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llvm-mirror/lib/Transforms/Vectorize/LoopVectorize.cpp
Matthew Simpson 18b4a9537b [LV] Avoid creating empty reduction entries (NFC) 
This patch prevents us from unintentionally creating entries in the reductions
map for PHIs that are not actually reductions. This is currently not an issue
since we bail out if we encounter PHIs other than inductions or reductions.
However the behavior could become problematic as we add support for additional
recurrence types.

llvm-svn: 256930
2016-01-06 12:50:29 +00:00

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//===- LoopVectorize.cpp - A Loop Vectorizer ------------------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
//
// This is the LLVM loop vectorizer. This pass modifies 'vectorizable' loops
// and generates target-independent LLVM-IR.
// The vectorizer uses the TargetTransformInfo analysis to estimate the costs
// of instructions in order to estimate the profitability of vectorization.
//
// The loop vectorizer combines consecutive loop iterations into a single
// 'wide' iteration. After this transformation the index is incremented
// by the SIMD vector width, and not by one.
//
// This pass has three parts:
// 1. The main loop pass that drives the different parts.
// 2. LoopVectorizationLegality - A unit that checks for the legality
// of the vectorization.
// 3. InnerLoopVectorizer - A unit that performs the actual
// widening of instructions.
// 4. LoopVectorizationCostModel - A unit that checks for the profitability
// of vectorization. It decides on the optimal vector width, which
// can be one, if vectorization is not profitable.
//
//===----------------------------------------------------------------------===//
//
// The reduction-variable vectorization is based on the paper:
// D. Nuzman and R. Henderson. Multi-platform Auto-vectorization.
//
// Variable uniformity checks are inspired by:
// Karrenberg, R. and Hack, S. Whole Function Vectorization.
//
// The interleaved access vectorization is based on the paper:
// Dorit Nuzman, Ira Rosen and Ayal Zaks. Auto-Vectorization of Interleaved
// Data for SIMD
//
// 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.
//
//===----------------------------------------------------------------------===//
#include "llvm/Transforms/Vectorize.h"
#include "llvm/ADT/DenseMap.h"
#include "llvm/ADT/Hashing.h"
#include "llvm/ADT/MapVector.h"
#include "llvm/ADT/SetVector.h"
#include "llvm/ADT/SmallPtrSet.h"
#include "llvm/ADT/SmallSet.h"
#include "llvm/ADT/SmallVector.h"
#include "llvm/ADT/Statistic.h"
#include "llvm/ADT/StringExtras.h"
#include "llvm/Analysis/AliasAnalysis.h"
#include "llvm/Analysis/BasicAliasAnalysis.h"
#include "llvm/Analysis/AliasSetTracker.h"
#include "llvm/Analysis/AssumptionCache.h"
#include "llvm/Analysis/BlockFrequencyInfo.h"
#include "llvm/Analysis/CodeMetrics.h"
#include "llvm/Analysis/DemandedBits.h"
#include "llvm/Analysis/GlobalsModRef.h"
#include "llvm/Analysis/LoopAccessAnalysis.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/IR/Constants.h"
#include "llvm/IR/DataLayout.h"
#include "llvm/IR/DebugInfo.h"
#include "llvm/IR/DerivedTypes.h"
#include "llvm/IR/DiagnosticInfo.h"
#include "llvm/IR/Dominators.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/PatternMatch.h"
#include "llvm/IR/Type.h"
#include "llvm/IR/Value.h"
#include "llvm/IR/ValueHandle.h"
#include "llvm/IR/Verifier.h"
#include "llvm/Pass.h"
#include "llvm/Support/BranchProbability.h"
#include "llvm/Support/CommandLine.h"
#include "llvm/Support/Debug.h"
#include "llvm/Support/raw_ostream.h"
#include "llvm/Transforms/Scalar.h"
#include "llvm/Transforms/Utils/BasicBlockUtils.h"
#include "llvm/Transforms/Utils/Local.h"
#include "llvm/Analysis/VectorUtils.h"
#include "llvm/Transforms/Utils/LoopUtils.h"
#include <algorithm>
#include <functional>
#include <map>
#include <tuple>
using namespace llvm;
using namespace llvm::PatternMatch;
#define LV_NAME "loop-vectorize"
#define DEBUG_TYPE LV_NAME
STATISTIC(LoopsVectorized, "Number of loops vectorized");
STATISTIC(LoopsAnalyzed, "Number of loops analyzed for vectorization");
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."));
static cl::opt<bool> MaximizeBandwidth(
"vectorizer-maximize-bandwidth", cl::init(false), cl::Hidden,
cl::desc("Maximize bandwidth when selecting vectorization factor which "
"will be determined by the smallest type in loop."));
/// This enables versioning on the strides of symbolically striding memory
/// accesses in code like the following.
/// for (i = 0; i < N; ++i)
/// A[i * Stride1] += B[i * Stride2] ...
///
/// Will be roughly translated to
/// if (Stride1 == 1 && Stride2 == 1) {
/// for (i = 0; i < N; i+=4)
/// A[i:i+3] += ...
/// } else
/// ...
static cl::opt<bool> EnableMemAccessVersioning(
"enable-mem-access-versioning", cl::init(true), cl::Hidden,
cl::desc("Enable symbolic stride memory access versioning"));
static cl::opt<bool> EnableInterleavedMemAccesses(
"enable-interleaved-mem-accesses", cl::init(false), cl::Hidden,
cl::desc("Enable vectorization on interleaved memory accesses in a loop"));
/// Maximum factor for an interleaved memory access.
static cl::opt<unsigned> MaxInterleaveGroupFactor(
"max-interleave-group-factor", cl::Hidden,
cl::desc("Maximum factor for an interleaved access group (default = 8)"),
cl::init(8));
/// We don't interleave loops with a known constant trip count below this
/// number.
static const unsigned TinyTripCountInterleaveThreshold = 128;
static cl::opt<unsigned> ForceTargetNumScalarRegs(
"force-target-num-scalar-regs", cl::init(0), cl::Hidden,
cl::desc("A flag that overrides the target's number of scalar registers."));
static cl::opt<unsigned> ForceTargetNumVectorRegs(
"force-target-num-vector-regs", cl::init(0), cl::Hidden,
cl::desc("A flag that overrides the target's number of vector registers."));
/// Maximum vectorization interleave count.
static const unsigned MaxInterleaveFactor = 16;
static cl::opt<unsigned> ForceTargetMaxScalarInterleaveFactor(
"force-target-max-scalar-interleave", cl::init(0), cl::Hidden,
cl::desc("A flag that overrides the target's max interleave factor for "
"scalar loops."));
static cl::opt<unsigned> ForceTargetMaxVectorInterleaveFactor(
"force-target-max-vector-interleave", cl::init(0), cl::Hidden,
cl::desc("A flag that overrides the target's max interleave factor for "
"vectorized loops."));
static cl::opt<unsigned> ForceTargetInstructionCost(
"force-target-instruction-cost", cl::init(0), cl::Hidden,
cl::desc("A flag that overrides the target's expected cost for "
"an instruction to a single constant value. Mostly "
"useful for getting consistent testing."));
static cl::opt<unsigned> SmallLoopCost(
"small-loop-cost", cl::init(20), cl::Hidden,
cl::desc(
"The cost of a loop that is considered 'small' by the interleaver."));
static cl::opt<bool> LoopVectorizeWithBlockFrequency(
"loop-vectorize-with-block-frequency", cl::init(false), cl::Hidden,
cl::desc("Enable the use of the block frequency analysis to access PGO "
"heuristics minimizing code growth in cold regions and being more "
"aggressive in hot regions."));
// Runtime interleave loops for load/store throughput.
static cl::opt<bool> EnableLoadStoreRuntimeInterleave(
"enable-loadstore-runtime-interleave", cl::init(true), cl::Hidden,
cl::desc(
"Enable runtime interleaving until load/store ports are saturated"));
/// The number of stores in a loop that are allowed to need predication.
static cl::opt<unsigned> NumberOfStoresToPredicate(
"vectorize-num-stores-pred", cl::init(1), cl::Hidden,
cl::desc("Max number of stores to be predicated behind an if."));
static cl::opt<bool> EnableIndVarRegisterHeur(
"enable-ind-var-reg-heur", cl::init(true), cl::Hidden,
cl::desc("Count the induction variable only once when interleaving"));
static cl::opt<bool> EnableCondStoresVectorization(
"enable-cond-stores-vec", cl::init(false), cl::Hidden,
cl::desc("Enable if predication of stores during vectorization."));
static cl::opt<unsigned> MaxNestedScalarReductionIC(
"max-nested-scalar-reduction-interleave", cl::init(2), cl::Hidden,
cl::desc("The maximum interleave count to use when interleaving a scalar "
"reduction in a nested loop."));
static cl::opt<unsigned> PragmaVectorizeMemoryCheckThreshold(
"pragma-vectorize-memory-check-threshold", cl::init(128), cl::Hidden,
cl::desc("The maximum allowed number of runtime memory checks with a "
"vectorize(enable) pragma."));
static cl::opt<unsigned> VectorizeSCEVCheckThreshold(
"vectorize-scev-check-threshold", cl::init(16), cl::Hidden,
cl::desc("The maximum number of SCEV checks allowed."));
static cl::opt<unsigned> PragmaVectorizeSCEVCheckThreshold(
"pragma-vectorize-scev-check-threshold", cl::init(128), cl::Hidden,
cl::desc("The maximum number of SCEV checks allowed with a "
"vectorize(enable) pragma"));
namespace {
// Forward declarations.
class LoopVectorizeHints;
class LoopVectorizationLegality;
class LoopVectorizationCostModel;
class LoopVectorizationRequirements;
/// \brief This modifies LoopAccessReport to initialize message with
/// loop-vectorizer-specific part.
class VectorizationReport : public LoopAccessReport {
public:
VectorizationReport(Instruction *I = nullptr)
: LoopAccessReport("loop not vectorized: ", I) {}
/// \brief This allows promotion of the loop-access analysis report into the
/// loop-vectorizer report. It modifies the message to add the
/// loop-vectorizer-specific part of the message.
explicit VectorizationReport(const LoopAccessReport &R)
: LoopAccessReport(Twine("loop not vectorized: ") + R.str(),
R.getInstr()) {}
};
/// 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) {
if (Scalar->isVoidTy() || VF == 1)
return Scalar;
return VectorType::get(Scalar, VF);
}
/// A helper function that returns GEP instruction and knows to skip a
/// 'bitcast'. The 'bitcast' may be skipped if the source and the destination
/// pointee types of the 'bitcast' have the same size.
/// For example:
/// bitcast double** %var to i64* - can be skipped
/// bitcast double** %var to i8* - can not
static GetElementPtrInst *getGEPInstruction(Value *Ptr) {
if (isa<GetElementPtrInst>(Ptr))
return cast<GetElementPtrInst>(Ptr);
if (isa<BitCastInst>(Ptr) &&
isa<GetElementPtrInst>(cast<BitCastInst>(Ptr)->getOperand(0))) {
Type *BitcastTy = Ptr->getType();
Type *GEPTy = cast<BitCastInst>(Ptr)->getSrcTy();
if (!isa<PointerType>(BitcastTy) || !isa<PointerType>(GEPTy))
return nullptr;
Type *Pointee1Ty = cast<PointerType>(BitcastTy)->getPointerElementType();
Type *Pointee2Ty = cast<PointerType>(GEPTy)->getPointerElementType();
const DataLayout &DL = cast<BitCastInst>(Ptr)->getModule()->getDataLayout();
if (DL.getTypeSizeInBits(Pointee1Ty) == DL.getTypeSizeInBits(Pointee2Ty))
return cast<GetElementPtrInst>(cast<BitCastInst>(Ptr)->getOperand(0));
}
return nullptr;
}
/// 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, PredicatedScalarEvolution &PSE,
LoopInfo *LI, DominatorTree *DT,
const TargetLibraryInfo *TLI,
const TargetTransformInfo *TTI, unsigned VecWidth,
unsigned UnrollFactor)
: OrigLoop(OrigLoop), PSE(PSE), LI(LI), DT(DT), TLI(TLI), TTI(TTI),
VF(VecWidth), UF(UnrollFactor), Builder(PSE.getSE()->getContext()),
Induction(nullptr), OldInduction(nullptr), WidenMap(UnrollFactor),
TripCount(nullptr), VectorTripCount(nullptr), Legal(nullptr),
AddedSafetyChecks(false) {}
// Perform the actual loop widening (vectorization).
// MinimumBitWidths maps scalar integer values to the smallest bitwidth they
// can be validly truncated to. The cost model has assumed this truncation
// will happen when vectorizing.
void vectorize(LoopVectorizationLegality *L,
MapVector<Instruction*,uint64_t> MinimumBitWidths) {
MinBWs = MinimumBitWidths;
Legal = L;
// Create a new empty loop. Unlink the old loop and connect the new one.
createEmptyLoop();
// 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();
}
// Return true if any runtime check is added.
bool IsSafetyChecksAdded() {
return AddedSafetyChecks;
}
virtual ~InnerLoopVectorizer() {}
protected:
/// A small list of PHINodes.
typedef SmallVector<PHINode*, 4> PhiVector;
/// When we unroll loops we have multiple vector values for each scalar.
/// This data structure holds the unrolled and vectorized values that
/// originated from one scalar instruction.
typedef SmallVector<Value*, 2> VectorParts;
// When we if-convert we need to create edge masks. We have to cache values
// so that we don't end up with exponential recursion/IR.
typedef DenseMap<std::pair<BasicBlock*, BasicBlock*>,
VectorParts> EdgeMaskCache;
/// Create an empty loop, based on the loop ranges of the old loop.
void createEmptyLoop();
/// Create a new induction variable inside L.
PHINode *createInductionVariable(Loop *L, Value *Start, Value *End,
Value *Step, Instruction *DL);
/// Copy and widen the instructions from the old loop.
virtual void vectorizeLoop();
/// \brief The Loop exit block may have single value PHI nodes where the
/// incoming value is 'Undef'. While vectorizing we only handled real values
/// that were defined inside the loop. Here we fix the 'undef case'.
/// See PR14725.
void fixLCSSAPHIs();
/// Shrinks vector element sizes based on information in "MinBWs".
void truncateToMinimalBitwidths();
/// 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(BasicBlock *BB, PhiVector *PV);
/// Vectorize a single PHINode in a block. This method handles the induction
/// variable canonicalization. It supports both VF = 1 for unrolled loops and
/// arbitrary length vectors.
void widenPHIInstruction(Instruction *PN, VectorParts &Entry,
unsigned UF, unsigned VF, PhiVector *PV);
/// Insert the new loop to the loop hierarchy and pass manager
/// and update the analysis passes.
void updateAnalysis();
/// This instruction is un-vectorizable. Implement it as a sequence
/// of scalars. If \p IfPredicateStore is true we need to 'hide' each
/// scalarized instruction behind an if block predicated on the control
/// dependence of the instruction.
virtual void scalarizeInstruction(Instruction *Instr,
bool IfPredicateStore=false);
/// Vectorize Load and Store instructions,
virtual void vectorizeMemoryInstruction(Instruction *Instr);
/// Create a broadcast instruction. This method generates a broadcast
/// instruction (shuffle) for loop invariant values and for the induction
/// value. If this is the induction variable then we extend it to N, N+1, ...
/// this is needed because each iteration in the loop corresponds to a SIMD
/// element.
virtual Value *getBroadcastInstrs(Value *V);
/// This function adds (StartIdx, StartIdx + Step, StartIdx + 2*Step, ...)
/// to each vector element of Val. The sequence starts at StartIndex.
virtual Value *getStepVector(Value *Val, int StartIdx, Value *Step);
/// 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);
/// Try to vectorize the interleaved access group that \p Instr belongs to.
void vectorizeInterleaveGroup(Instruction *Instr);
/// Generate a shuffle sequence that will reverse the vector Vec.
virtual Value *reverseVector(Value *Vec);
/// Returns (and creates if needed) the original loop trip count.
Value *getOrCreateTripCount(Loop *NewLoop);
/// Returns (and creates if needed) the trip count of the widened loop.
Value *getOrCreateVectorTripCount(Loop *NewLoop);
/// Emit a bypass check to see if the trip count would overflow, or we
/// wouldn't have enough iterations to execute one vector loop.
void emitMinimumIterationCountCheck(Loop *L, BasicBlock *Bypass);
/// Emit a bypass check to see if the vector trip count is nonzero.
void emitVectorLoopEnteredCheck(Loop *L, BasicBlock *Bypass);
/// Emit a bypass check to see if all of the SCEV assumptions we've
/// had to make are correct.
void emitSCEVChecks(Loop *L, BasicBlock *Bypass);
/// Emit bypass checks to check any memory assumptions we may have made.
void emitMemRuntimeChecks(Loop *L, BasicBlock *Bypass);
/// 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;
/// A wrapper around ScalarEvolution used to add runtime SCEV checks. Applies
/// dynamic knowledge to simplify SCEV expressions and converts them to a
/// more usable form.
PredicatedScalarEvolution &PSE;
/// Loop Info.
LoopInfo *LI;
/// Dominator Tree.
DominatorTree *DT;
/// Alias Analysis.
AliasAnalysis *AA;
/// Target Library Info.
const TargetLibraryInfo *TLI;
/// Target Transform Info.
const TargetTransformInfo *TTI;
/// The vectorization SIMD factor to use. Each vector will have this many
/// vector elements.
unsigned VF;
protected:
/// The vectorization unroll factor to use. Each scalar is vectorized to this
/// many different vector instructions.
unsigned UF;
/// The builder that we use
IRBuilder<> Builder;
// --- Vectorization state ---
/// The vector-loop preheader.
BasicBlock *LoopVectorPreHeader;
/// The scalar-loop preheader.
BasicBlock *LoopScalarPreHeader;
/// Middle Block between the vector and the scalar.
BasicBlock *LoopMiddleBlock;
///The ExitBlock of the scalar loop.
BasicBlock *LoopExitBlock;
///The vector loop body.
SmallVector<BasicBlock *, 4> 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;
/// Maps scalars to widened vectors.
ValueMap WidenMap;
/// Store instructions that should be predicated, as a pair
/// <StoreInst, Predicate>
SmallVector<std::pair<StoreInst*,Value*>, 4> PredicatedStores;
EdgeMaskCache MaskCache;
/// Trip count of the original loop.
Value *TripCount;
/// Trip count of the widened loop (TripCount - TripCount % (VF*UF))
Value *VectorTripCount;
/// Map of scalar integer values to the smallest bitwidth they can be legally
/// represented as. The vector equivalents of these values should be truncated
/// to this type.
