// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
-#include "LoopVectorize.h"
+//
+// 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/MapVector.h"
+#include "llvm/ADT/SmallPtrSet.h"
+#include "llvm/ADT/SmallSet.h"
+#include "llvm/ADT/SmallVector.h"
#include "llvm/ADT/StringExtras.h"
#include "llvm/Analysis/AliasAnalysis.h"
#include "llvm/Analysis/AliasSetTracker.h"
#include "llvm/Analysis/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/Constants.h"
-#include "llvm/DataLayout.h"
-#include "llvm/DerivedTypes.h"
-#include "llvm/Function.h"
-#include "llvm/Instructions.h"
-#include "llvm/IntrinsicInst.h"
-#include "llvm/LLVMContext.h"
-#include "llvm/Module.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/TargetTransformInfo.h"
+#include "llvm/Target/TargetLibraryInfo.h"
#include "llvm/Transforms/Scalar.h"
#include "llvm/Transforms/Utils/BasicBlockUtils.h"
#include "llvm/Transforms/Utils/Local.h"
-#include "llvm/Transforms/Vectorize.h"
-#include "llvm/Type.h"
-#include "llvm/Value.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;
+
+/// We use a metadata with this name to indicate that a scalar loop was
+/// vectorized and that we don't need to re-vectorize it if we run into it
+/// again.
+static const char*
+AlreadyVectorizedMDName = "llvm.vectorizer.already_vectorized";
+
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();
+ }
+
+private:
+ /// A small list of PHINodes.
+ typedef SmallVector<PHINode*, 4> PhiVector;
+ /// When we unroll loops we have multiple vector values for each scalar.
+ /// This data structure holds the unrolled and vectorized values that
+ /// originated from one scalar instruction.
+ typedef SmallVector<Value*, 2> VectorParts;
+
+ /// Add code that checks at runtime if the accessed arrays overlap.
+ /// Returns the comparator value or NULL if no check is needed.
+ 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.
+ void vectorizeLoop(LoopVectorizationLegality *Legal);
+
+ /// A helper function that computes the predicate of the block BB, assuming
+ /// that the header block of the loop is set to True. It returns the *entry*
+ /// mask for the block BB.
+ VectorParts createBlockInMask(BasicBlock *BB);
+ /// A helper function that computes the predicate of the edge between SRC
+ /// and DST.
+ VectorParts createEdgeMask(BasicBlock *Src, BasicBlock *Dst);
+
+ /// A helper function to vectorize a single BB within the innermost loop.
+ void vectorizeBlockInLoop(LoopVectorizationLegality *Legal, BasicBlock *BB,
+ PhiVector *PV);
+
+ /// Insert the new loop to the loop hierarchy and pass manager
+ /// and update the analysis passes.
+ void updateAnalysis();
+
+ /// This instruction is un-vectorizable. Implement it as a sequence
+ /// of scalars.
+ void scalarizeInstruction(Instruction *Instr);
+
+ /// Vectorize Load and Store instructions,
+ 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.
+ Value *getBroadcastInstrs(Value *V);
+
+ /// This function adds 0, 1, 2 ... to each vector element, starting at zero.
+ /// If Negate is set then negative numbers are added e.g. (0, -1, -2, ...).
+ /// The sequence starts at StartIndex.
+ Value *getConsecutiveVector(Value* Val, 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.
+ 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;
+ /// 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;
+};
+
+/// \brief Check if conditionally executed loads are hoistable.
+///
+/// This class has two functions. isHoistableLoad and canHoistAllLoads.
+/// isHoistableLoad should be called on all load instructions that are executed
+/// conditionally. After all conditional loads are processed, the client should
+/// call canHoistAllLoads to determine if all of the conditional execute loads
+/// have an unconditional memory access in the loop.
+class LoadHoisting {
+ typedef SmallPtrSet<Value *, 8> MemorySet;
+
+ Loop *TheLoop;
+ DominatorTree *DT;
+ MemorySet CondLoadAddrSet;
+
+public:
+ LoadHoisting(Loop *L, DominatorTree *D) : TheLoop(L), DT(D) {}
+
+ /// \brief Check if the instruction is a load with a identifiable address.
+ bool isHoistableLoad(Instruction *L);
+
+ /// \brief Check if all of the conditional loads are hoistable because there
+ /// exists an unconditional memory access to the same address in the loop.
+ bool canHoistAllLoads();
+};
+
+bool LoadHoisting::isHoistableLoad(Instruction *L) {
+ LoadInst *LI = dyn_cast<LoadInst>(L);
+ if (!LI)
+ return false;
+
+ CondLoadAddrSet.insert(LI->getPointerOperand());
+ return true;
+}
+
+static void addMemAccesses(BasicBlock *BB, SmallPtrSet<Value *, 8> &Set) {
+ for (BasicBlock::iterator BI = BB->begin(), BE = BB->end(); BI != BE; ++BI) {
+ Instruction *I = &*BI;
+ Value *Addr = 0;
+
+ // Try a load.
+ LoadInst *LI = dyn_cast<LoadInst>(I);
+ if (LI) {
+ Addr = LI->getPointerOperand();
+ Set.insert(Addr);
+ continue;
+ }
+
+ // Try a store.
+ StoreInst *SI = dyn_cast<StoreInst>(I);
+ if (!SI)
+ continue;
+
+ Addr = SI->getPointerOperand();
+ Set.insert(Addr);
+ }
+}
+
+bool LoadHoisting::canHoistAllLoads() {
+ // No conditional loads.
+ if (CondLoadAddrSet.empty())
+ return true;
+
+ MemorySet UncondMemAccesses;
+ std::vector<BasicBlock*> &LoopBlocks = TheLoop->getBlocksVector();
+ BasicBlock *LoopLatch = TheLoop->getLoopLatch();
+
+ // Iterate over the unconditional blocks and collect memory access addresses.
+ for (unsigned i = 0, e = LoopBlocks.size(); i < e; ++i) {
+ BasicBlock *BB = LoopBlocks[i];
+
+ // Ignore conditional blocks.
+ if (BB != LoopLatch && !DT->dominates(BB, LoopLatch))
+ continue;
+
+ addMemAccesses(BB, UncondMemAccesses);
+ }
+
+ // And make sure there is a matching unconditional access for every
+ // conditional load.
+ for (MemorySet::iterator MI = CondLoadAddrSet.begin(),
+ ME = CondLoadAddrSet.end(); MI != ME; ++MI)
+ if (!UncondMemAccesses.count(*MI))
+ return false;
+
+ return true;
+}
+
+/// 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, TargetTransformInfo* TTI,
+ AliasAnalysis *AA, TargetLibraryInfo *TLI)
+ : TheLoop(L), SE(SE), DL(DL), DT(DT), TTI(TTI), AA(AA), TLI(TLI),
+ Induction(0), WidestIndTy(0), HasFunNoNaNAttr(false),
+ LoadSpeculation(L, DT) {}
+
+ /// 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 POD 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!
+ 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 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, bool WritePtr);
+
+ /// 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;
+ /// Holds the information if this pointer is used for writing to memory.
+ SmallVector<bool, 2> IsWritePtr;
+ };
+
+ /// A POD for saving information about induction variables.
+ struct InductionInfo {
+ InductionInfo(Value *Start, InductionKind K) : StartValue(Start), IK(K) {}
+ InductionInfo() : StartValue(0), IK(IK_NoInduction) {}
+ /// Start value.
+ Value *StartValue;
+ /// Induction kind.
+ InductionKind IK;
+ };
+
+ /// ReductionList contains the reduction descriptors for all
+ /// of the reductions that were found in the loop.
+ typedef DenseMap<PHINode*, ReductionDescriptor> ReductionList;
+
+ /// InductionList saves induction variables and maps them to the
+ /// induction descriptor.
+ typedef MapVector<PHINode*, InductionInfo> InductionList;
+
+ /// Alias(Multi)Map stores the values (GEPs or underlying objects and their
+ /// respective Store/Load instruction(s) to calculate aliasing.
+ typedef MapVector<Value*, Instruction* > AliasMap;
+ typedef DenseMap<Value*, std::vector<Instruction*> > AliasMultiMap;
+
+ /// 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);
+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 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);
+ /// Return true if can compute the address bounds of Ptr within the loop.
+ bool hasComputableBounds(Value *Ptr);
+ /// Return true if there is the chance of write reorder.
+ bool hasPossibleGlobalWriteReorder(Value *Object,
+ Instruction *Inst,
+ AliasMultiMap &WriteObjects,
+ unsigned MaxByteWidth);
+ /// Return the AA location for a load or a store.
+ AliasAnalysis::Location getLoadStoreLocation(Instruction *Inst);
+
+
+ /// The loop that we evaluate.
+ Loop *TheLoop;
+ /// Scev analysis.
+ ScalarEvolution *SE;
+ /// DataLayout analysis.
+ DataLayout *DL;
+ /// Dominators.
+ DominatorTree *DT;
+ /// Target Info.
+ TargetTransformInfo *TTI;
+ /// Alias Analysis.
+ AliasAnalysis *AA;
+ /// 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;
+
+ /// Utility to determine whether loads can be speculated.
+ LoadHoisting LoadSpeculation;
+};
+
+/// 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;
+};
+
/// The LoopVectorize Pass.
struct LoopVectorize : public LoopPass {
/// Pass identification, replacement for typeid
LoopInfo *LI;
TargetTransformInfo *TTI;
DominatorTree *DT;
+ AliasAnalysis *AA;
+ TargetLibraryInfo *TLI;
virtual bool runOnLoop(Loop *L, LPPassManager &LPM) {
// We only vectorize innermost loops.
SE = &getAnalysis<ScalarEvolution>();
DL = getAnalysisIfAvailable<DataLayout>();
LI = &getAnalysis<LoopInfo>();
- TTI = getAnalysisIfAvailable<TargetTransformInfo>();
+ TTI = &getAnalysis<TargetTransformInfo>();
DT = &getAnalysis<DominatorTree>();
+ AA = getAnalysisIfAvailable<AliasAnalysis>();
+ TLI = getAnalysisIfAvailable<TargetLibraryInfo>();
+
+ if (DL == NULL) {
+ DEBUG(dbgs() << "LV: Not vectorizing because of missing data layout");
+ return false;
+ }
DEBUG(dbgs() << "LV: Checking a loop in \"" <<
L->getHeader()->getParent()->getName() << "\"\n");
// Check if it is legal to vectorize the loop.
- LoopVectorizationLegality LVL(L, SE, DL, DT);
+ LoopVectorizationLegality LVL(L, SE, DL, DT, TTI, AA, TLI);
if (!LVL.canVectorize()) {
DEBUG(dbgs() << "LV: Not vectorizing.\n");
return false;
}
- // Select the preffered vectorization factor.
- const VectorTargetTransformInfo *VTTI = 0;
- if (TTI)
- VTTI = TTI->getVectorTargetTransformInfo();
// Use the cost model.
