidestIndTy; |
| |
| /// 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; |
| /// Can we assume the absence of NaNs. |
| bool HasFunNoNaNAttr; |
| |
| unsigned MaxSafeDepDistBytes; |
| }; |
| |
| /// 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, |
| DataLayout *DL, const TargetLibraryInfo *TLI) |
| : TheLoop(L), SE(SE), LI(LI), Legal(Legal), TTI(TTI), DL(DL), TLI(TLI) {} |
| |
| /// Information about vectorization costs |
| struct VectorizationFactor { |
| unsigned Width; // Vector width with best cost |
| unsigned Cost; // Cost of the loop with that width |
| }; |
| /// \return The most profitable vectorization factor and the cost of that VF. |
| /// 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. |
| VectorizationFactor selectVectorizationFactor(bool OptForSize, |
| unsigned UserVF); |
| |
| /// \return The size (in bits) of the widest type in the code that |
| /// needs to be vectorized. We ignore values that remain scalar such as |
| /// 64 bit loop indices. |
| unsigned getWidestType(); |
| |
| /// \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. |
| /// VF and LoopCost are the selected vectorization factor and the cost of the |
| /// selected VF. |
| unsigned selectUnrollFactor(bool OptForSize, unsigned UserUF, unsigned VF, |
| unsigned LoopCost); |
| |
| /// \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); |
| |
| /// Returns whether the instruction is a load or store and will be a emitted |
| /// as a vector operation. |
| bool isConsecutiveLoadOrStore(Instruction *I); |
| |
| /// 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; |
| /// Target data layout information. |
| DataLayout *DL; |
| /// Target Library Info. |
| const TargetLibraryInfo *TLI; |
| }; |
| |
| /// Utility class for getting and setting loop vectorizer hints in the form |
| /// of loop metadata. |
| struct LoopVectorizeHints { |
| /// Vectorization width. |
| unsigned Width; |
| /// Vectorization unroll factor. |
| unsigned Unroll; |
| |
| LoopVectorizeHints(const Loop *L, bool DisableUnrolling) |
| : Width(VectorizationFactor) |
| , Unroll(DisableUnrolling ? 1 : VectorizationUnroll) |
| , LoopID(L->getLoopID()) { |
| getHints(L); |
| // The command line options override any loop metadata except for when |
| // width == 1 which is used to indicate the loop is already vectorized. |
| if (VectorizationFactor.getNumOccurrences() > 0 && Width != 1) |
| Width = VectorizationFactor; |
| if (VectorizationUnroll.getNumOccurrences() > 0) |
| Unroll = VectorizationUnroll; |
| |
| DEBUG(if (DisableUnrolling && Unroll == 1) |
| dbgs() << "LV: Unrolling disabled by the pass manager\n"); |
| } |
| |
| /// Return the loop vectorizer metadata prefix. |
| static StringRef Prefix() { return "llvm.vectorizer."; } |
| |
| MDNode *createHint(LLVMContext &Context, StringRef Name, unsigned V) { |
| SmallVector<Value*, 2> Vals; |
| Vals.push_back(MDString::get(Context, Name)); |
| Vals.push_back(ConstantInt::get(Type::getInt32Ty(Context), V)); |
| return MDNode::get(Context, Vals); |
| } |
| |
| /// Mark the loop L as already vectorized by setting the width to 1. |
| void setAlreadyVectorized(Loop *L) { |
| LLVMContext &Context = L->getHeader()->getContext(); |
| |
| Width = 1; |
| |
| // Create a new loop id with one more operand for the already_vectorized |
| // hint. If the loop already has a loop id then copy the existing operands. |
| SmallVector<Value*, 4> Vals(1); |
| if (LoopID) |
| for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) |
| Vals.push_back(LoopID->getOperand(i)); |
| |
| Vals.push_back(createHint(Context, Twine(Prefix(), "width").str(), Width)); |
| Vals.push_back(createHint(Context, Twine(Prefix(), "unroll").str(), 1)); |
| |
| MDNode *NewLoopID = MDNode::get(Context, Vals); |
| // Set operand 0 to refer to the loop id itself. |
| NewLoopID->replaceOperandWith(0, NewLoopID); |
| |
| L->setLoopID(NewLoopID); |
| if (LoopID) |
| LoopID->replaceAllUsesWith(NewLoopID); |
| |
| LoopID = NewLoopID; |
| } |
| |
| private: |
| MDNode *LoopID; |
| |
| /// Find hints specified in the loop metadata. |
| void getHints(const Loop *L) { |
| if (!LoopID) |
| return; |
| |
| // First operand should refer to the loop id itself. |
| assert(LoopID->getNumOperands() > 0 && "requires at least one operand"); |
| assert(LoopID->getOperand(0) == LoopID && "invalid loop id"); |
| |
| for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) { |
| const MDString *S = 0; |
| SmallVector<Value*, 4> Args; |
| |
| // The expected hint is either a MDString or a MDNode with the first |
| // operand a MDString. |
| if (const MDNode *MD = dyn_cast<MDNode>(LoopID->getOperand(i))) { |
| if (!MD || MD->getNumOperands() == 0) |
| continue; |
| S = dyn_cast<MDString>(MD->getOperand(0)); |
| for (unsigned i = 1, ie = MD->getNumOperands(); i < ie; ++i) |
| Args.push_back(MD->getOperand(i)); |
| } else { |
| S = dyn_cast<MDString>(LoopID->getOperand(i)); |
| assert(Args.size() == 0 && "too many arguments for MDString"); |
| } |
| |
| if (!S) |
| continue; |
| |
| // Check if the hint starts with the vectorizer prefix. |
| StringRef Hint = S->getString(); |
| if (!Hint.startswith(Prefix())) |
| continue; |
| // Remove the prefix. |
| Hint = Hint.substr(Prefix().size(), StringRef::npos); |
| |
| if (Args.size() == 1) |
| getHint(Hint, Args[0]); |
| } |
| } |
| |
| // Check string hint with one operand. |
| void getHint(StringRef Hint, Value *Arg) { |
| const ConstantInt *C = dyn_cast<ConstantInt>(Arg); |
| if (!C) return; |
| unsigned Val = C->getZExtValue(); |
| |
| if (Hint == "width") { |
| if (isPowerOf2_32(Val) && Val <= MaxVectorWidth) |
| Width = Val; |
| else |
| DEBUG(dbgs() << "LV: ignoring invalid width hint metadata\n"); |
| } else if (Hint == "unroll") { |
| if (isPowerOf2_32(Val) && Val <= MaxUnrollFactor) |
| Unroll = Val; |
| else |
| DEBUG(dbgs() << "LV: ignoring invalid unroll hint metadata\n"); |
| } else { |
| DEBUG(dbgs() << "LV: ignoring unknown hint " << Hint << '\n'); |
| } |
| } |
| }; |
| |
| /// The LoopVectorize Pass. |
| struct LoopVectorize : public LoopPass { |
| /// Pass identification, replacement for typeid |
| static char ID; |
| |
| explicit LoopVectorize(bool NoUnrolling = false) |
| : LoopPass(ID), DisableUnrolling(NoUnrolling) { |
| initializeLoopVectorizePass(*PassRegistry::getPassRegistry()); |
| } |
| |
| ScalarEvolution *SE; |
| DataLayout *DL; |
| LoopInfo *LI; |
| TargetTransformInfo *TTI; |
| DominatorTree *DT; |
| TargetLibraryInfo *TLI; |
| bool DisableUnrolling; |
| |
| 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>(); |
| TLI = getAnalysisIfAvailable<TargetLibraryInfo>(); |
| |
| // If the target claims to have no vector registers don't attempt |
| // vectorization. |
| if (!TTI->getNumberOfRegisters(true)) |
| return false; |
| |
| if (DL == NULL) { |
| DEBUG(dbgs() << "LV: Not vectorizing because of missing data layout\n"); |
| return false; |
| } |
| |
| DEBUG(dbgs() << "LV: Checking a loop in \"" << |
| L->getHeader()->getParent()->getName() << "\"\n"); |
| |
| LoopVectorizeHints Hints(L, DisableUnrolling); |
| |
| if (Hints.Width == 1 && Hints.Unroll == 1) { |
| DEBUG(dbgs() << "LV: Not vectorizing.\n"); |
| return false; |
| } |
| |
| // Check if it is legal to vectorize the loop. |
| LoopVectorizationLegality LVL(L, SE, DL, DT, TLI); |
| if (!LVL.canVectorize()) { |
| DEBUG(dbgs() << "LV: Not vectorizing.\n"); |
| return false; |
| } |
| |
| // Use the cost model. |
| LoopVectorizationCostModel CM(L, SE, LI, &LVL, *TTI, DL, TLI); |
| |
| // Check the function attributes 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; |
| } |
| |
| // Select the optimal vectorization factor. |
| LoopVectorizationCostModel::VectorizationFactor VF; |
| VF = CM.selectVectorizationFactor(OptForSize, Hints.Width); |
| // Select the unroll factor. |
| unsigned UF = CM.selectUnrollFactor(OptForSize, Hints.Unroll, VF.Width, |
| VF.Cost); |
| |
| DEBUG(dbgs() << "LV: Found a vectorizable loop ("<< VF.Width << ") in "<< |
| F->getParent()->getModuleIdentifier() << '\n'); |
| DEBUG(dbgs() << "LV: Unroll Factor is " << UF << '\n'); |
| |
| if (VF.Width == 1) { |
| DEBUG(dbgs() << "LV: Vectorization is possible but not beneficial.\n"); |
| if (UF == 1) |
| return false; |
| // We decided not to vectorize, but we may want to unroll. |
| InnerLoopUnroller Unroller(L, SE, LI, DT, DL, TLI, UF); |
| Unroller.vectorize(&LVL); |
| } else { |
| // If we decided that it is *legal* to vectorize the loop then do it. |
| InnerLoopVectorizer LB(L, SE, LI, DT, DL, TLI, VF.Width, UF); |
| LB.vectorize(&LVL); |
| } |
| |
| // Mark the loop as already vectorized to avoid vectorizing again. |
| Hints.setAlreadyVectorized(L); |
| |
| 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, |
| bool WritePtr, |
| unsigned DepSetId) { |
| const SCEV *Sc = SE->getSCEV(Ptr); |
| const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(Sc); |
| assert(AR && "Invalid addrec expression"); |
| const SCEV *Ex = SE->getBackedgeTakenCount(Lp); |
| const SCEV *ScEnd = AR->evaluateAtIteration(Ex, *SE); |
| Pointers.push_back(Ptr); |
| Starts.push_back(AR->getStart()); |
| Ends.push_back(ScEnd); |
| IsWritePtr.push_back(WritePtr); |
| DependencySetId.push_back(DepSetId); |
| } |
| |
| Value *InnerLoopVectorizer::getBroadcastInstrs(Value *V) { |
| // 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. |
| IRBuilder<>::InsertPointGuard Guard(Builder); |
| if (Invariant) |
| Builder.SetInsertPoint(LoopVectorPreHeader->getTerminator()); |
| |
| // Broadcast the scalar into all locations in the vector. |
| Value *Shuf = Builder.CreateVectorSplat(VF, V, "broadcast"); |
| |
| return Shuf; |
| } |
| |
| Value *InnerLoopVectorizer::getConsecutiveVector(Value* Val, int 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) { |
| int64_t Idx = Negate ? (-i) : i; |
| Indices.push_back(ConstantInt::get(ITy, StartIdx + Idx, Negate)); |
| } |
| |
| // 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"); |
| } |
| |
| /// \brief Find the operand of the GEP that should be checked for consecutive |
| /// stores. This ignores trailing indices that have no effect on the final |
| /// pointer. |
| static unsigned getGEPInductionOperand(DataLayout *DL, |
| const GetElementPtrInst *Gep) { |
| unsigned LastOperand = Gep->getNumOperands() - 1; |
| unsigned GEPAllocSize = DL->getTypeAllocSize( |
| cast<PointerType>(Gep->getType()->getScalarType())->getElementType()); |
| |
| // Walk backwards and try to peel off zeros. |
| while (LastOperand > 1 && match(Gep->getOperand(LastOperand), m_Zero())) { |
| // Find the type we're currently indexing into. |
| gep_type_iterator GEPTI = gep_type_begin(Gep); |
| std::advance(GEPTI, LastOperand - 1); |
| |
| // If it's a type with the same allocation size as the result of the GEP we |
| // can peel off the zero index. |
| if (DL->getTypeAllocSize(*GEPTI) != GEPAllocSize) |
| break; |
| --LastOperand; |
| } |
| |
| return LastOperand; |
| } |
| |
| int LoopVectorizationLegality::isConsecutivePtr(Value *Ptr) { |
| assert(Ptr->getType()->isPointerTy() && "Unexpected non ptr"); |
| // Make sure that the pointer does not point to structs. |
| if (Ptr->getType()->getPointerElementType()->isAggregateType()) |
| return 0; |
| |
| // 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; |
| else if (IK_ReversePtrInduction == II.IK) |
| return -1; |
| } |
| |
| GetElementPtrInst *Gep = dyn_cast_or_null<GetElementPtrInst>(Ptr); |
| if (!Gep) |
| return 0; |
| |
| unsigned NumOperands = Gep->getNumOperands(); |
| Value *GpPtr = Gep->getPointerOperand(); |
| // If this GEP value is a consecutive pointer induction variable and all of |
| // the indices are constant then we know it is consecutive. We can |
| Phi = dyn_cast<PHINode>(GpPtr); |
| if (Phi && Inductions.count(Phi)) { |
| |
| // Make sure that the pointer does not point to structs. |
| PointerType *GepPtrType = cast<PointerType>(GpPtr->getType()); |
| if (GepPtrType->getElementType()->isAggregateType()) |
| return 0; |
| |
| // Make sure that all of the index operands are loop invariant. |
| for (unsigned i = 1; i < NumOperands; ++i) |
| if (!SE->isLoopInvariant(SE->getSCEV(Gep->getOperand(i)), TheLoop)) |
| return 0; |
| |
| InductionInfo II = Inductions[Phi]; |
| if (IK_PtrInduction == II.IK) |
| return 1; |
| else if (IK_ReversePtrInduction == II.IK) |
| return -1; |
| } |
| |
| unsigned InductionOperand = getGEPInductionOperand(DL, Gep); |
| |
| // Check that all of the gep indices are uniform except for our induction |
| // operand. |
| for (unsigned i = 0; i != NumOperands; ++i) |
| if (i != InductionOperand && |
| !SE->isLoopInvariant(SE->getSCEV(Gep->getOperand(i)), TheLoop)) |
| return 0; |
| |
| // We can emit wide load/stores only if the last non-zero index is the |
| // induction variable. |
| const SCEV *Last = SE->getSCEV(Gep->getOperand(InductionOperand)); |
| 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); |
| return WidenMap.splat(V, B); |
| } |
| |
| 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::vectorizeMemoryInstruction(Instruction *Instr, |
| LoopVectorizationLegality *Legal) { |
| // Attempt to issue a wide load. |
| LoadInst *LI = dyn_cast<LoadInst>(Instr); |
| StoreInst *SI = dyn_cast<StoreInst>(Instr); |
| |
| assert((LI || SI) && "Invalid Load/Store instruction"); |
| |
| Type *ScalarDataTy = LI ? LI->getType() : SI->getValueOperand()->getType(); |
| Type *DataTy = VectorType::get(ScalarDataTy, VF); |
| Value *Ptr = LI ? LI->getPointerOperand() : SI->getPointerOperand(); |
| unsigned Alignment = LI ? LI->getAlignment() : SI->getAlignment(); |
| // An alignment of 0 means target abi alignment. We need to use the scalar's |
| // target abi alignment in such a case. |
| if (!Alignment) |
| Alignment = DL->getABITypeAlignment(ScalarDataTy); |
| unsigned AddressSpace = Ptr->getType()->getPointerAddressSpace(); |
| unsigned ScalarAllocatedSize = DL->getTypeAllocSize(ScalarDataTy); |
| unsigned VectorElementSize = DL->getTypeStoreSize(DataTy)/VF; |
| |
| if (ScalarAllocatedSize != VectorElementSize) |
| return scalarizeInstruction(Instr); |