MapVector<Instruction*,uint64_t> MinBWs;
LoopVectorizationLegality *Legal;
// Record whether runtime check is added.
bool AddedSafetyChecks;
};
class InnerLoopUnroller : public InnerLoopVectorizer {
public:
InnerLoopUnroller(Loop *OrigLoop, PredicatedScalarEvolution &PSE,
LoopInfo *LI, DominatorTree *DT,
const TargetLibraryInfo *TLI,
const TargetTransformInfo *TTI, unsigned UnrollFactor)
: InnerLoopVectorizer(OrigLoop, PSE, LI, DT, TLI, TTI, 1, UnrollFactor) {}
private:
void scalarizeInstruction(Instruction *Instr,
bool IfPredicateStore = false) override;
void vectorizeMemoryInstruction(Instruction *Instr) override;
Value *getBroadcastInstrs(Value *V) override;
Value *getStepVector(Value *Val, int StartIdx, Value *Step) override;
Value *reverseVector(Value *Vec) override;
};
/// \brief Look for a meaningful debug location on the instruction or it's
/// operands.
static Instruction *getDebugLocFromInstOrOperands(Instruction *I) {
if (!I)
return I;
DebugLoc Empty;
if (I->getDebugLoc() != Empty)
return I;
for (User::op_iterator OI = I->op_begin(), OE = I->op_end(); OI != OE; ++OI) {
if (Instruction *OpInst = dyn_cast<Instruction>(*OI))
if (OpInst->getDebugLoc() != Empty)
return OpInst;
}
return I;
}
/// \brief Set the debug location in the builder using the debug location in the
/// instruction.
static void setDebugLocFromInst(IRBuilder<> &B, const Value *Ptr) {
if (const Instruction *Inst = dyn_cast_or_null<Instruction>(Ptr))
B.SetCurrentDebugLocation(Inst->getDebugLoc());
else
B.SetCurrentDebugLocation(DebugLoc());
}
#ifndef NDEBUG
/// \return string containing a file name and a line # for the given loop.
static std::string getDebugLocString(const Loop *L) {
std::string Result;
if (L) {
raw_string_ostream OS(Result);
if (const DebugLoc LoopDbgLoc = L->getStartLoc())
LoopDbgLoc.print(OS);
else
// Just print the module name.
OS << L->getHeader()->getParent()->getParent()->getModuleIdentifier();
OS.flush();
}
return Result;
}
#endif
/// \brief Propagate known metadata from one instruction to another.
static void propagateMetadata(Instruction *To, const Instruction *From) {
SmallVector<std::pair<unsigned, MDNode *>, 4> Metadata;
From->getAllMetadataOtherThanDebugLoc(Metadata);
for (auto M : Metadata) {
unsigned Kind = M.first;
// These are safe to transfer (this is safe for TBAA, even when we
// if-convert, because should that metadata have had a control dependency
// on the condition, and thus actually aliased with some other
// non-speculated memory access when the condition was false, this would be
// caught by the runtime overlap checks).
if (Kind != LLVMContext::MD_tbaa &&
Kind != LLVMContext::MD_alias_scope &&
Kind != LLVMContext::MD_noalias &&
Kind != LLVMContext::MD_fpmath &&
Kind != LLVMContext::MD_nontemporal)
continue;
To->setMetadata(Kind, M.second);
}
}
/// \brief Propagate known metadata from one instruction to a vector of others.
static void propagateMetadata(SmallVectorImpl<Value *> &To,
const Instruction *From) {
for (Value *V : To)
if (Instruction *I = dyn_cast<Instruction>(V))
propagateMetadata(I, From);
}
/// \brief The group of interleaved loads/stores sharing the same stride and
/// close to each other.
///
/// Each member in this group has an index starting from 0, and the largest
/// index should be less than interleaved factor, which is equal to the absolute
/// value of the access's stride.
///
/// E.g. An interleaved load group of factor 4:
/// for (unsigned i = 0; i < 1024; i+=4) {
/// a = A[i]; // Member of index 0
/// b = A[i+1]; // Member of index 1
/// d = A[i+3]; // Member of index 3
/// ...
/// }
///
/// An interleaved store group of factor 4:
/// for (unsigned i = 0; i < 1024; i+=4) {
/// ...
/// A[i] = a; // Member of index 0
/// A[i+1] = b; // Member of index 1
/// A[i+2] = c; // Member of index 2
/// A[i+3] = d; // Member of index 3
/// }
///
/// Note: the interleaved load group could have gaps (missing members), but
/// the interleaved store group doesn't allow gaps.
class InterleaveGroup {
public:
InterleaveGroup(Instruction *Instr, int Stride, unsigned Align)
: Align(Align), SmallestKey(0), LargestKey(0), InsertPos(Instr) {
assert(Align && "The alignment should be non-zero");
Factor = std::abs(Stride);
assert(Factor > 1 && "Invalid interleave factor");
Reverse = Stride < 0;
Members[0] = Instr;
}
bool isReverse() const { return Reverse; }
unsigned getFactor() const { return Factor; }
unsigned getAlignment() const { return Align; }
unsigned getNumMembers() const { return Members.size(); }
/// \brief Try to insert a new member \p Instr with index \p Index and
/// alignment \p NewAlign. The index is related to the leader and it could be
/// negative if it is the new leader.
///
/// \returns false if the instruction doesn't belong to the group.
bool insertMember(Instruction *Instr, int Index, unsigned NewAlign) {
assert(NewAlign && "The new member's alignment should be non-zero");
int Key = Index + SmallestKey;
// Skip if there is already a member with the same index.
if (Members.count(Key))
return false;
if (Key > LargestKey) {
// The largest index is always less than the interleave factor.
if (Index >= static_cast<int>(Factor))
return false;
LargestKey = Key;
} else if (Key < SmallestKey) {
// The largest index is always less than the interleave factor.
if (LargestKey - Key >= static_cast<int>(Factor))
return false;
SmallestKey = Key;
}
// It's always safe to select the minimum alignment.
Align = std::min(Align, NewAlign);
Members[Key] = Instr;
return true;
}
/// \brief Get the member with the given index \p Index
///
/// \returns nullptr if contains no such member.
Instruction *getMember(unsigned Index) const {
int Key = SmallestKey + Index;
if (!Members.count(Key))
return nullptr;
return Members.find(Key)->second;
}
/// \brief Get the index for the given member. Unlike the key in the member
/// map, the index starts from 0.
unsigned getIndex(Instruction *Instr) const {
for (auto I : Members)
if (I.second == Instr)
return I.first - SmallestKey;
llvm_unreachable("InterleaveGroup contains no such member");
}
Instruction *getInsertPos() const { return InsertPos; }
void setInsertPos(Instruction *Inst) { InsertPos = Inst; }
private:
unsigned Factor; // Interleave Factor.
bool Reverse;
unsigned Align;
DenseMap<int, Instruction *> Members;
int SmallestKey;
int LargestKey;
// To avoid breaking dependences, vectorized instructions of an interleave
// group should be inserted at either the first load or the last store in
// program order.
//
// E.g. %even = load i32 // Insert Position
// %add = add i32 %even // Use of %even
// %odd = load i32
//
// store i32 %even
// %odd = add i32 // Def of %odd
// store i32 %odd // Insert Position
Instruction *InsertPos;
};
/// \brief Drive the analysis of interleaved memory accesses in the loop.
///
/// Use this class to analyze interleaved accesses only when we can vectorize
/// a loop. Otherwise it's meaningless to do analysis as the vectorization
/// on interleaved accesses is unsafe.
///
/// The analysis collects interleave groups and records the relationships
/// between the member and the group in a map.
class InterleavedAccessInfo {
public:
InterleavedAccessInfo(PredicatedScalarEvolution &PSE, Loop *L,
DominatorTree *DT)
: PSE(PSE), TheLoop(L), DT(DT) {}
~InterleavedAccessInfo() {
SmallSet<InterleaveGroup *, 4> DelSet;
// Avoid releasing a pointer twice.
for (auto &I : InterleaveGroupMap)
DelSet.insert(I.second);
for (auto *Ptr : DelSet)
delete Ptr;
}
/// \brief Analyze the interleaved accesses and collect them in interleave
/// groups. Substitute symbolic strides using \p Strides.
void analyzeInterleaving(const ValueToValueMap &Strides);
/// \brief Check if \p Instr belongs to any interleave group.
bool isInterleaved(Instruction *Instr) const {
return InterleaveGroupMap.count(Instr);
}
/// \brief Get the interleave group that \p Instr belongs to.
///
/// \returns nullptr if doesn't have such group.
InterleaveGroup *getInterleaveGroup(Instruction *Instr) const {
if (InterleaveGroupMap.count(Instr))
return InterleaveGroupMap.find(Instr)->second;
return nullptr;
}
private:
/// A wrapper around ScalarEvolution, used to add runtime SCEV checks.
/// Simplifies SCEV expressions in the context of existing SCEV assumptions.
/// The interleaved access analysis can also add new predicates (for example
/// by versioning strides of pointers).
PredicatedScalarEvolution &PSE;
Loop *TheLoop;
DominatorTree *DT;
/// Holds the relationships between the members and the interleave group.
DenseMap<Instruction *, InterleaveGroup *> InterleaveGroupMap;
/// \brief The descriptor for a strided memory access.
struct StrideDescriptor {
StrideDescriptor(int Stride, const SCEV *Scev, unsigned Size,
unsigned Align)
: Stride(Stride), Scev(Scev), Size(Size), Align(Align) {}
StrideDescriptor() : Stride(0), Scev(nullptr), Size(0), Align(0) {}
int Stride; // The access's stride. It is negative for a reverse access.
const SCEV *Scev; // The scalar expression of this access
unsigned Size; // The size of the memory object.
unsigned Align; // The alignment of this access.
};
/// \brief Create a new interleave group with the given instruction \p Instr,
/// stride \p Stride and alignment \p Align.
///
/// \returns the newly created interleave group.
InterleaveGroup *createInterleaveGroup(Instruction *Instr, int Stride,
unsigned Align) {
assert(!InterleaveGroupMap.count(Instr) &&
"Already in an interleaved access group");
InterleaveGroupMap[Instr] = new InterleaveGroup(Instr, Stride, Align);
return InterleaveGroupMap[Instr];
}
/// \brief Release the group and remove all the relationships.
void releaseGroup(InterleaveGroup *Group) {
for (unsigned i = 0; i < Group->getFactor(); i++)
if (Instruction *Member = Group->getMember(i))
InterleaveGroupMap.erase(Member);
delete Group;
}
/// \brief Collect all the accesses with a constant stride in program order.
void collectConstStridedAccesses(
MapVector<Instruction *, StrideDescriptor> &StrideAccesses,
const ValueToValueMap &Strides);
};
/// Utility class for getting and setting loop vectorizer hints in the form
/// of loop metadata.
/// This class keeps a number of loop annotations locally (as member variables)
/// and can, upon request, write them back as metadata on the loop. It will
/// initially scan the loop for existing metadata, and will update the local
/// values based on information in the loop.
/// We cannot write all values to metadata, as the mere presence of some info,
/// for example 'force', means a decision has been made. So, we need to be
/// careful NOT to add them if the user hasn't specifically asked so.
class LoopVectorizeHints {
enum HintKind {
HK_WIDTH,
HK_UNROLL,
HK_FORCE
};
/// Hint - associates name and validation with the hint value.
struct Hint {
const char * Name;
unsigned Value; // This may have to change for non-numeric values.
HintKind Kind;
Hint(const char * Name, unsigned Value, HintKind Kind)
: Name(Name), Value(Value), Kind(Kind) { }
bool validate(unsigned Val) {
switch (Kind) {
case HK_WIDTH:
return isPowerOf2_32(Val) && Val <= VectorizerParams::MaxVectorWidth;
case HK_UNROLL:
return isPowerOf2_32(Val) && Val <= MaxInterleaveFactor;
case HK_FORCE:
return (Val <= 1);
}
return false;
}
};
/// Vectorization width.
Hint Width;
/// Vectorization interleave factor.
Hint Interleave;
/// Vectorization forced
Hint Force;
/// Return the loop metadata prefix.
static StringRef Prefix() { return "llvm.loop."; }
public:
enum ForceKind {
FK_Undefined = -1, ///< Not selected.
FK_Disabled = 0, ///< Forcing disabled.
FK_Enabled = 1, ///< Forcing enabled.
};
LoopVectorizeHints(const Loop *L, bool DisableInterleaving)
: Width("vectorize.width", VectorizerParams::VectorizationFactor,
HK_WIDTH),
Interleave("interleave.count", DisableInterleaving, HK_UNROLL),
Force("vectorize.enable", FK_Undefined, HK_FORCE),
TheLoop(L) {
// Populate values with existing loop metadata.
getHintsFromMetadata();
// force-vector-interleave overrides DisableInterleaving.
if (VectorizerParams::isInterleaveForced())
Interleave.Value = VectorizerParams::VectorizationInterleave;
DEBUG(if (DisableInterleaving && Interleave.Value == 1) dbgs()
<< "LV: Interleaving disabled by the pass manager\n");
}
/// Mark the loop L as already vectorized by setting the width to 1.
void setAlreadyVectorized() {
Width.Value = Interleave.Value = 1;
Hint Hints[] = {Width, Interleave};
writeHintsToMetadata(Hints);
}
bool allowVectorization(Function *F, Loop *L, bool AlwaysVectorize) const {
if (getForce() == LoopVectorizeHints::FK_Disabled) {
DEBUG(dbgs() << "LV: Not vectorizing: #pragma vectorize disable.\n");
emitOptimizationRemarkAnalysis(F->getContext(),
vectorizeAnalysisPassName(), *F,
L->getStartLoc(), emitRemark());
return false;
}
if (!AlwaysVectorize && getForce() != LoopVectorizeHints::FK_Enabled) {
DEBUG(dbgs() << "LV: Not vectorizing: No #pragma vectorize enable.\n");
emitOptimizationRemarkAnalysis(F->getContext(),
vectorizeAnalysisPassName(), *F,
L->getStartLoc(), emitRemark());
return false;
}
if (getWidth() == 1 && getInterleave() == 1) {
// FIXME: Add a separate metadata to indicate when the loop has already
// been vectorized instead of setting width and count to 1.
DEBUG(dbgs() << "LV: Not vectorizing: Disabled/already vectorized.\n");
// FIXME: Add interleave.disable metadata. This will allow
// vectorize.disable to be used without disabling the pass and errors
// to differentiate between disabled vectorization and a width of 1.
emitOptimizationRemarkAnalysis(
F->getContext(), vectorizeAnalysisPassName(), *F, L->getStartLoc(),
"loop not vectorized: vectorization and interleaving are explicitly "
"disabled, or vectorize width and interleave count are both set to "
"1");
return false;
}
return true;
}
/// Dumps all the hint information.
std::string emitRemark() const {
VectorizationReport R;
if (Force.Value == LoopVectorizeHints::FK_Disabled)
R << "vectorization is explicitly disabled";
else {
R << "use -Rpass-analysis=loop-vectorize for more info";
if (Force.Value == LoopVectorizeHints::FK_Enabled) {
R << " (Force=true";
if (Width.Value != 0)
R << ", Vector Width=" << Width.Value;
if (Interleave.Value != 0)
R << ", Interleave Count=" << Interleave.Value;
R << ")";
}
}
return R.str();
}
unsigned getWidth() const { return Width.Value; }
unsigned getInterleave() const { return Interleave.Value; }
enum ForceKind getForce() const { return (ForceKind)Force.Value; }
const char *vectorizeAnalysisPassName() const {
// If hints are provided that don't disable vectorization use the
// AlwaysPrint pass name to force the frontend to print the diagnostic.
if (getWidth() == 1)
return LV_NAME;
if (getForce() == LoopVectorizeHints::FK_Disabled)
return LV_NAME;
if (getForce() == LoopVectorizeHints::FK_Undefined && getWidth() == 0)
return LV_NAME;
return DiagnosticInfo::AlwaysPrint;
}
bool allowReordering() const {
// When enabling loop hints are provided we allow the vectorizer to change
// the order of operations that is given by the scalar loop. This is not
// enabled by default because can be unsafe or inefficient. For example,
// reordering floating-point operations will change the way round-off
// error accumulates in the loop.
return getForce() == LoopVectorizeHints::FK_Enabled || getWidth() > 1;
}
private:
/// Find hints specified in the loop metadata and update local values.
void getHintsFromMetadata() {
MDNode *LoopID = TheLoop->getLoopID();
if (!LoopID)
return;
// First operand should refer to the loop id itself.
assert(LoopID->getNumOperands() > 0 && "requires at least one operand");
assert(LoopID->getOperand(0) == LoopID && "invalid loop id");
for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) {
const MDString *S = nullptr;
SmallVector<Metadata *, 4> Args;
// The expected hint is either a MDString or a MDNode with the first
// operand a MDString.
if (const MDNode *MD = dyn_cast<MDNode>(LoopID->getOperand(i))) {
if (!MD || MD->getNumOperands() == 0)
continue;
S = dyn_cast<MDString>(MD->getOperand(0));
for (unsigned i = 1, ie = MD->getNumOperands(); i < ie; ++i)
Args.push_back(MD->getOperand(i));
} else {
S = dyn_cast<MDString>(LoopID->getOperand(i));
assert(Args.size() == 0 && "too many arguments for MDString");
}
if (!S)
continue;
// Check if the hint starts with the loop metadata prefix.
StringRef Name = S->getString();
if (Args.size() == 1)
setHint(Name, Args[0]);
}
}
/// Checks string hint with one operand and set value if valid.
void setHint(StringRef Name, Metadata *Arg) {
if (!Name.startswith(Prefix()))
return;
Name = Name.substr(Prefix().size(), StringRef::npos);
const ConstantInt *C = mdconst::dyn_extract<ConstantInt>(Arg);
if (!C) return;
unsigned Val = C->getZExtValue();
Hint *Hints[] = {&Width, &Interleave, &Force};
for (auto H : Hints) {
if (Name == H->Name) {
if (H->validate(Val))
H->Value = Val;
else
DEBUG(dbgs() << "LV: ignoring invalid hint '" << Name << "'\n");
break;
}
}
}
/// Create a new hint from name / value pair.
MDNode *createHintMetadata(StringRef Name, unsigned V) const {
LLVMContext &Context = TheLoop->getHeader()->getContext();
Metadata *MDs[] = {MDString::get(Context, Name),
ConstantAsMetadata::get(
ConstantInt::get(Type::getInt32Ty(Context), V))};
return MDNode::get(Context, MDs);
}
/// Matches metadata with hint name.
bool matchesHintMetadataName(MDNode *Node, ArrayRef<Hint> HintTypes) {
MDString* Name = dyn_cast<MDString>(Node->getOperand(0));
if (!Name)
return false;
for (auto H : HintTypes)
if (Name->getString().endswith(H.Name))
return true;
return false;
}
/// Sets current hints into loop metadata, keeping other values intact.
void writeHintsToMetadata(ArrayRef<Hint> HintTypes) {
if (HintTypes.size() == 0)
return;
// Reserve the first element to LoopID (see below).
SmallVector<Metadata *, 4> MDs(1);
// If the loop already has metadata, then ignore the existing operands.
MDNode *LoopID = TheLoop->getLoopID();
if (LoopID) {
for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) {
MDNode *Node = cast<MDNode>(LoopID->getOperand(i));
// If node in update list, ignore old value.
if (!matchesHintMetadataName(Node, HintTypes))
MDs.push_back(Node);
}
}
// Now, add the missing hints.
for (auto H : HintTypes)
MDs.push_back(createHintMetadata(Twine(Prefix(), H.Name).str(), H.Value));
// Replace current metadata node with new one.
LLVMContext &Context = TheLoop->getHeader()->getContext();
MDNode *NewLoopID = MDNode::get(Context, MDs);
// Set operand 0 to refer to the loop id itself.
