--- /dev/null
+//===- LoopVectorize.h --- A Loop Vectorizer ------------------------------===//
+//
+// The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+//
+// This is the LLVM loop vectorizer. This pass modifies 'vectorizable' loops
+// and generates target-independent LLVM-IR. Legalization of the IR is done
+// in the codegen. However, the vectorizes uses (will use) the codegen
+// interfaces to generate IR that is likely to result in an optimal binary.
+//
+// The loop vectorizer combines consecutive loop iteration into a single
+// 'wide' iteration. After this transformation the index is incremented
+// by the SIMD vector width, and not by one.
+//
+// This pass has three parts:
+// 1. The main loop pass that drives the different parts.
+// 2. LoopVectorizationLegality - A unit that checks for the legality
+// of the vectorization.
+// 3. InnerLoopVectorizer - A unit that performs the actual
+// widening of instructions.
+// 4. LoopVectorizationCostModel - A unit that checks for the profitability
+// of vectorization. It decides on the optimal vector width, which
+// can be one, if vectorization is not profitable.
+//
+//===----------------------------------------------------------------------===//
+//
+// The reduction-variable vectorization is based on the paper:
+// D. Nuzman and R. Henderson. Multi-platform Auto-vectorization.
+//
+// Variable uniformity checks are inspired by:
+// Karrenberg, R. and Hack, S. Whole Function Vectorization.
+//
+// Other ideas/concepts are from:
+// A. Zaks and D. Nuzman. Autovectorization in GCC-two years later.
+//
+// S. Maleki, Y. Gao, M. Garzaran, T. Wong and D. Padua. An Evaluation of
+// Vectorizing Compilers.
+//
+//===----------------------------------------------------------------------===//
+#ifndef LLVM_TRANSFORM_VECTORIZE_LOOP_VECTORIZE_H
+#define LLVM_TRANSFORM_VECTORIZE_LOOP_VECTORIZE_H
+
+#define LV_NAME "loop-vectorize"
+#define DEBUG_TYPE LV_NAME
+
+#include "llvm/Analysis/ScalarEvolution.h"
+#include "llvm/ADT/SmallVector.h"
+#include "llvm/ADT/DenseMap.h"
+#include "llvm/ADT/SmallPtrSet.h"
+#include "llvm/IRBuilder.h"
+
+#include <algorithm>
+using namespace llvm;
+
+/// We don't vectorize loops with a known constant trip count below this number.
+const unsigned TinyTripCountThreshold = 16;
+
+/// When performing a runtime memory check, do not check more than this
+/// number of pointers. Notice that the check is quadratic!
+const unsigned RuntimeMemoryCheckThreshold = 4;
+
+/// This is the highest vector width that we try to generate.
+const unsigned MaxVectorSize = 8;
+
+namespace llvm {
+
+// Forward declarations.
+class LoopVectorizationLegality;
+class LoopVectorizationCostModel;
+class VectorTargetTransformInfo;
+
+/// 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:
+ /// Ctor.
+ InnerLoopVectorizer(Loop *Orig, ScalarEvolution *Se, LoopInfo *Li,
+ DominatorTree *Dt, DataLayout *Dl, unsigned VecWidth):
+ OrigLoop(Orig), SE(Se), LI(Li), DT(Dt), DL(Dl), VF(VecWidth),
+ Builder(Se->getContext()), Induction(0), OldInduction(0) { }
+
+ // Perform the actual loop widening (vectorization).
+ void vectorize(LoopVectorizationLegality *Legal) {
+ // Create a new empty loop. Unlink the old loop and connect the new one.
+ createEmptyLoop(Legal);
+ // Widen each instruction in the old loop to a new one in the new loop.
+ // Use the Legality module to find the induction and reduction variables.
+ vectorizeLoop(Legal);
+ // Register the new loop and update the analysis passes.
+ updateAnalysis();
+ }
+
+private:
+ /// A small list of PHINodes.
+ typedef SmallVector<PHINode*, 4> PhiVector;
+
+ /// Add code that checks at runtime if the accessed arrays overlap.
+ /// Returns the comparator value or NULL if no check is needed.
+ Value *addRuntimeCheck(LoopVectorizationLegality *Legal,
+ Instruction *Loc);
+ /// Create an empty loop, based on the loop ranges of the old loop.