- LoopVectorizationCostModel CM(L, SE, &LVL, VTTI);
+ LoopVectorizationCostModel CM(L, SE, LI, &LVL, *TTI, DL, TLI);
- // Check the function attribues to find out if this function should be
+ // 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;
- bool OptForSize = F->getFnAttributes().hasAttribute(SzAttr);
+ Attribute::AttrKind SzAttr = Attribute::OptimizeForSize;
+ Attribute::AttrKind FlAttr = Attribute::NoImplicitFloat;
+ unsigned FnIndex = AttributeSet::FunctionIndex;
+ bool OptForSize = F->getAttributes().hasAttribute(FnIndex, SzAttr);
+ bool NoFloat = F->getAttributes().hasAttribute(FnIndex, FlAttr);
+
+ if (NoFloat) {
+ DEBUG(dbgs() << "LV: Can't vectorize when the NoImplicitFloat"
+ "attribute is used.\n");
+ return false;
+ }
- unsigned VF = CM.selectVectorizationFactor(OptForSize, VectorizationFactor);
+ // Select the optimal vectorization factor.
+ LoopVectorizationCostModel::VectorizationFactor VF;
+ VF = CM.selectVectorizationFactor(OptForSize, VectorizationFactor);
+ // Select the unroll factor.
+ unsigned UF = CM.selectUnrollFactor(OptForSize, VectorizationUnroll,
+ VF.Width, VF.Cost);
- if (VF == 1) {
+ if (VF.Width == 1) {
DEBUG(dbgs() << "LV: Vectorization is possible but not beneficial.\n");
return false;
}
- DEBUG(dbgs() << "LV: Found a vectorizable loop ("<< VF << ") in "<<
+ DEBUG(dbgs() << "LV: Found a vectorizable loop ("<< VF.Width << ") in "<<
F->getParent()->getModuleIdentifier()<<"\n");
+ DEBUG(dbgs() << "LV: Unroll Factor is " << UF << "\n");
- // If we decided that it is *legal* to vectorizer the loop then do it.
- InnerLoopVectorizer LB(L, SE, LI, DT, DL, VF);
+ // 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);
DEBUG(verifyFunction(*L->getHeader()->getParent()));
LoopPass::getAnalysisUsage(AU);
AU.addRequiredID(LoopSimplifyID);
AU.addRequiredID(LCSSAID);
+ AU.addRequired<DominatorTree>();
AU.addRequired<LoopInfo>();
AU.addRequired<ScalarEvolution>();
- AU.addRequired<DominatorTree>();
+ AU.addRequired<TargetTransformInfo>();
AU.addPreserved<LoopInfo>();
AU.addPreserved<DominatorTree>();
}
};
-}// namespace
+} // end anonymous namespace
//===----------------------------------------------------------------------===//
// Implementation of LoopVectorizationLegality, InnerLoopVectorizer and
void
LoopVectorizationLegality::RuntimePointerCheck::insert(ScalarEvolution *SE,
- Loop *Lp, Value *Ptr) {
+ Loop *Lp, Value *Ptr,
+ bool WritePtr) {
const SCEV *Sc = SE->getSCEV(Ptr);
const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(Sc);
assert(AR && "Invalid addrec expression");
Pointers.push_back(Ptr);
Starts.push_back(AR->getStart());
Ends.push_back(ScEnd);
+ IsWritePtr.push_back(WritePtr);
}
Value *InnerLoopVectorizer::getBroadcastInstrs(Value *V) {
- // Create the types.
- LLVMContext &C = V->getContext();
- Type *VTy = VectorType::get(V->getType(), VF);
- Type *I32 = IntegerType::getInt32Ty(C);
-
// Save the current insertion location.
Instruction *Loc = Builder.GetInsertPoint();
if (Invariant)
Builder.SetInsertPoint(LoopVectorPreHeader->getTerminator());
- Constant *Zero = ConstantInt::get(I32, 0);
- Value *Zeros = ConstantAggregateZero::get(VectorType::get(I32, VF));
- Value *UndefVal = UndefValue::get(VTy);
- // Insert the value into a new vector.
- Value *SingleElem = Builder.CreateInsertElement(UndefVal, V, Zero);
// Broadcast the scalar into all locations in the vector.
- Value *Shuf = Builder.CreateShuffleVector(SingleElem, UndefVal, Zeros,
- "broadcast");
+ Value *Shuf = Builder.CreateVectorSplat(VF, V, "broadcast");
// Restore the builder insertion point.
if (Invariant)
return Shuf;
}
-Value *InnerLoopVectorizer::getConsecutiveVector(Value* Val, bool Negate) {
+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");
SmallVector<Constant*, 8> Indices;
// Create a vector of consecutive numbers from zero to VF.
- for (int i = 0; i < VLen; ++i)
- Indices.push_back(ConstantInt::get(ITy, Negate ? (-i): i ));
+ 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);
return Builder.CreateAdd(Val, Cv, "induction");
}
-bool LoopVectorizationLegality::isConsecutivePtr(Value *Ptr) {
+int LoopVectorizationLegality::isConsecutivePtr(Value *Ptr) {
assert(Ptr->getType()->isPointerTy() && "Unexpected non ptr");
+ // Make sure that the pointer does not point to structs.
+ if (cast<PointerType>(Ptr->getType())->getElementType()->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 (PtrInduction == II.IK)
- return true;
+ 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 false;
+ return 0;
unsigned NumOperands = Gep->getNumOperands();
Value *LastIndex = Gep->getOperand(NumOperands - 1);
+ 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;
+ }
+
// Check that all of the gep indices are uniform except for the last.
for (unsigned i = 0; i < NumOperands - 1; ++i)
if (!SE->isLoopInvariant(SE->getSCEV(Gep->getOperand(i)), TheLoop))
- return false;
+ return 0;
// We can emit wide load/stores only if the last index is the induction
// variable.
// The memory is consecutive because the last index is consecutive
// and all other indices are loop invariant.
if (Step->isOne())
- return true;
+ return 1;
+ if (Step->isAllOnesValue())
+ return -1;
}
- return false;
+ return 0;
}
bool LoopVectorizationLegality::isUniform(Value *V) {
return (SE->isLoopInvariant(SE->getSCEV(V), TheLoop));
}
-Value *InnerLoopVectorizer::getVectorValue(Value *V) {
+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 saved a vectorized copy of V, use it.
- Value *&MapEntry = WidenMap[V];
- if (MapEntry)
- return MapEntry;
- // Broadcast V and save the value for future uses.
+ // 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);
- MapEntry = B;
- return B;
+ return WidenMap.splat(V, B);
}
-Constant*
-InnerLoopVectorizer::getUniformVector(unsigned Val, Type* ScalarTy) {
- return ConstantVector::getSplat(VF, ConstantInt::get(ScalarTy, Val, true));
+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();
+
+ 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())) {
+ 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) {
+ 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();
+
+ Value *LastGepOperand = Gep->getOperand(NumOperands - 1);
+ VectorParts &GEPParts = getVectorValue(LastGepOperand);
+ Value *LastIndex = GEPParts[0];
+ LastIndex = Builder.CreateExtractElement(LastIndex, Zero);
+
+ // Create the new GEP with the new induction variable.
+ GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone());
+ Gep2->setOperand(NumOperands - 1, LastIndex);
+ Gep2->setName("gep.indvar.idx");
+ Ptr = Builder.Insert(Gep2);
+ } else {
+ // Use the induction element ptr.
+ assert(isa<PHINode>(Ptr) && "Invalid induction ptr");
+ VectorParts &PtrVal = getVectorValue(Ptr);
+ Ptr = Builder.CreateExtractElement(PtrVal[0], Zero);
+ }
+
+ // Handle Stores:
+ if (SI) {
+ assert(!Legal->isUniform(SI->getPointerOperand()) &&
+ "We do not allow storing to uniform addresses");
+
+ 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());
+ Builder.CreateStore(StoredVal[Part], VecPtr)->setAlignment(Alignment);
+ }
+ }
+
+ 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());
+ 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<Value*, 8> Params;
+ SmallVector<VectorParts, 4> Params;
// Find all of the vectorized parameters.
for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) {
// 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.count(SrcInst) && "Source operand is unavailable");
+ assert(WidenMap.has(SrcInst) && "Source operand is unavailable");
// The parameter is a vector value from earlier.
- Params.push_back(WidenMap[SrcInst]);
+ Params.push_back(WidenMap.get(SrcInst));
} else {
// The parameter is a scalar from outside the loop. Maybe even a constant.
- Params.push_back(SrcOp);
+ VectorParts Scalars;
+ Scalars.append(UF, SrcOp);
+ Params.push_back(Scalars);
}
}
// Does this instruction return a value ?
bool IsVoidRetTy = Instr->getType()->isVoidTy();
- Value *VecResults = 0;
-
- // If we have a return value, create an empty vector. We place the scalarized
- // instructions in this vector.
- if (!IsVoidRetTy)
- VecResults = UndefValue::get(VectorType::get(Instr->getType(), VF));
-
- // For each scalar that we create:
- for (unsigned i = 0; i < VF; ++i) {
- Instruction *Cloned = Instr->clone();
- if (!IsVoidRetTy)
- Cloned->setName(Instr->getName() + ".cloned");
- // Replace the operands of the cloned instrucions with extracted scalars.
- for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) {
- Value *Op = Params[op];
- // Param is a vector. Need to extract the right lane.
- if (Op->getType()->isVectorTy())
- Op = Builder.CreateExtractElement(Op, Builder.getInt32(i));
- Cloned->setOperand(op, Op);
- }
- // Place the cloned scalar in the new loop.
- Builder.Insert(Cloned);
+ 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 instrucions with extracted scalars.
+ for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) {
+ Value *Op = Params[op][Part];
+ // Param is a vector. Need to extract the right lane.
+ if (Op->getType()->isVectorTy())
+ Op = Builder.CreateExtractElement(Op, Builder.getInt32(Width));
+ Cloned->setOperand(op, Op);
+ }
- // 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 = Builder.CreateInsertElement(VecResults, Cloned,
- Builder.getInt32(i));
- }
+ // Place the cloned scalar in the new loop.
+ Builder.Insert(Cloned);
- if (!IsVoidRetTy)
- WidenMap[Instr] = VecResults;
+ // If the original scalar returns a value we need to place it in a vector
+ // so that future users will be able to use it.
+ if (!IsVoidRetTy)
+ VecResults[Part] = Builder.CreateInsertElement(VecResults[Part], Cloned,
+ Builder.getInt32(Width));
+ }
+ }
}
-Value*
+Instruction *
InnerLoopVectorizer::addRuntimeCheck(LoopVectorizationLegality *Legal,
Instruction *Loc) {
LoopVectorizationLegality::RuntimePointerCheck *PtrRtCheck =
if (!PtrRtCheck->Need)
return NULL;
- Value *MemoryRuntimeCheck = 0;
+ Instruction *MemoryRuntimeCheck = 0;
unsigned NumPointers = PtrRtCheck->Pointers.size();
SmallVector<Value* , 2> Starts;
SmallVector<Value* , 2> Ends;
}
}
+ IRBuilder<> ChkBuilder(Loc);
+
for (unsigned i = 0; i < NumPointers; ++i) {
for (unsigned j = i+1; j < NumPointers; ++j) {
- Instruction::CastOps Op = Instruction::BitCast;
- Value *Start0 = CastInst::Create(Op, Starts[i], PtrArithTy, "bc", Loc);
- Value *Start1 = CastInst::Create(Op, Starts[j], PtrArithTy, "bc", Loc);
- Value *End0 = CastInst::Create(Op, Ends[i], PtrArithTy, "bc", Loc);
- Value *End1 = CastInst::Create(Op, Ends[j], PtrArithTy, "bc", Loc);
-
- Value *Cmp0 = CmpInst::Create(Instruction::ICmp, CmpInst::ICMP_ULE,
- Start0, End1, "bound0", Loc);
- Value *Cmp1 = CmpInst::Create(Instruction::ICmp, CmpInst::ICMP_ULE,
- Start1, End0, "bound1", Loc);
- Value *IsConflict = BinaryOperator::Create(Instruction::And, Cmp0, Cmp1,
- "found.conflict", Loc);
+ // No need to check if two readonly pointers intersect.