NewLoopID->replaceOperandWith(0, NewLoopID);
TheLoop->setLoopID(NewLoopID);
}
/// The loop these hints belong to.
const Loop *TheLoop;
};
static void emitAnalysisDiag(const Function *TheFunction, const Loop *TheLoop,
const LoopVectorizeHints &Hints,
const LoopAccessReport &Message) {
const char *Name = Hints.vectorizeAnalysisPassName();
LoopAccessReport::emitAnalysis(Message, TheFunction, TheLoop, Name);
}
static void emitMissedWarning(Function *F, Loop *L,
const LoopVectorizeHints &LH) {
emitOptimizationRemarkMissed(F->getContext(), LV_NAME, *F, L->getStartLoc(),
LH.emitRemark());
if (LH.getForce() == LoopVectorizeHints::FK_Enabled) {
if (LH.getWidth() != 1)
emitLoopVectorizeWarning(
F->getContext(), *F, L->getStartLoc(),
"failed explicitly specified loop vectorization");
else if (LH.getInterleave() != 1)
emitLoopInterleaveWarning(
F->getContext(), *F, L->getStartLoc(),
"failed explicitly specified loop interleaving");
}
}
/// 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, PredicatedScalarEvolution &PSE,
DominatorTree *DT, TargetLibraryInfo *TLI,
AliasAnalysis *AA, Function *F,
const TargetTransformInfo *TTI,
LoopAccessAnalysis *LAA,
LoopVectorizationRequirements *R,
const LoopVectorizeHints *H)
: NumPredStores(0), TheLoop(L), PSE(PSE), TLI(TLI), TheFunction(F),
TTI(TTI), DT(DT), LAA(LAA), LAI(nullptr), InterleaveInfo(PSE, L, DT),
Induction(nullptr), WidestIndTy(nullptr), HasFunNoNaNAttr(false),
Requirements(R), Hints(H) {}
/// ReductionList contains the reduction descriptors for all
/// of the reductions that were found in the loop.
typedef DenseMap<PHINode *, RecurrenceDescriptor> ReductionList;
/// InductionList saves induction variables and maps them to the
/// induction descriptor.
typedef MapVector<PHINode*, InductionDescriptor> InductionList;
/// Returns true if it is legal to vectorize this loop.
/// This does not mean that it is profitable to vectorize this
/// loop, only that it is legal to do so.
bool canVectorize();
/// Returns the Induction variable.
PHINode *getInduction() { return Induction; }
/// Returns the reduction variables found in the loop.
ReductionList *getReductionVars() { return &Reductions; }
/// Returns the induction variables found in the loop.
InductionList *getInductionVars() { return &Inductions; }
/// Returns the widest induction type.
Type *getWidestInductionType() { return WidestIndTy; }
/// Returns True if V is an induction variable in this loop.
bool isInductionVariable(const Value *V);
/// Returns True if PN is a reduction variable in this loop.
bool isReductionVariable(PHINode *PN) { return Reductions.count(PN); }
/// 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.
const RuntimePointerChecking *getRuntimePointerChecking() const {
return LAI->getRuntimePointerChecking();
}
const LoopAccessInfo *getLAI() const {
return LAI;
}
/// \brief Check if \p Instr belongs to any interleaved access group.
bool isAccessInterleaved(Instruction *Instr) {
return InterleaveInfo.isInterleaved(Instr);
}
/// \brief Get the interleaved access group that \p Instr belongs to.
const InterleaveGroup *getInterleavedAccessGroup(Instruction *Instr) {
return InterleaveInfo.getInterleaveGroup(Instr);
}
unsigned getMaxSafeDepDistBytes() { return LAI->getMaxSafeDepDistBytes(); }
bool hasStride(Value *V) { return StrideSet.count(V); }
bool mustCheckStrides() { return !StrideSet.empty(); }
SmallPtrSet<Value *, 8>::iterator strides_begin() {
return StrideSet.begin();
}
SmallPtrSet<Value *, 8>::iterator strides_end() { return StrideSet.end(); }
/// Returns true if the target machine supports masked store operation
/// for the given \p DataType and kind of access to \p Ptr.
bool isLegalMaskedStore(Type *DataType, Value *Ptr) {
return isConsecutivePtr(Ptr) && TTI->isLegalMaskedStore(DataType);
}
/// Returns true if the target machine supports masked load operation
/// for the given \p DataType and kind of access to \p Ptr.
bool isLegalMaskedLoad(Type *DataType, Value *Ptr) {
return isConsecutivePtr(Ptr) && TTI->isLegalMaskedLoad(DataType);
}
/// Returns true if vector representation of the instruction \p I
/// requires mask.
bool isMaskRequired(const Instruction* I) {
return (MaskedOp.count(I) != 0);
}
unsigned getNumStores() const {
return LAI->getNumStores();
}
unsigned getNumLoads() const {
return LAI->getNumLoads();
}
unsigned getNumPredStores() const {
return NumPredStores;
}
private:
/// Check if a single basic block loop is vectorizable.
/// At this point we know that this is a loop with a constant trip count
/// and we only need to check individual instructions.
bool canVectorizeInstrs();
/// When we vectorize loops we may change the order in which
/// we read and write from memory. This method checks if it is
/// legal to vectorize the code, considering only memory constrains.
/// Returns true if the loop is vectorizable
bool canVectorizeMemory();
/// Return true if we can vectorize this loop using the IF-conversion
/// transformation.
bool canVectorizeWithIfConvert();
/// Collect the variables that need to stay uniform after vectorization.
void collectLoopUniforms();
/// Return true if all of the instructions in the block can be speculatively
/// executed. \p SafePtrs is a list of addresses that are known to be legal
/// and we know that we can read from them without segfault.
bool blockCanBePredicated(BasicBlock *BB, SmallPtrSetImpl<Value *> &SafePtrs);
/// \brief Collect memory access with loop invariant strides.
///
/// Looks for accesses like "a[i * StrideA]" where "StrideA" is loop
/// invariant.
void collectStridedAccess(Value *LoadOrStoreInst);
/// Report an analysis message to assist the user in diagnosing loops that are
/// not vectorized. These are handled as LoopAccessReport rather than
/// VectorizationReport because the << operator of VectorizationReport returns
/// LoopAccessReport.
void emitAnalysis(const LoopAccessReport &Message) const {
emitAnalysisDiag(TheFunction, TheLoop, *Hints, Message);
}
unsigned NumPredStores;
/// The loop that we evaluate.
Loop *TheLoop;
/// A wrapper around ScalarEvolution used to add runtime SCEV checks.
/// Applies dynamic knowledge to simplify SCEV expressions in the context
/// of existing SCEV assumptions. The analysis will also add a minimal set
/// of new predicates if this is required to enable vectorization and
/// unrolling.
PredicatedScalarEvolution &PSE;
/// Target Library Info.
TargetLibraryInfo *TLI;
/// Parent function
Function *TheFunction;
/// Target Transform Info
const TargetTransformInfo *TTI;
/// Dominator Tree.
DominatorTree *DT;
// LoopAccess analysis.
LoopAccessAnalysis *LAA;
// And the loop-accesses info corresponding to this loop. This pointer is
// null until canVectorizeMemory sets it up.
const LoopAccessInfo *LAI;
/// The interleave access information contains groups of interleaved accesses
/// with the same stride and close to each other.
InterleavedAccessInfo InterleaveInfo;
// --- 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;
/// Can we assume the absence of NaNs.
bool HasFunNoNaNAttr;
/// Vectorization requirements that will go through late-evaluation.
LoopVectorizationRequirements *Requirements;
/// Used to emit an analysis of any legality issues.
const LoopVectorizeHints *Hints;
ValueToValueMap Strides;
SmallPtrSet<Value *, 8> StrideSet;
/// While vectorizing these instructions we have to generate a
/// call to the appropriate masked intrinsic
SmallPtrSet<const Instruction *, 8> MaskedOp;
};
/// 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, PredicatedScalarEvolution &PSE,
LoopInfo *LI, LoopVectorizationLegality *Legal,
const TargetTransformInfo &TTI,
const TargetLibraryInfo *TLI, DemandedBits *DB,
AssumptionCache *AC, const Function *F,
const LoopVectorizeHints *Hints)
: TheLoop(L), PSE(PSE), LI(LI), Legal(Legal), TTI(TTI), TLI(TLI), DB(DB),
AC(AC), TheFunction(F), Hints(Hints) {}
/// 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);
/// \return The size (in bits) of the smallest and widest types in the code
/// that needs to be vectorized. We ignore values that remain scalar such as
/// 64 bit loop indices.
std::pair<unsigned, unsigned> getSmallestAndWidestTypes();
/// \return The desired interleave count.
/// If interleave count has been specified by metadata it will be returned.
/// Otherwise, the interleave count is computed and returned. VF and LoopCost
/// are the selected vectorization factor and the cost of the selected VF.
unsigned selectInterleaveCount(bool OptForSize, unsigned VF,
unsigned LoopCost);
/// \return The most profitable unroll factor.
/// 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 computeInterleaveCount(bool OptForSize, 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 Returns information about the register usages of the loop for the
/// given vectorization factors.
SmallVector<RegisterUsage, 8>
calculateRegisterUsage(const SmallVector<unsigned, 8> &VFs);
/// Collect values we want to ignore in the cost model.
void collectValuesToIgnore();
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);
/// Returns whether the instruction is a load or store and will be a emitted
/// as a vector operation.
bool isConsecutiveLoadOrStore(Instruction *I);
/// Report an analysis message to assist the user in diagnosing loops that are
/// not vectorized. These are handled as LoopAccessReport rather than
/// VectorizationReport because the << operator of VectorizationReport returns
/// LoopAccessReport.
void emitAnalysis(const LoopAccessReport &Message) const {
emitAnalysisDiag(TheFunction, TheLoop, *Hints, Message);
}
public:
/// Map of scalar integer values to the smallest bitwidth they can be legally
/// represented as. The vector equivalents of these values should be truncated
/// to this type.
MapVector<Instruction*,uint64_t> MinBWs;
/// The loop that we evaluate.
Loop *TheLoop;
/// Predicated scalar evolution analysis.
PredicatedScalarEvolution &PSE;
/// Loop Info analysis.
LoopInfo *LI;
/// Vectorization legality.
LoopVectorizationLegality *Legal;
/// Vector target information.
const TargetTransformInfo &TTI;
/// Target Library Info.
const TargetLibraryInfo *TLI;
/// Demanded bits analysis.
DemandedBits *DB;
/// Assumption cache.
AssumptionCache *AC;
const Function *TheFunction;
/// Loop Vectorize Hint.
const LoopVectorizeHints *Hints;
/// Values to ignore in the cost model.
SmallPtrSet<const Value *, 16> ValuesToIgnore;
/// Values to ignore in the cost model when VF > 1.
SmallPtrSet<const Value *, 16> VecValuesToIgnore;
};
/// \brief This holds vectorization requirements that must be verified late in
/// the process. The requirements are set by legalize and costmodel. Once
/// vectorization has been determined to be possible and profitable the
/// requirements can be verified by looking for metadata or compiler options.
/// For example, some loops require FP commutativity which is only allowed if
/// vectorization is explicitly specified or if the fast-math compiler option
/// has been provided.
/// Late evaluation of these requirements allows helpful diagnostics to be
/// composed that tells the user what need to be done to vectorize the loop. For
/// example, by specifying #pragma clang loop vectorize or -ffast-math. Late
/// evaluation should be used only when diagnostics can generated that can be
/// followed by a non-expert user.
class LoopVectorizationRequirements {
public:
LoopVectorizationRequirements()
: NumRuntimePointerChecks(0), UnsafeAlgebraInst(nullptr) {}
void addUnsafeAlgebraInst(Instruction *I) {
// First unsafe algebra instruction.
if (!UnsafeAlgebraInst)
UnsafeAlgebraInst = I;
}
void addRuntimePointerChecks(unsigned Num) { NumRuntimePointerChecks = Num; }
bool doesNotMeet(Function *F, Loop *L, const LoopVectorizeHints &Hints) {
const char *Name = Hints.vectorizeAnalysisPassName();
bool Failed = false;
if (UnsafeAlgebraInst && !Hints.allowReordering()) {
emitOptimizationRemarkAnalysisFPCommute(
F->getContext(), Name, *F, UnsafeAlgebraInst->getDebugLoc(),
VectorizationReport() << "cannot prove it is safe to reorder "
"floating-point operations");
Failed = true;
}
// Test if runtime memcheck thresholds are exceeded.
bool PragmaThresholdReached =
NumRuntimePointerChecks > PragmaVectorizeMemoryCheckThreshold;
bool ThresholdReached =
NumRuntimePointerChecks > VectorizerParams::RuntimeMemoryCheckThreshold;
if ((ThresholdReached && !Hints.allowReordering()) ||
PragmaThresholdReached) {
emitOptimizationRemarkAnalysisAliasing(
F->getContext(), Name, *F, L->getStartLoc(),
VectorizationReport()
<< "cannot prove it is safe to reorder memory operations");
DEBUG(dbgs() << "LV: Too many memory checks needed.\n");
Failed = true;
}
return Failed;
}
private:
unsigned NumRuntimePointerChecks;
Instruction *UnsafeAlgebraInst;
};
static void addInnerLoop(Loop &L, SmallVectorImpl<Loop *> &V) {
if (L.empty())
return V.push_back(&L);
for (Loop *InnerL : L)
addInnerLoop(*InnerL, V);
}
/// The LoopVectorize Pass.
struct LoopVectorize : public FunctionPass {
/// Pass identification, replacement for typeid
static char ID;
explicit LoopVectorize(bool NoUnrolling = false, bool AlwaysVectorize = true)
: FunctionPass(ID),
DisableUnrolling(NoUnrolling),
AlwaysVectorize(AlwaysVectorize) {
initializeLoopVectorizePass(*PassRegistry::getPassRegistry());
}
ScalarEvolution *SE;
LoopInfo *LI;
TargetTransformInfo *TTI;
DominatorTree *DT;
BlockFrequencyInfo *BFI;
TargetLibraryInfo *TLI;
DemandedBits *DB;
AliasAnalysis *AA;
AssumptionCache *AC;
LoopAccessAnalysis *LAA;
bool DisableUnrolling;
bool AlwaysVectorize;
BlockFrequency ColdEntryFreq;
bool runOnFunction(Function &F) override {
SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE();
LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo();
TTI = &getAnalysis<TargetTransformInfoWrapperPass>().getTTI(F);
DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree();
BFI = &getAnalysis<BlockFrequencyInfoWrapperPass>().getBFI();
auto *TLIP = getAnalysisIfAvailable<TargetLibraryInfoWrapperPass>();
TLI = TLIP ? &TLIP->getTLI() : nullptr;
AA = &getAnalysis<AAResultsWrapperPass>().getAAResults();
AC = &getAnalysis<AssumptionCacheTracker>().getAssumptionCache(F);
LAA = &getAnalysis<LoopAccessAnalysis>();
DB = &getAnalysis<DemandedBits>();
// Compute some weights outside of the loop over the loops. Compute this
// using a BranchProbability to re-use its scaling math.
const BranchProbability ColdProb(1, 5); // 20%
ColdEntryFreq = BlockFrequency(BFI->getEntryFreq()) * ColdProb;
// Don't attempt if
// 1. the target claims to have no vector registers, and
// 2. interleaving won't help ILP.
//
// The second condition is necessary because, even if the target has no
// vector registers, loop vectorization may still enable scalar
// interleaving.
if (!TTI->getNumberOfRegisters(true) && TTI->getMaxInterleaveFactor(1) < 2)
return false;
// Build up a worklist of inner-loops to vectorize. This is necessary as
// the act of vectorizing or partially unrolling a loop creates new loops
// and can invalidate iterators across the loops.
SmallVector<Loop *, 8> Worklist;
for (Loop *L : *LI)
addInnerLoop(*L, Worklist);
LoopsAnalyzed += Worklist.size();
// Now walk the identified inner loops.
bool Changed = false;
while (!Worklist.empty())
Changed |= processLoop(Worklist.pop_back_val());
// Process each loop nest in the function.
return Changed;
}
static void AddRuntimeUnrollDisableMetaData(Loop *L) {
SmallVector<Metadata *, 4> MDs;
// Reserve first location for self reference to the LoopID metadata node.
MDs.push_back(nullptr);
bool IsUnrollMetadata = false;
MDNode *LoopID = L->getLoopID();
if (LoopID) {
// First find existing loop unrolling disable metadata.
for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) {
MDNode *MD = dyn_cast<MDNode>(LoopID->getOperand(i));
if (MD) {
const MDString *S = dyn_cast<MDString>(MD->getOperand(0));
IsUnrollMetadata =
S && S->getString().startswith("llvm.loop.unroll.disable");
}
MDs.push_back(LoopID->getOperand(i));
}
}
if (!IsUnrollMetadata) {
// Add runtime unroll disable metadata.
LLVMContext &Context = L->getHeader()->getContext();
SmallVector<Metadata *, 1> DisableOperands;
DisableOperands.push_back(
MDString::get(Context, "llvm.loop.unroll.runtime.disable"));
MDNode *DisableNode = MDNode::get(Context, DisableOperands);
MDs.push_back(DisableNode);
MDNode *NewLoopID = MDNode::get(Context, MDs);
// Set operand 0 to refer to the loop id itself.
NewLoopID->replaceOperandWith(0, NewLoopID);
L->setLoopID(NewLoopID);
}
}
bool processLoop(Loop *L) {
assert(L->empty() && "Only process inner loops.");
#ifndef NDEBUG
const std::string DebugLocStr = getDebugLocString(L);
#endif /* NDEBUG */
DEBUG(dbgs() << "\nLV: Checking a loop in \""
<< L->getHeader()->getParent()->getName() << "\" from "
<< DebugLocStr << "\n");
LoopVectorizeHints Hints(L, DisableUnrolling);
DEBUG(dbgs() << "LV: Loop hints:"
<< " force="
<< (Hints.getForce() == LoopVectorizeHints::FK_Disabled
? "disabled"
: (Hints.getForce() == LoopVectorizeHints::FK_Enabled
? "enabled"
: "?")) << " width=" << Hints.getWidth()
<< " unroll=" << Hints.getInterleave() << "\n");
// Function containing loop
Function *F = L->getHeader()->getParent();
// Looking at the diagnostic output is the only way to determine if a loop
// was vectorized (other than looking at the IR or machine code), so it
// is important to generate an optimization remark for each loop. Most of
// these messages are generated by emitOptimizationRemarkAnalysis. Remarks
// generated by emitOptimizationRemark and emitOptimizationRemarkMissed are
// less verbose reporting vectorized loops and unvectorized loops that may
// benefit from vectorization, respectively.
if (!Hints.allowVectorization(F, L, AlwaysVectorize)) {
DEBUG(dbgs() << "LV: Loop hints prevent vectorization.\n");
return false;
}
// Check the loop for a trip count threshold:
// do not vectorize loops with a tiny trip count.
const unsigned TC = SE->getSmallConstantTripCount(L);
if (TC > 0u && TC < TinyTripCountVectorThreshold) {
DEBUG(dbgs() << "LV: Found a loop with a very small trip count. "
<< "This loop is not worth vectorizing.");
if (Hints.getForce() == LoopVectorizeHints::FK_Enabled)
DEBUG(dbgs() << " But vectorizing was explicitly forced.\n");
else {
DEBUG(dbgs() << "\n");
emitAnalysisDiag(F, L, Hints, VectorizationReport()
<< "vectorization is not beneficial "
"and is not explicitly forced");
return false;
}
}
PredicatedScalarEvolution PSE(*SE);
// Check if it is legal to vectorize the loop.