| |
| // If the pointer is loop invariant or if it is non consecutive, |
| // scalarize the load. |
| int ConsecutiveStride = Legal->isConsecutivePtr(Ptr); |
| bool Reverse = ConsecutiveStride < 0; |
| bool UniformLoad = LI && Legal->isUniform(Ptr); |
| if (!ConsecutiveStride || UniformLoad) |
| return scalarizeInstruction(Instr); |
| |
| Constant *Zero = Builder.getInt32(0); |
| VectorParts &Entry = WidenMap.get(Instr); |
| |
| // Handle consecutive loads/stores. |
| GetElementPtrInst *Gep = dyn_cast<GetElementPtrInst>(Ptr); |
| if (Gep && Legal->isInductionVariable(Gep->getPointerOperand())) { |
| setDebugLocFromInst(Builder, Gep); |
| Value *PtrOperand = Gep->getPointerOperand(); |
| Value *FirstBasePtr = getVectorValue(PtrOperand)[0]; |
| FirstBasePtr = Builder.CreateExtractElement(FirstBasePtr, Zero); |
| |
| // Create the new GEP with the new induction variable. |
| GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone()); |
| Gep2->setOperand(0, FirstBasePtr); |
| Gep2->setName("gep.indvar.base"); |
| Ptr = Builder.Insert(Gep2); |
| } else if (Gep) { |
| setDebugLocFromInst(Builder, Gep); |
| assert(SE->isLoopInvariant(SE->getSCEV(Gep->getPointerOperand()), |
| OrigLoop) && "Base ptr must be invariant"); |
| |
| // 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(); |
| unsigned InductionOperand = getGEPInductionOperand(DL, Gep); |
| // Create the new GEP with the new induction variable. |
| GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone()); |
| |
| for (unsigned i = 0; i < NumOperands; ++i) { |
| Value *GepOperand = Gep->getOperand(i); |
| Instruction *GepOperandInst = dyn_cast<Instruction>(GepOperand); |
| |
| // Update last index or loop invariant instruction anchored in loop. |
| if (i == InductionOperand || |
| (GepOperandInst && OrigLoop->contains(GepOperandInst))) { |
| assert((i == InductionOperand || |
| SE->isLoopInvariant(SE->getSCEV(GepOperandInst), OrigLoop)) && |
| "Must be last index or loop invariant"); |
| |
| VectorParts &GEPParts = getVectorValue(GepOperand); |
| Value *Index = GEPParts[0]; |
| Index = Builder.CreateExtractElement(Index, Zero); |
| Gep2->setOperand(i, Index); |
| Gep2->setName("gep.indvar.idx"); |
| } |
| } |
| Ptr = Builder.Insert(Gep2); |
| } else { |
| // Use the induction element ptr. |
| assert(isa<PHINode>(Ptr) && "Invalid induction ptr"); |
| setDebugLocFromInst(Builder, Ptr); |
| VectorParts &PtrVal = getVectorValue(Ptr); |
| Ptr = Builder.CreateExtractElement(PtrVal[0], Zero); |
| } |
| |
| // Handle Stores: |
| if (SI) { |
| assert(!Legal->isUniform(SI->getPointerOperand()) && |
| "We do not allow storing to uniform addresses"); |
| setDebugLocFromInst(Builder, SI); |
| // We don't want to update the value in the map as it might be used in |
| // another expression. So don't use a reference type for "StoredVal". |
| 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, |
| DataTy->getPointerTo(AddressSpace)); |
| Builder.CreateStore(StoredVal[Part], VecPtr)->setAlignment(Alignment); |
| } |
| return; |
| } |
| |
| // Handle loads. |
| assert(LI && "Must have a load instruction"); |
| setDebugLocFromInst(Builder, LI); |
| 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, |
| DataTy->getPointerTo(AddressSpace)); |
| Value *LI = Builder.CreateLoad(VecPtr, "wide.load"); |
| cast<LoadInst>(LI)->setAlignment(Alignment); |
| Entry[Part] = Reverse ? reverseVector(LI) : LI; |
| } |
| } |
| |
| 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; |
| |
| setDebugLocFromInst(Builder, Instr); |
| |
| // 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 vector unroll 'part': |
| for (unsigned Part = 0; Part < UF; ++Part) { |
| // For each scalar that we create: |
| for (unsigned Width = 0; Width < VF; ++Width) { |
| Instruction *Cloned = Instr->clone(); |
| if (!IsVoidRetTy) |
| Cloned->setName(Instr->getName() + ".cloned"); |
| // Replace the operands of the cloned instructions 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)); |
| } |
| } |
| } |
| |
| Instruction * |
| InnerLoopVectorizer::addRuntimeCheck(LoopVectorizationLegality *Legal, |
| Instruction *Loc) { |
| LoopVectorizationLegality::RuntimePointerCheck *PtrRtCheck = |
| Legal->getRuntimePointerCheck(); |
| |
| if (!PtrRtCheck->Need) |
| return NULL; |
| |
| unsigned NumPointers = PtrRtCheck->Pointers.size(); |
| SmallVector<TrackingVH<Value> , 2> Starts; |
| SmallVector<TrackingVH<Value> , 2> Ends; |
| |
| LLVMContext &Ctx = Loc->getContext(); |
| SCEVExpander Exp(*SE, "induction"); |
| |
| 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'); |
| unsigned AS = Ptr->getType()->getPointerAddressSpace(); |
| |
| // Use this type for pointer arithmetic. |
| Type *PtrArithTy = Type::getInt8PtrTy(Ctx, AS); |
| |
| 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); |
| } |
| } |
| |
| IRBuilder<> ChkBuilder(Loc); |
| // Our instructions might fold to a constant. |
| Value *MemoryRuntimeCheck = 0; |
| for (unsigned i = 0; i < NumPointers; ++i) { |
| for (unsigned j = i+1; j < NumPointers; ++j) { |
| // No need to check if two readonly pointers intersect. |
| if (!PtrRtCheck->IsWritePtr[i] && !PtrRtCheck->IsWritePtr[j]) |
| continue; |
| |
| // Only need to check pointers between two different dependency sets. |
| if (PtrRtCheck->DependencySetId[i] == PtrRtCheck->DependencySetId[j]) |
| continue; |
| |
| unsigned AS0 = Starts[i]->getType()->getPointerAddressSpace(); |
| unsigned AS1 = Starts[j]->getType()->getPointerAddressSpace(); |
| |
| assert((AS0 == Ends[j]->getType()->getPointerAddressSpace()) && |
| (AS1 == Ends[i]->getType()->getPointerAddressSpace()) && |
| "Trying to bounds check pointers with different address spaces"); |
| |
| Type *PtrArithTy0 = Type::getInt8PtrTy(Ctx, AS0); |
| Type *PtrArithTy1 = Type::getInt8PtrTy(Ctx, AS1); |
| |
| Value *Start0 = ChkBuilder.CreateBitCast(Starts[i], PtrArithTy0, "bc"); |
| Value *Start1 = ChkBuilder.CreateBitCast(Starts[j], PtrArithTy1, "bc"); |
| Value *End0 = ChkBuilder.CreateBitCast(Ends[i], PtrArithTy1, "bc"); |
| Value *End1 = ChkBuilder.CreateBitCast(Ends[j], PtrArithTy0, "bc"); |
| |
| Value *Cmp0 = ChkBuilder.CreateICmpULE(Start0, End1, "bound0"); |
| Value *Cmp1 = ChkBuilder.CreateICmpULE(Start1, End0, "bound1"); |
| Value *IsConflict = ChkBuilder.CreateAnd(Cmp0, Cmp1, "found.conflict"); |
| if (MemoryRuntimeCheck) |
| IsConflict = ChkBuilder.CreateOr(MemoryRuntimeCheck, IsConflict, |
| "conflict.rdx"); |
| MemoryRuntimeCheck = IsConflict; |
| } |
| } |
| |
| // We have to do this trickery because the IRBuilder might fold the check to a |
| // constant expression in which case there is no Instruction anchored in a |
| // the block. |
| Instruction *Check = BinaryOperator::CreateAnd(MemoryRuntimeCheck, |
| ConstantInt::getTrue(Ctx)); |
| ChkBuilder.Insert(Check, "memcheck.conflict"); |
| return Check; |
| } |
| |
| 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 (may consist of multiple blocks). |
| / | |
| / 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 = Legal->getWidestInductionType(); |
| |
| // Find the loop boundaries. |
| const SCEV *ExitCount = SE->getBackedgeTakenCount(OrigLoop); |
| assert(ExitCount != SE->getCouldNotCompute() && "Invalid loop count"); |
| |
| // The exit count might have the type of i64 while the phi is i32. This can |
| // happen if we have an induction variable that is sign extended before the |
| // compare. The only way that we get a backedge taken count is that the |
| // induction variable was signed and as such will not overflow. In such a case |
| // truncation is legal. |
| if (ExitCount->getType()->getPrimitiveSizeInBits() > |
| IdxTy->getPrimitiveSizeInBits()) |
| ExitCount = SE->getTruncateOrNoop(ExitCount, IdxTy); |
| |
| ExitCount = SE->getNoopOrZeroExtend(ExitCount, IdxTy); |
| // 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. |
| Builder.SetInsertPoint(BypassBlock->getTerminator()); |
| Value *StartIdx = ExtendedIdx = OldInduction ? |
| Builder.CreateZExt(OldInduction->getIncomingValueForBlock(BypassBlock), |
| IdxTy): |
| ConstantInt::get(IdxTy, 0); |
| |
| assert(BypassBlock && "Invalid loop structure"); |
| LoopBypassBlocks.push_back(BypassBlock); |
| |
| // 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"); |
| |
| // 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 |
| // before calling any utilities such as SCEV that require valid LoopInfo. |
| 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()); |
| |
| // Use this IR builder to create the loop instructions (Phi, Br, Cmp) |
| // inside the loop. |
| Builder.SetInsertPoint(VecBody->getFirstNonPHI()); |
| |
| // Generate the induction variable. |
| setDebugLocFromInst(Builder, getDebugLocFromInstOrOperands(OldInduction)); |
| 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); |
| |
| // This is the IR builder that we use to add all of the logic for bypassing |
| // the new vector loop. |
| IRBuilder<> BypassBuilder(BypassBlock->getTerminator()); |
| setDebugLocFromInst(BypassBuilder, |
| getDebugLocFromInstOrOperands(OldInduction)); |
| |
| // 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 = BypassBuilder.CreatePointerCast(Count, IdxTy, "ptrcnt.to.int"); |
| else |
| Count = BypassBuilder.CreateZExtOrTrunc(Count, IdxTy, "cnt.cast"); |
| } |
| |
| // Add the start index to the loop count to get the new end index. |
| Value *IdxEnd = BypassBuilder.CreateAdd(Count, StartIdx, "end.idx"); |
| |
| // Now we need to generate the expression for N - (N % VF), which is |
| // the part that the vectorized body will execute. |
| Value *R = BypassBuilder.CreateURem(Count, Step, "n.mod.vf"); |
| Value *CountRoundDown = BypassBuilder.CreateSub(Count, R, "n.vec"); |
| Value *IdxEndRoundDown = BypassBuilder.CreateAdd(CountRoundDown, StartIdx, |
| "end.idx.rnd.down"); |
| |
| // Now, compare the new count to zero. If it is zero skip the vector loop and |
| // jump to the scalar loop. |
| Value *Cmp = BypassBuilder.CreateICmpEQ(IdxEndRoundDown, StartIdx, |
| "cmp.zero"); |
| |
| BasicBlock *LastBypassBlock = BypassBlock; |
| |
| // Generate the code that checks in runtime if arrays overlap. We put the |
| // checks into a separate block to make the more common case of few elements |
| // faster. |
| Instruction *MemRuntimeCheck = addRuntimeCheck(Legal, |
| BypassBlock->getTerminator()); |
| if (MemRuntimeCheck) { |
| // Create a new block containing the memory check. |
| BasicBlock *CheckBlock = BypassBlock->splitBasicBlock(MemRuntimeCheck, |
| "vector.memcheck"); |
| if (ParentLoop) |
| ParentLoop->addBasicBlockToLoop(CheckBlock, LI->getBase()); |
| LoopBypassBlocks.push_back(CheckBlock); |
| |
| // Replace the branch into the memory check block with a conditional branch |
| // for the "few elements case". |
| Instruction *OldTerm = BypassBlock->getTerminator(); |
| BranchInst::Create(MiddleBlock, CheckBlock, Cmp, OldTerm); |
| OldTerm->eraseFromParent(); |
| |
| Cmp = MemRuntimeCheck; |
| LastBypassBlock = CheckBlock; |
| } |
| |
| LastBypassBlock->getTerminator()->eraseFromParent(); |
| BranchInst::Create(MiddleBlock, VectorPH, Cmp, |
| LastBypassBlock); |
| |
| // 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(); |
| // Set builder to point to last bypass block. |
| BypassBuilder.SetInsertPoint(LoopBypassBlocks.back()->getTerminator()); |
| for (I = List->begin(), E = List->end(); I != E; ++I) { |
| PHINode *OrigPhi = I->first; |
| LoopVectorizationLegality::InductionInfo II = I->second; |
| |
| Type *ResumeValTy = (OrigPhi == OldInduction) ? IdxTy : OrigPhi->getType(); |
| PHINode *ResumeVal = PHINode::Create(ResumeValTy, 2, "resume.val", |
| MiddleBlock->getTerminator()); |
| // We might have extended the type of the induction variable but we need a |
| // truncated version for the scalar loop. |
| PHINode *TruncResumeVal = (OrigPhi == OldInduction) ? |
| PHINode::Create(OrigPhi->getType(), 2, "trunc.resume.val", |
| MiddleBlock->getTerminator()) : 0; |
| |
| 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"); |
| |
| // We have the canonical induction variable. |
| if (OrigPhi == OldInduction) { |
| // Create a truncated version of the resume value for the scalar loop, |
| // we might have promoted the type to a larger width. |
| EndValue = |
| BypassBuilder.CreateTrunc(IdxEndRoundDown, OrigPhi->getType()); |
| // The new PHI merges the original incoming value, in case of a bypass, |
| // or the value at the end of the vectorized loop. |
| for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I) |
| TruncResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[I]); |
| TruncResumeVal->addIncoming(EndValue, VecBody); |
| |
| // We know what the end value is. |
| EndValue = IdxEndRoundDown; |
| // We also know which PHI node holds it. |
| ResumeIndex = ResumeVal; |
| break; |
| } |
| |
| // Not the canonical induction variable - add the vector loop count to the |
| // start value. |
| Value *CRD = BypassBuilder.CreateSExtOrTrunc(CountRoundDown, |
| II.StartValue->getType(), |
| "cast.crd"); |
| EndValue = BypassBuilder.CreateAdd(CRD, II.StartValue , "ind.end"); |
| break; |
| } |
| case LoopVectorizationLegality::IK_ReverseIntInduction: { |
| // Convert the CountRoundDown variable to the PHI size. |
| Value *CRD = BypassBuilder.CreateSExtOrTrunc(CountRoundDown, |
| II.StartValue->getType(), |
| "cast.crd"); |
| // Handle reverse integer induction counter. |
| EndValue = BypassBuilder.CreateSub(II.StartValue, CRD, "rev.ind.end"); |
| break; |
| } |
| case LoopVectorizationLegality::IK_PtrInduction: { |
| // For pointer induction variables, calculate the offset using |
| // the end index. |
| EndValue = BypassBuilder.CreateGEP(II.StartValue, CountRoundDown, |
| "ptr.ind.end"); |
| break; |
| } |
| case LoopVectorizationLegality::IK_ReversePtrInduction: { |
| // The value at the end of the loop for the reverse pointer is calculated |
| // by creating a GEP with a negative index starting from the start value. |
| Value *Zero = ConstantInt::get(CountRoundDown->getType(), 0); |
| Value *NegIdx = BypassBuilder.CreateSub(Zero, CountRoundDown, |
| "rev.ind.end"); |