+ if (!PtrRtCheck->IsWritePtr[i] && !PtrRtCheck->IsWritePtr[j])
+ continue;
+
+ Value *Start0 = ChkBuilder.CreateBitCast(Starts[i], PtrArithTy, "bc");
+ Value *Start1 = ChkBuilder.CreateBitCast(Starts[j], PtrArithTy, "bc");
+ Value *End0 = ChkBuilder.CreateBitCast(Ends[i], PtrArithTy, "bc");
+ Value *End1 = ChkBuilder.CreateBitCast(Ends[j], PtrArithTy, "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)
- MemoryRuntimeCheck = BinaryOperator::Create(Instruction::Or,
- MemoryRuntimeCheck,
- IsConflict,
- "conflict.rdx", Loc);
- else
- MemoryRuntimeCheck = IsConflict;
+ IsConflict = ChkBuilder.CreateOr(MemoryRuntimeCheck, IsConflict,
+ "conflict.rdx");
+ MemoryRuntimeCheck = cast<Instruction>(IsConflict);
}
}
the vectorized instructions while the old loop will continue to run the
scalar remainder.
- [ ] <-- vector loop bypass.
+ [ ] <-- vector loop bypass (may consist of multiple blocks).
/ |
/ v
| [ ] <-- vector pre header.
BasicBlock *ExitBlock = OrigLoop->getExitBlock();
assert(ExitBlock && "Must have an exit block");
+ // Mark the old scalar loop with metadata that tells us not to vectorize this
+ // loop again if we run into it.
+ MDNode *MD = MDNode::get(OldBasicBlock->getContext(), None);
+ OldBasicBlock->getTerminator()->setMetadata(AlreadyVectorizedMDName, MD);
+
// Some loops have a single integer induction variable, while other loops
// don't. One example is c++ iterators that often have multiple pointer
// induction variables. In the code below we also support a case where we
// don't have a single induction variable.
OldInduction = Legal->getInduction();
- Type *IdxTy = OldInduction ? OldInduction->getType() :
- DL->getIntPtrType(SE->getContext());
+ Type *IdxTy = Legal->getWidestInductionType();
// Find the loop boundaries.
const SCEV *ExitCount = SE->getExitCount(OrigLoop, OrigLoop->getLoopLatch());
// The loop index does not have to start at Zero. Find the original start
// value from the induction PHI node. If we don't have an induction variable
// then we know that it starts at zero.
- Value *StartIdx = OldInduction ?
- OldInduction->getIncomingValueForBlock(BypassBlock):
- ConstantInt::get(IdxTy, 0);
+ Builder.SetInsertPoint(BypassBlock->getTerminator());
+ Value *StartIdx = ExtendedIdx = OldInduction ?
+ Builder.CreateZExt(OldInduction->getIncomingValueForBlock(BypassBlock),
+ IdxTy):
+ ConstantInt::get(IdxTy, 0);
assert(BypassBlock && "Invalid loop structure");
-
- // Generate the code that checks in runtime if arrays overlap.
- Value *MemoryRuntimeCheck = addRuntimeCheck(Legal,
- BypassBlock->getTerminator());
+ LoopBypassBlocks.push_back(BypassBlock);
// Split the single block loop into the two loop structure described above.
BasicBlock *VectorPH =
BasicBlock *ScalarPH =
MiddleBlock->splitBasicBlock(MiddleBlock->getTerminator(), "scalar.ph");
- // This is the location in which we add all of the logic for bypassing
- // the new vector loop.
- Instruction *Loc = BypassBlock->getTerminator();
-
// Use this IR builder to create the loop instructions (Phi, Br, Cmp)
// inside the loop.
Builder.SetInsertPoint(VecBody->getFirstInsertionPt());
// Generate the induction variable.
Induction = Builder.CreatePHI(IdxTy, 2, "index");
- Constant *Step = ConstantInt::get(IdxTy, VF);
+ // 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());
// 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.
// The exit count can be of pointer type. Convert it to the correct
// integer type.
if (ExitCount->getType()->isPointerTy())
- Count = CastInst::CreatePointerCast(Count, IdxTy, "ptrcnt.to.int", Loc);
+ Count = BypassBuilder.CreatePointerCast(Count, IdxTy, "ptrcnt.to.int");
else
- Count = CastInst::CreateZExtOrBitCast(Count, IdxTy, "zext.cnt", Loc);
+ Count = BypassBuilder.CreateZExtOrTrunc(Count, IdxTy, "cnt.cast");
}
// Add the start index to the loop count to get the new end index.
- Value *IdxEnd = BinaryOperator::CreateAdd(Count, StartIdx, "end.idx", Loc);
+ 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.
- Constant *CIVF = ConstantInt::get(IdxTy, VF);
- Value *R = BinaryOperator::CreateURem(Count, CIVF, "n.mod.vf", Loc);
- Value *CountRoundDown = BinaryOperator::CreateSub(Count, R, "n.vec", Loc);
- Value *IdxEndRoundDown = BinaryOperator::CreateAdd(CountRoundDown, StartIdx,
- "end.idx.rnd.down", Loc);
+ 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 = CmpInst::Create(Instruction::ICmp, CmpInst::ICMP_EQ,
- IdxEndRoundDown,
- StartIdx,
- "cmp.zero", Loc);
-
- // If we are using memory runtime checks, include them in.
- if (MemoryRuntimeCheck)
- Cmp = BinaryOperator::Create(Instruction::Or, Cmp, MemoryRuntimeCheck,
- "CntOrMem", Loc);
+ 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");
+ 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;
+ }
- BranchInst::Create(MiddleBlock, VectorPH, Cmp, Loc);
- // Remove the old terminator.
- Loc->eraseFromParent();
+ 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
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;
- PHINode *ResumeVal = PHINode::Create(OrigPhi->getType(), 2, "resume.val",
+
+ 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::NoInduction:
+ case LoopVectorizationLegality::IK_NoInduction:
llvm_unreachable("Unknown induction");
- case LoopVectorizationLegality::IntInduction: {
- // Handle the integer induction counter:
+ case LoopVectorizationLegality::IK_IntInduction: {
+ // Handle the integer induction counter.
assert(OrigPhi->getType()->isIntegerTy() && "Invalid type");
- assert(OrigPhi == OldInduction && "Unknown integer PHI");
- // We know what the end value is.
- EndValue = IdxEndRoundDown;
- // We also know which PHI node holds it.
- ResumeIndex = ResumeVal;
+
+ // 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::ReverseIntInduction: {
+ case LoopVectorizationLegality::IK_ReverseIntInduction: {
// Convert the CountRoundDown variable to the PHI size.
- unsigned CRDSize = CountRoundDown->getType()->getScalarSizeInBits();
- unsigned IISize = II.StartValue->getType()->getScalarSizeInBits();
- Value *CRD = CountRoundDown;
- if (CRDSize > IISize)
- CRD = CastInst::Create(Instruction::Trunc, CountRoundDown,
- II.StartValue->getType(),
- "tr.crd", BypassBlock->getTerminator());
- else if (CRDSize < IISize)
- CRD = CastInst::Create(Instruction::SExt, CountRoundDown,
- II.StartValue->getType(),
- "sext.crd", BypassBlock->getTerminator());
- // Handle reverse integer induction counter:
- EndValue = BinaryOperator::CreateSub(II.StartValue, CRD, "rev.ind.end",
- BypassBlock->getTerminator());
+ 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::PtrInduction: {
+ case LoopVectorizationLegality::IK_PtrInduction: {
// For pointer induction variables, calculate the offset using
// the end index.
- EndValue = GetElementPtrInst::Create(II.StartValue, CountRoundDown,
- "ptr.ind.end",
- BypassBlock->getTerminator());
+ 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.
- ResumeVal->addIncoming(II.StartValue, BypassBlock);
+ 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);
- OrigPhi->setIncomingValue(BlockIdx, ResumeVal);
+ // 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
assert(!ResumeIndex && "Unexpected resume value found");
ResumeIndex = PHINode::Create(IdxTy, 2, "new.indc.resume.val",
MiddleBlock->getTerminator());
- ResumeIndex->addIncoming(StartIdx, BypassBlock);
+ for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I)
+ ResumeIndex->addIncoming(StartIdx, LoopBypassBlocks[I]);
ResumeIndex->addIncoming(IdxEndRoundDown, VecBody);
}
// Insert the new loop into the loop nest and register the new basic blocks.
if (ParentLoop) {
ParentLoop->addChildLoop(Lp);
+ for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I)
+ ParentLoop->addBasicBlockToLoop(LoopBypassBlocks[I], LI->getBase());
ParentLoop->addBasicBlockToLoop(ScalarPH, LI->getBase());
ParentLoop->addBasicBlockToLoop(VectorPH, LI->getBase());
ParentLoop->addBasicBlockToLoop(MiddleBlock, LI->getBase());
LoopExitBlock = ExitBlock;
LoopVectorBody = VecBody;
LoopScalarBody = OldBasicBlock;
- LoopBypassBlock = BypassBlock;
}
/// This function returns the identity element (or neutral element) for
/// the operation K.
-static unsigned
-getReductionIdentity(LoopVectorizationLegality::ReductionKind K) {
+Constant*
+LoopVectorizationLegality::getReductionIdentity(ReductionKind K, Type *Tp) {
switch (K) {
- case LoopVectorizationLegality::IntegerXor:
- case LoopVectorizationLegality::IntegerAdd:
- case LoopVectorizationLegality::IntegerOr:
+ case RK_IntegerXor:
+ case RK_IntegerAdd:
+ case RK_IntegerOr:
// Adding, Xoring, Oring zero to a number does not change it.
- return 0;
- case LoopVectorizationLegality::IntegerMult:
+ return ConstantInt::get(Tp, 0);
+ case RK_IntegerMult:
// Multiplying a number by 1 does not change it.
- return 1;
- case LoopVectorizationLegality::IntegerAnd:
+ return ConstantInt::get(Tp, 1);
+ case RK_IntegerAnd:
// AND-ing a number with an all-1 value does not change it.
- return -1;
+ 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 bool
-isTriviallyVectorizableIntrinsic(Instruction *Inst) {
- IntrinsicInst *II = dyn_cast<IntrinsicInst>(Inst);
- if (!II)
- return false;
- switch (II->getIntrinsicID()) {
- case Intrinsic::sqrt:
- case Intrinsic::sin:
- case Intrinsic::cos:
- case Intrinsic::exp:
- case Intrinsic::exp2:
- case Intrinsic::log:
- case Intrinsic::log10:
- case Intrinsic::log2:
- case Intrinsic::fabs:
- case Intrinsic::floor:
- case Intrinsic::ceil:
- case Intrinsic::trunc:
- case Intrinsic::rint:
- case Intrinsic::nearbyint:
- case Intrinsic::pow:
- case Intrinsic::fma:
- return true;
+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::floor:
+ case Intrinsic::ceil:
+ case Intrinsic::trunc:
+ case Intrinsic::rint:
+ case Intrinsic::nearbyint:
+ case Intrinsic::pow:
+ case Intrinsic::fma:
+ case Intrinsic::fmuladd:
+ 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.