LoopVectorizationRequirements Requirements;
LoopVectorizationLegality LVL(L, PSE, DT, TLI, AA, F, TTI, LAA,
&Requirements, &Hints);
if (!LVL.canVectorize()) {
DEBUG(dbgs() << "LV: Not vectorizing: Cannot prove legality.\n");
emitMissedWarning(F, L, Hints);
return false;
}
// Use the cost model.
LoopVectorizationCostModel CM(L, PSE, LI, &LVL, *TTI, TLI, DB, AC, F,
&Hints);
CM.collectValuesToIgnore();
// Check the function attributes to find out if this function should be
// optimized for size.
bool OptForSize = Hints.getForce() != LoopVectorizeHints::FK_Enabled &&
F->optForSize();
// Compute the weighted frequency of this loop being executed and see if it
// is less than 20% of the function entry baseline frequency. Note that we
// always have a canonical loop here because we think we *can* vectorize.
// FIXME: This is hidden behind a flag due to pervasive problems with
// exactly what block frequency models.
if (LoopVectorizeWithBlockFrequency) {
BlockFrequency LoopEntryFreq = BFI->getBlockFreq(L->getLoopPreheader());
if (Hints.getForce() != LoopVectorizeHints::FK_Enabled &&
LoopEntryFreq < ColdEntryFreq)
OptForSize = true;
}
// Check the function attributes to see if implicit floats are allowed.
// FIXME: This check doesn't seem possibly correct -- what if the loop is
// an integer loop and the vector instructions selected are purely integer
// vector instructions?
if (F->hasFnAttribute(Attribute::NoImplicitFloat)) {
DEBUG(dbgs() << "LV: Can't vectorize when the NoImplicitFloat"
"attribute is used.\n");
emitAnalysisDiag(
F, L, Hints,
VectorizationReport()
<< "loop not vectorized due to NoImplicitFloat attribute");
emitMissedWarning(F, L, Hints);
return false;
}
// Select the optimal vectorization factor.
const LoopVectorizationCostModel::VectorizationFactor VF =
CM.selectVectorizationFactor(OptForSize);
// Select the interleave count.
unsigned IC = CM.selectInterleaveCount(OptForSize, VF.Width, VF.Cost);
// Get user interleave count.
unsigned UserIC = Hints.getInterleave();
// Identify the diagnostic messages that should be produced.
std::string VecDiagMsg, IntDiagMsg;
bool VectorizeLoop = true, InterleaveLoop = true;
if (Requirements.doesNotMeet(F, L, Hints)) {
DEBUG(dbgs() << "LV: Not vectorizing: loop did not meet vectorization "
"requirements.\n");
emitMissedWarning(F, L, Hints);
return false;
}
if (VF.Width == 1) {
DEBUG(dbgs() << "LV: Vectorization is possible but not beneficial.\n");
VecDiagMsg =
"the cost-model indicates that vectorization is not beneficial";
VectorizeLoop = false;
}
if (IC == 1 && UserIC <= 1) {
// Tell the user interleaving is not beneficial.
DEBUG(dbgs() << "LV: Interleaving is not beneficial.\n");
IntDiagMsg =
"the cost-model indicates that interleaving is not beneficial";
InterleaveLoop = false;
if (UserIC == 1)
IntDiagMsg +=
" and is explicitly disabled or interleave count is set to 1";
} else if (IC > 1 && UserIC == 1) {
// Tell the user interleaving is beneficial, but it explicitly disabled.
DEBUG(dbgs()
<< "LV: Interleaving is beneficial but is explicitly disabled.");
IntDiagMsg = "the cost-model indicates that interleaving is beneficial "
"but is explicitly disabled or interleave count is set to 1";
InterleaveLoop = false;
}
// Override IC if user provided an interleave count.
IC = UserIC > 0 ? UserIC : IC;
// Emit diagnostic messages, if any.
const char *VAPassName = Hints.vectorizeAnalysisPassName();
if (!VectorizeLoop && !InterleaveLoop) {
// Do not vectorize or interleaving the loop.
emitOptimizationRemarkAnalysis(F->getContext(), VAPassName, *F,
L->getStartLoc(), VecDiagMsg);
emitOptimizationRemarkAnalysis(F->getContext(), LV_NAME, *F,
L->getStartLoc(), IntDiagMsg);
return false;
} else if (!VectorizeLoop && InterleaveLoop) {
DEBUG(dbgs() << "LV: Interleave Count is " << IC << '\n');
emitOptimizationRemarkAnalysis(F->getContext(), VAPassName, *F,
L->getStartLoc(), VecDiagMsg);
} else if (VectorizeLoop && !InterleaveLoop) {
DEBUG(dbgs() << "LV: Found a vectorizable loop (" << VF.Width << ") in "
<< DebugLocStr << '\n');
emitOptimizationRemarkAnalysis(F->getContext(), LV_NAME, *F,
L->getStartLoc(), IntDiagMsg);
} else if (VectorizeLoop && InterleaveLoop) {
DEBUG(dbgs() << "LV: Found a vectorizable loop (" << VF.Width << ") in "
<< DebugLocStr << '\n');
DEBUG(dbgs() << "LV: Interleave Count is " << IC << '\n');
}
if (!VectorizeLoop) {
assert(IC > 1 && "interleave count should not be 1 or 0");
// If we decided that it is not legal to vectorize the loop then
// interleave it.
InnerLoopUnroller Unroller(L, PSE, LI, DT, TLI, TTI, IC);
Unroller.vectorize(&LVL, CM.MinBWs);
emitOptimizationRemark(F->getContext(), LV_NAME, *F, L->getStartLoc(),
Twine("interleaved loop (interleaved count: ") +
Twine(IC) + ")");
} else {
// If we decided that it is *legal* to vectorize the loop then do it.
InnerLoopVectorizer LB(L, PSE, LI, DT, TLI, TTI, VF.Width, IC);
LB.vectorize(&LVL, CM.MinBWs);
++LoopsVectorized;
// Add metadata to disable runtime unrolling scalar loop when there's no
// runtime check about strides and memory. Because at this situation,
// scalar loop is rarely used not worthy to be unrolled.
if (!LB.IsSafetyChecksAdded())
AddRuntimeUnrollDisableMetaData(L);
// Report the vectorization decision.
emitOptimizationRemark(F->getContext(), LV_NAME, *F, L->getStartLoc(),
Twine("vectorized loop (vectorization width: ") +
Twine(VF.Width) + ", interleaved count: " +
Twine(IC) + ")");
}
// Mark the loop as already vectorized to avoid vectorizing again.
Hints.setAlreadyVectorized();
DEBUG(verifyFunction(*L->getHeader()->getParent()));
return true;
}
void getAnalysisUsage(AnalysisUsage &AU) const override {
AU.addRequired<AssumptionCacheTracker>();
AU.addRequiredID(LoopSimplifyID);
AU.addRequiredID(LCSSAID);
AU.addRequired<BlockFrequencyInfoWrapperPass>();
AU.addRequired<DominatorTreeWrapperPass>();
AU.addRequired<LoopInfoWrapperPass>();
AU.addRequired<ScalarEvolutionWrapperPass>();
AU.addRequired<TargetTransformInfoWrapperPass>();
AU.addRequired<AAResultsWrapperPass>();
AU.addRequired<LoopAccessAnalysis>();
AU.addRequired<DemandedBits>();
AU.addPreserved<LoopInfoWrapperPass>();
AU.addPreserved<DominatorTreeWrapperPass>();
AU.addPreserved<BasicAAWrapperPass>();
AU.addPreserved<AAResultsWrapperPass>();
AU.addPreserved<GlobalsAAWrapperPass>();
}
};
} // end anonymous namespace
//===----------------------------------------------------------------------===//
// Implementation of LoopVectorizationLegality, InnerLoopVectorizer and
// LoopVectorizationCostModel.
//===----------------------------------------------------------------------===//
Value *InnerLoopVectorizer::getBroadcastInstrs(Value *V) {
// We need to place the broadcast of invariant variables outside the loop.
Instruction *Instr = dyn_cast<Instruction>(V);
bool NewInstr =
(Instr && std::find(LoopVectorBody.begin(), LoopVectorBody.end(),
Instr->getParent()) != LoopVectorBody.end());
bool Invariant = OrigLoop->isLoopInvariant(V) && !NewInstr;
// Place the code for broadcasting invariant variables in the new preheader.
IRBuilder<>::InsertPointGuard Guard(Builder);
if (Invariant)
Builder.SetInsertPoint(LoopVectorPreHeader->getTerminator());
// Broadcast the scalar into all locations in the vector.
Value *Shuf = Builder.CreateVectorSplat(VF, V, "broadcast");
return Shuf;
}
Value *InnerLoopVectorizer::getStepVector(Value *Val, int StartIdx,
Value *Step) {
assert(Val->getType()->isVectorTy() && "Must be a vector");
assert(Val->getType()->getScalarType()->isIntegerTy() &&
"Elem must be an integer");
assert(Step->getType() == Val->getType()->getScalarType() &&
"Step has wrong type");
// Create the types.
Type *ITy = Val->getType()->getScalarType();
VectorType *Ty = cast<VectorType>(Val->getType());
int VLen = Ty->getNumElements();
SmallVector<Constant*, 8> Indices;
// Create a vector of consecutive numbers from zero to VF.
for (int i = 0; i < VLen; ++i)
Indices.push_back(ConstantInt::get(ITy, StartIdx + i));
// Add the consecutive indices to the vector value.
Constant *Cv = ConstantVector::get(Indices);
assert(Cv->getType() == Val->getType() && "Invalid consecutive vec");
Step = Builder.CreateVectorSplat(VLen, Step);
assert(Step->getType() == Val->getType() && "Invalid step vec");
// FIXME: The newly created binary instructions should contain nsw/nuw flags,
// which can be found from the original scalar operations.
Step = Builder.CreateMul(Cv, Step);
return Builder.CreateAdd(Val, Step, "induction");
}
int LoopVectorizationLegality::isConsecutivePtr(Value *Ptr) {
assert(Ptr->getType()->isPointerTy() && "Unexpected non-ptr");
auto *SE = PSE.getSE();
// Make sure that the pointer does not point to structs.
if (Ptr->getType()->getPointerElementType()->isAggregateType())
return 0;
// If this value is a pointer induction variable we know it is consecutive.
PHINode *Phi = dyn_cast_or_null<PHINode>(Ptr);
if (Phi && Inductions.count(Phi)) {
InductionDescriptor II = Inductions[Phi];
return II.getConsecutiveDirection();
}
GetElementPtrInst *Gep = getGEPInstruction(Ptr);
if (!Gep)
return 0;
unsigned NumOperands = Gep->getNumOperands();
Value *GpPtr = Gep->getPointerOperand();
// If this GEP value is a consecutive pointer induction variable and all of
// the indices are constant then we know it is consecutive. We can
Phi = dyn_cast<PHINode>(GpPtr);
if (Phi && Inductions.count(Phi)) {
// Make sure that the pointer does not point to structs.
PointerType *GepPtrType = cast<PointerType>(GpPtr->getType());
if (GepPtrType->getElementType()->isAggregateType())
return 0;
// Make sure that all of the index operands are loop invariant.
for (unsigned i = 1; i < NumOperands; ++i)
if (!SE->isLoopInvariant(PSE.getSCEV(Gep->getOperand(i)), TheLoop))
return 0;
InductionDescriptor II = Inductions[Phi];
return II.getConsecutiveDirection();
}
unsigned InductionOperand = getGEPInductionOperand(Gep);
// Check that all of the gep indices are uniform except for our induction
// operand.
for (unsigned i = 0; i != NumOperands; ++i)
if (i != InductionOperand &&
!SE->isLoopInvariant(PSE.getSCEV(Gep->getOperand(i)), TheLoop))
return 0;
// We can emit wide load/stores only if the last non-zero index is the
// induction variable.
const SCEV *Last = nullptr;
if (!Strides.count(Gep))
Last = PSE.getSCEV(Gep->getOperand(InductionOperand));
else {
// Because of the multiplication by a stride we can have a s/zext cast.
// We are going to replace this stride by 1 so the cast is safe to ignore.
//
// %indvars.iv = phi i64 [ 0, %entry ], [ %indvars.iv.next, %for.body ]
// %0 = trunc i64 %indvars.iv to i32
// %mul = mul i32 %0, %Stride1
// %idxprom = zext i32 %mul to i64 << Safe cast.
// %arrayidx = getelementptr inbounds i32* %B, i64 %idxprom
//
Last = replaceSymbolicStrideSCEV(PSE, Strides,
Gep->getOperand(InductionOperand), Gep);
if (const SCEVCastExpr *C = dyn_cast<SCEVCastExpr>(Last))
Last =
(C->getSCEVType() == scSignExtend || C->getSCEVType() == scZeroExtend)
? C->getOperand()
: Last;
}
if (const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(Last)) {
const SCEV *Step = AR->getStepRecurrence(*SE);
// The memory is consecutive because the last index is consecutive
// and all other indices are loop invariant.
if (Step->isOne())
return 1;
if (Step->isAllOnesValue())
return -1;
}
return 0;
}
bool LoopVectorizationLegality::isUniform(Value *V) {
return LAI->isUniform(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 have a stride that is replaced by one, do it here.
if (Legal->hasStride(V))
V = ConstantInt::get(V->getType(), 1);
// If we have this scalar in the map, return it.
if (WidenMap.has(V))
return WidenMap.get(V);
// If this scalar is unknown, assume that it is a constant or that it is
// loop invariant. Broadcast V and save the value for future uses.
Value *B = getBroadcastInstrs(V);
return WidenMap.splat(V, B);
}
Value *InnerLoopVectorizer::reverseVector(Value *Vec) {
assert(Vec->getType()->isVectorTy() && "Invalid type");
SmallVector<Constant*, 8> ShuffleMask;
for (unsigned i = 0; i < VF; ++i)
ShuffleMask.push_back(Builder.getInt32(VF - i - 1));
return Builder.CreateShuffleVector(Vec, UndefValue::get(Vec->getType()),
ConstantVector::get(ShuffleMask),
"reverse");
}
// Get a mask to interleave \p NumVec vectors into a wide vector.
// I.e. <0, VF, VF*2, ..., VF*(NumVec-1), 1, VF+1, VF*2+1, ...>
// E.g. For 2 interleaved vectors, if VF is 4, the mask is:
// <0, 4, 1, 5, 2, 6, 3, 7>
static Constant *getInterleavedMask(IRBuilder<> &Builder, unsigned VF,
unsigned NumVec) {
SmallVector<Constant *, 16> Mask;
for (unsigned i = 0; i < VF; i++)
for (unsigned j = 0; j < NumVec; j++)
Mask.push_back(Builder.getInt32(j * VF + i));
return ConstantVector::get(Mask);
}
// Get the strided mask starting from index \p Start.
// I.e. <Start, Start + Stride, ..., Start + Stride*(VF-1)>
static Constant *getStridedMask(IRBuilder<> &Builder, unsigned Start,
unsigned Stride, unsigned VF) {
SmallVector<Constant *, 16> Mask;
for (unsigned i = 0; i < VF; i++)
Mask.push_back(Builder.getInt32(Start + i * Stride));
return ConstantVector::get(Mask);
}
// Get a mask of two parts: The first part consists of sequential integers
// starting from 0, The second part consists of UNDEFs.
// I.e. <0, 1, 2, ..., NumInt - 1, undef, ..., undef>
static Constant *getSequentialMask(IRBuilder<> &Builder, unsigned NumInt,
unsigned NumUndef) {
SmallVector<Constant *, 16> Mask;
for (unsigned i = 0; i < NumInt; i++)
Mask.push_back(Builder.getInt32(i));
Constant *Undef = UndefValue::get(Builder.getInt32Ty());
for (unsigned i = 0; i < NumUndef; i++)
Mask.push_back(Undef);
return ConstantVector::get(Mask);
}
// Concatenate two vectors with the same element type. The 2nd vector should
// not have more elements than the 1st vector. If the 2nd vector has less
// elements, extend it with UNDEFs.
static Value *ConcatenateTwoVectors(IRBuilder<> &Builder, Value *V1,
Value *V2) {
VectorType *VecTy1 = dyn_cast<VectorType>(V1->getType());
VectorType *VecTy2 = dyn_cast<VectorType>(V2->getType());
assert(VecTy1 && VecTy2 &&
VecTy1->getScalarType() == VecTy2->getScalarType() &&
"Expect two vectors with the same element type");
unsigned NumElts1 = VecTy1->getNumElements();
unsigned NumElts2 = VecTy2->getNumElements();
assert(NumElts1 >= NumElts2 && "Unexpect the first vector has less elements");
if (NumElts1 > NumElts2) {
// Extend with UNDEFs.
Constant *ExtMask =
getSequentialMask(Builder, NumElts2, NumElts1 - NumElts2);
V2 = Builder.CreateShuffleVector(V2, UndefValue::get(VecTy2), ExtMask);
}
Constant *Mask = getSequentialMask(Builder, NumElts1 + NumElts2, 0);
return Builder.CreateShuffleVector(V1, V2, Mask);
}
// Concatenate vectors in the given list. All vectors have the same type.
static Value *ConcatenateVectors(IRBuilder<> &Builder,
ArrayRef<Value *> InputList) {
unsigned NumVec = InputList.size();
assert(NumVec > 1 && "Should be at least two vectors");
SmallVector<Value *, 8> ResList;
ResList.append(InputList.begin(), InputList.end());
do {
SmallVector<Value *, 8> TmpList;
for (unsigned i = 0; i < NumVec - 1; i += 2) {
Value *V0 = ResList[i], *V1 = ResList[i + 1];
assert((V0->getType() == V1->getType() || i == NumVec - 2) &&
"Only the last vector may have a different type");
TmpList.push_back(ConcatenateTwoVectors(Builder, V0, V1));
}
// Push the last vector if the total number of vectors is odd.
if (NumVec % 2 != 0)
TmpList.push_back(ResList[NumVec - 1]);
ResList = TmpList;
NumVec = ResList.size();
} while (NumVec > 1);
return ResList[0];
}
// Try to vectorize the interleave group that \p Instr belongs to.
//
// E.g. Translate following interleaved load group (factor = 3):
// for (i = 0; i < N; i+=3) {
// R = Pic[i]; // Member of index 0
// G = Pic[i+1]; // Member of index 1
// B = Pic[i+2]; // Member of index 2
// ... // do something to R, G, B
// }
// To:
// %wide.vec = load <12 x i32> ; Read 4 tuples of R,G,B
// %R.vec = shuffle %wide.vec, undef, <0, 3, 6, 9> ; R elements
// %G.vec = shuffle %wide.vec, undef, <1, 4, 7, 10> ; G elements
// %B.vec = shuffle %wide.vec, undef, <2, 5, 8, 11> ; B elements
//
// Or translate following interleaved store group (factor = 3):
// for (i = 0; i < N; i+=3) {
// ... do something to R, G, B
// Pic[i] = R; // Member of index 0
// Pic[i+1] = G; // Member of index 1
// Pic[i+2] = B; // Member of index 2
// }
// To:
// %R_G.vec = shuffle %R.vec, %G.vec, <0, 1, 2, ..., 7>
// %B_U.vec = shuffle %B.vec, undef, <0, 1, 2, 3, u, u, u, u>
// %interleaved.vec = shuffle %R_G.vec, %B_U.vec,
// <0, 4, 8, 1, 5, 9, 2, 6, 10, 3, 7, 11> ; Interleave R,G,B elements
// store <12 x i32> %interleaved.vec ; Write 4 tuples of R,G,B
void InnerLoopVectorizer::vectorizeInterleaveGroup(Instruction *Instr) {
const InterleaveGroup *Group = Legal->getInterleavedAccessGroup(Instr);
assert(Group && "Fail to get an interleaved access group.");
// Skip if current instruction is not the insert position.
if (Instr != Group->getInsertPos())
return;
LoadInst *LI = dyn_cast<LoadInst>(Instr);
StoreInst *SI = dyn_cast<StoreInst>(Instr);
Value *Ptr = LI ? LI->getPointerOperand() : SI->getPointerOperand();
// Prepare for the vector type of the interleaved load/store.