| EndValue = BypassBuilder.CreateGEP(II.StartValue, NegIdx, |
| "rev.ptr.ind.end"); |
| 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. |
| for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I) { |
| if (OrigPhi == OldInduction) |
| ResumeVal->addIncoming(StartIdx, LoopBypassBlocks[I]); |
| else |
| ResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[I]); |
| } |
| ResumeVal->addIncoming(EndValue, VecBody); |
| |
| // Fix the scalar body counter (PHI node). |
| unsigned BlockIdx = OrigPhi->getBasicBlockIndex(ScalarPH); |
| // The old inductions phi node in the scalar body needs the truncated value. |
| if (OrigPhi == OldInduction) |
| OrigPhi->setIncomingValue(BlockIdx, TruncResumeVal); |
| else |
| 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()); |
| for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I) |
| ResumeIndex->addIncoming(StartIdx, LoopBypassBlocks[I]); |
| 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()); |
| |
| // Save the state. |
| LoopVectorPreHeader = VectorPH; |
| LoopScalarPreHeader = ScalarPH; |
| LoopMiddleBlock = MiddleBlock; |
| LoopExitBlock = ExitBlock; |
| LoopVectorBody = VecBody; |
| LoopScalarBody = OldBasicBlock; |
| |
| LoopVectorizeHints Hints(Lp, true); |
| Hints.setAlreadyVectorized(Lp); |
| } |
| |
| /// This function returns the identity element (or neutral element) for |
| /// the operation K. |
| Constant* |
| LoopVectorizationLegality::getReductionIdentity(ReductionKind K, Type *Tp) { |
| switch (K) { |
| case RK_IntegerXor: |
| case RK_IntegerAdd: |
| case RK_IntegerOr: |
| // Adding, Xoring, Oring zero to a number does not change it. |
| return ConstantInt::get(Tp, 0); |
| case RK_IntegerMult: |
| // Multiplying a number by 1 does not change it. |
| return ConstantInt::get(Tp, 1); |
| case RK_IntegerAnd: |
| // AND-ing a number with an all-1 value does not change it. |
| return ConstantInt::get(Tp, -1, true); |
| case RK_FloatMult: |
| // Multiplying a number by 1 does not change it. |
| return ConstantFP::get(Tp, 1.0L); |
| case RK_FloatAdd: |
| // Adding zero to a number does not change it. |
| return ConstantFP::get(Tp, 0.0L); |
| default: |
| llvm_unreachable("Unknown reduction kind"); |
| } |
| } |
| |
| static Intrinsic::ID checkUnaryFloatSignature(const CallInst &I, |
| Intrinsic::ID ValidIntrinsicID) { |
| if (I.getNumArgOperands() != 1 || |
| !I.getArgOperand(0)->getType()->isFloatingPointTy() || |
| I.getType() != I.getArgOperand(0)->getType() || |
| !I.onlyReadsMemory()) |
| return Intrinsic::not_intrinsic; |
| |
| return ValidIntrinsicID; |
| } |
| |
| static Intrinsic::ID checkBinaryFloatSignature(const CallInst &I, |
| Intrinsic::ID ValidIntrinsicID) { |
| if (I.getNumArgOperands() != 2 || |
| !I.getArgOperand(0)->getType()->isFloatingPointTy() || |
| !I.getArgOperand(1)->getType()->isFloatingPointTy() || |
| I.getType() != I.getArgOperand(0)->getType() || |
| I.getType() != I.getArgOperand(1)->getType() || |
| !I.onlyReadsMemory()) |
| return Intrinsic::not_intrinsic; |
| |
| return ValidIntrinsicID; |
| } |
| |
| |
| static Intrinsic::ID |
| getIntrinsicIDForCall(CallInst *CI, const TargetLibraryInfo *TLI) { |
| // If we have an intrinsic call, check if it is trivially vectorizable. |
| if (IntrinsicInst *II = dyn_cast<IntrinsicInst>(CI)) { |
| 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::copysign: |
| case Intrinsic::floor: |
| case Intrinsic::ceil: |
| case Intrinsic::trunc: |
| case Intrinsic::rint: |
| case Intrinsic::nearbyint: |
| case Intrinsic::round: |
| case Intrinsic::pow: |
| case Intrinsic::fma: |
| case Intrinsic::fmuladd: |
| case Intrinsic::lifetime_start: |
| case Intrinsic::lifetime_end: |
| return II->getIntrinsicID(); |
| default: |
| return Intrinsic::not_intrinsic; |
| } |
| } |
| |
| if (!TLI) |
| return Intrinsic::not_intrinsic; |
| |
| LibFunc::Func Func; |
| Function *F = CI->getCalledFunction(); |
| // We're going to make assumptions on the semantics of the functions, check |
| // that the target knows that it's available in this environment and it does |
| // not have local linkage. |
| if (!F || F->hasLocalLinkage() || !TLI->getLibFunc(F->getName(), Func)) |
| return Intrinsic::not_intrinsic; |
| |
| // Otherwise check if we have a call to a function that can be turned into a |
| // vector intrinsic. |
| switch (Func) { |
| default: |
| break; |
| case LibFunc::sin: |
| case LibFunc::sinf: |
| case LibFunc::sinl: |
| return checkUnaryFloatSignature(*CI, Intrinsic::sin); |
| case LibFunc::cos: |
| case LibFunc::cosf: |
| case LibFunc::cosl: |
| return checkUnaryFloatSignature(*CI, Intrinsic::cos); |
| case LibFunc::exp: |
| case LibFunc::expf: |
| case LibFunc::expl: |
| return checkUnaryFloatSignature(*CI, Intrinsic::exp); |
| case LibFunc::exp2: |
| case LibFunc::exp2f: |
| case LibFunc::exp2l: |
| return checkUnaryFloatSignature(*CI, Intrinsic::exp2); |
| case LibFunc::log: |
| case LibFunc::logf: |
| case LibFunc::logl: |
| return checkUnaryFloatSignature(*CI, Intrinsic::log); |
| case LibFunc::log10: |
| case LibFunc::log10f: |
| case LibFunc::log10l: |
| return checkUnaryFloatSignature(*CI, Intrinsic::log10); |
| case LibFunc::log2: |
| case LibFunc::log2f: |
| case LibFunc::log2l: |
| return checkUnaryFloatSignature(*CI, Intrinsic::log2); |
| case LibFunc::fabs: |
| case LibFunc::fabsf: |
| case LibFunc::fabsl: |
| return checkUnaryFloatSignature(*CI, Intrinsic::fabs); |
| case LibFunc::copysign: |
| case LibFunc::copysignf: |
| case LibFunc::copysignl: |
| return checkBinaryFloatSignature(*CI, Intrinsic::copysign); |
| case LibFunc::floor: |
| case LibFunc::floorf: |
| case LibFunc::floorl: |
| return checkUnaryFloatSignature(*CI, Intrinsic::floor); |
| case LibFunc::ceil: |
| case LibFunc::ceilf: |
| case LibFunc::ceill: |
| return checkUnaryFloatSignature(*CI, Intrinsic::ceil); |
| case LibFunc::trunc: |
| case LibFunc::truncf: |
| case LibFunc::truncl: |
| return checkUnaryFloatSignature(*CI, Intrinsic::trunc); |
| case LibFunc::rint: |
| case LibFunc::rintf: |
| case LibFunc::rintl: |
| return checkUnaryFloatSignature(*CI, Intrinsic::rint); |
| case LibFunc::nearbyint: |
| case LibFunc::nearbyintf: |
| case LibFunc::nearbyintl: |
| return checkUnaryFloatSignature(*CI, Intrinsic::nearbyint); |
| case LibFunc::round: |
| case LibFunc::roundf: |
| case LibFunc::roundl: |
| return checkUnaryFloatSignature(*CI, Intrinsic::round); |
| case LibFunc::pow: |
| case LibFunc::powf: |
| case LibFunc::powl: |
| return checkBinaryFloatSignature(*CI, Intrinsic::pow); |
| } |
| |
| return Intrinsic::not_intrinsic; |
| } |
| |
| /// This function translates the reduction kind to an LLVM binary operator. |
| static unsigned |
| 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; |
| case LoopVectorizationLegality::RK_IntegerMinMax: |
| return Instruction::ICmp; |
| case LoopVectorizationLegality::RK_FloatMinMax: |
| return Instruction::FCmp; |
| default: |
| llvm_unreachable("Unknown reduction operation"); |
| } |
| } |
| |
| Value *createMinMaxOp(IRBuilder<> &Builder, |
| LoopVectorizationLegality::MinMaxReductionKind RK, |
| Value *Left, |
| Value *Right) { |
| CmpInst::Predicate P = CmpInst::ICMP_NE; |
| switch (RK) { |
| default: |
| llvm_unreachable("Unknown min/max reduction kind"); |
| case LoopVectorizationLegality::MRK_UIntMin: |
| P = CmpInst::ICMP_ULT; |
| break; |
| case LoopVectorizationLegality::MRK_UIntMax: |
| P = CmpInst::ICMP_UGT; |
| break; |
| case LoopVectorizationLegality::MRK_SIntMin: |
| P = CmpInst::ICMP_SLT; |
| break; |
| case LoopVectorizationLegality::MRK_SIntMax: |
| P = CmpInst::ICMP_SGT; |
| break; |
| case LoopVectorizationLegality::MRK_FloatMin: |
| P = CmpInst::FCMP_OLT; |
| break; |
| case LoopVectorizationLegality::MRK_FloatMax: |
| P = CmpInst::FCMP_OGT; |
| break; |
| } |
| |
| Value *Cmp; |
| if (RK == LoopVectorizationLegality::MRK_FloatMin || |
| RK == LoopVectorizationLegality::MRK_FloatMax) |
| Cmp = Builder.CreateFCmp(P, Left, Right, "rdx.minmax.cmp"); |
| else |
| Cmp = Builder.CreateICmp(P, Left, Right, "rdx.minmax.cmp"); |
| |
| Value *Select = Builder.CreateSelect(Cmp, Left, Right, "rdx.minmax.select"); |
| return Select; |
| } |
| |
| namespace { |
| struct CSEDenseMapInfo { |
| static bool canHandle(Instruction *I) { |
| return isa<InsertElementInst>(I) || isa<ExtractElementInst>(I) || |
| isa<ShuffleVectorInst>(I) || isa<GetElementPtrInst>(I); |
| } |
| static inline Instruction *getEmptyKey() { |
| return DenseMapInfo<Instruction *>::getEmptyKey(); |
| } |
| static inline Instruction *getTombstoneKey() { |
| return DenseMapInfo<Instruction *>::getTombstoneKey(); |
| } |
| static unsigned getHashValue(Instruction *I) { |
| assert(canHandle(I) && "Unknown instruction!"); |
| return hash_combine(I->getOpcode(), hash_combine_range(I->value_op_begin(), |
| I->value_op_end())); |
| } |
| static bool isEqual(Instruction *LHS, Instruction *RHS) { |
| if (LHS == getEmptyKey() || RHS == getEmptyKey() || |
| LHS == getTombstoneKey() || RHS == getTombstoneKey()) |
| return LHS == RHS; |
| return LHS->isIdenticalTo(RHS); |
| } |
| }; |
| } |
| |
| ///\brief Perform cse of induction variable instructions. |
| static void cse(BasicBlock *BB) { |
| // Perform simple cse. |
| SmallDenseMap<Instruction *, Instruction *, 4, CSEDenseMapInfo> CSEMap; |
| for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E;) { |
| Instruction *In = I++; |
| |
| if (!CSEDenseMapInfo::canHandle(In)) |
| continue; |
| |
| // Check if we can replace this instruction with any of the |
| // visited instructions. |
| if (Instruction *V = CSEMap.lookup(In)) { |
| In->replaceAllUsesWith(V); |
| In->eraseFromParent(); |
| continue; |
| } |
| |
| CSEMap[In] = In; |
| } |
| } |
| |
| 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. |
| // |
| //===------------------------------------------------===// |
| Constant *Zero = Builder.getInt32(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]; |
| |
| setDebugLocFromInst(Builder, RdxDesc.StartValue); |
| |
| // 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(LoopBypassBlocks.front()->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. |
| Value *Identity; |
| Value *VectorStart; |
| if (RdxDesc.Kind == LoopVectorizationLegality::RK_IntegerMinMax || |
| RdxDesc.Kind == LoopVectorizationLegality::RK_FloatMinMax) { |
| // MinMax reduction have the start value as their identify. |
| if (VF == 1) { |
| VectorStart = Identity = RdxDesc.StartValue; |
| } else { |
| VectorStart = Identity = Builder.CreateVectorSplat(VF, |
| RdxDesc.StartValue, |
| "minmax.ident"); |
| } |
| } else { |
| // Handle other reduction kinds: |
| Constant *Iden = |
| LoopVectorizationLegality::getReductionIdentity(RdxDesc.Kind, |
| VecTy->getScalarType()); |
| if (VF == 1) { |
| Identity = Iden; |
| // This vector is the Identity vector where the first element is the |
| // incoming scalar reduction. |
| VectorStart = RdxDesc.StartValue; |
| } else { |
| Identity = ConstantVector::getSplat(VF, Iden); |
| |
| // This vector is the Identity vector where the first element is the |
| // incoming scalar reduction. |
| 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; |
| setDebugLocFromInst(Builder, RdxDesc.LoopExitInstr); |
| 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; |
| for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I) |
| NewPhi->addIncoming(StartVal, LoopBypassBlocks[I]); |
| NewPhi->addIncoming(RdxExitVal[part], LoopVectorBody); |
| RdxParts.push_back(NewPhi); |
| } |
| |
| // Reduce all of the unrolled parts into a single vector. |
| Value *ReducedPartRdx = RdxParts[0]; |
| unsigned Op = getReductionBinOp(RdxDesc.Kind); |
| setDebugLocFromInst(Builder, ReducedPartRdx); |
| for (unsigned part = 1; part < UF; ++part) { |
| if (Op != Instruction::ICmp && Op != Instruction::FCmp) |
| ReducedPartRdx = Builder.CreateBinOp((Instruction::BinaryOps)Op, |
| RdxParts[part], ReducedPartRdx, |
| "bin.rdx"); |
| else |
| ReducedPartRdx = createMinMaxOp(Builder, RdxDesc.MinMaxKind, |
| ReducedPartRdx, RdxParts[part]); |
| } |
| |
| if (VF > 1) { |
| // 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"); |
| |
| if (Op != Instruction::ICmp && Op != Instruction::FCmp) |
| TmpVec = Builder.CreateBinOp((Instruction::BinaryOps)Op, TmpVec, Shuf, |
| "bin.rdx"); |
| else |
| TmpVec = createMinMaxOp(Builder, RdxDesc.MinMaxKind, TmpVec, Shuf); |
| } |
| |
| // The result is in the first element of the vector. |
| ReducedPartRdx = 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) break; |
| |
| // 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(ReducedPartRdx, 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, ReducedPartRdx); |
| (RdxPhi)->setIncomingValue(IncomingEdgeBlockIdx, RdxDesc.LoopExitInstr); |
| }// end of for each redux variable. |
| |
| fixLCSSAPHIs(); |
| |
| // Remove redundant induction instructions. |
| cse(LoopVectorBody); |
| } |
| |
| void InnerLoopVectorizer::fixLCSSAPHIs() { |
| for (BasicBlock::iterator LEI = LoopExitBlock->begin(), |
| LEE = LoopExitBlock->end(); LEI != LEE; ++LEI) { |
| PHINode *LCSSAPhi = dyn_cast<PHINode>(LEI); |
| if (!LCSSAPhi) break; |
| 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"); |
| |
| // Look for cached value. |
| std::pair<BasicBlock*, BasicBlock*> Edge(Src, Dst); |
| EdgeMaskCache::iterator ECEntryIt = MaskCache.find(Edge); |
| if (ECEntryIt != MaskCache.end()) |
| return ECEntryIt->second; |
| |
| 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]); |
| |
| MaskCache[Edge] = EdgeMask; |
| return EdgeMask; |
| } |
| |
| MaskCache[Edge] = SrcMask; |
| 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::widenPHIInstruction(Instruction *PN, |
| InnerLoopVectorizer::VectorParts &Entry, |
| LoopVectorizationLegality *Legal, |
| unsigned UF, unsigned VF, PhiVector *PV) { |
| PHINode* P = cast<PHINode>(PN); |
| // Handle reduction variables: |
| if (Legal->getReductionVars()->count(P)) { |
| for (unsigned part = 0; part < UF; ++part) { |
| // This is phase one of vectorizing PHIs. |
| Type *VecTy = (VF == 1) ? PN->getType() : |
| VectorType::get(PN->getType(), VF); |