+ if (!F || !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:
- return false;
+ break;
+ case LibFunc::sin:
+ case LibFunc::sinf:
+ case LibFunc::sinl:
+ return Intrinsic::sin;
+ case LibFunc::cos:
+ case LibFunc::cosf:
+ case LibFunc::cosl:
+ return Intrinsic::cos;
+ case LibFunc::exp:
+ case LibFunc::expf:
+ case LibFunc::expl:
+ return Intrinsic::exp;
+ case LibFunc::exp2:
+ case LibFunc::exp2f:
+ case LibFunc::exp2l:
+ return Intrinsic::exp2;
+ case LibFunc::log:
+ case LibFunc::logf:
+ case LibFunc::logl:
+ return Intrinsic::log;
+ case LibFunc::log10:
+ case LibFunc::log10f:
+ case LibFunc::log10l:
+ return Intrinsic::log10;
+ case LibFunc::log2:
+ case LibFunc::log2f:
+ case LibFunc::log2l:
+ return Intrinsic::log2;
+ case LibFunc::fabs:
+ case LibFunc::fabsf:
+ case LibFunc::fabsl:
+ return Intrinsic::fabs;
+ case LibFunc::floor:
+ case LibFunc::floorf:
+ case LibFunc::floorl:
+ return Intrinsic::floor;
+ case LibFunc::ceil:
+ case LibFunc::ceilf:
+ case LibFunc::ceill:
+ return Intrinsic::ceil;
+ case LibFunc::trunc:
+ case LibFunc::truncf:
+ case LibFunc::truncl:
+ return Intrinsic::trunc;
+ case LibFunc::rint:
+ case LibFunc::rintf:
+ case LibFunc::rintl:
+ return Intrinsic::rint;
+ case LibFunc::nearbyint:
+ case LibFunc::nearbyintf:
+ case LibFunc::nearbyintl:
+ return Intrinsic::nearbyint;
+ case LibFunc::pow:
+ case LibFunc::powf:
+ case LibFunc::powl:
+ return Intrinsic::pow;
}
- return false;
+
+ 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;
}
void
// the cost-model.
//
//===------------------------------------------------===//
- BasicBlock &BB = *OrigLoop->getHeader();
- Constant *Zero =
- ConstantInt::get(IntegerType::getInt32Ty(BB.getContext()), 0);
+ 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
for (PhiVector::iterator it = RdxPHIsToFix.begin(), e = RdxPHIsToFix.end();
it != e; ++it) {
PHINode *RdxPhi = *it;
- PHINode *VecRdxPhi = dyn_cast<PHINode>(WidenMap[RdxPhi]);
assert(RdxPhi && "Unable to recover vectorized PHI");
// Find the reduction variable descriptor.
// To do so, we need to generate the 'identity' vector and overide
// one of the elements with the incoming scalar reduction. We need
// to do it in the vector-loop preheader.
- Builder.SetInsertPoint(LoopBypassBlock->getTerminator());
+ Builder.SetInsertPoint(LoopBypassBlocks.front()->getTerminator());
// This is the vector-clone of the value that leaves the loop.
- Value *VectorExit = getVectorValue(RdxDesc.LoopExitInstr);
- Type *VecTy = VectorExit->getType();
+ VectorParts &VectorExit = getVectorValue(RdxDesc.LoopExitInstr);
+ Type *VecTy = VectorExit[0]->getType();
// Find the reduction identity variable. Zero for addition, or, xor,
// one for multiplication, -1 for And.
- Constant *Identity = getUniformVector(getReductionIdentity(RdxDesc.Kind),
- VecTy->getScalarType());
-
- // This vector is the Identity vector where the first element is the
- // incoming scalar reduction.
- Value *VectorStart = Builder.CreateInsertElement(Identity,
- RdxDesc.StartValue, Zero);
+ Value *Identity;
+ Value *VectorStart;
+ if (RdxDesc.Kind == LoopVectorizationLegality::RK_IntegerMinMax ||
+ RdxDesc.Kind == LoopVectorizationLegality::RK_FloatMinMax) {
+ // MinMax reduction have the start value as their identify.
+ VectorStart = Identity = Builder.CreateVectorSplat(VF, RdxDesc.StartValue,
+ "minmax.ident");
+ } else {
+ Constant *Iden =
+ LoopVectorizationLegality::getReductionIdentity(RdxDesc.Kind,
+ VecTy->getScalarType());
+ 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
// Reductions do not have to start at zero. They can start with
// any loop invariant values.
- VecRdxPhi->addIncoming(VectorStart, VecPreheader);
- Value *Val =
- getVectorValue(RdxPhi->getIncomingValueForBlock(OrigLoop->getLoopLatch()));
- VecRdxPhi->addIncoming(Val, LoopVectorBody);
+ 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.
// instructions.
Builder.SetInsertPoint(LoopMiddleBlock->getFirstInsertionPt());
- // This PHINode contains the vectorized reduction variable, or
- // the initial value vector, if we bypass the vector loop.
- PHINode *NewPhi = Builder.CreatePHI(VecTy, 2, "rdx.vec.exit.phi");
- NewPhi->addIncoming(VectorStart, LoopBypassBlock);
- NewPhi->addIncoming(getVectorValue(RdxDesc.LoopExitInstr), LoopVectorBody);
+ VectorParts RdxParts;
+ for (unsigned part = 0; part < UF; ++part) {
+ // This PHINode contains the vectorized reduction variable, or
+ // the initial value vector, if we bypass the vector loop.
+ VectorParts &RdxExitVal = getVectorValue(RdxDesc.LoopExitInstr);
+ PHINode *NewPhi = Builder.CreatePHI(VecTy, 2, "rdx.vec.exit.phi");
+ Value *StartVal = (part == 0) ? VectorStart : Identity;
+ 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);
+ 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]);
+ }
// 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 = NewPhi;
+ 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.
ConstantVector::get(ShuffleMask),
"rdx.shuf");
- // Emit the operation on the shuffled value.
- switch (RdxDesc.Kind) {
- case LoopVectorizationLegality::IntegerAdd:
- TmpVec = Builder.CreateAdd(TmpVec, Shuf, "add.rdx");
- break;
- case LoopVectorizationLegality::IntegerMult:
- TmpVec = Builder.CreateMul(TmpVec, Shuf, "mul.rdx");
- break;
- case LoopVectorizationLegality::IntegerOr:
- TmpVec = Builder.CreateOr(TmpVec, Shuf, "or.rdx");
- break;
- case LoopVectorizationLegality::IntegerAnd:
- TmpVec = Builder.CreateAnd(TmpVec, Shuf, "and.rdx");
- break;
- case LoopVectorizationLegality::IntegerXor:
- TmpVec = Builder.CreateXor(TmpVec, Shuf, "xor.rdx");
- break;
- default:
- llvm_unreachable("Unknown reduction operation");
- }
+ 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.
(RdxPhi)->setIncomingValue(SelfEdgeBlockIdx, Scalar0);
(RdxPhi)->setIncomingValue(IncomingEdgeBlockIdx, RdxDesc.LoopExitInstr);
}// end of for each redux variable.
+
+ // The Loop exit block may have single value PHI nodes where the incoming
+ // value is 'undef'. While vectorizing we only handled real values that
+ // were defined inside the loop. Here we handle the 'undef case'.
+ // See PR14725.
+ for (BasicBlock::iterator LEI = LoopExitBlock->begin(),
+ LEE = LoopExitBlock->end(); LEI != LEE; ++LEI) {
+ PHINode *LCSSAPhi = dyn_cast<PHINode>(LEI);
+ if (!LCSSAPhi) continue;
+ if (LCSSAPhi->getNumIncomingValues() == 1)
+ LCSSAPhi->addIncoming(UndefValue::get(LCSSAPhi->getType()),
+ LoopMiddleBlock);
+ }
}
-Value *InnerLoopVectorizer::createEdgeMask(BasicBlock *Src, BasicBlock *Dst) {
+InnerLoopVectorizer::VectorParts
+InnerLoopVectorizer::createEdgeMask(BasicBlock *Src, BasicBlock *Dst) {
assert(std::find(pred_begin(Dst), pred_end(Dst), Src) != pred_end(Dst) &&
"Invalid edge");
- Value *SrcMask = createBlockInMask(Src);
+ VectorParts SrcMask = createBlockInMask(Src);
// The terminator has to be a branch inst!
BranchInst *BI = dyn_cast<BranchInst>(Src->getTerminator());
assert(BI && "Unexpected terminator found");
- Value *EdgeMask = SrcMask;
if (BI->isConditional()) {
- EdgeMask = getVectorValue(BI->getCondition());
+ VectorParts EdgeMask = getVectorValue(BI->getCondition());
+
if (BI->getSuccessor(0) != Dst)
- EdgeMask = Builder.CreateNot(EdgeMask);
+ for (unsigned part = 0; part < UF; ++part)
+ EdgeMask[part] = Builder.CreateNot(EdgeMask[part]);
+
+ for (unsigned part = 0; part < UF; ++part)
+ EdgeMask[part] = Builder.CreateAnd(EdgeMask[part], SrcMask[part]);
+ return EdgeMask;
}
- return Builder.CreateAnd(EdgeMask, SrcMask);
+ return SrcMask;
}
-Value *InnerLoopVectorizer::createBlockInMask(BasicBlock *BB) {
+InnerLoopVectorizer::VectorParts
+InnerLoopVectorizer::createBlockInMask(BasicBlock *BB) {
assert(OrigLoop->contains(BB) && "Block is not a part of a loop");
// Loop incoming mask is all-one.
// This is the block mask. We OR all incoming edges, and with zero.
Value *Zero = ConstantInt::get(IntegerType::getInt1Ty(BB->getContext()), 0);
- Value *BlockMask = getVectorValue(Zero);
+ VectorParts BlockMask = getVectorValue(Zero);
// For each pred:
- for (pred_iterator it = pred_begin(BB), e = pred_end(BB); it != e; ++it)
- BlockMask = Builder.CreateOr(BlockMask, createEdgeMask(*it, BB));
+ for (pred_iterator it = pred_begin(BB), e = pred_end(BB); it != e; ++it) {
+ VectorParts EM = createEdgeMask(*it, BB);
+ for (unsigned part = 0; part < UF; ++part)
+ BlockMask[part] = Builder.CreateOr(BlockMask[part], EM[part]);
+ }
return BlockMask;
}
void
InnerLoopVectorizer::vectorizeBlockInLoop(LoopVectorizationLegality *Legal,
BasicBlock *BB, PhiVector *PV) {
- Constant *Zero =
- ConstantInt::get(IntegerType::getInt32Ty(BB->getContext()), 0);
-
// For each instruction in the old loop.
for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
+ VectorParts &Entry = WidenMap.get(it);
switch (it->getOpcode()) {
case Instruction::Br:
// Nothing to do for PHIs and BR, since we already took care of the
PHINode* P = cast<PHINode>(it);
// Handle reduction variables:
if (Legal->getReductionVars()->count(P)) {
- // This is phase one of vectorizing PHIs.