Type *ScalarTy = LI ? LI->getType() : SI->getValueOperand()->getType();
unsigned InterleaveFactor = Group->getFactor();
Type *VecTy = VectorType::get(ScalarTy, InterleaveFactor * VF);
Type *PtrTy = VecTy->getPointerTo(Ptr->getType()->getPointerAddressSpace());
// Prepare for the new pointers.
setDebugLocFromInst(Builder, Ptr);
VectorParts &PtrParts = getVectorValue(Ptr);
SmallVector<Value *, 2> NewPtrs;
unsigned Index = Group->getIndex(Instr);
for (unsigned Part = 0; Part < UF; Part++) {
// Extract the pointer for current instruction from the pointer vector. A
// reverse access uses the pointer in the last lane.
Value *NewPtr = Builder.CreateExtractElement(
PtrParts[Part],
Group->isReverse() ? Builder.getInt32(VF - 1) : Builder.getInt32(0));
// Notice current instruction could be any index. Need to adjust the address
// to the member of index 0.
//
// E.g. a = A[i+1]; // Member of index 1 (Current instruction)
// b = A[i]; // Member of index 0
// Current pointer is pointed to A[i+1], adjust it to A[i].
//
// E.g. A[i+1] = a; // Member of index 1
// A[i] = b; // Member of index 0
// A[i+2] = c; // Member of index 2 (Current instruction)
// Current pointer is pointed to A[i+2], adjust it to A[i].
NewPtr = Builder.CreateGEP(NewPtr, Builder.getInt32(-Index));
// Cast to the vector pointer type.
NewPtrs.push_back(Builder.CreateBitCast(NewPtr, PtrTy));
}
setDebugLocFromInst(Builder, Instr);
Value *UndefVec = UndefValue::get(VecTy);
// Vectorize the interleaved load group.
if (LI) {
for (unsigned Part = 0; Part < UF; Part++) {
Instruction *NewLoadInstr = Builder.CreateAlignedLoad(
NewPtrs[Part], Group->getAlignment(), "wide.vec");
for (unsigned i = 0; i < InterleaveFactor; i++) {
Instruction *Member = Group->getMember(i);
// Skip the gaps in the group.
if (!Member)
continue;
Constant *StrideMask = getStridedMask(Builder, i, InterleaveFactor, VF);
Value *StridedVec = Builder.CreateShuffleVector(
NewLoadInstr, UndefVec, StrideMask, "strided.vec");
// If this member has different type, cast the result type.
if (Member->getType() != ScalarTy) {
VectorType *OtherVTy = VectorType::get(Member->getType(), VF);
StridedVec = Builder.CreateBitOrPointerCast(StridedVec, OtherVTy);
}
VectorParts &Entry = WidenMap.get(Member);
Entry[Part] =
Group->isReverse() ? reverseVector(StridedVec) : StridedVec;
}
propagateMetadata(NewLoadInstr, Instr);
}
return;
}
// The sub vector type for current instruction.
VectorType *SubVT = VectorType::get(ScalarTy, VF);
// Vectorize the interleaved store group.
for (unsigned Part = 0; Part < UF; Part++) {
// Collect the stored vector from each member.
SmallVector<Value *, 4> StoredVecs;
for (unsigned i = 0; i < InterleaveFactor; i++) {
// Interleaved store group doesn't allow a gap, so each index has a member
Instruction *Member = Group->getMember(i);
assert(Member && "Fail to get a member from an interleaved store group");
Value *StoredVec =
getVectorValue(dyn_cast<StoreInst>(Member)->getValueOperand())[Part];
if (Group->isReverse())
StoredVec = reverseVector(StoredVec);
// If this member has different type, cast it to an unified type.
if (StoredVec->getType() != SubVT)
StoredVec = Builder.CreateBitOrPointerCast(StoredVec, SubVT);
StoredVecs.push_back(StoredVec);
}
// Concatenate all vectors into a wide vector.
Value *WideVec = ConcatenateVectors(Builder, StoredVecs);
// Interleave the elements in the wide vector.
Constant *IMask = getInterleavedMask(Builder, VF, InterleaveFactor);
Value *IVec = Builder.CreateShuffleVector(WideVec, UndefVec, IMask,
"interleaved.vec");
Instruction *NewStoreInstr =
Builder.CreateAlignedStore(IVec, NewPtrs[Part], Group->getAlignment());
propagateMetadata(NewStoreInstr, Instr);
}
}
void InnerLoopVectorizer::vectorizeMemoryInstruction(Instruction *Instr) {
// 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");
// Try to vectorize the interleave group if this access is interleaved.
if (Legal->isAccessInterleaved(Instr))
return vectorizeInterleaveGroup(Instr);
Type *ScalarDataTy = LI ? LI->getType() : SI->getValueOperand()->getType();
Type *DataTy = VectorType::get(ScalarDataTy, VF);
Value *Ptr = LI ? LI->getPointerOperand() : SI->getPointerOperand();
unsigned Alignment = LI ? LI->getAlignment() : SI->getAlignment();
// An alignment of 0 means target abi alignment. We need to use the scalar's
// target abi alignment in such a case.
const DataLayout &DL = Instr->getModule()->getDataLayout();
if (!Alignment)
Alignment = DL.getABITypeAlignment(ScalarDataTy);
unsigned AddressSpace = Ptr->getType()->getPointerAddressSpace();
unsigned ScalarAllocatedSize = DL.getTypeAllocSize(ScalarDataTy);
unsigned VectorElementSize = DL.getTypeStoreSize(DataTy) / VF;
if (SI && Legal->blockNeedsPredication(SI->getParent()) &&
!Legal->isMaskRequired(SI))
return scalarizeInstruction(Instr, true);
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 = getGEPInstruction(Ptr);
if (Gep && Legal->isInductionVariable(Gep->getPointerOperand())) {
setDebugLocFromInst(Builder, Gep);
Value *PtrOperand = Gep->getPointerOperand();
Value *FirstBasePtr = getVectorValue(PtrOperand)[0];
FirstBasePtr = Builder.CreateExtractElement(FirstBasePtr, Zero);
// Create the new GEP with the new induction variable.
GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone());
Gep2->setOperand(0, FirstBasePtr);
Gep2->setName("gep.indvar.base");
Ptr = Builder.Insert(Gep2);
} else if (Gep) {
setDebugLocFromInst(Builder, Gep);
assert(PSE.getSE()->isLoopInvariant(PSE.getSCEV(Gep->getPointerOperand()),
OrigLoop) &&
"Base ptr must be invariant");
// The last index does not have to be the induction. It can be
// consecutive and be a function of the index. For example A[I+1];
unsigned NumOperands = Gep->getNumOperands();
unsigned InductionOperand = getGEPInductionOperand(Gep);
// Create the new GEP with the new induction variable.
GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone());
for (unsigned i = 0; i < NumOperands; ++i) {
Value *GepOperand = Gep->getOperand(i);
Instruction *GepOperandInst = dyn_cast<Instruction>(GepOperand);
// Update last index or loop invariant instruction anchored in loop.
if (i == InductionOperand ||
(GepOperandInst && OrigLoop->contains(GepOperandInst))) {
assert((i == InductionOperand ||
PSE.getSE()->isLoopInvariant(PSE.getSCEV(GepOperandInst),
OrigLoop)) &&
"Must be last index or loop invariant");
VectorParts &GEPParts = getVectorValue(GepOperand);
Value *Index = GEPParts[0];
Index = Builder.CreateExtractElement(Index, Zero);
Gep2->setOperand(i, Index);
Gep2->setName("gep.indvar.idx");
}
}
Ptr = Builder.Insert(Gep2);
} else {
// Use the induction element ptr.
assert(isa<PHINode>(Ptr) && "Invalid induction ptr");
setDebugLocFromInst(Builder, Ptr);
VectorParts &PtrVal = getVectorValue(Ptr);
Ptr = Builder.CreateExtractElement(PtrVal[0], Zero);
}
VectorParts Mask = createBlockInMask(Instr->getParent());
// Handle Stores:
if (SI) {
assert(!Legal->isUniform(SI->getPointerOperand()) &&
"We do not allow storing to uniform addresses");
setDebugLocFromInst(Builder, SI);
// We don't want to update the value in the map as it might be used in
// another expression. So don't use a reference type for "StoredVal".
VectorParts StoredVal = getVectorValue(SI->getValueOperand());
for (unsigned Part = 0; Part < UF; ++Part) {
// Calculate the pointer for the specific unroll-part.
Value *PartPtr =
Builder.CreateGEP(nullptr, 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(nullptr, Ptr, Builder.getInt32(-Part * VF));
PartPtr = Builder.CreateGEP(nullptr, PartPtr, Builder.getInt32(1 - VF));
Mask[Part] = reverseVector(Mask[Part]);
}
Value *VecPtr = Builder.CreateBitCast(PartPtr,
DataTy->getPointerTo(AddressSpace));
Instruction *NewSI;
if (Legal->isMaskRequired(SI))
NewSI = Builder.CreateMaskedStore(StoredVal[Part], VecPtr, Alignment,
Mask[Part]);
else
NewSI = Builder.CreateAlignedStore(StoredVal[Part], VecPtr, Alignment);
propagateMetadata(NewSI, SI);
}
return;
}
// Handle loads.
assert(LI && "Must have a load instruction");
setDebugLocFromInst(Builder, LI);
for (unsigned Part = 0; Part < UF; ++Part) {
// Calculate the pointer for the specific unroll-part.
Value *PartPtr =
Builder.CreateGEP(nullptr, Ptr, Builder.getInt32(Part * VF));
if (Reverse) {
// If the address is consecutive but reversed, then the
// wide load needs to start at the last vector element.
PartPtr = Builder.CreateGEP(nullptr, Ptr, Builder.getInt32(-Part * VF));
PartPtr = Builder.CreateGEP(nullptr, PartPtr, Builder.getInt32(1 - VF));
Mask[Part] = reverseVector(Mask[Part]);
}
Instruction* NewLI;
Value *VecPtr = Builder.CreateBitCast(PartPtr,
DataTy->getPointerTo(AddressSpace));
if (Legal->isMaskRequired(LI))
NewLI = Builder.CreateMaskedLoad(VecPtr, Alignment, Mask[Part],
UndefValue::get(DataTy),
"wide.masked.load");
else
NewLI = Builder.CreateAlignedLoad(VecPtr, Alignment, "wide.load");
propagateMetadata(NewLI, LI);
Entry[Part] = Reverse ? reverseVector(NewLI) : NewLI;
}
}
void InnerLoopVectorizer::scalarizeInstruction(Instruction *Instr,
bool IfPredicateStore) {
assert(!Instr->getType()->isAggregateType() && "Can't handle vectors");
// Holds vector parameters or scalars, in case of uniform vals.
SmallVector<VectorParts, 4> Params;
setDebugLocFromInst(Builder, Instr);
// Find all of the vectorized parameters.
for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) {
Value *SrcOp = Instr->getOperand(op);
// If we are accessing the old induction variable, use the new one.
if (SrcOp == OldInduction) {
Params.push_back(getVectorValue(SrcOp));
continue;
}
// Try using previously calculated values.
Instruction *SrcInst = dyn_cast<Instruction>(SrcOp);
// If the src is an instruction that appeared earlier in the basic block,
// then it should already be vectorized.
if (SrcInst && OrigLoop->contains(SrcInst)) {
assert(WidenMap.has(SrcInst) && "Source operand is unavailable");
// The parameter is a vector value from earlier.
Params.push_back(WidenMap.get(SrcInst));
} else {
// The parameter is a scalar from outside the loop. Maybe even a constant.
VectorParts Scalars;
Scalars.append(UF, SrcOp);
Params.push_back(Scalars);
}
}
assert(Params.size() == Instr->getNumOperands() &&
"Invalid number of operands");
// Does this instruction return a value ?
bool IsVoidRetTy = Instr->getType()->isVoidTy();
Value *UndefVec = IsVoidRetTy ? nullptr :
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);
VectorParts Cond;
if (IfPredicateStore) {
assert(Instr->getParent()->getSinglePredecessor() &&
"Only support single predecessor blocks");
Cond = createEdgeMask(Instr->getParent()->getSinglePredecessor(),
Instr->getParent());
}
// 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) {
// Start if-block.
Value *Cmp = nullptr;
if (IfPredicateStore) {
Cmp = Builder.CreateExtractElement(Cond[Part], Builder.getInt32(Width));
Cmp = Builder.CreateICmp(ICmpInst::ICMP_EQ, Cmp,
ConstantInt::get(Cmp->getType(), 1));
}
Instruction *Cloned = Instr->clone();
if (!IsVoidRetTy)
Cloned->setName(Instr->getName() + ".cloned");
// Replace the operands of the cloned instructions with extracted scalars.
for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) {
Value *Op = Params[op][Part];
// Param is a vector. Need to extract the right lane.
if (Op->getType()->isVectorTy())
Op = Builder.CreateExtractElement(Op, Builder.getInt32(Width));
Cloned->setOperand(op, Op);
}
// Place the cloned scalar in the new loop.
Builder.Insert(Cloned);
// If the original scalar returns a value we need to place it in a vector
// so that future users will be able to use it.
if (!IsVoidRetTy)
VecResults[Part] = Builder.CreateInsertElement(VecResults[Part], Cloned,
Builder.getInt32(Width));
// End if-block.
if (IfPredicateStore)
PredicatedStores.push_back(std::make_pair(cast<StoreInst>(Cloned),
Cmp));
}
}
}
PHINode *InnerLoopVectorizer::createInductionVariable(Loop *L, Value *Start,
Value *End, Value *Step,
Instruction *DL) {
BasicBlock *Header = L->getHeader();
BasicBlock *Latch = L->getLoopLatch();
// As we're just creating this loop, it's possible no latch exists
// yet. If so, use the header as this will be a single block loop.
if (!Latch)
Latch = Header;
IRBuilder<> Builder(&*Header->getFirstInsertionPt());
setDebugLocFromInst(Builder, getDebugLocFromInstOrOperands(OldInduction));
auto *Induction = Builder.CreatePHI(Start->getType(), 2, "index");
Builder.SetInsertPoint(Latch->getTerminator());
// Create i+1 and fill the PHINode.
Value *Next = Builder.CreateAdd(Induction, Step, "index.next");
Induction->addIncoming(Start, L->getLoopPreheader());
Induction->addIncoming(Next, Latch);
// Create the compare.
Value *ICmp = Builder.CreateICmpEQ(Next, End);
Builder.CreateCondBr(ICmp, L->getExitBlock(), Header);
// Now we have two terminators. Remove the old one from the block.
Latch->getTerminator()->eraseFromParent();
return Induction;
}
Value *InnerLoopVectorizer::getOrCreateTripCount(Loop *L) {
if (TripCount)
return TripCount;
IRBuilder<> Builder(L->getLoopPreheader()->getTerminator());
// Find the loop boundaries.
ScalarEvolution *SE = PSE.getSE();
const SCEV *BackedgeTakenCount = SE->getBackedgeTakenCount(OrigLoop);
assert(BackedgeTakenCount != SE->getCouldNotCompute() &&
"Invalid loop count");
Type *IdxTy = Legal->getWidestInductionType();
// The exit count might have the type of i64 while the phi is i32. This can
// happen if we have an induction variable that is sign extended before the
// compare. The only way that we get a backedge taken count is that the
// induction variable was signed and as such will not overflow. In such a case
// truncation is legal.
if (BackedgeTakenCount->getType()->getPrimitiveSizeInBits() >
IdxTy->getPrimitiveSizeInBits())
BackedgeTakenCount = SE->getTruncateOrNoop(BackedgeTakenCount, IdxTy);
BackedgeTakenCount = SE->getNoopOrZeroExtend(BackedgeTakenCount, IdxTy);
// Get the total trip count from the count by adding 1.
const SCEV *ExitCount = SE->getAddExpr(
BackedgeTakenCount, SE->getOne(BackedgeTakenCount->getType()));
const DataLayout &DL = L->getHeader()->getModule()->getDataLayout();
// Expand the trip count and place the new instructions in the preheader.
// Notice that the pre-header does not change, only the loop body.
SCEVExpander Exp(*SE, DL, "induction");
// Count holds the overall loop count (N).
TripCount = Exp.expandCodeFor(ExitCount, ExitCount->getType(),
L->getLoopPreheader()->getTerminator());
if (TripCount->getType()->isPointerTy())
TripCount =
CastInst::CreatePointerCast(TripCount, IdxTy,
"exitcount.ptrcnt.to.int",
L->getLoopPreheader()->getTerminator());
return TripCount;
}
Value *InnerLoopVectorizer::getOrCreateVectorTripCount(Loop *L) {
if (VectorTripCount)
return VectorTripCount;
Value *TC = getOrCreateTripCount(L);
IRBuilder<> Builder(L->getLoopPreheader()->getTerminator());
// Now we need to generate the expression for N - (N % VF), which is
// the part that the vectorized body will execute.
// 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(TC->getType(), VF * UF);
Value *R = Builder.CreateURem(TC, Step, "n.mod.vf");
VectorTripCount = Builder.CreateSub(TC, R, "n.vec");
return VectorTripCount;
}
void InnerLoopVectorizer::emitMinimumIterationCountCheck(Loop *L,
BasicBlock *Bypass) {
Value *Count = getOrCreateTripCount(L);
BasicBlock *BB = L->getLoopPreheader();
IRBuilder<> Builder(BB->getTerminator());
// Generate code to check that the loop's trip count that we computed by
// adding one to the backedge-taken count will not overflow.
Value *CheckMinIters =
Builder.CreateICmpULT(Count,
ConstantInt::get(Count->getType(), VF * UF),
"min.iters.check");
BasicBlock *NewBB = BB->splitBasicBlock(BB->getTerminator(),
"min.iters.checked");
if (L->getParentLoop())
L->getParentLoop()->addBasicBlockToLoop(NewBB, *LI);
ReplaceInstWithInst(BB->getTerminator(),
BranchInst::Create(Bypass, NewBB, CheckMinIters));
LoopBypassBlocks.push_back(BB);
}
void InnerLoopVectorizer::emitVectorLoopEnteredCheck(Loop *L,
BasicBlock *Bypass) {
Value *TC = getOrCreateVectorTripCount(L);
BasicBlock *BB = L->getLoopPreheader();
IRBuilder<> Builder(BB->getTerminator());
// Now, compare the new count to zero. If it is zero skip the vector loop and
// jump to the scalar loop.
Value *Cmp = Builder.CreateICmpEQ(TC, Constant::getNullValue(TC->getType()),
"cmp.zero");
// Generate code to check that the loop's trip count that we computed by
// adding one to the backedge-taken count will not overflow.