+ void createEmptyLoop(LoopVectorizationLegality *Legal);
+ /// Copy and widen the instructions from the old loop.
+ void vectorizeLoop(LoopVectorizationLegality *Legal);
+
+ /// A helper function that computes the predicate of the block BB, assuming
+ /// that the header block of the loop is set to True. It returns the *entry*
+ /// mask for the block BB.
+ Value *createBlockInMask(BasicBlock *BB);
+ /// A helper function that computes the predicate of the edge between SRC
+ /// and DST.
+ Value *createEdgeMask(BasicBlock *Src, BasicBlock *Dst);
+
+ /// A helper function to vectorize a single BB within the innermost loop.
+ void vectorizeBlockInLoop(LoopVectorizationLegality *Legal, BasicBlock *BB,
+ PhiVector *PV);
+
+ /// Insert the new loop to the loop hierarchy and pass manager
+ /// and update the analysis passes.
+ void updateAnalysis();
+
+ /// This instruction is un-vectorizable. Implement it as a sequence
+ /// of scalars.
+ void scalarizeInstruction(Instruction *Instr);
+
+ /// Create a broadcast instruction. This method generates a broadcast
+ /// instruction (shuffle) for loop invariant values and for the induction
+ /// value. If this is the induction variable then we extend it to N, N+1, ...
+ /// this is needed because each iteration in the loop corresponds to a SIMD
+ /// element.
+ Value *getBroadcastInstrs(Value *V);
+
+ /// This function adds 0, 1, 2 ... to each vector element, starting at zero.
+ /// If Negate is set then negative numbers are added e.g. (0, -1, -2, ...).
+ Value *getConsecutiveVector(Value* Val, bool Negate = false);
+
+ /// 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.
+ Value *getVectorValue(Value *V);
+
+ /// Get a uniform vector of constant integers. We use this to get
+ /// vectors of ones and zeros for the reduction code.
+ Constant* getUniformVector(unsigned Val, Type* ScalarTy);
+
+ typedef DenseMap<Value*, Value*> ValueMap;
+
+ /// The original loop.
+ Loop *OrigLoop;
+ // Scev analysis to use.
+ ScalarEvolution *SE;
+ // Loop Info.
+ LoopInfo *LI;
+ // Dominator Tree.
+ DominatorTree *DT;
+ // Data Layout.
+ DataLayout *DL;
+ // The vectorization factor to use.
+ unsigned VF;
+
+ // The builder that we use
+ IRBuilder<> Builder;
+
+ // --- Vectorization state ---
+
+ /// The vector-loop preheader.
+ BasicBlock *LoopVectorPreHeader;
+ /// The scalar-loop preheader.
+ BasicBlock *LoopScalarPreHeader;
+ /// Middle Block between the vector and the scalar.
+ BasicBlock *LoopMiddleBlock;
+ ///The ExitBlock of the scalar loop.
+ BasicBlock *LoopExitBlock;
+ ///The vector loop body.
+ BasicBlock *LoopVectorBody;
+ ///The scalar loop body.
+ BasicBlock *LoopScalarBody;
+ ///The first bypass block.
+ BasicBlock *LoopBypassBlock;
+
+ /// The new Induction variable which was added to the new block.
+ PHINode *Induction;
+ /// The induction variable of the old basic block.
+ PHINode *OldInduction;
+ // Maps scalars to widened vectors.
+ ValueMap WidenMap;
+};
+
+/// LoopVectorizationLegality checks if it is legal to vectorize a loop, and
+/// to what vectorization factor.
+/// This class does not look at the profitability of vectorization, only the
+/// legality. This class has two main kinds of checks:
+/// * Memory checks - The code in canVectorizeMemory checks if vectorization
+/// will change the order of memory accesses in a way that will change the
+/// correctness of the program.
+/// * Scalars checks - The code in canVectorizeInstrs and canVectorizeMemory
+/// checks for a number of different conditions, such as the availability of a
+/// single induction variable, that all types are supported and vectorize-able,
+/// etc. This code reflects the capabilities of InnerLoopVectorizer.
+/// This class is also used by InnerLoopVectorizer for identifying
+/// induction variable and the different reduction variables.
+class LoopVectorizationLegality {
+public:
+ LoopVectorizationLegality(Loop *Lp, ScalarEvolution *Se, DataLayout *Dl,
+ DominatorTree *Dt):
+ TheLoop(Lp), SE(Se), DL(Dl), DT(Dt), Induction(0) { }
+
+ /// This enum represents the kinds of reductions that we support.