- Type *VecTy = VectorType::get(it->getType(), VF);
- WidenMap[it] =
- PHINode::Create(VecTy, 2, "vec.phi",
- LoopVectorBody->getFirstInsertionPt());
+ for (unsigned part = 0; part < UF; ++part) {
+ // This is phase one of vectorizing PHIs.
+ Type *VecTy = VectorType::get(it->getType(), VF);
+ Entry[part] = PHINode::Create(VecTy, 2, "vec.phi",
+ LoopVectorBody-> getFirstInsertionPt());
+ }
PV->push_back(P);
continue;
}
// 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.
- Value *Cond = createEdgeMask(P->getIncomingBlock(0), P->getParent());
- WidenMap[P] =
- Builder.CreateSelect(Cond,
- getVectorValue(P->getIncomingValue(0)),
- getVectorValue(P->getIncomingValue(1)),
- "predphi");
+
+ unsigned NumIncoming = P->getNumIncomingValues();
+ assert(NumIncoming > 1 && "Invalid PHI");
+
+ // 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 don't need to 'select' the first PHI operand because it is
+ // the default value if all of the other masks don't match.
+ if (In == 0)
+ Entry[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");
+ }
+ }
continue;
}
Legal->getInductionVars()->lookup(P);
switch (II.IK) {
- case LoopVectorizationLegality::NoInduction:
+ case LoopVectorizationLegality::IK_NoInduction:
llvm_unreachable("Unknown induction");
- case LoopVectorizationLegality::IntInduction: {
- assert(P == OldInduction && "Unexpected PHI");
- Value *Broadcasted = getBroadcastInstrs(Induction);
- // After broadcasting the induction variable we need to make the
- // vector consecutive by adding 0, 1, 2 ...
- Value *ConsecutiveInduction = getConsecutiveVector(Broadcasted);
- WidenMap[OldInduction] = ConsecutiveInduction;
+ 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);
continue;
}
- case LoopVectorizationLegality::ReverseIntInduction:
- case LoopVectorizationLegality::PtrInduction:
+ case LoopVectorizationLegality::IK_ReverseIntInduction:
+ case LoopVectorizationLegality::IK_PtrInduction:
+ case LoopVectorizationLegality::IK_ReversePtrInduction:
// Handle reverse integer and pointer inductions.
- Value *StartIdx = 0;
- // If we have a single integer induction variable then use it.
- // Otherwise, start counting at zero.
- if (OldInduction) {
- LoopVectorizationLegality::InductionInfo OldII =
- Legal->getInductionVars()->lookup(OldInduction);
- StartIdx = OldII.StartValue;
- } else {
- StartIdx = ConstantInt::get(Induction->getType(), 0);
- }
+ 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::ReverseIntInduction == II.IK) {
+ if (LoopVectorizationLegality::IK_ReverseIntInduction == II.IK) {
IntegerType *DstTy = cast<IntegerType>(II.StartValue->getType());
Value *CNI = Builder.CreateSExtOrTrunc(NormalizedIdx, DstTy,
"resize.norm.idx");
Value *Broadcasted = getBroadcastInstrs(ReverseInd);
// After broadcasting the induction variable we need to make the
// vector consecutive by adding ... -3, -2, -1, 0.
- Value *ConsecutiveInduction = getConsecutiveVector(Broadcasted,
- true);
- WidenMap[it] = ConsecutiveInduction;
+ for (unsigned part = 0; part < UF; ++part)
+ Entry[part] = getConsecutiveVector(Broadcasted, -(int)VF * part,
+ true);
continue;
}
// 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.
- Value *VecVal = UndefValue::get(VectorType::get(P->getType(), VF));
- for (unsigned int i = 0; i < VF; ++i) {
- Constant *Idx = ConstantInt::get(Induction->getType(), i);
- Value *GlobalIdx = Builder.CreateAdd(NormalizedIdx, Idx,
- "gep.idx");
- Value *SclrGep = Builder.CreateGEP(II.StartValue, GlobalIdx,
- "next.gep");
- VecVal = Builder.CreateInsertElement(VecVal, SclrGep,
- Builder.getInt32(i),
- "insert.gep");
+ for (unsigned part = 0; part < UF; ++part) {
+ 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;
}
-
- WidenMap[it] = VecVal;
continue;
}
case Instruction::Xor: {
// Just widen binops.
BinaryOperator *BinOp = dyn_cast<BinaryOperator>(it);
- Value *A = getVectorValue(it->getOperand(0));
- Value *B = getVectorValue(it->getOperand(1));
+ VectorParts &A = getVectorValue(it->getOperand(0));
+ VectorParts &B = getVectorValue(it->getOperand(1));
// Use this vector value for all users of the original instruction.
- Value *V = Builder.CreateBinOp(BinOp->getOpcode(), A, B);
- WidenMap[it] = V;
-
- // Update the NSW, NUW and Exact flags.
- BinaryOperator *VecOp = cast<BinaryOperator>(V);
- if (isa<OverflowingBinaryOperator>(BinOp)) {
- VecOp->setHasNoSignedWrap(BinOp->hasNoSignedWrap());
- VecOp->setHasNoUnsignedWrap(BinOp->hasNoUnsignedWrap());
+ 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;
}
- if (isa<PossiblyExactOperator>(VecOp))
- VecOp->setIsExact(BinOp->isExact());
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.
- Value *Cond = it->getOperand(0);
- bool InvariantCond = SE->isLoopInvariant(SE->getSCEV(Cond), OrigLoop);
+ bool InvariantCond = SE->isLoopInvariant(SE->getSCEV(it->getOperand(0)),
+ OrigLoop);
// The condition can be loop invariant but still defined inside the
// loop. This means that we can't just use the original 'cond' value.
// We have to take the 'vectorized' value and pick the first lane.
// Instcombine will make this a no-op.
- Cond = getVectorValue(Cond);
- if (InvariantCond)
- Cond = Builder.CreateExtractElement(Cond, Builder.getInt32(0));
-
- Value *Op0 = getVectorValue(it->getOperand(1));
- Value *Op1 = getVectorValue(it->getOperand(2));
- WidenMap[it] = Builder.CreateSelect(Cond, Op0, Op1);
+ VectorParts &Cond = getVectorValue(it->getOperand(0));
+ VectorParts &Op0 = getVectorValue(it->getOperand(1));
+ VectorParts &Op1 = getVectorValue(it->getOperand(2));
+ Value *ScalarCond = Builder.CreateExtractElement(Cond[0],
+ Builder.getInt32(0));
+ for (unsigned Part = 0; Part < UF; ++Part) {
+ Entry[Part] = Builder.CreateSelect(
+ InvariantCond ? ScalarCond : Cond[Part],
+ Op0[Part],
+ Op1[Part]);
+ }
break;
}
// Widen compares. Generate vector compares.
bool FCmp = (it->getOpcode() == Instruction::FCmp);
CmpInst *Cmp = dyn_cast<CmpInst>(it);
- Value *A = getVectorValue(it->getOperand(0));
- Value *B = getVectorValue(it->getOperand(1));
- if (FCmp)
- WidenMap[it] = Builder.CreateFCmp(Cmp->getPredicate(), A, B);
- else
- WidenMap[it] = Builder.CreateICmp(Cmp->getPredicate(), A, B);
- break;
- }
-
- case Instruction::Store: {
- // Attempt to issue a wide store.
- StoreInst *SI = dyn_cast<StoreInst>(it);
- Type *StTy = VectorType::get(SI->getValueOperand()->getType(), VF);
- Value *Ptr = SI->getPointerOperand();
- unsigned Alignment = SI->getAlignment();
-
- assert(!Legal->isUniform(Ptr) &&
- "We do not allow storing to uniform addresses");
-
- GetElementPtrInst *Gep = dyn_cast<GetElementPtrInst>(Ptr);
-
- // This store does not use GEPs.
- if (!Legal->isConsecutivePtr(Ptr)) {
- scalarizeInstruction(it);
- break;
+ 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;
}
-
- if (Gep) {
- // The last index does not have to be the induction. It can be
- // consecutive and be a function of the index. For example A[I+1];
- unsigned NumOperands = Gep->getNumOperands();
- Value *LastIndex = getVectorValue(Gep->getOperand(NumOperands - 1));
- LastIndex = Builder.CreateExtractElement(LastIndex, Zero);
-
- // Create the new GEP with the new induction variable.
- GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone());
- Gep2->setOperand(NumOperands - 1, LastIndex);
- Ptr = Builder.Insert(Gep2);
- } else {
- // Use the induction element ptr.
- assert(isa<PHINode>(Ptr) && "Invalid induction ptr");
- Ptr = Builder.CreateExtractElement(getVectorValue(Ptr), Zero);
- }
- Ptr = Builder.CreateBitCast(Ptr, StTy->getPointerTo());
- Value *Val = getVectorValue(SI->getValueOperand());
- Builder.CreateStore(Val, Ptr)->setAlignment(Alignment);
break;
}
- case Instruction::Load: {
- // Attempt to issue a wide load.
- LoadInst *LI = dyn_cast<LoadInst>(it);
- Type *RetTy = VectorType::get(LI->getType(), VF);
- Value *Ptr = LI->getPointerOperand();
- unsigned Alignment = LI->getAlignment();
- GetElementPtrInst *Gep = dyn_cast<GetElementPtrInst>(Ptr);
-
- // If the pointer is loop invariant or if it is non consecutive,
- // scalarize the load.
- bool Con = Legal->isConsecutivePtr(Ptr);
- if (Legal->isUniform(Ptr) || !Con) {
- scalarizeInstruction(it);
- break;
- }
- if (Gep) {
- // The last index does not have to be the induction. It can be
- // consecutive and be a function of the index. For example A[I+1];
- unsigned NumOperands = Gep->getNumOperands();
- Value *LastIndex = getVectorValue(Gep->getOperand(NumOperands -1));
- LastIndex = Builder.CreateExtractElement(LastIndex, Zero);
-
- // Create the new GEP with the new induction variable.
- GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone());
- Gep2->setOperand(NumOperands - 1, LastIndex);
- Ptr = Builder.Insert(Gep2);
- } else {
- // Use the induction element ptr.
- assert(isa<PHINode>(Ptr) && "Invalid induction ptr");
- Ptr = Builder.CreateExtractElement(getVectorValue(Ptr), Zero);
- }
-
- Ptr = Builder.CreateBitCast(Ptr, RetTy->getPointerTo());
- LI = Builder.CreateLoad(Ptr);
- LI->setAlignment(Alignment);
- // Use this vector value for all users of the load.
- WidenMap[it] = LI;
- break;
- }
+ case Instruction::Store:
+ case Instruction::Load:
+ vectorizeMemoryInstruction(it, Legal);
+ break;
case Instruction::ZExt:
case Instruction::SExt:
case Instruction::FPToUI:
Value *ScalarCast = Builder.CreateCast(CI->getOpcode(), Induction,
CI->getType());
Value *Broadcasted = getBroadcastInstrs(ScalarCast);
- WidenMap[it] = getConsecutiveVector(Broadcasted);
+ for (unsigned Part = 0; Part < UF; ++Part)
+ Entry[Part] = getConsecutiveVector(Broadcasted, VF * Part, false);
break;
}
/// Vectorize casts.