BasicBlock *NewBB = BB->splitBasicBlock(BB->getTerminator(),
"vector.ph");
if (L->getParentLoop())
L->getParentLoop()->addBasicBlockToLoop(NewBB, *LI);
ReplaceInstWithInst(BB->getTerminator(),
BranchInst::Create(Bypass, NewBB, Cmp));
LoopBypassBlocks.push_back(BB);
}
void InnerLoopVectorizer::emitSCEVChecks(Loop *L, BasicBlock *Bypass) {
BasicBlock *BB = L->getLoopPreheader();
// Generate the code to check that the SCEV assumptions that we made.
// We want the new basic block to start at the first instruction in a
// sequence of instructions that form a check.
SCEVExpander Exp(*PSE.getSE(), Bypass->getModule()->getDataLayout(),
"scev.check");
Value *SCEVCheck =
Exp.expandCodeForPredicate(&PSE.getUnionPredicate(), BB->getTerminator());
if (auto *C = dyn_cast<ConstantInt>(SCEVCheck))
if (C->isZero())
return;
// Create a new block containing the stride check.
BB->setName("vector.scevcheck");
auto *NewBB = BB->splitBasicBlock(BB->getTerminator(), "vector.ph");
if (L->getParentLoop())
L->getParentLoop()->addBasicBlockToLoop(NewBB, *LI);
ReplaceInstWithInst(BB->getTerminator(),
BranchInst::Create(Bypass, NewBB, SCEVCheck));
LoopBypassBlocks.push_back(BB);
AddedSafetyChecks = true;
}
void InnerLoopVectorizer::emitMemRuntimeChecks(Loop *L,
BasicBlock *Bypass) {
BasicBlock *BB = L->getLoopPreheader();
// 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 *FirstCheckInst;
Instruction *MemRuntimeCheck;
std::tie(FirstCheckInst, MemRuntimeCheck) =
Legal->getLAI()->addRuntimeChecks(BB->getTerminator());
if (!MemRuntimeCheck)
return;
// Create a new block containing the memory check.
BB->setName("vector.memcheck");
auto *NewBB = BB->splitBasicBlock(BB->getTerminator(), "vector.ph");
if (L->getParentLoop())
L->getParentLoop()->addBasicBlockToLoop(NewBB, *LI);
ReplaceInstWithInst(BB->getTerminator(),
BranchInst::Create(Bypass, NewBB, MemRuntimeCheck));
LoopBypassBlocks.push_back(BB);
AddedSafetyChecks = true;
}
void InnerLoopVectorizer::createEmptyLoop() {
/*
In this function we generate a new loop. The new loop will contain
the vectorized instructions while the old loop will continue to run the
scalar remainder.
[ ] <-- loop iteration number check.
/ |
/ v
| [ ] <-- vector loop bypass (may consist of multiple blocks).
| / |
| / v
|| [ ] <-- vector pre header.
|/ |
| v
| [ ] \
| [ ]_| <-- vector loop.
| |
| v
| -[ ] <--- middle-block.
| / |
| / v
-|- >[ ] <--- new preheader.
| |
| v
| [ ] \
| [ ]_| <-- old scalar loop to handle remainder.
\ |
\ v
>[ ] <-- exit block.
...
*/
BasicBlock *OldBasicBlock = OrigLoop->getHeader();
BasicBlock *VectorPH = OrigLoop->getLoopPreheader();
BasicBlock *ExitBlock = OrigLoop->getExitBlock();
assert(VectorPH && "Invalid loop structure");
assert(ExitBlock && "Must have an exit block");
// Some loops have a single integer induction variable, while other loops
// don't. One example is c++ iterators that often have multiple pointer
// induction variables. In the code below we also support a case where we
// don't have a single induction variable.
//
// We try to obtain an induction variable from the original loop as hard
// as possible. However if we don't find one that:
// - is an integer
// - counts from zero, stepping by one
// - is the size of the widest induction variable type
// then we create a new one.
OldInduction = Legal->getInduction();
Type *IdxTy = Legal->getWidestInductionType();
// Split the single block loop into the two loop structure described above.
BasicBlock *VecBody =
VectorPH->splitBasicBlock(VectorPH->getTerminator(), "vector.body");
BasicBlock *MiddleBlock =
VecBody->splitBasicBlock(VecBody->getTerminator(), "middle.block");
BasicBlock *ScalarPH =
MiddleBlock->splitBasicBlock(MiddleBlock->getTerminator(), "scalar.ph");
// Create and register the new vector loop.
Loop* Lp = new Loop();
Loop *ParentLoop = OrigLoop->getParentLoop();
// Insert the new loop into the loop nest and register the new basic blocks
// before calling any utilities such as SCEV that require valid LoopInfo.
if (ParentLoop) {
ParentLoop->addChildLoop(Lp);
ParentLoop->addBasicBlockToLoop(ScalarPH, *LI);
ParentLoop->addBasicBlockToLoop(MiddleBlock, *LI);
} else {
LI->addTopLevelLoop(Lp);
}
Lp->addBasicBlockToLoop(VecBody, *LI);
// Find the loop boundaries.
Value *Count = getOrCreateTripCount(Lp);
Value *StartIdx = ConstantInt::get(IdxTy, 0);
// We need to test whether the backedge-taken count is uint##_max. Adding one
// to it will cause overflow and an incorrect loop trip count in the vector
// body. In case of overflow we want to directly jump to the scalar remainder
// loop.
emitMinimumIterationCountCheck(Lp, ScalarPH);
// Now, compare the new count to zero. If it is zero skip the vector loop and
// jump to the scalar loop.
emitVectorLoopEnteredCheck(Lp, ScalarPH);
// Generate the code to check any assumptions that we've made for SCEV
// expressions.
emitSCEVChecks(Lp, ScalarPH);
// 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.
emitMemRuntimeChecks(Lp, ScalarPH);
// Generate the induction variable.
// The loop step is equal to the vectorization factor (num of SIMD elements)
// times the unroll factor (num of SIMD instructions).
Value *CountRoundDown = getOrCreateVectorTripCount(Lp);
Constant *Step = ConstantInt::get(IdxTy, VF * UF);
Induction =
createInductionVariable(Lp, StartIdx, CountRoundDown, Step,
getDebugLocFromInstOrOperands(OldInduction));
// We are going to resume the execution of the scalar loop.
// Go over all of the induction variables that we found and fix the
// PHIs that are left in the scalar version of the loop.
// The starting values of PHI nodes depend on the counter of the last
// iteration in the vectorized loop.
// If we come from a bypass edge then we need to start from the original
// start value.
// This variable saves the new starting index for the scalar loop. It is used
// to test if there are any tail iterations left once the vector loop has
// completed.
LoopVectorizationLegality::InductionList::iterator I, E;
LoopVectorizationLegality::InductionList *List = Legal->getInductionVars();
for (I = List->begin(), E = List->end(); I != E; ++I) {
PHINode *OrigPhi = I->first;
InductionDescriptor II = I->second;
// Create phi nodes to merge from the backedge-taken check block.
PHINode *BCResumeVal = PHINode::Create(OrigPhi->getType(), 3,
"bc.resume.val",
ScalarPH->getTerminator());
Value *EndValue;
if (OrigPhi == OldInduction) {
// We know what the end value is.
EndValue = CountRoundDown;
} else {
IRBuilder<> B(LoopBypassBlocks.back()->getTerminator());
Value *CRD = B.CreateSExtOrTrunc(CountRoundDown,
II.getStepValue()->getType(),
"cast.crd");
EndValue = II.transform(B, CRD);
EndValue->setName("ind.end");
}
// The new PHI merges the original incoming value, in case of a bypass,
// or the value at the end of the vectorized loop.
BCResumeVal->addIncoming(EndValue, MiddleBlock);
// Fix the scalar body counter (PHI node).
unsigned BlockIdx = OrigPhi->getBasicBlockIndex(ScalarPH);
// The old induction's phi node in the scalar body needs the truncated
// value.
for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I)
BCResumeVal->addIncoming(II.getStartValue(), LoopBypassBlocks[I]);
OrigPhi->setIncomingValue(BlockIdx, BCResumeVal);
}
// Add a check in the middle block to see if we have completed
// all of the iterations in the first vector loop.
// If (N - N%VF) == N, then we *don't* need to run the remainder.
Value *CmpN = CmpInst::Create(Instruction::ICmp, CmpInst::ICMP_EQ, Count,
CountRoundDown, "cmp.n",
MiddleBlock->getTerminator());
ReplaceInstWithInst(MiddleBlock->getTerminator(),
BranchInst::Create(ExitBlock, ScalarPH, CmpN));
// Get ready to start creating new instructions into the vectorized body.
Builder.SetInsertPoint(&*VecBody->getFirstInsertionPt());
// Save the state.
LoopVectorPreHeader = Lp->getLoopPreheader();
LoopScalarPreHeader = ScalarPH;
LoopMiddleBlock = MiddleBlock;
LoopExitBlock = ExitBlock;
LoopVectorBody.push_back(VecBody);
LoopScalarBody = OldBasicBlock;
LoopVectorizeHints Hints(Lp, true);
Hints.setAlreadyVectorized();
}
namespace {
struct CSEDenseMapInfo {
static bool canHandle(Instruction *I) {
return isa<InsertElementInst>(I) || isa<ExtractElementInst>(I) ||
isa<ShuffleVectorInst>(I) || isa<GetElementPtrInst>(I);
}
static inline Instruction *getEmptyKey() {
return DenseMapInfo<Instruction *>::getEmptyKey();
}
static inline Instruction *getTombstoneKey() {
return DenseMapInfo<Instruction *>::getTombstoneKey();
}
static unsigned getHashValue(Instruction *I) {
assert(canHandle(I) && "Unknown instruction!");
return hash_combine(I->getOpcode(), hash_combine_range(I->value_op_begin(),
I->value_op_end()));
}
static bool isEqual(Instruction *LHS, Instruction *RHS) {
if (LHS == getEmptyKey() || RHS == getEmptyKey() ||
LHS == getTombstoneKey() || RHS == getTombstoneKey())
return LHS == RHS;
return LHS->isIdenticalTo(RHS);
}
};
}
/// \brief Check whether this block is a predicated block.
/// Due to if predication of stores we might create a sequence of "if(pred) a[i]
/// = ...; " blocks. We start with one vectorized basic block. For every
/// conditional block we split this vectorized block. Therefore, every second
/// block will be a predicated one.
static bool isPredicatedBlock(unsigned BlockNum) {
return BlockNum % 2;
}
///\brief Perform cse of induction variable instructions.
static void cse(SmallVector<BasicBlock *, 4> &BBs) {
// Perform simple cse.
SmallDenseMap<Instruction *, Instruction *, 4, CSEDenseMapInfo> CSEMap;
for (unsigned i = 0, e = BBs.size(); i != e; ++i) {
BasicBlock *BB = BBs[i];
for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E;) {
Instruction *In = &*I++;
if (!CSEDenseMapInfo::canHandle(In))
continue;
// Check if we can replace this instruction with any of the
// visited instructions.
if (Instruction *V = CSEMap.lookup(In)) {
In->replaceAllUsesWith(V);
In->eraseFromParent();
continue;
}
// Ignore instructions in conditional blocks. We create "if (pred) a[i] =
// ...;" blocks for predicated stores. Every second block is a predicated
// block.
if (isPredicatedBlock(i))
continue;
CSEMap[In] = In;
}
}
}
/// \brief Adds a 'fast' flag to floating point operations.
static Value *addFastMathFlag(Value *V) {
if (isa<FPMathOperator>(V)){
FastMathFlags Flags;
Flags.setUnsafeAlgebra();
cast<Instruction>(V)->setFastMathFlags(Flags);
}
return V;
}
/// Estimate the overhead of scalarizing a value. Insert and Extract are set if
/// the result needs to be inserted and/or extracted from vectors.
static unsigned getScalarizationOverhead(Type *Ty, bool Insert, bool Extract,
const TargetTransformInfo &TTI) {
if (Ty->isVoidTy())
return 0;
assert(Ty->isVectorTy() && "Can only scalarize vectors");
unsigned Cost = 0;
for (int i = 0, e = Ty->getVectorNumElements(); i < e; ++i) {
if (Insert)
Cost += TTI.getVectorInstrCost(Instruction::InsertElement, Ty, i);
if (Extract)
Cost += TTI.getVectorInstrCost(Instruction::ExtractElement, Ty, i);
}
return Cost;
}
// Estimate cost of a call instruction CI if it were vectorized with factor VF.
// Return the cost of the instruction, including scalarization overhead if it's
// needed. The flag NeedToScalarize shows if the call needs to be scalarized -
// i.e. either vector version isn't available, or is too expensive.
static unsigned getVectorCallCost(CallInst *CI, unsigned VF,
const TargetTransformInfo &TTI,
const TargetLibraryInfo *TLI,
bool &NeedToScalarize) {
Function *F = CI->getCalledFunction();
StringRef FnName = CI->getCalledFunction()->getName();
Type *ScalarRetTy = CI->getType();
SmallVector<Type *, 4> Tys, ScalarTys;
for (auto &ArgOp : CI->arg_operands())
ScalarTys.push_back(ArgOp->getType());
// Estimate cost of scalarized vector call. The source operands are assumed
// to be vectors, so we need to extract individual elements from there,
// execute VF scalar calls, and then gather the result into the vector return
// value.
unsigned ScalarCallCost = TTI.getCallInstrCost(F, ScalarRetTy, ScalarTys);
if (VF == 1)
return ScalarCallCost;
// Compute corresponding vector type for return value and arguments.
Type *RetTy = ToVectorTy(ScalarRetTy, VF);
for (unsigned i = 0, ie = ScalarTys.size(); i != ie; ++i)
Tys.push_back(ToVectorTy(ScalarTys[i], VF));
// Compute costs of unpacking argument values for the scalar calls and
// packing the return values to a vector.
unsigned ScalarizationCost =
getScalarizationOverhead(RetTy, true, false, TTI);
for (unsigned i = 0, ie = Tys.size(); i != ie; ++i)
ScalarizationCost += getScalarizationOverhead(Tys[i], false, true, TTI);
unsigned Cost = ScalarCallCost * VF + ScalarizationCost;
// If we can't emit a vector call for this function, then the currently found
// cost is the cost we need to return.
NeedToScalarize = true;
if (!TLI || !TLI->isFunctionVectorizable(FnName, VF) || CI->isNoBuiltin())
return Cost;
// If the corresponding vector cost is cheaper, return its cost.
unsigned VectorCallCost = TTI.getCallInstrCost(nullptr, RetTy, Tys);
if (VectorCallCost < Cost) {
NeedToScalarize = false;
return VectorCallCost;
}
return Cost;
}
// Estimate cost of an intrinsic call instruction CI if it were vectorized with
// factor VF. Return the cost of the instruction, including scalarization
// overhead if it's needed.
static unsigned getVectorIntrinsicCost(CallInst *CI, unsigned VF,
const TargetTransformInfo &TTI,
const TargetLibraryInfo *TLI) {
Intrinsic::ID ID = getIntrinsicIDForCall(CI, TLI);
assert(ID && "Expected intrinsic call!");
Type *RetTy = ToVectorTy(CI->getType(), VF);
SmallVector<Type *, 4> Tys;
for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i)
Tys.push_back(ToVectorTy(CI->getArgOperand(i)->getType(), VF));
return TTI.getIntrinsicInstrCost(ID, RetTy, Tys);
}
static Type *smallestIntegerVectorType(Type *T1, Type *T2) {
IntegerType *I1 = cast<IntegerType>(T1->getVectorElementType());
IntegerType *I2 = cast<IntegerType>(T2->getVectorElementType());
return I1->getBitWidth() < I2->getBitWidth() ? T1 : T2;
}
static Type *largestIntegerVectorType(Type *T1, Type *T2) {
IntegerType *I1 = cast<IntegerType>(T1->getVectorElementType());
IntegerType *I2 = cast<IntegerType>(T2->getVectorElementType());
return I1->getBitWidth() > I2->getBitWidth() ? T1 : T2;
}
void InnerLoopVectorizer::truncateToMinimalBitwidths() {
// For every instruction `I` in MinBWs, truncate the operands, create a
// truncated version of `I` and reextend its result. InstCombine runs
// later and will remove any ext/trunc pairs.
//
for (auto &KV : MinBWs) {
VectorParts &Parts = WidenMap.get(KV.first);
for (Value *&I : Parts) {
if (I->use_empty())
continue;
Type *OriginalTy = I->getType();
Type *ScalarTruncatedTy = IntegerType::get(OriginalTy->getContext(),
KV.second);
Type *TruncatedTy = VectorType::get(ScalarTruncatedTy,
OriginalTy->getVectorNumElements());
if (TruncatedTy == OriginalTy)
continue;
IRBuilder<> B(cast<Instruction>(I));
auto ShrinkOperand = [&](Value *V) -> Value* {
if (auto *ZI = dyn_cast<ZExtInst>(V))
if (ZI->getSrcTy() == TruncatedTy)
return ZI->getOperand(0);
return B.CreateZExtOrTrunc(V, TruncatedTy);
};
// The actual instruction modification depends on the instruction type,
// unfortunately.
Value *NewI = nullptr;
if (BinaryOperator *BO = dyn_cast<BinaryOperator>(I)) {
NewI = B.CreateBinOp(BO->getOpcode(),
ShrinkOperand(BO->getOperand(0)),
ShrinkOperand(BO->getOperand(1)));
cast<BinaryOperator>(NewI)->copyIRFlags(I);
} else if (ICmpInst *CI = dyn_cast<ICmpInst>(I)) {
NewI = B.CreateICmp(CI->getPredicate(),
ShrinkOperand(CI->getOperand(0)),
ShrinkOperand(CI->getOperand(1)));
} else if (SelectInst *SI = dyn_cast<SelectInst>(I)) {
NewI = B.CreateSelect(SI->getCondition(),
ShrinkOperand(SI->getTrueValue()),
ShrinkOperand(SI->getFalseValue()));
} else if (CastInst *CI = dyn_cast<CastInst>(I)) {
switch (CI->getOpcode()) {
default: llvm_unreachable("Unhandled cast!");
case Instruction::Trunc:
NewI = ShrinkOperand(CI->getOperand(0));
break;
case Instruction::SExt:
NewI = B.CreateSExtOrTrunc(CI->getOperand(0),
smallestIntegerVectorType(OriginalTy,
TruncatedTy));
break;
case Instruction::ZExt:
NewI = B.CreateZExtOrTrunc(CI->getOperand(0),
smallestIntegerVectorType(OriginalTy,
TruncatedTy));
break;
}
} else if (ShuffleVectorInst *SI = dyn_cast<ShuffleVectorInst>(I)) {
auto Elements0 = SI->getOperand(0)->getType()->getVectorNumElements();
auto *O0 =
B.CreateZExtOrTrunc(SI->getOperand(0),
VectorType::get(ScalarTruncatedTy, Elements0));
auto Elements1 = SI->getOperand(1)->getType()->getVectorNumElements();
auto *O1 =
B.CreateZExtOrTrunc(SI->getOperand(1),
VectorType::get(ScalarTruncatedTy, Elements1));
NewI = B.CreateShuffleVector(O0, O1, SI->getMask());
} else if (isa<LoadInst>(I)) {
// Don't do anything with the operands, just extend the result.
continue;
} else {
llvm_unreachable("Unhandled instruction type!");
}
// Lastly, extend the result.