| Entry[part] = PHINode::Create(VecTy, 2, "vec.phi", |
| LoopVectorBody-> getFirstInsertionPt()); |
| } |
| PV->push_back(P); |
| return; |
| } |
| |
| setDebugLocFromInst(Builder, P); |
| // 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. |
| |
| unsigned NumIncoming = P->getNumIncomingValues(); |
| |
| // Generate a sequence of selects of the form: |
| // SELECT(Mask3, In3, |
| // SELECT(Mask2, In2, |
| // ( ...))) |
| for (unsigned In = 0; In < NumIncoming; In++) { |
| VectorParts Cond = createEdgeMask(P->getIncomingBlock(In), |
| P->getParent()); |
| VectorParts &In0 = getVectorValue(P->getIncomingValue(In)); |
| |
| for (unsigned part = 0; part < UF; ++part) { |
| // We might have single edge PHIs (blocks) - use an identity |
| // 'select' for the first PHI operand. |
| if (In == 0) |
| Entry[part] = Builder.CreateSelect(Cond[part], In0[part], |
| In0[part]); |
| else |
| // Select between the current value and the previous incoming edge |
| // based on the incoming mask. |
| Entry[part] = Builder.CreateSelect(Cond[part], In0[part], |
| Entry[part], "predphi"); |
| } |
| } |
| return; |
| } |
| |
| // 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->getType() == II.StartValue->getType() && "Types must match"); |
| Type *PhiTy = P->getType(); |
| Value *Broadcasted; |
| if (P == OldInduction) { |
| // Handle the canonical induction variable. We might have had to |
| // extend the type. |
| Broadcasted = Builder.CreateTrunc(Induction, PhiTy); |
| } else { |
| // Handle other induction variables that are now based on the |
| // canonical one. |
| Value *NormalizedIdx = Builder.CreateSub(Induction, ExtendedIdx, |
| "normalized.idx"); |
| NormalizedIdx = Builder.CreateSExtOrTrunc(NormalizedIdx, PhiTy); |
| Broadcasted = Builder.CreateAdd(II.StartValue, NormalizedIdx, |
| "offset.idx"); |
| } |
| Broadcasted = getBroadcastInstrs(Broadcasted); |
| // After broadcasting the induction variable we need to make the vector |
| // consecutive by adding 0, 1, 2, etc. |
| for (unsigned part = 0; part < UF; ++part) |
| Entry[part] = getConsecutiveVector(Broadcasted, VF * part, false); |
| return; |
| } |
| case LoopVectorizationLegality::IK_ReverseIntInduction: |
| case LoopVectorizationLegality::IK_PtrInduction: |
| case LoopVectorizationLegality::IK_ReversePtrInduction: |
| // Handle reverse integer and pointer inductions. |
| Value *StartIdx = ExtendedIdx; |
| // 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, -(int)VF * part, |
| true); |
| return; |
| } |
| |
| // Handle the pointer induction variable case. |
| assert(P->getType()->isPointerTy() && "Unexpected type."); |
| |
| // Is this a reverse induction ptr or a consecutive induction ptr. |
| bool Reverse = (LoopVectorizationLegality::IK_ReversePtrInduction == |
| II.IK); |
| |
| // 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) { |
| if (VF == 1) { |
| int EltIndex = (part) * (Reverse ? -1 : 1); |
| Constant *Idx = ConstantInt::get(Induction->getType(), EltIndex); |
| Value *GlobalIdx; |
| if (Reverse) |
| GlobalIdx = Builder.CreateSub(Idx, NormalizedIdx, "gep.ridx"); |
| else |
| GlobalIdx = Builder.CreateAdd(NormalizedIdx, Idx, "gep.idx"); |
| |
| Value *SclrGep = Builder.CreateGEP(II.StartValue, GlobalIdx, |
| "next.gep"); |
| Entry[part] = SclrGep; |
| continue; |
| } |
| |
| Value *VecVal = UndefValue::get(VectorType::get(P->getType(), VF)); |
| for (unsigned int i = 0; i < VF; ++i) { |
| int EltIndex = (i + part * VF) * (Reverse ? -1 : 1); |
| Constant *Idx = ConstantInt::get(Induction->getType(), EltIndex); |
| Value *GlobalIdx; |
| if (!Reverse) |
| GlobalIdx = Builder.CreateAdd(NormalizedIdx, Idx, "gep.idx"); |
| else |
| GlobalIdx = Builder.CreateSub(Idx, NormalizedIdx, "gep.ridx"); |
| |
| Value *SclrGep = Builder.CreateGEP(II.StartValue, GlobalIdx, |
| "next.gep"); |
| VecVal = Builder.CreateInsertElement(VecVal, SclrGep, |
| Builder.getInt32(i), |
| "insert.gep"); |
| } |
| Entry[part] = VecVal; |
| } |
| return; |
| } |
| } |
| |
| void |
| InnerLoopVectorizer::vectorizeBlockInLoop(LoopVectorizationLegality *Legal, |
| BasicBlock *BB, PhiVector *PV) { |
| // 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:{ |
| // Vectorize PHINodes. |
| widenPHIInstruction(it, Entry, Legal, UF, VF, PV); |
| 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); |
| setDebugLocFromInst(Builder, BinOp); |
| 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. Notice: V can be an Undef. |
| BinaryOperator *VecOp = dyn_cast<BinaryOperator>(V); |
| if (VecOp && isa<OverflowingBinaryOperator>(BinOp)) { |
| VecOp->setHasNoSignedWrap(BinOp->hasNoSignedWrap()); |
| VecOp->setHasNoUnsignedWrap(BinOp->hasNoUnsignedWrap()); |
| } |
| if (VecOp && 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); |
| setDebugLocFromInst(Builder, it); |
| |
| // 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 = (VF == 1) ? Cond[0] : |
| 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); |
| setDebugLocFromInst(Builder, 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: |
| case Instruction::Load: |
| vectorizeMemoryInstruction(it, Legal); |
| 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); |
| setDebugLocFromInst(Builder, 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 = (VF == 1) ? CI->getType() : |
| VectorType::get(CI->getType(), 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: { |
| // Ignore dbg intrinsics. |
| if (isa<DbgInfoIntrinsic>(it)) |
| break; |
| setDebugLocFromInst(Builder, it); |
| |
| Module *M = BB->getParent()->getParent(); |
| CallInst *CI = cast<CallInst>(it); |
| Intrinsic::ID ID = getIntrinsicIDForCall(CI, TLI); |
| assert(ID && "Not an intrinsic call!"); |
| switch (ID) { |
| case Intrinsic::lifetime_end: |
| case Intrinsic::lifetime_start: |
| scalarizeInstruction(it); |
| break; |
| default: |
| for (unsigned Part = 0; Part < UF; ++Part) { |
| SmallVector<Value *, 4> Args; |
| for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i) { |
| VectorParts &Arg = getVectorValue(CI->getArgOperand(i)); |
| Args.push_back(Arg[Part]); |
| } |
| Type *Tys[] = {CI->getType()}; |
| if (VF > 1) |
| Tys[0] = VectorType::get(CI->getType()->getScalarType(), VF); |
| |
| Function *F = Intrinsic::getDeclaration(M, ID, Tys); |
| Entry[Part] = Builder.CreateCall(F, Args); |
| } |
| break; |
| } |
| 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(LoopBypassBlocks.front(), LoopExitBlock) && |
| "Entry does not dominate exit."); |
| |
| for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I) |
| DT->addNewBlock(LoopBypassBlocks[I], LoopBypassBlocks[I-1]); |
| DT->addNewBlock(LoopVectorPreHeader, LoopBypassBlocks.back()); |
| DT->addNewBlock(LoopVectorBody, LoopVectorPreHeader); |
| DT->addNewBlock(LoopMiddleBlock, LoopBypassBlocks.front()); |
| DT->addNewBlock(LoopScalarPreHeader, LoopMiddleBlock); |
| DT->changeImmediateDominator(LoopScalarBody, LoopScalarPreHeader); |
| DT->changeImmediateDominator(LoopExitBlock, LoopMiddleBlock); |
| |
| DEBUG(DT->verifyAnalysis()); |
| } |
| |
| /// \brief Check whether it is safe to if-convert this phi node. |
| /// |
| /// Phi nodes with constant expressions that can trap are not safe to if |
| /// convert. |
| static bool canIfConvertPHINodes(BasicBlock *BB) { |
| for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E; ++I) { |
| PHINode *Phi = dyn_cast<PHINode>(I); |
| if (!Phi) |
| return true; |
| for (unsigned p = 0, e = Phi->getNumIncomingValues(); p != e; ++p) |
| if (Constant *C = dyn_cast<Constant>(Phi->getIncomingValue(p))) |
| if (C->canTrap()) |
| return false; |
| } |
| return true; |
| } |
| |
| bool LoopVectorizationLegality::canVectorizeWithIfConvert() { |
| if (!EnableIfConversion) |
| return false; |
| |
| assert(TheLoop->getNumBlocks() > 1 && "Single block loops are vectorizable"); |
| |
| // A list of pointers that we can safely read and write to. |
| SmallPtrSet<Value *, 8> SafePointes; |
| |
| // Collect safe addresses. |
| for (Loop::block_iterator BI = TheLoop->block_begin(), |
| BE = TheLoop->block_end(); BI != BE; ++BI) { |
| BasicBlock *BB = *BI; |
| |
| if (blockNeedsPredication(BB)) |
| continue; |
| |
| for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E; ++I) { |
| if (LoadInst *LI = dyn_cast<LoadInst>(I)) |
| SafePointes.insert(LI->getPointerOperand()); |
| else if (StoreInst *SI = dyn_cast<StoreInst>(I)) |
| SafePointes.insert(SI->getPointerOperand()); |
| } |
| } |
| |
| // Collect the blocks that need predication. |
| BasicBlock *Header = TheLoop->getHeader(); |
| for (Loop::block_iterator BI = TheLoop->block_begin(), |
| BE = TheLoop->block_end(); BI != BE; ++BI) { |
| BasicBlock *BB = *BI; |
| |
| // We don't support switch statements inside loops. |
| if (!isa<BranchInst>(BB->getTerminator())) |
| return false; |
| |
| // We must be able to predicate all blocks that need to be predicated. |
| if (blockNeedsPredication(BB)) { |
| if (!blockCanBePredicated(BB, SafePointes)) |
| return false; |
| } else if (BB != Header && !canIfConvertPHINodes(BB)) |
| return false; |
| |
| } |
| |
| // We can if-convert this loop. |
| return true; |
| } |
| |
| bool LoopVectorizationLegality::canVectorize() { |
| // We must have a loop in canonical form. Loops with indirectbr in them cannot |
| // be canonicalized. |
| if (!TheLoop->getLoopPreheader()) |
| return false; |
| |
| // 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; |
| |
| // We need to have a loop header. |
| DEBUG(dbgs() << "LV: Found a loop: " << |
| TheLoop->getHeader()->getName() << '\n'); |
| |
| // Check if we can if-convert non single-bb loops. |
| unsigned NumBlocks = TheLoop->getNumBlocks(); |
| if (NumBlocks != 1 && !canVectorizeWithIfConvert()) { |
| DEBUG(dbgs() << "LV: Can't if-convert the loop.\n"); |
| return false; |
| } |
| |
| // ScalarEvolution needs to be able to find the exit count. |
| const SCEV *ExitCount = SE->getBackedgeTakenCount(TheLoop); |
| 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. |
| BasicBlock *Latch = TheLoop->getLoopLatch(); |
| 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; |
| } |
| |
| static Type *convertPointerToIntegerType(DataLayout &DL, Type *Ty) { |
| if (Ty->isPointerTy()) |
| return DL.getIntPtrType(Ty); |
| |
| // It is possible that char's or short's overflow when we ask for the loop's |
| // trip count, work around this by changing the type size. |
| if (Ty->getScalarSizeInBits() < 32) |
| return Type::getInt32Ty(Ty->getContext()); |
| |
| return Ty; |
| } |
| |
| static Type* getWiderType(DataLayout &DL, Type *Ty0, Type *Ty1) { |
| Ty0 = convertPointerToIntegerType(DL, Ty0); |
| Ty1 = convertPointerToIntegerType(DL, Ty1); |
| if (Ty0->getScalarSizeInBits() > Ty1->getScalarSizeInBits()) |
| return Ty0; |
| return Ty1; |
| } |
| |
| /// \brief Check that the instruction has outside loop users and is not an |
| /// identified reduction variable. |
| static bool hasOutsideLoopUser(const Loop *TheLoop, Instruction *Inst, |
| SmallPtrSet<Value *, 4> &Reductions) { |
| // Reduction instructions are allowed to have exit users. All other |
| // instructions must not have external users. |
| if (!Reductions.count(Inst)) |
| //Check that all of the users of the loop are inside the BB. |
| for (Value::use_iterator I = Inst->use_begin(), E = Inst->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 true; |
| } |
| } |
| return false; |
| } |
| |
| bool LoopVectorizationLegality::canVectorizeInstrs() { |
| BasicBlock *PreHeader = TheLoop->getLoopPreheader(); |
| BasicBlock *Header = TheLoop->getHeader(); |
| |
| // Look for the attribute signaling the absence of NaNs. |
| Function &F = *Header->getParent(); |
| if (F.hasFnAttribute("no-nans-fp-math")) |
| HasFunNoNaNAttr = F.getAttributes().getAttribute( |
| AttributeSet::FunctionIndex, |
| "no-nans-fp-math").getValueAsString() == "true"; |
| |
| // 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)) { |
| Type *PhiTy = Phi->getType(); |
| // Check that this PHI type is allowed. |
| if (!PhiTy->isIntegerTy() && |
| !PhiTy->isFloatingPointTy() && |
| !PhiTy->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) { |
| // Check that this instruction has no outside users or is an |
| // identified reduction value with an outside user. |
| if(!hasOutsideLoopUser(TheLoop, it, AllowedExit)) |
| continue; |
| return false; |
| } |
| |
| // We only allow if-converted PHIs with more than two incoming values. |
| if (Phi->getNumIncomingValues() != 2) { |
| DEBUG(dbgs() << "LV: Found an invalid PHI.\n"); |
| return false; |
| } |
| |
| // 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) { |
| // Get the widest type. |
| if (!WidestIndTy) |
| WidestIndTy = convertPointerToIntegerType(*DL, PhiTy); |
| else |
| WidestIndTy = getWiderType(*DL, PhiTy, WidestIndTy); |
| |
| // Int inductions are special because we only allow one IV. |
| if (IK == IK_IntInduction) { |
| // Use the phi node with the widest type as induction. Use the last |
| // one if there are multiple (no good reason for doing this other |
| // than it is expedient). |
| if (!Induction || PhiTy == WidestIndTy) |
| Induction = Phi; |
| } |
| |
| DEBUG(dbgs() << "LV: Found an induction variable.\n"); |
| Inductions[Phi] = InductionInfo(StartValue, IK); |
| |
| // Until we explicitly handle the case of an induction variable with |
| // an outside loop user we have to give up vectorizing this loop. |
| if (hasOutsideLoopUser(TheLoop, it, AllowedExit)) |
| return false; |
| |
| 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_IntegerMinMax)) { |
| DEBUG(dbgs() << "LV: Found a MINMAX 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; |
| } |
| if (AddReductionVar(Phi, RK_FloatMinMax)) { |
| DEBUG(dbgs() << "LV: Found an float MINMAX 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. However, we can ignore dbg intrinsic |
| // calls and we do handle certain intrinsic and libm functions. |
| CallInst *CI = dyn_cast<CallInst>(it); |
| if (CI && !getIntrinsicIDForCall(CI, TLI) && !isa<DbgInfoIntrinsic>(CI)) { |
| DEBUG(dbgs() << "LV: Found a call site.\n"); |
| return false; |
| } |
| |
| // Check that the instruction return type is vectorizable. |