- Value *A = getVectorValue(it->getOperand(0));
Type *DestTy = VectorType::get(CI->getType()->getScalarType(), VF);
- WidenMap[it] = Builder.CreateCast(CI->getOpcode(), A, DestTy);
+
+ VectorParts &A = getVectorValue(it->getOperand(0));
+ for (unsigned Part = 0; Part < UF; ++Part)
+ Entry[Part] = Builder.CreateCast(CI->getOpcode(), A[Part], DestTy);
break;
}
case Instruction::Call: {
- assert(isTriviallyVectorizableIntrinsic(it));
+ // Ignore dbg intrinsics.
+ if (isa<DbgInfoIntrinsic>(it))
+ break;
+
Module *M = BB->getParent()->getParent();
- IntrinsicInst *II = cast<IntrinsicInst>(it);
- Intrinsic::ID ID = II->getIntrinsicID();
- SmallVector<Value*, 4> Args;
- for (unsigned i = 0, ie = II->getNumArgOperands(); i != ie; ++i)
- Args.push_back(getVectorValue(II->getArgOperand(i)));
- Type *Tys[] = { VectorType::get(II->getType()->getScalarType(), VF) };
- Function *F = Intrinsic::getDeclaration(M, ID, Tys);
- WidenMap[it] = Builder.CreateCall(F, Args);
+ CallInst *CI = cast<CallInst>(it);
+ Intrinsic::ID ID = getIntrinsicIDForCall(CI, TLI);
+ assert(ID && "Not an intrinsic call!");
+ 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[] = { VectorType::get(CI->getType()->getScalarType(), VF) };
+ Function *F = Intrinsic::getDeclaration(M, ID, Tys);
+ Entry[Part] = Builder.CreateCall(F, Args);
+ }
break;
}
SE->forgetLoop(OrigLoop);
// Update the dominator tree information.
- assert(DT->properlyDominates(LoopBypassBlock, LoopExitBlock) &&
+ assert(DT->properlyDominates(LoopBypassBlocks.front(), LoopExitBlock) &&
"Entry does not dominate exit.");
- DT->addNewBlock(LoopVectorPreHeader, LoopBypassBlock);
+ 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, LoopBypassBlock);
+ DT->addNewBlock(LoopMiddleBlock, LoopBypassBlocks.front());
DT->addNewBlock(LoopScalarPreHeader, LoopMiddleBlock);
DT->changeImmediateDominator(LoopScalarBody, LoopScalarPreHeader);
DT->changeImmediateDominator(LoopExitBlock, LoopMiddleBlock);
if (!isa<BranchInst>(BB->getTerminator()))
return false;
- // We must have at most two predecessors because we need to convert
- // all PHIs to selects.
- unsigned Preds = std::distance(pred_begin(BB), pred_end(BB));
- if (Preds > 2)
- return false;
-
// We must be able to predicate all blocks that need to be predicated.
if (blockNeedsPredication(BB) && !blockCanBePredicated(BB))
return false;
// Do not loop-vectorize loops with a tiny trip count.
unsigned TC = SE->getSmallConstantTripCount(TheLoop, Latch);
- if (TC > 0u && TC < TinyTripCountThreshold) {
+ 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;
return true;
}
+static Type *convertPointerToIntegerType(DataLayout &DL, Type *Ty) {
+ if (Ty->isPointerTy())
+ return DL.getIntPtrType(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;
+}
+
bool LoopVectorizationLegality::canVectorizeInstrs() {
BasicBlock *PreHeader = TheLoop->getLoopPreheader();
BasicBlock *Header = TheLoop->getHeader();
+ // If we marked the scalar loop as "already vectorized" then no need
+ // to vectorize it again.
+ if (Header->getTerminator()->getMetadata(AlreadyVectorizedMDName)) {
+ DEBUG(dbgs() << "LV: This loop was vectorized before\n");
+ return false;
+ }
+
+ // 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) {
++it) {
if (PHINode *Phi = dyn_cast<PHINode>(it)) {
- // This should not happen because the loop should be normalized.
- if (Phi->getNumIncomingValues() != 2) {
- DEBUG(dbgs() << "LV: Found an invalid PHI.\n");
- return false;
- }
-
+ Type *PhiTy = Phi->getType();
// Check that this PHI type is allowed.
- if (!Phi->getType()->isIntegerTy() &&
- !Phi->getType()->isPointerTy()) {
+ if (!PhiTy->isIntegerTy() &&
+ !PhiTy->isFloatingPointTy() &&
+ !PhiTy->isPointerTy()) {
DEBUG(dbgs() << "LV: Found an non-int non-pointer PHI.\n");
return false;
}
if (*bb != Header)
continue;
+ // 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 (NoInduction != IK) {
+ 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 == IntInduction) {
- if (Induction) {
- DEBUG(dbgs() << "LV: Found too many inductions."<< *Phi <<"\n");
- return false;
- }
- Induction = Phi;
+ 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");
continue;
}
- if (AddReductionVar(Phi, IntegerAdd)) {
+ if (AddReductionVar(Phi, RK_IntegerAdd)) {
DEBUG(dbgs() << "LV: Found an ADD reduction PHI."<< *Phi <<"\n");
continue;
}
- if (AddReductionVar(Phi, IntegerMult)) {
+ if (AddReductionVar(Phi, RK_IntegerMult)) {
DEBUG(dbgs() << "LV: Found a MUL reduction PHI."<< *Phi <<"\n");
continue;
}
- if (AddReductionVar(Phi, IntegerOr)) {
+ if (AddReductionVar(Phi, RK_IntegerOr)) {
DEBUG(dbgs() << "LV: Found an OR reduction PHI."<< *Phi <<"\n");
continue;
}
- if (AddReductionVar(Phi, IntegerAnd)) {
+ if (AddReductionVar(Phi, RK_IntegerAnd)) {
DEBUG(dbgs() << "LV: Found an AND reduction PHI."<< *Phi <<"\n");
continue;
}
- if (AddReductionVar(Phi, IntegerXor)) {
+ 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.
+ // 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 && !isTriviallyVectorizableIntrinsic(it)) {
+ if (CI && !getIntrinsicIDForCall(CI, TLI) && !isa<DbgInfoIntrinsic>(CI)) {
DEBUG(dbgs() << "LV: Found a call site.\n");
return false;
}
- // We do not re-vectorize vectors.
+ // Check that the instruction return type is vectorizable.
if (!VectorType::isValidElementType(it->getType()) &&
!it->getType()->isVoidTy()) {
DEBUG(dbgs() << "LV: Found unvectorizable type." << "\n");
return false;
}
+ // Check that the stored type is vectorizable.
+ if (StoreInst *ST = dyn_cast<StoreInst>(it)) {
+ Type *T = ST->getValueOperand()->getType();
+ if (!VectorType::isValidElementType(T))
+ return false;
+ }
+
// Reduction instructions are allowed to have exit users.
// All other instructions must not have external users.
if (!AllowedExit.count(it))
if (!Induction) {
DEBUG(dbgs() << "LV: Did not find one integer induction var.\n");
- assert(getInductionVars()->size() && "No induction variables");
+ if (Inductions.empty())
+ return false;
}
return true;
}
}
+AliasAnalysis::Location
+LoopVectorizationLegality::getLoadStoreLocation(Instruction *Inst) {
+ if (StoreInst *Store = dyn_cast<StoreInst>(Inst))
+ return AA->getLocation(Store);
+ else if (LoadInst *Load = dyn_cast<LoadInst>(Inst))
+ return AA->getLocation(Load);
+
+ llvm_unreachable("Should be either load or store instruction");
+}
+
+bool
+LoopVectorizationLegality::hasPossibleGlobalWriteReorder(
+ Value *Object,
+ Instruction *Inst,
+ AliasMultiMap& WriteObjects,
+ unsigned MaxByteWidth) {
+
+ AliasAnalysis::Location ThisLoc = getLoadStoreLocation(Inst);
+
+ std::vector<Instruction*>::iterator
+ it = WriteObjects[Object].begin(),
+ end = WriteObjects[Object].end();
+
+ for (; it != end; ++it) {
+ Instruction* I = *it;
+ if (I == Inst)
+ continue;
+
+ AliasAnalysis::Location ThatLoc = getLoadStoreLocation(I);
+ if (AA->alias(ThisLoc.getWithNewSize(MaxByteWidth),
+ ThatLoc.getWithNewSize(MaxByteWidth)))
+ return true;
+ }
+ return false;
+}
+
bool LoopVectorizationLegality::canVectorizeMemory() {
+
typedef SmallVector<Value*, 16> ValueVector;
typedef SmallPtrSet<Value*, 16> ValueSet;
// Holds the Load and Store *instructions*.
PtrRtCheck.Pointers.clear();
PtrRtCheck.Need = false;
+ const bool IsAnnotatedParallel = TheLoop->isAnnotatedParallel();
+
// For each block.
for (Loop::block_iterator bb = TheLoop->block_begin(),
be = TheLoop->block_end(); bb != be; ++bb) {
if (it->mayReadFromMemory()) {
LoadInst *Ld = dyn_cast<LoadInst>(it);
if (!Ld) return false;
- if (!Ld->isSimple()) {
+ if (!Ld->isSimple() && !IsAnnotatedParallel) {
DEBUG(dbgs() << "LV: Found a non-simple load.\n");
return false;
}
if (it->mayWriteToMemory()) {
StoreInst *St = dyn_cast<StoreInst>(it);
if (!St) return false;
- if (!St->isSimple()) {
+ if (!St->isSimple() && !IsAnnotatedParallel) {
DEBUG(dbgs() << "LV: Found a non-simple store.\n");
return false;
}
return true;
}
- // Holds the read and read-write *pointers* that we find.
- ValueVector Reads;
- ValueVector ReadWrites;
+ // Holds the read and read-write *pointers* that we find. These maps hold
+ // unique values for pointers (so no need for multi-map).
+ AliasMap Reads;
+ AliasMap ReadWrites;
// Holds the analyzed pointers. We don't want to call GetUnderlyingObjects
// multiple times on the same object. If the ptr is accessed twice, once
// If we did *not* see this pointer before, insert it to
// the read-write list. At this phase it is only a 'write' list.
if (Seen.insert(Ptr))
- ReadWrites.push_back(Ptr);
+ ReadWrites.insert(std::make_pair(Ptr, ST));
+ }
+
+ 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) {
// If the address of i is unknown (for example A[B[i]]) then we may
// read a few words, modify, and write a few words, and some of the
// words may be written to the same address.