NewI->takeName(cast<Instruction>(I));
Value *Res = B.CreateZExtOrTrunc(NewI, OriginalTy);
I->replaceAllUsesWith(Res);
cast<Instruction>(I)->eraseFromParent();
I = Res;
}
}
// We'll have created a bunch of ZExts that are now parentless. Clean up.
for (auto &KV : MinBWs) {
VectorParts &Parts = WidenMap.get(KV.first);
for (Value *&I : Parts) {
ZExtInst *Inst = dyn_cast<ZExtInst>(I);
if (Inst && Inst->use_empty()) {
Value *NewI = Inst->getOperand(0);
Inst->eraseFromParent();
I = NewI;
}
}
}
}
void InnerLoopVectorizer::vectorizeLoop() {
//===------------------------------------------------===//
//
// Notice: any optimization or new instruction that go
// into the code below should be also be implemented in
// the cost-model.
//
//===------------------------------------------------===//
Constant *Zero = Builder.getInt32(0);
// In order to support reduction variables we need to be able to vectorize
// Phi nodes. Phi nodes have cycles, so we need to vectorize them in two
// stages. First, we create a new vector PHI node with no incoming edges.
// We use this value when we vectorize all of the instructions that use the
// PHI. Next, after all of the instructions in the block are complete we
// add the new incoming edges to the PHI. At this point all of the
// instructions in the basic block are vectorized, so we can use them to
// construct the PHI.
PhiVector RdxPHIsToFix;
// Scan the loop in a topological order to ensure that defs are vectorized
// before users.
LoopBlocksDFS DFS(OrigLoop);
DFS.perform(LI);
// Vectorize all of the blocks in the original loop.
for (LoopBlocksDFS::RPOIterator bb = DFS.beginRPO(),
be = DFS.endRPO(); bb != be; ++bb)
vectorizeBlockInLoop(*bb, &RdxPHIsToFix);
// Insert truncates and extends for any truncated instructions as hints to
// InstCombine.
if (VF > 1)
truncateToMinimalBitwidths();
// At this point every instruction in the original loop is widened to
// a vector form. We are almost done. Now, we need to fix the PHI nodes
// that we vectorized. The PHI nodes are currently empty because we did
// not want to introduce cycles. Notice that the remaining PHI nodes
// that we need to fix are reduction variables.
// Create the 'reduced' values for each of the induction vars.
// The reduced values are the vector values that we scalarize and combine
// after the loop is finished.
for (PhiVector::iterator it = RdxPHIsToFix.begin(), e = RdxPHIsToFix.end();
it != e; ++it) {
PHINode *RdxPhi = *it;
assert(RdxPhi && "Unable to recover vectorized PHI");
// Find the reduction variable descriptor.
assert(Legal->isReductionVariable(RdxPhi) &&
"Unable to find the reduction variable");
RecurrenceDescriptor RdxDesc = (*Legal->getReductionVars())[RdxPhi];
RecurrenceDescriptor::RecurrenceKind RK = RdxDesc.getRecurrenceKind();
TrackingVH<Value> ReductionStartValue = RdxDesc.getRecurrenceStartValue();
Instruction *LoopExitInst = RdxDesc.getLoopExitInstr();
RecurrenceDescriptor::MinMaxRecurrenceKind MinMaxKind =
RdxDesc.getMinMaxRecurrenceKind();
setDebugLocFromInst(Builder, ReductionStartValue);
// We need to generate a reduction vector from the incoming scalar.
// To do so, we need to generate the 'identity' vector and override
// one of the elements with the incoming scalar reduction. We need
// to do it in the vector-loop preheader.
Builder.SetInsertPoint(LoopBypassBlocks[1]->getTerminator());
// This is the vector-clone of the value that leaves the loop.
VectorParts &VectorExit = getVectorValue(LoopExitInst);
Type *VecTy = VectorExit[0]->getType();
// Find the reduction identity variable. Zero for addition, or, xor,
// one for multiplication, -1 for And.
Value *Identity;
Value *VectorStart;
if (RK == RecurrenceDescriptor::RK_IntegerMinMax ||
RK == RecurrenceDescriptor::RK_FloatMinMax) {
// MinMax reduction have the start value as their identify.
if (VF == 1) {
VectorStart = Identity = ReductionStartValue;
} else {
VectorStart = Identity =
Builder.CreateVectorSplat(VF, ReductionStartValue, "minmax.ident");
}
} else {
// Handle other reduction kinds:
Constant *Iden = RecurrenceDescriptor::getRecurrenceIdentity(
RK, VecTy->getScalarType());
if (VF == 1) {
Identity = Iden;
// This vector is the Identity vector where the first element is the
// incoming scalar reduction.
VectorStart = ReductionStartValue;
} else {
Identity = ConstantVector::getSplat(VF, Iden);
// This vector is the Identity vector where the first element is the
// incoming scalar reduction.
VectorStart =
Builder.CreateInsertElement(Identity, ReductionStartValue, Zero);
}
}
// Fix the vector-loop phi.
// Reductions do not have to start at zero. They can start with
// any loop invariant values.
VectorParts &VecRdxPhi = WidenMap.get(RdxPhi);
BasicBlock *Latch = OrigLoop->getLoopLatch();
Value *LoopVal = RdxPhi->getIncomingValueForBlock(Latch);
VectorParts &Val = getVectorValue(LoopVal);
for (unsigned part = 0; part < UF; ++part) {
// Make sure to add the reduction stat value only to the
// first unroll part.
Value *StartVal = (part == 0) ? VectorStart : Identity;
cast<PHINode>(VecRdxPhi[part])->addIncoming(StartVal,
LoopVectorPreHeader);
cast<PHINode>(VecRdxPhi[part])->addIncoming(Val[part],
LoopVectorBody.back());
}
// Before each round, move the insertion point right between
// the PHIs and the values we are going to write.
// This allows us to write both PHINodes and the extractelement
// instructions.
Builder.SetInsertPoint(&*LoopMiddleBlock->getFirstInsertionPt());
VectorParts RdxParts = getVectorValue(LoopExitInst);
setDebugLocFromInst(Builder, LoopExitInst);
// If the vector reduction can be performed in a smaller type, we truncate
// then extend the loop exit value to enable InstCombine to evaluate the
// entire expression in the smaller type.
if (VF > 1 && RdxPhi->getType() != RdxDesc.getRecurrenceType()) {
Type *RdxVecTy = VectorType::get(RdxDesc.getRecurrenceType(), VF);
Builder.SetInsertPoint(LoopVectorBody.back()->getTerminator());
for (unsigned part = 0; part < UF; ++part) {
Value *Trunc = Builder.CreateTrunc(RdxParts[part], RdxVecTy);
Value *Extnd = RdxDesc.isSigned() ? Builder.CreateSExt(Trunc, VecTy)
: Builder.CreateZExt(Trunc, VecTy);
for (Value::user_iterator UI = RdxParts[part]->user_begin();
UI != RdxParts[part]->user_end();)
if (*UI != Trunc) {
(*UI++)->replaceUsesOfWith(RdxParts[part], Extnd);
RdxParts[part] = Extnd;
} else {
++UI;
}
}
Builder.SetInsertPoint(&*LoopMiddleBlock->getFirstInsertionPt());
for (unsigned part = 0; part < UF; ++part)
RdxParts[part] = Builder.CreateTrunc(RdxParts[part], RdxVecTy);
}
// Reduce all of the unrolled parts into a single vector.
Value *ReducedPartRdx = RdxParts[0];
unsigned Op = RecurrenceDescriptor::getRecurrenceBinOp(RK);
setDebugLocFromInst(Builder, ReducedPartRdx);
for (unsigned part = 1; part < UF; ++part) {
if (Op != Instruction::ICmp && Op != Instruction::FCmp)
// Floating point operations had to be 'fast' to enable the reduction.
ReducedPartRdx = addFastMathFlag(
Builder.CreateBinOp((Instruction::BinaryOps)Op, RdxParts[part],
ReducedPartRdx, "bin.rdx"));
else
ReducedPartRdx = RecurrenceDescriptor::createMinMaxOp(
Builder, MinMaxKind, ReducedPartRdx, RdxParts[part]);
}
if (VF > 1) {
// VF is a power of 2 so we can emit the reduction using log2(VF) shuffles
// and vector ops, reducing the set of values being computed by half each
// round.
assert(isPowerOf2_32(VF) &&
"Reduction emission only supported for pow2 vectors!");
Value *TmpVec = ReducedPartRdx;
SmallVector<Constant*, 32> ShuffleMask(VF, nullptr);
for (unsigned i = VF; i != 1; i >>= 1) {
// Move the upper half of the vector to the lower half.
for (unsigned j = 0; j != i/2; ++j)
ShuffleMask[j] = Builder.getInt32(i/2 + j);
// Fill the rest of the mask with undef.
std::fill(&ShuffleMask[i/2], ShuffleMask.end(),
UndefValue::get(Builder.getInt32Ty()));
Value *Shuf =
Builder.CreateShuffleVector(TmpVec,
UndefValue::get(TmpVec->getType()),
ConstantVector::get(ShuffleMask),
"rdx.shuf");
if (Op != Instruction::ICmp && Op != Instruction::FCmp)
// Floating point operations had to be 'fast' to enable the reduction.
TmpVec = addFastMathFlag(Builder.CreateBinOp(
(Instruction::BinaryOps)Op, TmpVec, Shuf, "bin.rdx"));
else
TmpVec = RecurrenceDescriptor::createMinMaxOp(Builder, MinMaxKind,
TmpVec, Shuf);
}
// The result is in the first element of the vector.
ReducedPartRdx = Builder.CreateExtractElement(TmpVec,
Builder.getInt32(0));
// If the reduction can be performed in a smaller type, we need to extend
// the reduction to the wider type before we branch to the original loop.
if (RdxPhi->getType() != RdxDesc.getRecurrenceType())
ReducedPartRdx =
RdxDesc.isSigned()
? Builder.CreateSExt(ReducedPartRdx, RdxPhi->getType())
: Builder.CreateZExt(ReducedPartRdx, RdxPhi->getType());
}
// Create a phi node that merges control-flow from the backedge-taken check
// block and the middle block.
PHINode *BCBlockPhi = PHINode::Create(RdxPhi->getType(), 2, "bc.merge.rdx",
LoopScalarPreHeader->getTerminator());
for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I)
BCBlockPhi->addIncoming(ReductionStartValue, LoopBypassBlocks[I]);
BCBlockPhi->addIncoming(ReducedPartRdx, LoopMiddleBlock);
// Now, we need to fix the users of the reduction variable
// inside and outside of the scalar remainder loop.
// We know that the loop is in LCSSA form. We need to update the
// PHI nodes in the exit blocks.
for (BasicBlock::iterator LEI = LoopExitBlock->begin(),
LEE = LoopExitBlock->end(); LEI != LEE; ++LEI) {
PHINode *LCSSAPhi = dyn_cast<PHINode>(LEI);
if (!LCSSAPhi) break;
// All PHINodes need to have a single entry edge, or two if
// we already fixed them.
assert(LCSSAPhi->getNumIncomingValues() < 3 && "Invalid LCSSA PHI");
// We found our reduction value exit-PHI. Update it with the
// incoming bypass edge.
if (LCSSAPhi->getIncomingValue(0) == LoopExitInst) {
// Add an edge coming from the bypass.
LCSSAPhi->addIncoming(ReducedPartRdx, LoopMiddleBlock);
break;
}
}// end of the LCSSA phi scan.
// Fix the scalar loop reduction variable with the incoming reduction sum
// from the vector body and from the backedge value.
int IncomingEdgeBlockIdx =
(RdxPhi)->getBasicBlockIndex(OrigLoop->getLoopLatch());
assert(IncomingEdgeBlockIdx >= 0 && "Invalid block index");
// Pick the other block.
int SelfEdgeBlockIdx = (IncomingEdgeBlockIdx ? 0 : 1);
(RdxPhi)->setIncomingValue(SelfEdgeBlockIdx, BCBlockPhi);
(RdxPhi)->setIncomingValue(IncomingEdgeBlockIdx, LoopExitInst);
}// end of for each redux variable.
fixLCSSAPHIs();
// Make sure DomTree is updated.
updateAnalysis();
// Predicate any stores.
for (auto KV : PredicatedStores) {
BasicBlock::iterator I(KV.first);
auto *BB = SplitBlock(I->getParent(), &*std::next(I), DT, LI);
auto *T = SplitBlockAndInsertIfThen(KV.second, &*I, /*Unreachable=*/false,
/*BranchWeights=*/nullptr, DT);
I->moveBefore(T);
I->getParent()->setName("pred.store.if");
BB->setName("pred.store.continue");
}
DEBUG(DT->verifyDomTree());
// Remove redundant induction instructions.
cse(LoopVectorBody);
}
void InnerLoopVectorizer::fixLCSSAPHIs() {
for (BasicBlock::iterator LEI = LoopExitBlock->begin(),
LEE = LoopExitBlock->end(); LEI != LEE; ++LEI) {
PHINode *LCSSAPhi = dyn_cast<PHINode>(LEI);
if (!LCSSAPhi) break;
if (LCSSAPhi->getNumIncomingValues() == 1)
LCSSAPhi->addIncoming(UndefValue::get(LCSSAPhi->getType()),
LoopMiddleBlock);
}
}
InnerLoopVectorizer::VectorParts
InnerLoopVectorizer::createEdgeMask(BasicBlock *Src, BasicBlock *Dst) {
assert(std::find(pred_begin(Dst), pred_end(Dst), Src) != pred_end(Dst) &&
"Invalid edge");
// Look for cached value.
std::pair<BasicBlock*, BasicBlock*> Edge(Src, Dst);
EdgeMaskCache::iterator ECEntryIt = MaskCache.find(Edge);
if (ECEntryIt != MaskCache.end())
return ECEntryIt->second;
VectorParts SrcMask = createBlockInMask(Src);
// The terminator has to be a branch inst!
BranchInst *BI = dyn_cast<BranchInst>(Src->getTerminator());
assert(BI && "Unexpected terminator found");
if (BI->isConditional()) {
VectorParts EdgeMask = getVectorValue(BI->getCondition());
if (BI->getSuccessor(0) != Dst)
for (unsigned part = 0; part < UF; ++part)
EdgeMask[part] = Builder.CreateNot(EdgeMask[part]);
for (unsigned part = 0; part < UF; ++part)
EdgeMask[part] = Builder.CreateAnd(EdgeMask[part], SrcMask[part]);
MaskCache[Edge] = EdgeMask;
return EdgeMask;
}
MaskCache[Edge] = SrcMask;
return SrcMask;
}
InnerLoopVectorizer::VectorParts
InnerLoopVectorizer::createBlockInMask(BasicBlock *BB) {
assert(OrigLoop->contains(BB) && "Block is not a part of a loop");
// Loop incoming mask is all-one.
if (OrigLoop->getHeader() == BB) {
Value *C = ConstantInt::get(IntegerType::getInt1Ty(BB->getContext()), 1);
return getVectorValue(C);
}
// This is the block mask. We OR all incoming edges, and with zero.
Value *Zero = ConstantInt::get(IntegerType::getInt1Ty(BB->getContext()), 0);
VectorParts BlockMask = getVectorValue(Zero);
// For each pred:
for (pred_iterator it = pred_begin(BB), e = pred_end(BB); it != e; ++it) {
VectorParts EM = createEdgeMask(*it, BB);
for (unsigned part = 0; part < UF; ++part)
BlockMask[part] = Builder.CreateOr(BlockMask[part], EM[part]);
}
return BlockMask;
}
void InnerLoopVectorizer::widenPHIInstruction(
Instruction *PN, InnerLoopVectorizer::VectorParts &Entry, unsigned UF,
unsigned VF, PhiVector *PV) {
PHINode* P = cast<PHINode>(PN);
// Handle reduction variables:
if (Legal->isReductionVariable(P)) {
for (unsigned part = 0; part < UF; ++part) {
// This is phase one of vectorizing PHIs.
Type *VecTy = (VF == 1) ? PN->getType() :
VectorType::get(PN->getType(), VF);
Entry[part] = PHINode::Create(
VecTy, 2, "vec.phi", &*LoopVectorBody.back()->getFirstInsertionPt());
}
PV->push_back(P);
return;
}
setDebugLocFromInst(Builder, P);
// Check for PHI nodes that are lowered to vector selects.
if (P->getParent() != OrigLoop->getHeader()) {
// We know that all PHIs in non-header blocks are converted into
// selects, so we don't have to worry about the insertion order and we
// can just use the builder.
// At this point we generate the predication tree. There may be
// duplications since this is a simple recursive scan, but future
// optimizations will clean it up.
unsigned NumIncoming = P->getNumIncomingValues();
// Generate a sequence of selects of the form:
// SELECT(Mask3, In3,
// SELECT(Mask2, In2,
// ( ...)))
for (unsigned In = 0; In < NumIncoming; In++) {
VectorParts Cond = createEdgeMask(P->getIncomingBlock(In),
P->getParent());
VectorParts &In0 = getVectorValue(P->getIncomingValue(In));
for (unsigned part = 0; part < UF; ++part) {
// We might have single edge PHIs (blocks) - use an identity
// 'select' for the first PHI operand.
if (In == 0)
Entry[part] = Builder.CreateSelect(Cond[part], In0[part],
In0[part]);
else
// Select between the current value and the previous incoming edge
// based on the incoming mask.
Entry[part] = Builder.CreateSelect(Cond[part], In0[part],
Entry[part], "predphi");
}
}
return;
}
// This PHINode must be an induction variable.
// Make sure that we know about it.
assert(Legal->getInductionVars()->count(P) &&
"Not an induction variable");
InductionDescriptor II = Legal->getInductionVars()->lookup(P);
// FIXME: The newly created binary instructions should contain nsw/nuw flags,
// which can be found from the original scalar operations.
switch (II.getKind()) {
case InductionDescriptor::IK_NoInduction:
llvm_unreachable("Unknown induction");
case InductionDescriptor::IK_IntInduction: {
assert(P->getType() == II.getStartValue()->getType() &&
"Types must match");
// Handle other induction variables that are now based on the
// canonical one.
Value *V = Induction;
if (P != OldInduction) {
V = Builder.CreateSExtOrTrunc(Induction, P->getType());
V = II.transform(Builder, V);
V->setName("offset.idx");
}
Value *Broadcasted = getBroadcastInstrs(V);
// 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] = getStepVector(Broadcasted, VF * part, II.getStepValue());
return;
}
case InductionDescriptor::IK_PtrInduction:
// Handle the pointer induction variable case.
assert(P->getType()->isPointerTy() && "Unexpected type.");
// This is the normalized GEP that starts counting at zero.