| // Also, we can't vectorize extractelement instructions. |
| if ((!VectorType::isValidElementType(it->getType()) && |
| !it->getType()->isVoidTy()) || isa<ExtractElementInst>(it)) { |
| 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 (hasOutsideLoopUser(TheLoop, it, AllowedExit)) |
| return false; |
| |
| } // next instr. |
| |
| } |
| |
| if (!Induction) { |
| DEBUG(dbgs() << "LV: Did not find one integer induction var.\n"); |
| if (Inductions.empty()) |
| return false; |
| } |
| |
| 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. |
| Worklist.insert(Worklist.end(), I->op_begin(), I->op_end()); |
| } |
| } |
| |
| namespace { |
| /// \brief Analyses memory accesses in a loop. |
| /// |
| /// Checks whether run time pointer checks are needed and builds sets for data |
| /// dependence checking. |
| class AccessAnalysis { |
| public: |
| /// \brief Read or write access location. |
| typedef PointerIntPair<Value *, 1, bool> MemAccessInfo; |
| typedef SmallPtrSet<MemAccessInfo, 8> MemAccessInfoSet; |
| |
| /// \brief Set of potential dependent memory accesses. |
| typedef EquivalenceClasses<MemAccessInfo> DepCandidates; |
| |
| AccessAnalysis(DataLayout *Dl, DepCandidates &DA) : |
| DL(Dl), DepCands(DA), AreAllWritesIdentified(true), |
| AreAllReadsIdentified(true), IsRTCheckNeeded(false) {} |
| |
| /// \brief Register a load and whether it is only read from. |
| void addLoad(Value *Ptr, bool IsReadOnly) { |
| Accesses.insert(MemAccessInfo(Ptr, false)); |
| if (IsReadOnly) |
| ReadOnlyPtr.insert(Ptr); |
| } |
| |
| /// \brief Register a store. |
| void addStore(Value *Ptr) { |
| Accesses.insert(MemAccessInfo(Ptr, true)); |
| } |
| |
| /// \brief Check whether we can check the pointers at runtime for |
| /// non-intersection. |
| bool canCheckPtrAtRT(LoopVectorizationLegality::RuntimePointerCheck &RtCheck, |
| unsigned &NumComparisons, ScalarEvolution *SE, |
| Loop *TheLoop, bool ShouldCheckStride = false); |
| |
| /// \brief Goes over all memory accesses, checks whether a RT check is needed |
| /// and builds sets of dependent accesses. |
| void buildDependenceSets() { |
| // Process read-write pointers first. |
| processMemAccesses(false); |
| // Next, process read pointers. |
| processMemAccesses(true); |
| } |
| |
| bool isRTCheckNeeded() { return IsRTCheckNeeded; } |
| |
| bool isDependencyCheckNeeded() { return !CheckDeps.empty(); } |
| void resetDepChecks() { CheckDeps.clear(); } |
| |
| MemAccessInfoSet &getDependenciesToCheck() { return CheckDeps; } |
| |
| private: |
| typedef SetVector<MemAccessInfo> PtrAccessSet; |
| typedef DenseMap<Value*, MemAccessInfo> UnderlyingObjToAccessMap; |
| |
| /// \brief Go over all memory access or only the deferred ones if |
| /// \p UseDeferred is true and check whether runtime pointer checks are needed |
| /// and build sets of dependency check candidates. |
| void processMemAccesses(bool UseDeferred); |
| |
| /// Set of all accesses. |
| PtrAccessSet Accesses; |
| |
| /// Set of access to check after all writes have been processed. |
| PtrAccessSet DeferredAccesses; |
| |
| /// Map of pointers to last access encountered. |
| UnderlyingObjToAccessMap ObjToLastAccess; |
| |
| /// Set of accesses that need a further dependence check. |
| MemAccessInfoSet CheckDeps; |
| |
| /// Set of pointers that are read only. |
| SmallPtrSet<Value*, 16> ReadOnlyPtr; |
| |
| /// Set of underlying objects already written to. |
| SmallPtrSet<Value*, 16> WriteObjects; |
| |
| DataLayout *DL; |
| |
| /// Sets of potentially dependent accesses - members of one set share an |
| /// underlying pointer. The set "CheckDeps" identfies which sets really need a |
| /// dependence check. |
| DepCandidates &DepCands; |
| |
| bool AreAllWritesIdentified; |
| bool AreAllReadsIdentified; |
| bool IsRTCheckNeeded; |
| }; |
| |
| } // end anonymous namespace |
| |
| /// \brief Check whether a pointer can participate in a runtime bounds check. |
| static bool hasComputableBounds(ScalarEvolution *SE, Value *Ptr) { |
| const SCEV *PtrScev = SE->getSCEV(Ptr); |
| const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PtrScev); |
| if (!AR) |
| return false; |
| |
| return AR->isAffine(); |
| } |
| |
| /// \brief Check the stride of the pointer and ensure that it does not wrap in |
| /// the address space. |
| static int isStridedPtr(ScalarEvolution *SE, DataLayout *DL, Value *Ptr, |
| const Loop *Lp); |
| |
| bool AccessAnalysis::canCheckPtrAtRT( |
| LoopVectorizationLegality::RuntimePointerCheck &RtCheck, |
| unsigned &NumComparisons, ScalarEvolution *SE, |
| Loop *TheLoop, bool ShouldCheckStride) { |
| // Find pointers with computable bounds. We are going to use this information |
| // to place a runtime bound check. |
| unsigned NumReadPtrChecks = 0; |
| unsigned NumWritePtrChecks = 0; |
| bool CanDoRT = true; |
| |
| bool IsDepCheckNeeded = isDependencyCheckNeeded(); |
| // We assign consecutive id to access from different dependence sets. |
| // Accesses within the same set don't need a runtime check. |
| unsigned RunningDepId = 1; |
| DenseMap<Value *, unsigned> DepSetId; |
| |
| for (PtrAccessSet::iterator AI = Accesses.begin(), AE = Accesses.end(); |
| AI != AE; ++AI) { |
| const MemAccessInfo &Access = *AI; |
| Value *Ptr = Access.getPointer(); |
| bool IsWrite = Access.getInt(); |
| |
| // Just add write checks if we have both. |
| if (!IsWrite && Accesses.count(MemAccessInfo(Ptr, true))) |
| continue; |
| |
| if (IsWrite) |
| ++NumWritePtrChecks; |
| else |
| ++NumReadPtrChecks; |
| |
| if (hasComputableBounds(SE, Ptr) && |
| // When we run after a failing dependency check we have to make sure we |
| // don't have wrapping pointers. |
| (!ShouldCheckStride || isStridedPtr(SE, DL, Ptr, TheLoop) == 1)) { |
| // The id of the dependence set. |
| unsigned DepId; |
| |
| if (IsDepCheckNeeded) { |
| Value *Leader = DepCands.getLeaderValue(Access).getPointer(); |
| unsigned &LeaderId = DepSetId[Leader]; |
| if (!LeaderId) |
| LeaderId = RunningDepId++; |
| DepId = LeaderId; |
| } else |
| // Each access has its own dependence set. |
| DepId = RunningDepId++; |
| |
| RtCheck.insert(SE, TheLoop, Ptr, IsWrite, DepId); |
| |
| DEBUG(dbgs() << "LV: Found a runtime check ptr:" << *Ptr << '\n'); |
| } else { |
| CanDoRT = false; |
| } |
| } |
| |
| if (IsDepCheckNeeded && CanDoRT && RunningDepId == 2) |
| NumComparisons = 0; // Only one dependence set. |
| else { |
| NumComparisons = (NumWritePtrChecks * (NumReadPtrChecks + |
| NumWritePtrChecks - 1)); |
| } |
| |
| // If the pointers that we would use for the bounds comparison have different |
| // address spaces, assume the values aren't directly comparable, so we can't |
| // use them for the runtime check. We also have to assume they could |
| // overlap. In the future there should be metadata for whether address spaces |
| // are disjoint. |
| unsigned NumPointers = RtCheck.Pointers.size(); |
| for (unsigned i = 0; i < NumPointers; ++i) { |
| for (unsigned j = i + 1; j < NumPointers; ++j) { |
| // Only need to check pointers between two different dependency sets. |
| if (RtCheck.DependencySetId[i] == RtCheck.DependencySetId[j]) |
| continue; |
| |
| Value *PtrI = RtCheck.Pointers[i]; |
| Value *PtrJ = RtCheck.Pointers[j]; |
| |
| unsigned ASi = PtrI->getType()->getPointerAddressSpace(); |
| unsigned ASj = PtrJ->getType()->getPointerAddressSpace(); |
| if (ASi != ASj) { |
| DEBUG(dbgs() << "LV: Runtime check would require comparison between" |
| " different address spaces\n"); |
| return false; |
| } |
| } |
| } |
| |
| return CanDoRT; |
| } |
| |
| static bool isFunctionScopeIdentifiedObject(Value *Ptr) { |
| return isNoAliasArgument(Ptr) || isNoAliasCall(Ptr) || isa<AllocaInst>(Ptr); |
| } |
| |
| void AccessAnalysis::processMemAccesses(bool UseDeferred) { |
| // We process the set twice: first we process read-write pointers, last we |
| // process read-only pointers. This allows us to skip dependence tests for |
| // read-only pointers. |
| |
| PtrAccessSet &S = UseDeferred ? DeferredAccesses : Accesses; |
| for (PtrAccessSet::iterator AI = S.begin(), AE = S.end(); AI != AE; ++AI) { |
| const MemAccessInfo &Access = *AI; |
| Value *Ptr = Access.getPointer(); |
| bool IsWrite = Access.getInt(); |
| |
| DepCands.insert(Access); |
| |
| // Memorize read-only pointers for later processing and skip them in the |
| // first round (they need to be checked after we have seen all write |
| // pointers). Note: we also mark pointer that are not consecutive as |
| // "read-only" pointers (so that we check "a[b[i]] +="). Hence, we need the |
| // second check for "!IsWrite". |
| bool IsReadOnlyPtr = ReadOnlyPtr.count(Ptr) && !IsWrite; |
| if (!UseDeferred && IsReadOnlyPtr) { |
| DeferredAccesses.insert(Access); |
| continue; |
| } |
| |
| bool NeedDepCheck = false; |
| // Check whether there is the possiblity of dependency because of underlying |
| // objects being the same. |
| typedef SmallVector<Value*, 16> ValueVector; |
| ValueVector TempObjects; |
| GetUnderlyingObjects(Ptr, TempObjects, DL); |
| for (ValueVector::iterator UI = TempObjects.begin(), UE = TempObjects.end(); |
| UI != UE; ++UI) { |
| Value *UnderlyingObj = *UI; |
| |
| // If this is a write then it needs to be an identified object. If this a |
| // read and all writes (so far) are identified function scope objects we |
| // don't need an identified underlying object but only an Argument (the |
| // next write is going to invalidate this assumption if it is |
| // unidentified). |
| // This is a micro-optimization for the case where all writes are |
| // identified and we have one argument pointer. |
| // Otherwise, we do need a runtime check. |
| if ((IsWrite && !isFunctionScopeIdentifiedObject(UnderlyingObj)) || |
| (!IsWrite && (!AreAllWritesIdentified || |
| !isa<Argument>(UnderlyingObj)) && |
| !isIdentifiedObject(UnderlyingObj))) { |
| DEBUG(dbgs() << "LV: Found an unidentified " << |
| (IsWrite ? "write" : "read" ) << " ptr: " << *UnderlyingObj << |
| "\n"); |
| IsRTCheckNeeded = (IsRTCheckNeeded || |
| !isIdentifiedObject(UnderlyingObj) || |
| !AreAllReadsIdentified); |
| |
| if (IsWrite) |
| AreAllWritesIdentified = false; |
| if (!IsWrite) |
| AreAllReadsIdentified = false; |
| } |
| |
| // If this is a write - check other reads and writes for conflicts. If |
| // this is a read only check other writes for conflicts (but only if there |
| // is no other write to the ptr - this is an optimization to catch "a[i] = |
| // a[i] + " without having to do a dependence check). |
| if ((IsWrite || IsReadOnlyPtr) && WriteObjects.count(UnderlyingObj)) |
| NeedDepCheck = true; |
| |
| if (IsWrite) |
| WriteObjects.insert(UnderlyingObj); |
| |
| // Create sets of pointers connected by shared underlying objects. |
| UnderlyingObjToAccessMap::iterator Prev = |
| ObjToLastAccess.find(UnderlyingObj); |
| if (Prev != ObjToLastAccess.end()) |
| DepCands.unionSets(Access, Prev->second); |
| |
| ObjToLastAccess[UnderlyingObj] = Access; |
| } |
| |
| if (NeedDepCheck) |
| CheckDeps.insert(Access); |
| } |
| } |
| |
| namespace { |
| /// \brief Checks memory dependences among accesses to the same underlying |
| /// object to determine whether there vectorization is legal or not (and at |
| /// which vectorization factor). |
| /// |
| /// This class works under the assumption that we already checked that memory |
| /// locations with different underlying pointers are "must-not alias". |
| /// We use the ScalarEvolution framework to symbolically evalutate access |
| /// functions pairs. Since we currently don't restructure the loop we can rely |
| /// on the program order of memory accesses to determine their safety. |
| /// At the moment we will only deem accesses as safe for: |
| /// * A negative constant distance assuming program order. |
| /// |
| /// Safe: tmp = a[i + 1]; OR a[i + 1] = x; |
| /// a[i] = tmp; y = a[i]; |
| /// |
| /// The latter case is safe because later checks guarantuee that there can't |
| /// be a cycle through a phi node (that is, we check that "x" and "y" is not |
| /// the same variable: a header phi can only be an induction or a reduction, a |
| /// reduction can't have a memory sink, an induction can't have a memory |
| /// source). This is important and must not be violated (or we have to |
| /// resort to checking for cycles through memory). |
| /// |
| /// * A positive constant distance assuming program order that is bigger |
| /// than the biggest memory access. |
| /// |
| /// tmp = a[i] OR b[i] = x |
| /// a[i+2] = tmp y = b[i+2]; |
| /// |
| /// Safe distance: 2 x sizeof(a[0]), and 2 x sizeof(b[0]), respectively. |
| /// |
| /// * Zero distances and all accesses have the same size. |
| /// |
| class MemoryDepChecker { |
| public: |
| typedef PointerIntPair<Value *, 1, bool> MemAccessInfo; |
| typedef SmallPtrSet<MemAccessInfo, 8> MemAccessInfoSet; |
| |
| MemoryDepChecker(ScalarEvolution *Se, DataLayout *Dl, const Loop *L) |
| : SE(Se), DL(Dl), InnermostLoop(L), AccessIdx(0), |
| ShouldRetryWithRuntimeCheck(false) {} |
| |
| /// \brief Register the location (instructions are given increasing numbers) |
| /// of a write access. |
| void addAccess(StoreInst *SI) { |
| Value *Ptr = SI->getPointerOperand(); |
| Accesses[MemAccessInfo(Ptr, true)].push_back(AccessIdx); |
| InstMap.push_back(SI); |
| ++AccessIdx; |
| } |
| |
| /// \brief Register the location (instructions are given increasing numbers) |
| /// of a write access. |
| void addAccess(LoadInst *LI) { |
| Value *Ptr = LI->getPointerOperand(); |
| Accesses[MemAccessInfo(Ptr, false)].push_back(AccessIdx); |
| InstMap.push_back(LI); |
| ++AccessIdx; |
| } |
| |
| /// \brief Check whether the dependencies between the accesses are safe. |
| /// |
| /// Only checks sets with elements in \p CheckDeps. |
| bool areDepsSafe(AccessAnalysis::DepCandidates &AccessSets, |
| MemAccessInfoSet &CheckDeps); |
| |
| /// \brief The maximum number of bytes of a vector register we can vectorize |
| /// the accesses safely with. |
| unsigned getMaxSafeDepDistBytes() { return MaxSafeDepDistBytes; } |
| |