- if (Seen.insert(Ptr) || !isConsecutivePtr(Ptr))
- Reads.push_back(Ptr);
+ if (Seen.insert(Ptr) || 0 == isConsecutivePtr(Ptr))
+ Reads.insert(std::make_pair(Ptr, LD));
}
// If we write (or read-write) to a single destination and there are no
return true;
}
+ unsigned NumReadPtrs = 0;
+ unsigned NumWritePtrs = 0;
+
// Find pointers with computable bounds. We are going to use this information
// to place a runtime bound check.
bool CanDoRT = true;
- for (I = ReadWrites.begin(), IE = ReadWrites.end(); I != IE; ++I)
- if (hasComputableBounds(*I)) {
- PtrRtCheck.insert(SE, TheLoop, *I);
- DEBUG(dbgs() << "LV: Found a runtime check ptr:" << **I <<"\n");
+ AliasMap::iterator MI, ME;
+ for (MI = ReadWrites.begin(), ME = ReadWrites.end(); MI != ME; ++MI) {
+ Value *V = (*MI).first;
+ if (hasComputableBounds(V)) {
+ PtrRtCheck.insert(SE, TheLoop, V, true);
+ NumWritePtrs++;
+ DEBUG(dbgs() << "LV: Found a runtime check ptr:" << *V <<"\n");
} else {
CanDoRT = false;
break;
}
- for (I = Reads.begin(), IE = Reads.end(); I != IE; ++I)
- if (hasComputableBounds(*I)) {
- PtrRtCheck.insert(SE, TheLoop, *I);
- DEBUG(dbgs() << "LV: Found a runtime check ptr:" << **I <<"\n");
+ }
+ for (MI = Reads.begin(), ME = Reads.end(); MI != ME; ++MI) {
+ Value *V = (*MI).first;
+ if (hasComputableBounds(V)) {
+ PtrRtCheck.insert(SE, TheLoop, V, false);
+ NumReadPtrs++;
+ DEBUG(dbgs() << "LV: Found a runtime check ptr:" << *V <<"\n");
} else {
CanDoRT = false;
break;
}
+ }
// Check that we did not collect too many pointers or found a
// unsizeable pointer.
- if (!CanDoRT || PtrRtCheck.Pointers.size() > RuntimeMemoryCheckThreshold) {
+ unsigned NumComparisons = (NumWritePtrs * (NumReadPtrs + NumWritePtrs - 1));
+ DEBUG(dbgs() << "LV: We need to compare " << NumComparisons << " ptrs.\n");
+ if (!CanDoRT || NumComparisons > RuntimeMemoryCheckThreshold) {
PtrRtCheck.reset();
CanDoRT = false;
}
bool NeedRTCheck = false;
+ // Biggest vectorized access possible, vector width * unroll factor.
+ // TODO: We're being very pessimistic here, find a way to know the
+ // real access width before getting here.
+ unsigned MaxByteWidth = (TTI->getRegisterBitWidth(true) / 8) *
+ TTI->getMaximumUnrollFactor();
// Now that the pointers are in two lists (Reads and ReadWrites), we
// can check that there are no conflicts between each of the writes and
// between the writes to the reads.
- ValueSet WriteObjects;
+ // Note that WriteObjects duplicates the stores (indexed now by underlying
+ // objects) to avoid pointing to elements inside ReadWrites.
+ // TODO: Maybe create a new type where they can interact without duplication.
+ AliasMultiMap WriteObjects;
ValueVector TempObjects;
// Check that the read-writes do not conflict with other read-write
// pointers.
- for (I = ReadWrites.begin(), IE = ReadWrites.end(); I != IE; ++I) {
- GetUnderlyingObjects(*I, TempObjects, DL);
- for (ValueVector::iterator it=TempObjects.begin(), e=TempObjects.end();
- it != e; ++it) {
- if (!isIdentifiedObject(*it)) {
- DEBUG(dbgs() << "LV: Found an unidentified write ptr:"<< **it <<"\n");
+ bool AllWritesIdentified = true;
+ for (MI = ReadWrites.begin(), ME = ReadWrites.end(); MI != ME; ++MI) {
+ Value *Val = (*MI).first;
+ Instruction *Inst = (*MI).second;
+
+ GetUnderlyingObjects(Val, TempObjects, DL);
+ for (ValueVector::iterator UI=TempObjects.begin(), UE=TempObjects.end();
+ UI != UE; ++UI) {
+ if (!isIdentifiedObject(*UI)) {
+ DEBUG(dbgs() << "LV: Found an unidentified write ptr:"<< **UI <<"\n");
NeedRTCheck = true;
+ AllWritesIdentified = false;
}
- if (!WriteObjects.insert(*it)) {
+
+ // Never seen it before, can't alias.
+ if (WriteObjects[*UI].empty()) {
+ DEBUG(dbgs() << "LV: Adding Underlying value:" << **UI <<"\n");
+ WriteObjects[*UI].push_back(Inst);
+ continue;
+ }
+ // Direct alias found.
+ if (!AA || dyn_cast<GlobalValue>(*UI) == NULL) {
DEBUG(dbgs() << "LV: Found a possible write-write reorder:"
- << **it <<"\n");
+ << **UI <<"\n");
return false;
}
+ DEBUG(dbgs() << "LV: Found a conflicting global value:"
+ << **UI <<"\n");
+ DEBUG(dbgs() << "LV: While examining store:" << *Inst <<"\n");
+ DEBUG(dbgs() << "LV: On value:" << *Val <<"\n");
+
+ // If global alias, make sure they do alias.
+ if (hasPossibleGlobalWriteReorder(*UI,
+ Inst,
+ WriteObjects,
+ MaxByteWidth)) {
+ DEBUG(dbgs() << "LV: Found a possible write-write reorder:" << **UI
+ << "\n");
+ return false;
+ }
+
+ // Didn't alias, insert into map for further reference.
+ WriteObjects[*UI].push_back(Inst);
}
TempObjects.clear();
}
/// Check that the reads don't conflict with the read-writes.
- for (I = Reads.begin(), IE = Reads.end(); I != IE; ++I) {
- GetUnderlyingObjects(*I, TempObjects, DL);
- for (ValueVector::iterator it=TempObjects.begin(), e=TempObjects.end();
- it != e; ++it) {
- if (!isIdentifiedObject(*it)) {
- DEBUG(dbgs() << "LV: Found an unidentified read ptr:"<< **it <<"\n");
+ for (MI = Reads.begin(), ME = Reads.end(); MI != ME; ++MI) {
+ Value *Val = (*MI).first;
+ GetUnderlyingObjects(Val, TempObjects, DL);
+ for (ValueVector::iterator UI=TempObjects.begin(), UE=TempObjects.end();
+ UI != UE; ++UI) {
+ // If all of the writes are identified then we don't care if the read
+ // pointer is identified or not.
+ if (!AllWritesIdentified && !isIdentifiedObject(*UI)) {
+ DEBUG(dbgs() << "LV: Found an unidentified read ptr:"<< **UI <<"\n");
NeedRTCheck = true;
}
- if (WriteObjects.count(*it)) {
- DEBUG(dbgs() << "LV: Found a possible read/write reorder:"
- << **it <<"\n");
+
+ // Never seen it before, can't alias.
+ if (WriteObjects[*UI].empty())
+ continue;
+ // Direct alias found.
+ if (!AA || dyn_cast<GlobalValue>(*UI) == NULL) {
+ DEBUG(dbgs() << "LV: Found a possible write-write reorder:"
+ << **UI <<"\n");
+ return false;
+ }
+ DEBUG(dbgs() << "LV: Found a global value: "
+ << **UI <<"\n");
+ Instruction *Inst = (*MI).second;
+ DEBUG(dbgs() << "LV: While examining load:" << *Inst <<"\n");
+ DEBUG(dbgs() << "LV: On value:" << *Val <<"\n");
+
+ // If global alias, make sure they do alias.
+ if (hasPossibleGlobalWriteReorder(*UI,
+ Inst,
+ WriteObjects,
+ MaxByteWidth)) {
+ DEBUG(dbgs() << "LV: Found a possible read-write reorder:" << **UI
+ << "\n");
return false;
}
}
return true;
}
+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)
// 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();
- // Iter is our iterator. We start with the PHI node and scan for all of the
- // users of this instruction. All users must be instructions which can be
- // used as reduction variables (such as ADD). We may have a single
- // out-of-block user. They cycle must end with the original PHI.
- // Also, we can't have multiple block-local users.
- Instruction *Iter = Phi;
- while (true) {
- // If the instruction has no users then this is a broken
- // chain and can't be a reduction variable.
- if (Iter->use_empty())
+ // 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;
- // Any reduction instr must be of one of the allowed kinds.
- if (!isReductionInstr(Iter, Kind))
+ bool IsAPhi = isa<PHINode>(Cur);
+
+ // A header PHI use other than the original PHI.
+ if (Cur != Phi && IsAPhi && Cur->getParent() == Phi->getParent())
return false;
- // Did we find a user inside this block ?
- bool FoundInBlockUser = false;
- // Did we reach the initial PHI node ?
- bool FoundStartPHI = false;
-
- // For each of the *users* of iter.
- for (Value::use_iterator it = Iter->use_begin(), e = Iter->use_end();
- it != e; ++it) {
- Instruction *U = cast<Instruction>(*it);
- // We already know that the PHI is a user.
- if (U == Phi) {
- FoundStartPHI = true;
- continue;
- }
+ // 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 = U->getParent();
+ BasicBlock *Parent = Usr->getParent();
if (!TheLoop->contains(Parent)) {
// Exit if you find multiple outside users.
if (ExitInstruction != 0)
return false;
- ExitInstruction = Iter;
- }
-
- // We allow in-loop PHINodes which are not the original reduction PHI
- // node. If this PHI is the only user of Iter (happens in IF w/ no ELSE
- // structure) then don't skip this PHI.
- if (isa<PHINode>(U) && U->getParent() != TheLoop->getHeader() &&
- TheLoop->contains(U) && Iter->getNumUses() > 1)
+ ExitInstruction = Cur;
continue;
+ }
- // We can't have multiple inside users.
- if (FoundInBlockUser)
- return false;
- FoundInBlockUser = true;
- Iter = U;
+ // Process instructions only once (termination).
+ if (VisitedInsts.insert(Usr)) {
+ if (isa<PHINode>(Usr))
+ PHIs.push_back(Usr);
+ else
+ NonPHIs.push_back(Usr);
+ }
+ // Remember that we completed the cycle.
+ if (Usr == Phi)
+ FoundStartPHI = true;
}
+ Worklist.append(PHIs.begin(), PHIs.end());
+ Worklist.append(NonPHIs.begin(), NonPHIs.end());
+ }
- // We found a reduction var if we have reached the original
- // phi node and we only have a single instruction with out-of-loop
- // users.
- if (FoundStartPHI && ExitInstruction) {
- // This instruction is allowed to have out-of-loop users.
- AllowedExit.insert(ExitInstruction);
+ // 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;
- // Save the description of this reduction variable.
- ReductionDescriptor RD(RdxStart, ExitInstruction, Kind);
- Reductions[Phi] = RD;
- return true;
- }
+ if (!FoundStartPHI || !FoundReduxOp || !ExitInstruction)
+ return false;
- // If we've reached the start PHI but did not find an outside user then
- // this is dead code. Abort.
- if (FoundStartPHI)
- 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);
}
-bool
+LoopVectorizationLegality::ReductionInstDesc
LoopVectorizationLegality::isReductionInstr(Instruction *I,
- ReductionKind Kind) {
+ ReductionKind Kind,
+ ReductionInstDesc &Prev) {
+ bool FP = I->getType()->isFloatingPointTy();
+ bool FastMath = (FP && I->isCommutative() && I->isAssociative());
switch (I->getOpcode()) {
default:
- return false;
+ return ReductionInstDesc(false, I);
case Instruction::PHI:
- // possibly.