+ enum ReductionKind {
+ NoReduction, /// Not a reduction.
+ IntegerAdd, /// Sum of numbers.
+ IntegerMult, /// Product of numbers.
+ IntegerOr, /// Bitwise or logical OR of numbers.
+ IntegerAnd, /// Bitwise or logical AND of numbers.
+ IntegerXor /// Bitwise or logical XOR of numbers.
+ };
+
+ /// This enum represents the kinds of inductions that we support.
+ enum InductionKind {
+ NoInduction, /// Not an induction variable.
+ IntInduction, /// Integer induction variable. Step = 1.
+ ReverseIntInduction, /// Reverse int induction variable. Step = -1.
+ PtrInduction /// Pointer induction variable. Step = sizeof(elem).
+ };
+
+ /// This POD struct holds information about reduction variables.
+ struct ReductionDescriptor {
+ // Default C'tor
+ ReductionDescriptor():
+ StartValue(0), LoopExitInstr(0), Kind(NoReduction) {}
+
+ // C'tor.
+ ReductionDescriptor(Value *Start, Instruction *Exit, ReductionKind K):
+ StartValue(Start), LoopExitInstr(Exit), Kind(K) {}
+
+ // The starting value of the reduction.
+ // It does not have to be zero!
+ Value *StartValue;
+ // The instruction who's value is used outside the loop.
+ Instruction *LoopExitInstr;
+ // The kind of the reduction.
+ ReductionKind Kind;
+ };
+
+ // This POD struct holds information about the memory runtime legality
+ // check that a group of pointers do not overlap.
+ struct RuntimePointerCheck {
+ RuntimePointerCheck(): Need(false) {}
+
+ /// Reset the state of the pointer runtime information.
+ void reset() {
+ Need = false;
+ Pointers.clear();
+ Starts.clear();
+ Ends.clear();
+ }
+
+ /// Insert a pointer and calculate the start and end SCEVs.
+ void insert(ScalarEvolution *SE, Loop *Lp, Value *Ptr);
+
+ /// This flag indicates if we need to add the runtime check.
+ bool Need;
+ /// Holds the pointers that we need to check.
+ SmallVector<Value*, 2> Pointers;
+ /// Holds the pointer value at the beginning of the loop.
+ SmallVector<const SCEV*, 2> Starts;
+ /// Holds the pointer value at the end of the loop.
+ SmallVector<const SCEV*, 2> Ends;
+ };
+
+ /// A POD for saving information about induction variables.
+ struct InductionInfo {
+ /// Ctors.
+ InductionInfo(Value *Start, InductionKind K):
+ StartValue(Start), IK(K) {};
+ InductionInfo(): StartValue(0), IK(NoInduction) {};
+ /// Start value.
+ Value *StartValue;
+ /// Induction kind.
+ InductionKind IK;
+ };
+
+ /// ReductionList contains the reduction descriptors for all
+ /// of the reductions that were found in the loop.
+ typedef DenseMap<PHINode*, ReductionDescriptor> ReductionList;
+
+ /// InductionList saves induction variables and maps them to the
+ /// induction descriptor.
+ typedef DenseMap<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; }
+
+ /// 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.
+ bool isConsecutivePtr(Value *Ptr);
+
+ /// Returns true if the value V is uniform within the loop.
+ bool isUniform(Value *V);
+
+ /// Returns true if this instruction will remain scalar after vectorization.
+ bool isUniformAfterVectorization(Instruction* I) {return Uniforms.count(I);}
+
+ /// Returns the information that we collected about runtime memory check.
+ RuntimePointerCheck *getRuntimePointerCheck() {return &PtrRtCheck; }
+private:
+ /// Check if a single basic block loop is vectorizable.
+ /// At this point we know that this is a loop with a constant trip count
+ /// and we only need to check individual instructions.
+ bool canVectorizeInstrs();
+
+ /// When we vectorize loops we may change the order in which
+ /// we read and write from memory. This method checks if it is
+ /// legal to vectorize the code, considering only memory constrains.
+ /// Returns true if the loop is vectorizable
+ bool canVectorizeMemory();
+
+ /// Return true if we can vectorize this loop using the IF-conversion
+ /// transformation.