| /// \brief In same cases when the dependency check fails we can still |
| /// vectorize the loop with a dynamic array access check. |
| bool shouldRetryWithRuntimeCheck() { return ShouldRetryWithRuntimeCheck; } |
| |
| private: |
| ScalarEvolution *SE; |
| DataLayout *DL; |
| const Loop *InnermostLoop; |
| |
| /// \brief Maps access locations (ptr, read/write) to program order. |
| DenseMap<MemAccessInfo, std::vector<unsigned> > Accesses; |
| |
| /// \brief Memory access instructions in program order. |
| SmallVector<Instruction *, 16> InstMap; |
| |
| /// \brief The program order index to be used for the next instruction. |
| unsigned AccessIdx; |
| |
| // We can access this many bytes in parallel safely. |
| unsigned MaxSafeDepDistBytes; |
| |
| /// \brief If we see a non constant dependence distance we can still try to |
| /// vectorize this loop with runtime checks. |
| bool ShouldRetryWithRuntimeCheck; |
| |
| /// \brief Check whether there is a plausible dependence between the two |
| /// accesses. |
| /// |
| /// Access \p A must happen before \p B in program order. The two indices |
| /// identify the index into the program order map. |
| /// |
| /// This function checks whether there is a plausible dependence (or the |
| /// absence of such can't be proved) between the two accesses. If there is a |
| /// plausible dependence but the dependence distance is bigger than one |
| /// element access it records this distance in \p MaxSafeDepDistBytes (if this |
| /// distance is smaller than any other distance encountered so far). |
| /// Otherwise, this function returns true signaling a possible dependence. |
| bool isDependent(const MemAccessInfo &A, unsigned AIdx, |
| const MemAccessInfo &B, unsigned BIdx); |
| |
| /// \brief Check whether the data dependence could prevent store-load |
| /// forwarding. |
| bool couldPreventStoreLoadForward(unsigned Distance, unsigned TypeByteSize); |
| }; |
| |
| } // end anonymous namespace |
| |
| static bool isInBoundsGep(Value *Ptr) { |
| if (GetElementPtrInst *GEP = dyn_cast<GetElementPtrInst>(Ptr)) |
| return GEP->isInBounds(); |
| return false; |
| } |
| |
| /// \brief Check whether the access through \p Ptr has a constant stride. |
| static int isStridedPtr(ScalarEvolution *SE, DataLayout *DL, Value *Ptr, |
| const Loop *Lp) { |
| const Type *Ty = Ptr->getType(); |
| assert(Ty->isPointerTy() && "Unexpected non ptr"); |
| |
| // Make sure that the pointer does not point to aggregate types. |
| const PointerType *PtrTy = cast<PointerType>(Ty); |
| if (PtrTy->getElementType()->isAggregateType()) { |
| DEBUG(dbgs() << "LV: Bad stride - Not a pointer to a scalar type" << *Ptr << |
| "\n"); |
| return 0; |
| } |
| |
| const SCEV *PtrScev = SE->getSCEV(Ptr); |
| const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PtrScev); |
| if (!AR) { |
| DEBUG(dbgs() << "LV: Bad stride - Not an AddRecExpr pointer " |
| << *Ptr << " SCEV: " << *PtrScev << "\n"); |
| return 0; |
| } |
| |
| // The accesss function must stride over the innermost loop. |
| if (Lp != AR->getLoop()) { |
| DEBUG(dbgs() << "LV: Bad stride - Not striding over innermost loop " << |
| *Ptr << " SCEV: " << *PtrScev << "\n"); |
| } |
| |
| // The address calculation must not wrap. Otherwise, a dependence could be |
| // inverted. |
| // An inbounds getelementptr that is a AddRec with a unit stride |
| // cannot wrap per definition. The unit stride requirement is checked later. |
| // An getelementptr without an inbounds attribute and unit stride would have |
| // to access the pointer value "0" which is undefined behavior in address |
| // space 0, therefore we can also vectorize this case. |
| bool IsInBoundsGEP = isInBoundsGep(Ptr); |
| bool IsNoWrapAddRec = AR->getNoWrapFlags(SCEV::NoWrapMask); |
| bool IsInAddressSpaceZero = PtrTy->getAddressSpace() == 0; |
| if (!IsNoWrapAddRec && !IsInBoundsGEP && !IsInAddressSpaceZero) { |
| DEBUG(dbgs() << "LV: Bad stride - Pointer may wrap in the address space " |
| << *Ptr << " SCEV: " << *PtrScev << "\n"); |
| return 0; |
| } |
| |
| // Check the step is constant. |
| const SCEV *Step = AR->getStepRecurrence(*SE); |
| |
| // Calculate the pointer stride and check if it is consecutive. |
| const SCEVConstant *C = dyn_cast<SCEVConstant>(Step); |
| if (!C) { |
| DEBUG(dbgs() << "LV: Bad stride - Not a constant strided " << *Ptr << |
| " SCEV: " << *PtrScev << "\n"); |
| return 0; |
| } |
| |
| int64_t Size = DL->getTypeAllocSize(PtrTy->getElementType()); |
| const APInt &APStepVal = C->getValue()->getValue(); |
| |
| // Huge step value - give up. |
| if (APStepVal.getBitWidth() > 64) |
| return 0; |
| |
| int64_t StepVal = APStepVal.getSExtValue(); |
| |
| // Strided access. |
| int64_t Stride = StepVal / Size; |
| int64_t Rem = StepVal % Size; |
| if (Rem) |
| return 0; |
| |
| // If the SCEV could wrap but we have an inbounds gep with a unit stride we |
| // know we can't "wrap around the address space". In case of address space |
| // zero we know that this won't happen without triggering undefined behavior. |
| if (!IsNoWrapAddRec && (IsInBoundsGEP || IsInAddressSpaceZero) && |
| Stride != 1 && Stride != -1) |
| return 0; |
| |
| return Stride; |
| } |
| |
| bool MemoryDepChecker::couldPreventStoreLoadForward(unsigned Distance, |
| unsigned TypeByteSize) { |
| // If loads occur at a distance that is not a multiple of a feasible vector |
| // factor store-load forwarding does not take place. |
| // Positive dependences might cause troubles because vectorizing them might |
| // prevent store-load forwarding making vectorized code run a lot slower. |
| // a[i] = a[i-3] ^ a[i-8]; |
| // The stores to a[i:i+1] don't align with the stores to a[i-3:i-2] and |
| // hence on your typical architecture store-load forwarding does not take |
| // place. Vectorizing in such cases does not make sense. |
| // Store-load forwarding distance. |
| const unsigned NumCyclesForStoreLoadThroughMemory = 8*TypeByteSize; |
| // Maximum vector factor. |
| unsigned MaxVFWithoutSLForwardIssues = MaxVectorWidth*TypeByteSize; |
| if(MaxSafeDepDistBytes < MaxVFWithoutSLForwardIssues) |
| MaxVFWithoutSLForwardIssues = MaxSafeDepDistBytes; |
| |
| for (unsigned vf = 2*TypeByteSize; vf <= MaxVFWithoutSLForwardIssues; |
| vf *= 2) { |
| if (Distance % vf && Distance / vf < NumCyclesForStoreLoadThroughMemory) { |
| MaxVFWithoutSLForwardIssues = (vf >>=1); |
| break; |
| } |
| } |
| |
| if (MaxVFWithoutSLForwardIssues< 2*TypeByteSize) { |
| DEBUG(dbgs() << "LV: Distance " << Distance << |
| " that could cause a store-load forwarding conflict\n"); |
| return true; |
| } |
| |
| if (MaxVFWithoutSLForwardIssues < MaxSafeDepDistBytes && |
| MaxVFWithoutSLForwardIssues != MaxVectorWidth*TypeByteSize) |
| MaxSafeDepDistBytes = MaxVFWithoutSLForwardIssues; |
| return false; |
| } |
| |
| bool MemoryDepChecker::isDependent(const MemAccessInfo &A, unsigned AIdx, |
| const MemAccessInfo &B, unsigned BIdx) { |
| assert (AIdx < BIdx && "Must pass arguments in program order"); |
| |
| Value *APtr = A.getPointer(); |
| Value *BPtr = B.getPointer(); |
| bool AIsWrite = A.getInt(); |
| bool BIsWrite = B.getInt(); |
| |
| // Two reads are independent. |
| if (!AIsWrite && !BIsWrite) |
| return false; |
| |
| const SCEV *AScev = SE->getSCEV(APtr); |
| const SCEV *BScev = SE->getSCEV(BPtr); |
| |
| int StrideAPtr = isStridedPtr(SE, DL, APtr, InnermostLoop); |
| int StrideBPtr = isStridedPtr(SE, DL, BPtr, InnermostLoop); |
| |
| const SCEV *Src = AScev; |
| const SCEV *Sink = BScev; |
| |
| // If the induction step is negative we have to invert source and sink of the |
| // dependence. |
| if (StrideAPtr < 0) { |
| //Src = BScev; |
| //Sink = AScev; |
| std::swap(APtr, BPtr); |
| std::swap(Src, Sink); |
| std::swap(AIsWrite, BIsWrite); |
| std::swap(AIdx, BIdx); |
| std::swap(StrideAPtr, StrideBPtr); |
| } |
| |
| const SCEV *Dist = SE->getMinusSCEV(Sink, Src); |
| |
| DEBUG(dbgs() << "LV: Src Scev: " << *Src << "Sink Scev: " << *Sink |
| << "(Induction step: " << StrideAPtr << ")\n"); |
| DEBUG(dbgs() << "LV: Distance for " << *InstMap[AIdx] << " to " |
| << *InstMap[BIdx] << ": " << *Dist << "\n"); |
| |
| // Need consecutive accesses. We don't want to vectorize |
| // "A[B[i]] += ..." and similar code or pointer arithmetic that could wrap in |
| // the address space. |
| if (!StrideAPtr || !StrideBPtr || StrideAPtr != StrideBPtr){ |
| DEBUG(dbgs() << "Non-consecutive pointer access\n"); |
| return true; |
| } |
| |
| const SCEVConstant *C = dyn_cast<SCEVConstant>(Dist); |
| if (!C) { |
| DEBUG(dbgs() << "LV: Dependence because of non constant distance\n"); |
| ShouldRetryWithRuntimeCheck = true; |
| return true; |
| } |
| |
| Type *ATy = APtr->getType()->getPointerElementType(); |
| Type *BTy = BPtr->getType()->getPointerElementType(); |
| unsigned TypeByteSize = DL->getTypeAllocSize(ATy); |
| |
| // Negative distances are not plausible dependencies. |
| const APInt &Val = C->getValue()->getValue(); |
| if (Val.isNegative()) { |
| bool IsTrueDataDependence = (AIsWrite && !BIsWrite); |
| if (IsTrueDataDependence && |
| (couldPreventStoreLoadForward(Val.abs().getZExtValue(), TypeByteSize) || |
| ATy != BTy)) |
| return true; |
| |
| DEBUG(dbgs() << "LV: Dependence is negative: NoDep\n"); |
| return false; |
| } |
| |
| // Write to the same location with the same size. |
| // Could be improved to assert type sizes are the same (i32 == float, etc). |
| if (Val == 0) { |
| if (ATy == BTy) |
| return false; |
| DEBUG(dbgs() << "LV: Zero dependence difference but different types\n"); |
| return true; |
| } |
| |
| assert(Val.isStrictlyPositive() && "Expect a positive value"); |
| |
| // Positive distance bigger than max vectorization factor. |
| if (ATy != BTy) { |
| DEBUG(dbgs() << |
| "LV: ReadWrite-Write positive dependency with different types\n"); |
| return false; |
| } |
| |
| unsigned Distance = (unsigned) Val.getZExtValue(); |
| |
| // Bail out early if passed-in parameters make vectorization not feasible. |
| unsigned ForcedFactor = VectorizationFactor ? VectorizationFactor : 1; |
| unsigned ForcedUnroll = VectorizationUnroll ? VectorizationUnroll : 1; |
| |
| // The distance must be bigger than the size needed for a vectorized version |
| // of the operation and the size of the vectorized operation must not be |
| // bigger than the currrent maximum size. |
| if (Distance < 2*TypeByteSize || |
| 2*TypeByteSize > MaxSafeDepDistBytes || |
| Distance < TypeByteSize * ForcedUnroll * ForcedFactor) { |
| DEBUG(dbgs() << "LV: Failure because of Positive distance " |
| << Val.getSExtValue() << '\n'); |
| return true; |
| } |
| |
| MaxSafeDepDistBytes = Distance < MaxSafeDepDistBytes ? |
| Distance : MaxSafeDepDistBytes; |
| |
| bool IsTrueDataDependence = (!AIsWrite && BIsWrite); |
| if (IsTrueDataDependence && |
| couldPreventStoreLoadForward(Distance, TypeByteSize)) |
| return true; |
| |
| DEBUG(dbgs() << "LV: Positive distance " << Val.getSExtValue() << |
| " with max VF = " << MaxSafeDepDistBytes / TypeByteSize << '\n'); |
| |
| return false; |
| } |
| |
| bool |
| MemoryDepChecker::areDepsSafe(AccessAnalysis::DepCandidates &AccessSets, |
| MemAccessInfoSet &CheckDeps) { |
| |
| MaxSafeDepDistBytes = -1U; |
| while (!CheckDeps.empty()) { |
| MemAccessInfo CurAccess = *CheckDeps.begin(); |
| |
| // Get the relevant memory access set. |
| EquivalenceClasses<MemAccessInfo>::iterator I = |
| AccessSets.findValue(AccessSets.getLeaderValue(CurAccess)); |
| |
| // Check accesses within this set. |
| EquivalenceClasses<MemAccessInfo>::member_iterator AI, AE; |
| AI = AccessSets.member_begin(I), AE = AccessSets.member_end(); |
| |
| // Check every access pair. |
| while (AI != AE) { |
| CheckDeps.erase(*AI); |
| EquivalenceClasses<MemAccessInfo>::member_iterator OI = llvm::next(AI); |
| while (OI != AE) { |
| // Check every accessing instruction pair in program order. |
| for (std::vector<unsigned>::iterator I1 = Accesses[*AI].begin(), |
| I1E = Accesses[*AI].end(); I1 != I1E; ++I1) |
| for (std::vector<unsigned>::iterator I2 = Accesses[*OI].begin(), |
| I2E = Accesses[*OI].end(); I2 != I2E; ++I2) { |
| if (*I1 < *I2 && isDependent(*AI, *I1, *OI, *I2)) |
| return false; |
| if (*I2 < *I1 && isDependent(*OI, *I2, *AI, *I1)) |
| return false; |
| } |
| ++OI; |
| } |
| AI++; |
| } |
| } |
| return true; |
| } |
| |
| bool LoopVectorizationLegality::canVectorizeMemory() { |
| |
| typedef SmallVector<Value*, 16> ValueVector; |
| typedef SmallPtrSet<Value*, 16> ValueSet; |
| |
| // Holds the Load and Store *instructions*. |
| ValueVector Loads; |
| ValueVector Stores; |
| |
| // Holds all the different accesses in the loop. |
| unsigned NumReads = 0; |
| unsigned NumReadWrites = 0; |
| |
| PtrRtCheck.Pointers.clear(); |
| PtrRtCheck.Need = false; |
| |
| const bool IsAnnotatedParallel = TheLoop->isAnnotatedParallel(); |
| MemoryDepChecker DepChecker(SE, DL, TheLoop); |
| |
| // 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()) { |
| // Many math library functions read the rounding mode. We will only |
| // vectorize a loop if it contains known function calls that don't set |
| // the flag. Therefore, it is safe to ignore this read from memory. |
| CallInst *Call = dyn_cast<CallInst>(it); |
| if (Call && getIntrinsicIDForCall(Call, TLI)) |
| continue; |
| |
| LoadInst *Ld = dyn_cast<LoadInst>(it); |
| if (!Ld) return false; |
| if (!Ld->isSimple() && !IsAnnotatedParallel) { |
| DEBUG(dbgs() << "LV: Found a non-simple load.\n"); |
| return false; |
| } |
| Loads.push_back(Ld); |
| DepChecker.addAccess(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() && !IsAnnotatedParallel) { |
| DEBUG(dbgs() << "LV: Found a non-simple store.\n"); |
| return false; |
| } |
| Stores.push_back(St); |
| DepChecker.addAccess(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; |
| } |
| |
| AccessAnalysis::DepCandidates DependentAccesses; |
| AccessAnalysis Accesses(DL, DependentAccesses); |
| |
| // 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)) { |
| ++NumReadWrites; |
| Accesses.addStore(Ptr); |
| } |
| } |
| |
| if (IsAnnotatedParallel) { |
| DEBUG(dbgs() |