- return true;
- case Instruction::Add:
+ if (FP && (Kind != RK_FloatMult && Kind != RK_FloatAdd &&
+ Kind != RK_FloatMinMax))
+ return ReductionInstDesc(false, I);
+ return ReductionInstDesc(I, Prev.MinMaxKind);
case Instruction::Sub:
- return Kind == IntegerAdd;
+ case Instruction::Add:
+ return ReductionInstDesc(Kind == RK_IntegerAdd, I);
case Instruction::Mul:
- return Kind == IntegerMult;
+ return ReductionInstDesc(Kind == RK_IntegerMult, I);
case Instruction::And:
- return Kind == IntegerAnd;
+ return ReductionInstDesc(Kind == RK_IntegerAnd, I);
case Instruction::Or:
- return Kind == IntegerOr;
+ return ReductionInstDesc(Kind == RK_IntegerOr, I);
case Instruction::Xor:
- return Kind == IntegerXor;
+ 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);
}
}
Type *PhiTy = Phi->getType();
// We only handle integer and pointer inductions variables.
if (!PhiTy->isIntegerTy() && !PhiTy->isPointerTy())
- return NoInduction;
+ return IK_NoInduction;
- // Check that the PHI is consecutive and starts at zero.
+ // 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 NoInduction;
+ 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 IntInduction;
+ return IK_IntInduction;
if (Step->isAllOnesValue())
- return ReverseIntInduction;
- return NoInduction;
+ 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 NoInduction;
+ 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 PtrInduction;
+ return IK_PtrInduction;
+ else if (C->getValue()->equalsInt(0 - Size))
+ return IK_ReversePtrInduction;
- return NoInduction;
+ return IK_NoInduction;
}
bool LoopVectorizationLegality::isInductionVariable(const Value *V) {
bool LoopVectorizationLegality::blockCanBePredicated(BasicBlock *BB) {
for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
- // We don't predicate loads/stores at the moment.
- if (it->mayReadFromMemory() || it->mayWriteToMemory() || it->mayThrow())
+ // We might be able to hoist the load.
+ if (it->mayReadFromMemory() && !LoadSpeculation.isHoistableLoad(it))
+ return false;
+
+ // We predicate stores at the moment.
+ if (it->mayWriteToMemory() || it->mayThrow())
return false;
// The instructions below can trap.
}
}
+ // Check that we can actually speculate the hoistable loads.
+ if (!LoadSpeculation.canHoistAllLoads())
+ return false;
+
return true;
}
return AR->isAffine();
}
-unsigned
+LoopVectorizationCostModel::VectorizationFactor
LoopVectorizationCostModel::selectVectorizationFactor(bool OptForSize,
- unsigned UserVF) {
+ 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 1;
+ 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 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 we are unable to calculate the trip count then don't try to vectorize.
if (TC < 2) {
DEBUG(dbgs() << "LV: Aborting. A tail loop is required in Os.\n");
- return 1;
+ return Factor;
}
// Find the maximum SIMD width that can fit within the trip count.
// zero then we require a tail.
if (VF < 2) {
DEBUG(dbgs() << "LV: Aborting. A tail loop is required in Os.\n");
- return 1;
+ return Factor;
}
}
assert(isPowerOf2_32(UserVF) && "VF needs to be a power of two");
DEBUG(dbgs() << "LV: Using user VF "<<UserVF<<".\n");
- return UserVF;
- }
-
- if (!VTTI) {
- DEBUG(dbgs() << "LV: No vector target information. Not vectorizing. \n");
- return 1;
+ Factor.Width = UserVF;
+ return Factor;
}
float Cost = expectedCost(1);
}
DEBUG(dbgs() << "LV: Selecting VF = : "<< Width << ".\n");
- return Width;
+ 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;
+
+ // 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;
+
+ if (Legal->getReductionVars()->size()) {
+ 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 < 20) {
+ DEBUG(dbgs() << "LV: Unrolling to reduce branch cost. \n");
+ unsigned NewUF = 20/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) {
// 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);
Cost += C;
DEBUG(dbgs() << "LV: Found an estimated cost of "<< C <<" for VF " <<
unsigned
LoopVectorizationCostModel::getInstructionCost(Instruction *I, unsigned VF) {
- assert(VTTI && "Invalid vector target transformation info");
-
// If we know that this instruction will remain uniform, check the cost of
// the scalar version.
if (Legal->isUniformAfterVectorization(I))
// TODO: We need to estimate the cost of intrinsic calls.
switch (I->getOpcode()) {
case Instruction::GetElementPtr:
- // We mark this instruction as zero-cost because scalar GEPs are usually
- // lowered to the intruction addressing mode. At the moment we don't
- // generate vector geps.
+ // 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 VTTI->getCFInstrCost(I->getOpcode());
+ return TTI.getCFInstrCost(I->getOpcode());
}
case Instruction::PHI:
//TODO: IF-converted IFs become selects.
case Instruction::AShr:
case Instruction::And:
case Instruction::Or:
- case Instruction::Xor:
- return VTTI->getArithmeticInstrCost(I->getOpcode(), VectorTy);
+ 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)
+ if (!ScalarCond)
CondTy = VectorType::get(CondTy, VF);
- return VTTI->getCmpSelInstrCost(I->getOpcode(), VectorTy, CondTy);
+ return TTI.getCmpSelInstrCost(I->getOpcode(), VectorTy, CondTy);
}
case Instruction::ICmp:
case Instruction::FCmp: {
Type *ValTy = I->getOperand(0)->getType();
VectorTy = ToVectorTy(ValTy, VF);
- return VTTI->getCmpSelInstrCost(I->getOpcode(), VectorTy);
+ return TTI.getCmpSelInstrCost(I->getOpcode(), VectorTy);
}
- case Instruction::Store: {
- StoreInst *SI = cast<StoreInst>(I);
- Type *ValTy = SI->getValueOperand()->getType();
+ 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 VTTI->getMemoryOpCost(I->getOpcode(), VectorTy,
- SI->getAlignment(),
- SI->getPointerAddressSpace());
-
- // Scalarized stores.
- if (!Legal->isConsecutivePtr(SI->getPointerOperand())) {
+ 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) {
unsigned Cost = 0;
-
// The cost of extracting from the value vector and pointer vector.
- Type *PtrTy = ToVectorTy(I->getOperand(0)->getType(), VF);
+ Type *PtrTy = ToVectorTy(Ptr->getType(), VF);
for (unsigned i = 0; i < VF; ++i) {
- Cost += VTTI->getVectorInstrCost(Instruction::ExtractElement,
- VectorTy, i);
- Cost += VTTI->getVectorInstrCost(Instruction::ExtractElement,
- PtrTy, 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 stores.
- Cost += VF * VTTI->getMemoryOpCost(I->getOpcode(),
- ValTy->getScalarType(),
- SI->getAlignment(),
- SI->getPointerAddressSpace());
+ // The cost of the scalar loads/stores.
+ Cost += VF * TTI.getAddressComputationCost(ValTy->getScalarType());
+ Cost += VF * TTI.getMemoryOpCost(I->getOpcode(), ValTy->getScalarType(),
+ Alignment, AS);
return Cost;
}
- // Wide stores.
- return VTTI->getMemoryOpCost(I->getOpcode(), VectorTy, SI->getAlignment(),
- SI->getPointerAddressSpace());
- }
- case Instruction::Load: {
- LoadInst *LI = cast<LoadInst>(I);
-
- if (VF == 1)
- return VTTI->getMemoryOpCost(I->getOpcode(), VectorTy,
- LI->getAlignment(),
- LI->getPointerAddressSpace());
-
- // Scalarized loads.
- if (!Legal->isConsecutivePtr(LI->getPointerOperand())) {
- unsigned Cost = 0;
- Type *PtrTy = ToVectorTy(I->getOperand(0)->getType(), VF);
-
- // The cost of extracting from the pointer vector.
- for (unsigned i = 0; i < VF; ++i)
- Cost += VTTI->getVectorInstrCost(Instruction::ExtractElement,
- PtrTy, i);
-
- // The cost of inserting data to the result vector.
- for (unsigned i = 0; i < VF; ++i)
- Cost += VTTI->getVectorInstrCost(Instruction::InsertElement,
- VectorTy, i);
-
- // The cost of the scalar stores.
- Cost += VF * VTTI->getMemoryOpCost(I->getOpcode(),
- RetTy->getScalarType(),
- LI->getAlignment(),
- LI->getPointerAddressSpace());
- return Cost;
- }
+ // Wide load/stores.
+ unsigned Cost = TTI.getAddressComputationCost(VectorTy);
+ Cost += TTI.getMemoryOpCost(I->getOpcode(), VectorTy, Alignment, AS);
- // Wide loads.
- return VTTI->getMemoryOpCost(I->getOpcode(), VectorTy, LI->getAlignment(),
- LI->getPointerAddressSpace());
+ if (Reverse)
+ Cost += TTI.getShuffleCost(TargetTransformInfo::SK_Reverse,
+ VectorTy, 0);
+ return Cost;
}
case Instruction::ZExt:
case Instruction::SExt:
// The cost of these is the same as the scalar operation.
if (I->getOpcode() == Instruction::Trunc &&
Legal->isInductionVariable(I->getOperand(0)))
- return VTTI->getCastInstrCost(I->getOpcode(), I->getType(),
- I->getOperand(0)->getType());
+ return TTI.getCastInstrCost(I->getOpcode(), I->getType(),
+ I->getOperand(0)->getType());
Type *SrcVecTy = ToVectorTy(I->getOperand(0)->getType(), VF);
- return VTTI->getCastInstrCost(I->getOpcode(), VectorTy, SrcVecTy);
+ return TTI.getCastInstrCost(I->getOpcode(), VectorTy, SrcVecTy);
}
case Instruction::Call: {
- assert(isTriviallyVectorizableIntrinsic(I));
- IntrinsicInst *II = cast<IntrinsicInst>(I);
- Type *RetTy = ToVectorTy(II->getType(), VF);
+ 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 = II->getNumArgOperands(); i != ie; ++i)
- Tys.push_back(ToVectorTy(II->getArgOperand(i)->getType(), VF));
- return VTTI->getIntrinsicInstrCost(II->getIntrinsicID(), RetTy, 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
// elements, times the vector width.
unsigned Cost = 0;
- if (RetTy->isVoidTy() || VF != 1) {
- unsigned InsCost = VTTI->getVectorInstrCost(Instruction::InsertElement,
- VectorTy);
- unsigned ExtCost = VTTI->getVectorInstrCost(Instruction::ExtractElement,
- VectorTy);
+ 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.
// The cost of executing VF copies of the scalar instruction. This opcode
// is unknown. Assume that it is the same as 'mul'.
- Cost += VF * VTTI->getArithmeticInstrCost(Instruction::Mul, VectorTy);
+ Cost += VF * TTI.getArithmeticInstrCost(Instruction::Mul, VectorTy);
return Cost;
}
}// end of switch.
static const char lv_name[] = "Loop Vectorization";
INITIALIZE_PASS_BEGIN(LoopVectorize, LV_NAME, lv_name, false, false)
INITIALIZE_AG_DEPENDENCY(AliasAnalysis)
+INITIALIZE_AG_DEPENDENCY(TargetTransformInfo)
INITIALIZE_PASS_DEPENDENCY(ScalarEvolution)
INITIALIZE_PASS_DEPENDENCY(LoopSimplify)
INITIALIZE_PASS_END(LoopVectorize, LV_NAME, lv_name, false, false)
}
}
+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;
+}
projects / oota-llvm.git / blobdiff