+ bool canVectorizeWithIfConvert();
+
+ /// Collect the variables that need to stay uniform after vectorization.
+ void collectLoopUniforms();
+
+ /// Return true if all of the instructions in the block can be speculatively
+ /// executed.
+ bool blockCanBePredicated(BasicBlock *BB);
+
+ /// Returns True, if 'Phi' is the kind of reduction variable for type
+ /// 'Kind'. If this is a reduction variable, it adds it to ReductionList.
+ bool AddReductionVar(PHINode *Phi, ReductionKind Kind);
+ /// Returns true if the instruction I can be a reduction variable of type
+ /// 'Kind'.
+ bool isReductionInstr(Instruction *I, ReductionKind Kind);
+ /// Returns the induction kind of Phi. This function may return NoInduction
+ /// if the PHI is not an induction variable.
+ InductionKind isInductionVariable(PHINode *Phi);
+ /// Return true if can compute the address bounds of Ptr within the loop.
+ bool hasComputableBounds(Value *Ptr);
+
+ /// The loop that we evaluate.
+ Loop *TheLoop;
+ /// Scev analysis.
+ ScalarEvolution *SE;
+ /// DataLayout analysis.
+ DataLayout *DL;
+ // Dominators.
+ DominatorTree *DT;
+
+ // --- vectorization state --- //
+
+ /// Holds the integer induction variable. This is the counter of the
+ /// loop.
+ PHINode *Induction;
+ /// Holds the reduction variables.
+ ReductionList Reductions;
+ /// Holds all of the induction variables that we found in the loop.
+ /// Notice that inductions don't need to start at zero and that induction
+ /// variables can be pointers.
+ InductionList Inductions;
+
+ /// Allowed outside users. This holds the reduction
+ /// vars which can be accessed from outside the loop.
+ SmallPtrSet<Value*, 4> AllowedExit;
+ /// This set holds the variables which are known to be uniform after
+ /// vectorization.
+ SmallPtrSet<Instruction*, 4> Uniforms;
+ /// We need to check that all of the pointers in this list are disjoint
+ /// at runtime.
+ RuntimePointerCheck PtrRtCheck;
+};
+
+/// LoopVectorizationCostModel - estimates the expected speedups due to
+/// vectorization.
+/// In many cases vectorization is not profitable. This can happen because
+/// of a number of reasons. In this class we mainly attempt to predict
+/// the expected speedup/slowdowns due to the supported instruction set.
+/// We use the VectorTargetTransformInfo to query the different backends
+/// for the cost of different operations.
+class LoopVectorizationCostModel {
+public:
+ /// C'tor.
+ LoopVectorizationCostModel(Loop *Lp, ScalarEvolution *Se,
+ LoopVectorizationLegality *Leg,
+ const VectorTargetTransformInfo *Vtti):
+ TheLoop(Lp), SE(Se), Legal(Leg), VTTI(Vtti) { }
+
+ /// Returns the most profitable vectorization factor for the loop that is
+ /// smaller or equal to the VF argument. This method checks every power
+ /// of two up to VF.
+ unsigned findBestVectorizationFactor(unsigned VF = MaxVectorSize);
+
+private:
+ /// Returns the expected execution cost. The unit of the cost does
+ /// not matter because we use the 'cost' units to compare different
+ /// vector widths. The cost that is returned is *not* normalized by
+ /// the factor width.
+ unsigned expectedCost(unsigned VF);
+
+ /// Returns the execution time cost of an instruction for a given vector
+ /// width. Vector width of one means scalar.
+ unsigned getInstructionCost(Instruction *I, unsigned VF);
+
+ /// A helper function for converting Scalar types to vector types.
+ /// If the incoming type is void, we return void. If the VF is 1, we return
+ /// the scalar type.
+ static Type* ToVectorTy(Type *Scalar, unsigned VF);
+
+ /// The loop that we evaluate.
+ Loop *TheLoop;
+ /// Scev analysis.
+ ScalarEvolution *SE;
+
+ /// Vectorization legality.
+ LoopVectorizationLegality *Legal;
+ /// Vector target information.
+ const VectorTargetTransformInfo *VTTI;
+};
+
+}// namespace llvm
+
+#endif //LLVM_TRANSFORM_VECTORIZE_LOOP_VECTORIZE_H
+
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