| << "LV: A loop annotated parallel, ignore memory dependency " |
| << "checks.\n"); |
| return true; |
| } |
| |
| 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. |
| bool IsReadOnlyPtr = false; |
| if (Seen.insert(Ptr) || !isStridedPtr(SE, DL, Ptr, TheLoop)) { |
| ++NumReads; |
| IsReadOnlyPtr = true; |
| } |
| Accesses.addLoad(Ptr, IsReadOnlyPtr); |
| } |
| |
| // 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 (NumReadWrites == 1 && NumReads == 0) { |
| DEBUG(dbgs() << "LV: Found a write-only loop!\n"); |
| return true; |
| } |
| |
| // Build dependence sets and check whether we need a runtime pointer bounds |
| // check. |
| Accesses.buildDependenceSets(); |
| bool NeedRTCheck = Accesses.isRTCheckNeeded(); |
| |
| // Find pointers with computable bounds. We are going to use this information |
| // to place a runtime bound check. |
| unsigned NumComparisons = 0; |
| bool CanDoRT = false; |
| if (NeedRTCheck) |
| CanDoRT = Accesses.canCheckPtrAtRT(PtrRtCheck, NumComparisons, SE, TheLoop); |
| |
| |
| DEBUG(dbgs() << "LV: We need to do " << NumComparisons << |
| " pointer comparisons.\n"); |
| |
| // If we only have one set of dependences to check pointers among we don't |
| // need a runtime check. |
| if (NumComparisons == 0 && NeedRTCheck) |
| NeedRTCheck = false; |
| |
| // Check that we did not collect too many pointers or found an unsizeable |
| // pointer. |
| if (!CanDoRT || NumComparisons > RuntimeMemoryCheckThreshold) { |
| PtrRtCheck.reset(); |
| CanDoRT = false; |
| } |
| |
| if (CanDoRT) { |
| DEBUG(dbgs() << "LV: We can perform a memory runtime check if needed.\n"); |
| } |
| |
| if (NeedRTCheck && !CanDoRT) { |
| DEBUG(dbgs() << "LV: We can't vectorize because we can't find " << |
| "the array bounds.\n"); |
| PtrRtCheck.reset(); |
| return false; |
| } |
| |
| PtrRtCheck.Need = NeedRTCheck; |
| |
| bool CanVecMem = true; |
| if (Accesses.isDependencyCheckNeeded()) { |
| DEBUG(dbgs() << "LV: Checking memory dependencies\n"); |
| CanVecMem = DepChecker.areDepsSafe(DependentAccesses, |
| Accesses.getDependenciesToCheck()); |
| MaxSafeDepDistBytes = DepChecker.getMaxSafeDepDistBytes(); |
| |
| if (!CanVecMem && DepChecker.shouldRetryWithRuntimeCheck()) { |
| DEBUG(dbgs() << "LV: Retrying with memory checks\n"); |
| NeedRTCheck = true; |
| |
| // Clear the dependency checks. We assume they are not needed. |
| Accesses.resetDepChecks(); |
| |
| PtrRtCheck.reset(); |
| PtrRtCheck.Need = true; |
| |
| CanDoRT = Accesses.canCheckPtrAtRT(PtrRtCheck, NumComparisons, SE, |
| TheLoop, true); |
| // Check that we did not collect too many pointers or found an unsizeable |
| // pointer. |
| if (!CanDoRT || NumComparisons > RuntimeMemoryCheckThreshold) { |
| DEBUG(dbgs() << "LV: Can't vectorize with memory checks\n"); |
| PtrRtCheck.reset(); |
| return false; |
| } |
| |
| CanVecMem = true; |
| } |
| } |
| |
| DEBUG(dbgs() << "LV: We" << (NeedRTCheck ? "" : " don't") << |
| " need a runtime memory check.\n"); |
| |
| return CanVecMem; |
| } |
| |
| static bool hasMultipleUsesOf(Instruction *I, |
| SmallPtrSet<Instruction *, 8> &Insts) { |
| unsigned NumUses = 0; |
| for(User::op_iterator Use = I->op_begin(), E = I->op_end(); Use != E; ++Use) { |
| if (Insts.count(dyn_cast<Instruction>(*Use))) |
| ++NumUses; |
| if (NumUses > 1) |
| return true; |
| } |
| |
| return false; |
| } |
| |
| static bool areAllUsesIn(Instruction *I, SmallPtrSet<Instruction *, 8> &Set) { |
| for(User::op_iterator Use = I->op_begin(), E = I->op_end(); Use != E; ++Use) |
| if (!Set.count(dyn_cast<Instruction>(*Use))) |
| return false; |
| 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 reduction operation in our scan. |
| bool FoundReduxOp = false; |
| |
| // 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 must have a single out-of-block user. The cycle |
| // must include the original PHI. |
| bool FoundStartPHI = false; |
| |
| // To recognize min/max patterns formed by a icmp select sequence, we store |
| // the number of instruction we saw from the recognized min/max pattern, |
| // to make sure we only see exactly the two instructions. |
| unsigned NumCmpSelectPatternInst = 0; |
| ReductionInstDesc ReduxDesc(false, 0); |
| |
| SmallPtrSet<Instruction *, 8> VisitedInsts; |
| SmallVector<Instruction *, 8> Worklist; |
| Worklist.push_back(Phi); |
| VisitedInsts.insert(Phi); |
| |
| // A value in the reduction can be used: |
| // - By the reduction: |
| // - Reduction operation: |
| // - One use of reduction value (safe). |
| // - Multiple use of reduction value (not safe). |
| // - PHI: |
| // - All uses of the PHI must be the reduction (safe). |
| // - Otherwise, not safe. |
| // - By one instruction outside of the loop (safe). |
| // - By further instructions outside of the loop (not safe). |
| // - By an instruction that is not part of the reduction (not safe). |
| // This is either: |
| // * An instruction type other than PHI or the reduction operation. |
| // * A PHI in the header other than the initial PHI. |
| while (!Worklist.empty()) { |
| Instruction *Cur = Worklist.back(); |
| Worklist.pop_back(); |
| |
| // No Users. |
| // If the instruction has no users then this is a broken chain and can't be |
| // a reduction variable. |
| if (Cur->use_empty()) |
| return false; |
| |
| bool IsAPhi = isa<PHINode>(Cur); |
| |
| // A header PHI use other than the original PHI. |
| if (Cur != Phi && IsAPhi && Cur->getParent() == Phi->getParent()) |
| return false; |
| |
| // Reductions of instructions such as Div, and Sub is only possible if the |
| // LHS is the reduction variable. |
| if (!Cur->isCommutative() && !IsAPhi && !isa<SelectInst>(Cur) && |
| !isa<ICmpInst>(Cur) && !isa<FCmpInst>(Cur) && |
| !VisitedInsts.count(dyn_cast<Instruction>(Cur->getOperand(0)))) |
| return false; |
| |
| // Any reduction instruction must be of one of the allowed kinds. |
| ReduxDesc = isReductionInstr(Cur, Kind, ReduxDesc); |
| if (!ReduxDesc.IsReduction) |
| return false; |
| |
| // A reduction operation must only have one use of the reduction value. |
| if (!IsAPhi && Kind != RK_IntegerMinMax && Kind != RK_FloatMinMax && |
| hasMultipleUsesOf(Cur, VisitedInsts)) |
| return false; |
| |
| // All inputs to a PHI node must be a reduction value. |
| if(IsAPhi && Cur != Phi && !areAllUsesIn(Cur, VisitedInsts)) |
| return false; |
| |
| if (Kind == RK_IntegerMinMax && (isa<ICmpInst>(Cur) || |
| isa<SelectInst>(Cur))) |
| ++NumCmpSelectPatternInst; |
| if (Kind == RK_FloatMinMax && (isa<FCmpInst>(Cur) || |
| isa<SelectInst>(Cur))) |
| ++NumCmpSelectPatternInst; |
| |
| // Check whether we found a reduction operator. |
| FoundReduxOp |= !IsAPhi; |
| |
| // Process users of current instruction. Push non PHI nodes after PHI nodes |
| // onto the stack. This way we are going to have seen all inputs to PHI |
| // nodes once we get to them. |
| SmallVector<Instruction *, 8> NonPHIs; |
| SmallVector<Instruction *, 8> PHIs; |
| for (Value::use_iterator UI = Cur->use_begin(), E = Cur->use_end(); UI != E; |
| ++UI) { |
| Instruction *Usr = cast<Instruction>(*UI); |
| |
| // Check if we found the exit user. |
| BasicBlock *Parent = Usr->getParent(); |
| if (!TheLoop->contains(Parent)) { |
| // Exit if you find multiple outside users or if the header phi node is |
| // being used. In this case the user uses the value of the previous |
| // iteration, in which case we would loose "VF-1" iterations of the |
| // reduction operation if we vectorize. |
| if (ExitInstruction != 0 || Cur == Phi) |
| return false; |
| |
| // The instruction used by an outside user must be the last instruction |
| // before we feed back to the reduction phi. Otherwise, we loose VF-1 |
| // operations on the value. |
| if (std::find(Phi->op_begin(), Phi->op_end(), Cur) == Phi->op_end()) |
| return false; |
| |
| ExitInstruction = Cur; |
| continue; |
| } |
| |
| // Process instructions only once (termination). Each reduction cycle |
| // value must only be used once, except by phi nodes and min/max |
| // reductions which are represented as a cmp followed by a select. |
| ReductionInstDesc IgnoredVal(false, 0); |
| if (VisitedInsts.insert(Usr)) { |
| if (isa<PHINode>(Usr)) |
| PHIs.push_back(Usr); |
| else |
| NonPHIs.push_back(Usr); |
| } else if (!isa<PHINode>(Usr) && |
| ((!isa<FCmpInst>(Usr) && |
| !isa<ICmpInst>(Usr) && |
| !isa<SelectInst>(Usr)) || |
| !isMinMaxSelectCmpPattern(Usr, IgnoredVal).IsReduction)) |
| return false; |
| |
| // Remember that we completed the cycle. |
| if (Usr == Phi) |
| FoundStartPHI = true; |
| } |
| Worklist.append(PHIs.begin(), PHIs.end()); |
| Worklist.append(NonPHIs.begin(), NonPHIs.end()); |
| } |
| |
| // This means we have seen one but not the other instruction of the |
| // pattern or more than just a select and cmp. |
| if ((Kind == RK_IntegerMinMax || Kind == RK_FloatMinMax) && |
| NumCmpSelectPatternInst != 2) |
| return false; |
| |
| if (!FoundStartPHI || !FoundReduxOp || !ExitInstruction) |
| return false; |
| |
| // 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. |
| |
| // 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, |
| ReduxDesc.MinMaxKind); |
| 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 true; |
| } |
| |
| /// Returns true if the instruction is a Select(ICmp(X, Y), X, Y) instruction |
| /// pattern corresponding to a min(X, Y) or max(X, Y). |
| LoopVectorizationLegality::ReductionInstDesc |
| LoopVectorizationLegality::isMinMaxSelectCmpPattern(Instruction *I, |
| ReductionInstDesc &Prev) { |
| |
| assert((isa<ICmpInst>(I) || isa<FCmpInst>(I) || isa<SelectInst>(I)) && |
| "Expect a select instruction"); |
| Instruction *Cmp = 0; |
| SelectInst *Select = 0; |
| |
| // We must handle the select(cmp()) as a single instruction. Advance to the |
| // select. |
| if ((Cmp = dyn_cast<ICmpInst>(I)) || (Cmp = dyn_cast<FCmpInst>(I))) { |
| if (!Cmp->hasOneUse() || !(Select = dyn_cast<SelectInst>(*I->use_begin()))) |
| return ReductionInstDesc(false, I); |
| return ReductionInstDesc(Select, Prev.MinMaxKind); |
| } |
| |
| // Only handle single use cases for now. |
| if (!(Select = dyn_cast<SelectInst>(I))) |
| return ReductionInstDesc(false, I); |
| if (!(Cmp = dyn_cast<ICmpInst>(I->getOperand(0))) && |
| !(Cmp = dyn_cast<FCmpInst>(I->getOperand(0)))) |
| return ReductionInstDesc(false, I); |
| if (!Cmp->hasOneUse()) |
| return ReductionInstDesc(false, I); |
| |
| Value *CmpLeft; |
| Value *CmpRight; |
| |
| // Look for a min/max pattern. |
| if (m_UMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) |
| return ReductionInstDesc(Select, MRK_UIntMin); |
| else if (m_UMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) |
| return ReductionInstDesc(Select, MRK_UIntMax); |
| else if (m_SMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) |
| return ReductionInstDesc(Select, MRK_SIntMax); |
| else if (m_SMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) |
| return ReductionInstDesc(Select, MRK_SIntMin); |
| else if (m_OrdFMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) |
| return ReductionInstDesc(Select, MRK_FloatMin); |
| else if (m_OrdFMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) |
| return ReductionInstDesc(Select, MRK_FloatMax); |
| else if (m_UnordFMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) |
| return ReductionInstDesc(Select, MRK_FloatMin); |
| else if (m_UnordFMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select)) |
| return ReductionInstDesc(Select, MRK_FloatMax); |
| |
| return ReductionInstDesc(false, I); |
| } |
| |
| LoopVectorizationLegality::ReductionInstDesc |
| LoopVectorizationLegality::isReductionInstr(Instruction *I, |
| ReductionKind Kind, |
| ReductionInstDesc &Prev) { |
| bool FP = I->getType()->isFloatingPointTy(); |
| bool FastMath = (FP && I->isCommutative() && I->isAssociative()); |
| switch (I->getOpcode()) { |
| default: |
| return ReductionInstDesc(false, I); |
| case Instruction::PHI: |
| if (FP && (Kind != RK_FloatMult && Kind != RK_FloatAdd && |
| Kind != RK_FloatMinMax)) |
| return ReductionInstDesc(false, I); |
| return ReductionInstDesc(I, Prev.MinMaxKind); |
| case Instruction::Sub: |
| case Instruction::Add: |
| return ReductionInstDesc(Kind == RK_IntegerAdd, I); |
| case Instruction::Mul: |
| return ReductionInstDesc(Kind == RK_IntegerMult, I); |
| case Instruction::And: |
| return ReductionInstDesc(Kind == RK_IntegerAnd, I); |
| case Instruction::Or: |
| return ReductionInstDesc(Kind == RK_IntegerOr, I); |
| case Instruction::Xor: |
| return ReductionInstDesc(Kind == RK_IntegerXor, I); |
| case Instruction::FMul: |
| return ReductionInstDesc(Kind == RK_FloatMult && FastMath, I); |
| case Instruction::FAdd: |
| return ReductionInstDesc(Kind == RK_FloatAdd && FastMath, I); |
| case Instruction::FCmp: |
| case Instruction::ICmp: |
| case Instruction::Select: |
| if (Kind != RK_IntegerMinMax && |
| (!HasFunNoNaNAttr || Kind != RK_FloatMinMax)) |
| return ReductionInstDesc(false, I); |
| return isMinMaxSelectCmpPattern(I, Prev); |
| } |
| } |
| |
| 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. |
| 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; |
| else if (C->getValue()->equalsInt(0 - Size)) |
| return IK_ReversePtrInduction; |
| |
| 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, |
| SmallPtrSet<Value *, 8>& SafePtrs) { |
| for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { |
| // We might be able to hoist the load. |
| if (it->mayReadFromMemory()) { |
| LoadInst *LI = dyn_cast<LoadInst>(it); |
| if (!LI || !SafePtrs.count(LI->getPointerOperand())) |
| return false; |
| } |
| |
| // We don't predicate stores at the moment. |
| if (it->mayWriteToMemory() || it->mayThrow()) |
| return false; |
| |
| // Check that we don't have a constant expression that can trap as operand. |
| for (Instruction::op_iterator OI = it->op_begin(), OE = it->op_end(); |
| OI != OE; ++OI) { |
| if (Constant *C = dyn_cast<Constant>(*OI)) |
| if (C->canTrap()) |
| 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; |
| } |
| |
| LoopVectorizationCostModel::VectorizationFactor |
| LoopVectorizationCostModel::selectVectorizationFactor(bool OptForSize, |
| unsigned UserVF) { |
| // Width 1 means no vectorize |
| VectorizationFactor Factor = { 1U, 0U }; |
| if (OptForSize && Legal->getRuntimePointerCheck()->Need) { |
| DEBUG(dbgs() << "LV: Aborting. Runtime ptr check is required in Os.\n"); |
| return Factor; |
| } |
| |
| // Find the trip count. |
| unsigned TC = SE->getSmallConstantTripCount(TheLoop, TheLoop->getLoopLatch()); |
| DEBUG(dbgs() << "LV: Found trip count: " << TC << '\n'); |
| |
| unsigned WidestType = getWidestType(); |
| unsigned WidestRegister = TTI.getRegisterBitWidth(true); |
| unsigned MaxSafeDepDist = -1U; |
| if (Legal->getMaxSafeDepDistBytes() != -1U) |
| MaxSafeDepDist = Legal->getMaxSafeDepDistBytes() * 8; |
| WidestRegister = ((WidestRegister < MaxSafeDepDist) ? |
| WidestRegister : MaxSafeDepDist); |
| unsigned MaxVectorSize = WidestRegister / WidestType; |
| DEBUG(dbgs() << "LV: The Widest type: " << WidestType << " bits.\n"); |
| DEBUG(dbgs() << "LV: The Widest register is: " |
| << WidestRegister << " bits.\n"); |
| |
| if (MaxVectorSize == 0) { |
| DEBUG(dbgs() << "LV: The target has no vector registers.\n"); |
| MaxVectorSize = 1; |
| } |
| |
| assert(MaxVectorSize <= 32 && "Did not expect to pack so many elements" |
| " into one vector!"); |
| |
| 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 Factor; |
| } |
| |
| // 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 Factor; |
| } |
| } |
| |
| if (UserVF != 0) { |
| assert(isPowerOf2_32(UserVF) && "VF needs to be a power of two"); |
| DEBUG(dbgs() << "LV: Using user VF " << UserVF << ".\n"); |
| |
| Factor.Width = UserVF; |
| return Factor; |
| } |
| |
| 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"); |
| Factor.Width = Width; |
| Factor.Cost = Width * Cost; |
| return Factor; |
| } |
| |
| unsigned LoopVectorizationCostModel::getWidestType() { |
| unsigned MaxWidth = 8; |
| |
| // For each block. |
| for (Loop::block_iterator bb = TheLoop->block_begin(), |
| be = TheLoop->block_end(); bb != be; ++bb) { |
| BasicBlock *BB = *bb; |
| |
| // For each instruction in the loop. |
| for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { |
| Type *T = it->getType(); |
| |
| // Only examine Loads, Stores and PHINodes. |
| if (!isa<LoadInst>(it) && !isa<StoreInst>(it) && !isa<PHINode>(it)) |
| continue; |
| |
| // Examine PHI nodes that are reduction variables. |
| if (PHINode *PN = dyn_cast<PHINode>(it)) |
| if (!Legal->getReductionVars()->count(PN)) |
| continue; |
| |
| // Examine the stored values. |
| if (StoreInst *ST = dyn_cast<StoreInst>(it)) |
| T = ST->getValueOperand()->getType(); |
| |
| // Ignore loaded pointer types and stored pointer types that are not |
| // consecutive. However, we do want to take consecutive stores/loads of |
| // pointer vectors into account. |
| if (T->isPointerTy() && !isConsecutiveLoadOrStore(it)) |
| continue; |
| |
| MaxWidth = std::max(MaxWidth, |
| (unsigned)DL->getTypeSizeInBits(T->getScalarType())); |
| } |
| } |
| |
| return MaxWidth; |
| } |
| |
| unsigned |
| LoopVectorizationCostModel::selectUnrollFactor(bool OptForSize, |
| unsigned UserUF, |
| unsigned VF, |
| unsigned LoopCost) { |
| |
| // -- The unroll heuristics -- |
| // We unroll the loop in order to expose ILP and reduce the loop overhead. |
| // There are many micro-architectural considerations that we can't predict |
| // at this level. For example frontend pressure (on decode or fetch) due to |
| // code size, or the number and capabilities of the execution ports. |
| // |
| // We use the following heuristics to select the unroll factor: |
| // 1. If the code has reductions the we unroll in order to break the cross |
| // iteration dependency. |
| // 2. If the loop is really small then we unroll in order to reduce the loop |
| // overhead. |
| // 3. We don't unroll if we think that we will spill registers to memory due |
| // to the increased register pressure. |
| |
| // 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; |
| |
| // We used the distance for the unroll factor. |
| if (Legal->getMaxSafeDepDistBytes() != -1U) |
| 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; |
| |
| // Clamp the unroll factor ranges to reasonable factors. |
| unsigned MaxUnrollSize = TTI.getMaximumUnrollFactor(); |
| |
| // If we did not calculate the cost for VF (because the user selected the VF) |
| // then we calculate the cost of VF here. |
| if (LoopCost == 0) |
| LoopCost = expectedCost(VF); |
| |
| // Clamp the calculated UF to be between the 1 and the max unroll factor |
| // that the target allows. |
| if (UF > MaxUnrollSize) |
| UF = MaxUnrollSize; |
| else if (UF < 1) |
| UF = 1; |
| |
| bool HasReductions = Legal->getReductionVars()->size(); |
| |
| // Decide if we want to unroll if we decided that it is legal to vectorize |
| // but not profitable. |
| if (VF == 1) { |
| if (TheLoop->getNumBlocks() > 1 || !HasReductions || |
| LoopCost > SmallLoopCost) |
| return 1; |
| |
| return UF; |
| } |
| |
| if (HasReductions) { |
| DEBUG(dbgs() << "LV: Unrolling because of reductions.\n"); |
| return UF; |
| } |
| |
| // We want to unroll tiny loops in order to reduce the loop overhead. |
| // We assume that the cost overhead is 1 and we use the cost model |
| // to estimate the cost of the loop and unroll until the cost of the |
| // loop overhead is about 5% of the cost of the loop. |
| DEBUG(dbgs() << "LV: Loop cost is " << LoopCost << '\n'); |
| if (LoopCost < SmallLoopCost) { |
| DEBUG(dbgs() << "LV: Unrolling to reduce branch cost.\n"); |
| unsigned NewUF = SmallLoopCost / (LoopCost + 1); |
| return std::min(NewUF, UF); |
| } |
| |
| DEBUG(dbgs() << "LV: Not Unrolling.\n"); |
| return 1; |
| } |
| |
| 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) { |
| // Skip dbg intrinsics. |
| if (isa<DbgInfoIntrinsic>(it)) |
| continue; |
| |
| unsigned C = getInstructionCost(it, VF); |
| BlockCost += 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 (VF == 1 && Legal->blockNeedsPredication(*bb)) |
| BlockCost /= 2; |
| |
| Cost += BlockCost; |
| } |
| |
| return Cost; |
| } |
| |
| /// \brief Check whether the address computation for a non-consecutive memory |
| /// access looks like an unlikely candidate for being merged into the indexing |
| /// mode. |
| /// |
| /// We look for a GEP which has one index that is an induction variable and all |
| /// other indices are loop invariant. If the stride of this access is also |
| /// within a small bound we decide that this address computation can likely be |
| /// merged into the addressing mode. |
| /// In all other cases, we identify the address computation as complex. |
| static bool isLikelyComplexAddressComputation(Value *Ptr, |
| LoopVectorizationLegality *Legal, |
| ScalarEvolution *SE, |
| const Loop *TheLoop) { |
| GetElementPtrInst *Gep = dyn_cast<GetElementPtrInst>(Ptr); |
| if (!Gep) |
| return true; |
| |
| // We are looking for a gep with all loop invariant indices except for one |
| // which should be an induction variable. |
| unsigned NumOperands = Gep->getNumOperands(); |
| for (unsigned i = 1; i < NumOperands; ++i) { |
| Value *Opd = Gep->getOperand(i); |
| if (!SE->isLoopInvariant(SE->getSCEV(Opd), TheLoop) && |
| !Legal->isInductionVariable(Opd)) |
| return true; |
| } |
| |
| // Now we know we have a GEP ptr, %inv, %ind, %inv. Make sure that the step |
| // can likely be merged into the address computation. |
| unsigned MaxMergeDistance = 64; |
| |
| const SCEVAddRecExpr *AddRec = dyn_cast<SCEVAddRecExpr>(SE->getSCEV(Ptr)); |
| if (!AddRec) |
| return true; |
| |
| // Check the step is constant. |
| const SCEV *Step = AddRec->getStepRecurrence(*SE); |
| // Calculate the pointer stride and check if it is consecutive. |
| const SCEVConstant *C = dyn_cast<SCEVConstant>(Step); |
| if (!C) |
| return true; |
| |
| const APInt &APStepVal = C->getValue()->getValue(); |
| |
| // Huge step value - give up. |
| if (APStepVal.getBitWidth() > 64) |
| return true; |
| |
| int64_t StepVal = APStepVal.getSExtValue(); |
| |
| return StepVal > MaxMergeDistance; |
| } |
| |
| 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 the cost of GEPs in |
| // vectorized code depends on whether the corresponding memory instruction |
| // is scalarized or not. Therefore, we handle GEPs with the memory |
| // instruction cost. |
| 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: { |
| // Certain instructions can be cheaper to vectorize if they have a constant |
| // second vector operand. One example of this are shifts on x86. |
| TargetTransformInfo::OperandValueKind Op1VK = |
| TargetTransformInfo::OK_AnyValue; |
| TargetTransformInfo::OperandValueKind Op2VK = |
| TargetTransformInfo::OK_AnyValue; |
| |
| if (isa<ConstantInt>(I->getOperand(1))) |
| Op2VK = TargetTransformInfo::OK_UniformConstantValue; |
| |
| return TTI.getArithmeticInstrCost(I->getOpcode(), VectorTy, Op1VK, Op2VK); |
| } |
| 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: |
| case Instruction::Load: { |
| StoreInst *SI = dyn_cast<StoreInst>(I); |
| LoadInst *LI = dyn_cast<LoadInst>(I); |
| Type *ValTy = (SI ? SI->getValueOperand()->getType() : |
| LI->getType()); |
| VectorTy = ToVectorTy(ValTy, VF); |
| |
| unsigned Alignment = SI ? SI->getAlignment() : LI->getAlignment(); |
| unsigned AS = SI ? SI->getPointerAddressSpace() : |
| LI->getPointerAddressSpace(); |
| Value *Ptr = SI ? SI->getPointerOperand() : LI->getPointerOperand(); |
| // We add the cost of address computation here instead of with the gep |
| // instruction because only here we know whether the operation is |
| // scalarized. |
| if (VF == 1) |
| return TTI.getAddressComputationCost(VectorTy) + |
| TTI.getMemoryOpCost(I->getOpcode(), VectorTy, Alignment, AS); |
| |
| // Scalarized loads/stores. |
| int ConsecutiveStride = Legal->isConsecutivePtr(Ptr); |
| bool Reverse = ConsecutiveStride < 0; |
| unsigned ScalarAllocatedSize = DL->getTypeAllocSize(ValTy); |
| unsigned VectorElementSize = DL->getTypeStoreSize(VectorTy)/VF; |
| if (!ConsecutiveStride || ScalarAllocatedSize != VectorElementSize) { |
| bool IsComplexComputation = |
| isLikelyComplexAddressComputation(Ptr, Legal, SE, TheLoop); |
| unsigned Cost = 0; |
| // The cost of extracting from the value vector and pointer vector. |
| Type *PtrTy = ToVectorTy(Ptr->getType(), VF); |
| for (unsigned i = 0; i < VF; ++i) { |
| // The cost of extracting the pointer operand. |
| Cost += TTI.getVectorInstrCost(Instruction::ExtractElement, PtrTy, i); |
| // In case of STORE, the cost of ExtractElement from the vector. |
| // In case of LOAD, the cost of InsertElement into the returned |
| // vector. |
| Cost += TTI.getVectorInstrCost(SI ? Instruction::ExtractElement : |
| Instruction::InsertElement, |
| VectorTy, i); |
| } |
| |
| // The cost of the scalar loads/stores. |
| Cost += VF * TTI.getAddressComputationCost(PtrTy, IsComplexComputation); |
| Cost += VF * TTI.getMemoryOpCost(I->getOpcode(), ValTy->getScalarType(), |
| Alignment, AS); |
| return Cost; |
| } |
| |
| // Wide load/stores. |
| unsigned Cost = TTI.getAddressComputationCost(VectorTy); |
| Cost += TTI.getMemoryOpCost(I->getOpcode(), VectorTy, Alignment, AS); |
| |
| 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: { |
| CallInst *CI = cast<CallInst>(I); |
| Intrinsic::ID ID = getIntrinsicIDForCall(CI, TLI); |
| assert(ID && "Not an intrinsic call!"); |
| Type *RetTy = ToVectorTy(CI->getType(), VF); |
| SmallVector<Type*, 4> Tys; |
| for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i) |
| Tys.push_back(ToVectorTy(CI->getArgOperand(i)->getType(), VF)); |
| return TTI.getIntrinsicInstrCost(ID, 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(TargetTransformInfo) |
| INITIALIZE_PASS_DEPENDENCY(DominatorTree) |
| INITIALIZE_PASS_DEPENDENCY(ScalarEvolution) |
| INITIALIZE_PASS_DEPENDENCY(LCSSA) |
| INITIALIZE_PASS_DEPENDENCY(LoopInfo) |
| INITIALIZE_PASS_DEPENDENCY(LoopSimplify) |
| INITIALIZE_PASS_END(LoopVectorize, LV_NAME, lv_name, false, false) |
| |
| namespace llvm { |
| Pass *createLoopVectorizePass(bool NoUnrolling) { |
| return new LoopVectorize(NoUnrolling); |
| } |
| } |
| |
| bool LoopVectorizationCostModel::isConsecutiveLoadOrStore(Instruction *Inst) { |
| // Check for a store. |
| if (StoreInst *ST = dyn_cast<StoreInst>(Inst)) |
| return Legal->isConsecutivePtr(ST->getPointerOperand()) != 0; |
| |
| // Check for a load. |
| if (LoadInst *LI = dyn_cast<LoadInst>(Inst)) |
| return Legal->isConsecutivePtr(LI->getPointerOperand()) != 0; |
| |
| return false; |
| } |
| |
| |
| void InnerLoopUnroller::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; |
| |
| setDebugLocFromInst(Builder, Instr); |
| |
| // 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(Instr->getType()); |
| // Create a new entry in the WidenMap and initialize it to Undef or Null. |
| VectorParts &VecResults = WidenMap.splat(Instr, UndefVec); |
| |
| // For each vector unroll 'part': |
| for (unsigned Part = 0; Part < UF; ++Part) { |
| // For each scalar that we create: |
| |
| Instruction *Cloned = Instr->clone(); |
| if (!IsVoidRetTy) |
| Cloned->setName(Instr->getName() + ".cloned"); |
| // Replace the operands of the cloned instructions with extracted scalars. |
| for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) { |
| Value *Op = Params[op][Part]; |
| 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] = Cloned; |
| } |
| } |
| |
| void |
| InnerLoopUnroller::vectorizeMemoryInstruction(Instruction *Instr, |
| LoopVectorizationLegality*) { |
| return scalarizeInstruction(Instr); |
| } |
| |
| Value *InnerLoopUnroller::reverseVector(Value *Vec) { |
| return Vec; |
| } |
| |
| Value *InnerLoopUnroller::getBroadcastInstrs(Value *V) { |
| return V; |
| } |
| |
| Value *InnerLoopUnroller::getConsecutiveVector(Value* Val, int StartIdx, |
| bool Negate) { |
| // When unrolling and the VF is 1, we only need to add a simple scalar. |
| Type *ITy = Val->getType(); |
| assert(!ITy->isVectorTy() && "Val must be a scalar"); |
| Constant *C = ConstantInt::get(ITy, StartIdx, Negate); |
| return Builder.CreateAdd(Val, C, "induction"); |
| } |
| |