Value *PtrInd = Induction;
PtrInd = Builder.CreateSExtOrTrunc(PtrInd, II.getStepValue()->getType());
// This is the vector of results. Notice that we don't generate
// vector geps because scalar geps result in better code.
for (unsigned part = 0; part < UF; ++part) {
if (VF == 1) {
int EltIndex = part;
Constant *Idx = ConstantInt::get(PtrInd->getType(), EltIndex);
Value *GlobalIdx = Builder.CreateAdd(PtrInd, Idx);
Value *SclrGep = II.transform(Builder, GlobalIdx);
SclrGep->setName("next.gep");
Entry[part] = SclrGep;
continue;
}
Value *VecVal = UndefValue::get(VectorType::get(P->getType(), VF));
for (unsigned int i = 0; i < VF; ++i) {
int EltIndex = i + part * VF;
Constant *Idx = ConstantInt::get(PtrInd->getType(), EltIndex);
Value *GlobalIdx = Builder.CreateAdd(PtrInd, Idx);
Value *SclrGep = II.transform(Builder, GlobalIdx);
SclrGep->setName("next.gep");
VecVal = Builder.CreateInsertElement(VecVal, SclrGep,
Builder.getInt32(i),
"insert.gep");
}
Entry[part] = VecVal;
}
return;
}
}
void InnerLoopVectorizer::vectorizeBlockInLoop(BasicBlock *BB, PhiVector *PV) {
// For each instruction in the old loop.
for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
VectorParts &Entry = WidenMap.get(&*it);
switch (it->getOpcode()) {
case Instruction::Br:
// Nothing to do for PHIs and BR, since we already took care of the
// loop control flow instructions.
continue;
case Instruction::PHI: {
// Vectorize PHINodes.
widenPHIInstruction(&*it, Entry, UF, VF, PV);
continue;
}// End of PHI.
case Instruction::Add:
case Instruction::FAdd:
case Instruction::Sub:
case Instruction::FSub:
case Instruction::Mul:
case Instruction::FMul:
case Instruction::UDiv:
case Instruction::SDiv:
case Instruction::FDiv:
case Instruction::URem:
case Instruction::SRem:
case Instruction::FRem:
case Instruction::Shl:
case Instruction::LShr:
case Instruction::AShr:
case Instruction::And:
case Instruction::Or:
case Instruction::Xor: {
// Just widen binops.
BinaryOperator *BinOp = dyn_cast<BinaryOperator>(it);
setDebugLocFromInst(Builder, BinOp);
VectorParts &A = getVectorValue(it->getOperand(0));
VectorParts &B = getVectorValue(it->getOperand(1));
// Use this vector value for all users of the original instruction.
for (unsigned Part = 0; Part < UF; ++Part) {
Value *V = Builder.CreateBinOp(BinOp->getOpcode(), A[Part], B[Part]);
if (BinaryOperator *VecOp = dyn_cast<BinaryOperator>(V))
VecOp->copyIRFlags(BinOp);
Entry[Part] = V;
}
propagateMetadata(Entry, &*it);
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.
auto *SE = PSE.getSE();
bool InvariantCond =
SE->isLoopInvariant(PSE.getSCEV(it->getOperand(0)), OrigLoop);
setDebugLocFromInst(Builder, &*it);
// The condition can be loop invariant but still defined inside the
// loop. This means that we can't just use the original 'cond' value.
// We have to take the 'vectorized' value and pick the first lane.
// Instcombine will make this a no-op.
VectorParts &Cond = getVectorValue(it->getOperand(0));
VectorParts &Op0 = getVectorValue(it->getOperand(1));
VectorParts &Op1 = getVectorValue(it->getOperand(2));
Value *ScalarCond = (VF == 1) ? Cond[0] :
Builder.CreateExtractElement(Cond[0], Builder.getInt32(0));
for (unsigned Part = 0; Part < UF; ++Part) {
Entry[Part] = Builder.CreateSelect(
InvariantCond ? ScalarCond : Cond[Part],
Op0[Part],
Op1[Part]);
}
propagateMetadata(Entry, &*it);
break;
}
case Instruction::ICmp:
case Instruction::FCmp: {
// Widen compares. Generate vector compares.
bool FCmp = (it->getOpcode() == Instruction::FCmp);
CmpInst *Cmp = dyn_cast<CmpInst>(it);
setDebugLocFromInst(Builder, &*it);
VectorParts &A = getVectorValue(it->getOperand(0));
VectorParts &B = getVectorValue(it->getOperand(1));
for (unsigned Part = 0; Part < UF; ++Part) {
Value *C = nullptr;
if (FCmp) {
C = Builder.CreateFCmp(Cmp->getPredicate(), A[Part], B[Part]);
cast<FCmpInst>(C)->copyFastMathFlags(&*it);
} else {
C = Builder.CreateICmp(Cmp->getPredicate(), A[Part], B[Part]);
}
Entry[Part] = C;
}
propagateMetadata(Entry, &*it);
break;
}
case Instruction::Store:
case Instruction::Load:
vectorizeMemoryInstruction(&*it);
break;
case Instruction::ZExt:
case Instruction::SExt:
case Instruction::FPToUI:
case Instruction::FPToSI:
case Instruction::FPExt:
case Instruction::PtrToInt:
case Instruction::IntToPtr:
case Instruction::SIToFP:
case Instruction::UIToFP:
case Instruction::Trunc:
case Instruction::FPTrunc:
case Instruction::BitCast: {
CastInst *CI = dyn_cast<CastInst>(it);
setDebugLocFromInst(Builder, &*it);
/// Optimize the special case where the source is the induction
/// variable. Notice that we can only optimize the 'trunc' case
/// because: a. FP conversions lose precision, b. sext/zext may wrap,
/// c. other casts depend on pointer size.
if (CI->getOperand(0) == OldInduction &&
it->getOpcode() == Instruction::Trunc) {
Value *ScalarCast = Builder.CreateCast(CI->getOpcode(), Induction,
CI->getType());
Value *Broadcasted = getBroadcastInstrs(ScalarCast);
InductionDescriptor II =
Legal->getInductionVars()->lookup(OldInduction);
Constant *Step = ConstantInt::getSigned(
CI->getType(), II.getStepValue()->getSExtValue());
for (unsigned Part = 0; Part < UF; ++Part)
Entry[Part] = getStepVector(Broadcasted, VF * Part, Step);
propagateMetadata(Entry, &*it);
break;
}
/// Vectorize casts.
Type *DestTy = (VF == 1) ? CI->getType() :
VectorType::get(CI->getType(), VF);
VectorParts &A = getVectorValue(it->getOperand(0));
for (unsigned Part = 0; Part < UF; ++Part)
Entry[Part] = Builder.CreateCast(CI->getOpcode(), A[Part], DestTy);
propagateMetadata(Entry, &*it);
break;
}
case Instruction::Call: {
// Ignore dbg intrinsics.
if (isa<DbgInfoIntrinsic>(it))
break;
setDebugLocFromInst(Builder, &*it);
Module *M = BB->getParent()->getParent();
CallInst *CI = cast<CallInst>(it);
StringRef FnName = CI->getCalledFunction()->getName();
Function *F = CI->getCalledFunction();
Type *RetTy = ToVectorTy(CI->getType(), VF);
SmallVector<Type *, 4> Tys;
for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i)
Tys.push_back(ToVectorTy(CI->getArgOperand(i)->getType(), VF));
Intrinsic::ID ID = getIntrinsicIDForCall(CI, TLI);
if (ID &&
(ID == Intrinsic::assume || ID == Intrinsic::lifetime_end ||
ID == Intrinsic::lifetime_start)) {
scalarizeInstruction(&*it);
break;
}
// The flag shows whether we use Intrinsic or a usual Call for vectorized
// version of the instruction.
// Is it beneficial to perform intrinsic call compared to lib call?
bool NeedToScalarize;
unsigned CallCost = getVectorCallCost(CI, VF, *TTI, TLI, NeedToScalarize);
bool UseVectorIntrinsic =
ID && getVectorIntrinsicCost(CI, VF, *TTI, TLI) <= CallCost;
if (!UseVectorIntrinsic && NeedToScalarize) {
scalarizeInstruction(&*it);
break;
}
for (unsigned Part = 0; Part < UF; ++Part) {
SmallVector<Value *, 4> Args;
for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i) {
Value *Arg = CI->getArgOperand(i);
// Some intrinsics have a scalar argument - don't replace it with a
// vector.
if (!UseVectorIntrinsic || !hasVectorInstrinsicScalarOpd(ID, i)) {
VectorParts &VectorArg = getVectorValue(CI->getArgOperand(i));
Arg = VectorArg[Part];
}
Args.push_back(Arg);
}
Function *VectorF;
if (UseVectorIntrinsic) {
// Use vector version of the intrinsic.
Type *TysForDecl[] = {CI->getType()};
if (VF > 1)
TysForDecl[0] = VectorType::get(CI->getType()->getScalarType(), VF);
VectorF = Intrinsic::getDeclaration(M, ID, TysForDecl);
} else {
// Use vector version of the library call.
StringRef VFnName = TLI->getVectorizedFunction(FnName, VF);
assert(!VFnName.empty() && "Vector function name is empty.");
VectorF = M->getFunction(VFnName);
if (!VectorF) {
// Generate a declaration
FunctionType *FTy = FunctionType::get(RetTy, Tys, false);
VectorF =
Function::Create(FTy, Function::ExternalLinkage, VFnName, M);
VectorF->copyAttributesFrom(F);
}
}
assert(VectorF && "Can't create vector function.");
Entry[Part] = Builder.CreateCall(VectorF, Args);
}
propagateMetadata(Entry, &*it);
break;
}
default:
// All other instructions are unsupported. Scalarize them.
scalarizeInstruction(&*it);
break;
}// end of switch.
}// end of for_each instr.
}
void InnerLoopVectorizer::updateAnalysis() {
// Forget the original basic block.
PSE.getSE()->forgetLoop(OrigLoop);
// Update the dominator tree information.
assert(DT->properlyDominates(LoopBypassBlocks.front(), LoopExitBlock) &&
"Entry does not dominate exit.");
for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I)
DT->addNewBlock(LoopBypassBlocks[I], LoopBypassBlocks[I-1]);
DT->addNewBlock(LoopVectorPreHeader, LoopBypassBlocks.back());
// We don't predicate stores by this point, so the vector body should be a
// single loop.
assert(LoopVectorBody.size() == 1 && "Expected single block loop!");
DT->addNewBlock(LoopVectorBody[0], LoopVectorPreHeader);
DT->addNewBlock(LoopMiddleBlock, LoopVectorBody.back());
DT->addNewBlock(LoopScalarPreHeader, LoopBypassBlocks[0]);
DT->changeImmediateDominator(LoopScalarBody, LoopScalarPreHeader);
DT->changeImmediateDominator(LoopExitBlock, LoopBypassBlocks[0]);
DEBUG(DT->verifyDomTree());
}
/// \brief Check whether it is safe to if-convert this phi node.
///
/// Phi nodes with constant expressions that can trap are not safe to if
/// convert.
static bool canIfConvertPHINodes(BasicBlock *BB) {
for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E; ++I) {
PHINode *Phi = dyn_cast<PHINode>(I);
if (!Phi)
return true;
for (unsigned p = 0, e = Phi->getNumIncomingValues(); p != e; ++p)
if (Constant *C = dyn_cast<Constant>(Phi->getIncomingValue(p)))
if (C->canTrap())
return false;
}
return true;
}
bool LoopVectorizationLegality::canVectorizeWithIfConvert() {
if (!EnableIfConversion) {
emitAnalysis(VectorizationReport() << "if-conversion is disabled");
return false;
}
assert(TheLoop->getNumBlocks() > 1 && "Single block loops are vectorizable");
// A list of pointers that we can safely read and write to.
SmallPtrSet<Value *, 8> SafePointes;
// Collect safe addresses.
for (Loop::block_iterator BI = TheLoop->block_begin(),
BE = TheLoop->block_end(); BI != BE; ++BI) {
BasicBlock *BB = *BI;
if (blockNeedsPredication(BB))
continue;
for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E; ++I) {
if (LoadInst *LI = dyn_cast<LoadInst>(I))
SafePointes.insert(LI->getPointerOperand());
else if (StoreInst *SI = dyn_cast<StoreInst>(I))
SafePointes.insert(SI->getPointerOperand());
}
}
// Collect the blocks that need predication.
BasicBlock *Header = TheLoop->getHeader();
for (Loop::block_iterator BI = TheLoop->block_begin(),
BE = TheLoop->block_end(); BI != BE; ++BI) {
BasicBlock *BB = *BI;
// We don't support switch statements inside loops.
if (!isa<BranchInst>(BB->getTerminator())) {
emitAnalysis(VectorizationReport(BB->getTerminator())
<< "loop contains a switch statement");
return false;
}
// We must be able to predicate all blocks that need to be predicated.
if (blockNeedsPredication(BB)) {
if (!blockCanBePredicated(BB, SafePointes)) {
emitAnalysis(VectorizationReport(BB->getTerminator())
<< "control flow cannot be substituted for a select");
return false;
}
} else if (BB != Header && !canIfConvertPHINodes(BB)) {
emitAnalysis(VectorizationReport(BB->getTerminator())
<< "control flow cannot be substituted for a select");
return false;
}
}
// We can if-convert this loop.
return true;
}
bool LoopVectorizationLegality::canVectorize() {
// We must have a loop in canonical form. Loops with indirectbr in them cannot
// be canonicalized.
if (!TheLoop->getLoopPreheader()) {
emitAnalysis(
VectorizationReport() <<
"loop control flow is not understood by vectorizer");
return false;
}
// We can only vectorize innermost loops.
if (!TheLoop->empty()) {
emitAnalysis(VectorizationReport() << "loop is not the innermost loop");
return false;
}
// We must have a single backedge.
if (TheLoop->getNumBackEdges() != 1) {
emitAnalysis(
VectorizationReport() <<
"loop control flow is not understood by vectorizer");
return false;
}
// We must have a single exiting block.
if (!TheLoop->getExitingBlock()) {
emitAnalysis(
VectorizationReport() <<
"loop control flow is not understood by vectorizer");
return false;
}
// We only handle bottom-tested loops, i.e. loop in which the condition is
// checked at the end of each iteration. With that we can assume that all
// instructions in the loop are executed the same number of times.
if (TheLoop->getExitingBlock() != TheLoop->getLoopLatch()) {
emitAnalysis(
VectorizationReport() <<
"loop control flow is not understood by vectorizer");
return false;
}
// We need to have a loop header.
DEBUG(dbgs() << "LV: Found a loop: " <<
TheLoop->getHeader()->getName() << '\n');
// Check if we can if-convert non-single-bb loops.
unsigned NumBlocks = TheLoop->getNumBlocks();
if (NumBlocks != 1 && !canVectorizeWithIfConvert()) {
DEBUG(dbgs() << "LV: Can't if-convert the loop.\n");
return false;
}
// ScalarEvolution needs to be able to find the exit count.
const SCEV *ExitCount = PSE.getSE()->getBackedgeTakenCount(TheLoop);
if (ExitCount == PSE.getSE()->getCouldNotCompute()) {
emitAnalysis(VectorizationReport()
<< "could not determine number of loop iterations");
DEBUG(dbgs() << "LV: SCEV could not compute the loop exit count.\n");
return false;
}
// Check if we can vectorize the instructions and CFG in this loop.
if (!canVectorizeInstrs()) {
DEBUG(dbgs() << "LV: Can't vectorize the instructions or CFG\n");
return false;
}
// Go over each instruction and look at memory deps.
if (!canVectorizeMemory()) {
DEBUG(dbgs() << "LV: Can't vectorize due to memory conflicts\n");
return false;
}
// Collect all of the variables that remain uniform after vectorization.
collectLoopUniforms();
DEBUG(dbgs() << "LV: We can vectorize this loop"
<< (LAI->getRuntimePointerChecking()->Need
? " (with a runtime bound check)"
: "")
<< "!\n");
bool UseInterleaved = TTI->enableInterleavedAccessVectorization();
// If an override option has been passed in for interleaved accesses, use it.
if (EnableInterleavedMemAccesses.getNumOccurrences() > 0)
UseInterleaved = EnableInterleavedMemAccesses;
// Analyze interleaved memory accesses.
if (UseInterleaved)
InterleaveInfo.analyzeInterleaving(Strides);
unsigned SCEVThreshold = VectorizeSCEVCheckThreshold;
if (Hints->getForce() == LoopVectorizeHints::FK_Enabled)
SCEVThreshold = PragmaVectorizeSCEVCheckThreshold;
if (PSE.getUnionPredicate().getComplexity() > SCEVThreshold) {
emitAnalysis(VectorizationReport()
<< "Too many SCEV assumptions need to be made and checked "
<< "at runtime");
DEBUG(dbgs() << "LV: Too many SCEV checks needed.\n");
return false;
}
// Okay! We can vectorize. At this point we don't have any other mem analysis
// which may limit our maximum vectorization factor, so just return true with
// no restrictions.
return true;
}
static Type *convertPointerToIntegerType(const DataLayout &DL, Type *Ty) {
if (Ty->isPointerTy())
return DL.getIntPtrType(Ty);
// It is possible that char's or short's overflow when we ask for the loop's
// trip count, work around this by changing the type size.
if (Ty->getScalarSizeInBits() < 32)
return Type::getInt32Ty(Ty->getContext());
return Ty;
}
static Type* getWiderType(const DataLayout &DL, Type *Ty0, Type *Ty1) {
Ty0 = convertPointerToIntegerType(DL, Ty0);
Ty1 = convertPointerToIntegerType(DL, Ty1);
if (Ty0->getScalarSizeInBits() > Ty1->getScalarSizeInBits())
return Ty0;
return Ty1;
}
/// \brief Check that the instruction has outside loop users and is not an
/// identified reduction variable.
static bool hasOutsideLoopUser(const Loop *TheLoop, Instruction *Inst,
SmallPtrSetImpl<Value *> &Reductions) {
// Reduction instructions are allowed to have exit users. All other
// instructions must not have external users.
if (!Reductions.count(Inst))
//Check that all of the users of the loop are inside the BB.
for (User *U : Inst->users()) {
Instruction *UI = cast<Instruction>(U);
// This user may be a reduction exit value.
if (!TheLoop->contains(UI)) {
DEBUG(dbgs() << "LV: Found an outside user for : " << *UI << '\n');
return true;
}
}
return false;
}
bool LoopVectorizationLegality::canVectorizeInstrs() {
BasicBlock *Header = TheLoop->getHeader();
// Look for the attribute signaling the absence of NaNs.
Function &F = *Header->getParent();
const DataLayout &DL = F.getParent()->getDataLayout();
if (F.hasFnAttribute("no-nans-fp-math"))
HasFunNoNaNAttr =
F.getFnAttribute("no-nans-fp-math").getValueAsString() == "true";
// For each block in the loop.
for (Loop::block_iterator bb = TheLoop->block_begin(),
be = TheLoop->block_end(); bb != be; ++bb) {
// Scan the instructions in the block and look for hazards.
for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e;
++it) {
if (PHINode *Phi = dyn_cast<PHINode>(it)) {
Type *PhiTy = Phi->getType();
// Check that this PHI type is allowed.
if (!PhiTy->isIntegerTy() &&
!PhiTy->isFloatingPointTy() &&
!PhiTy->isPointerTy()) {
emitAnalysis(VectorizationReport(&*it)
<< "loop control flow is not understood by vectorizer");
DEBUG(dbgs() << "LV: Found an non-int non-pointer PHI.\n");
return false;
}
// If this PHINode is not in the header block, then we know that we
// can convert it to select during if-conversion. No need to check if
// the PHIs in this block are induction or reduction variables.
if (*bb != Header) {
// Check that this instruction has no outside users or is an
// identified reduction value with an outside user.
if (!hasOutsideLoopUser(TheLoop, &*it, AllowedExit))
continue;
emitAnalysis(VectorizationReport(&*it) <<
"value could not be identified as "
"an induction or reduction variable");
return false;
}
// We only allow if-converted PHIs with exactly two incoming values.
if (Phi->getNumIncomingValues() != 2) {
emitAnalysis(VectorizationReport(&*it)
<< "control flow not understood by vectorizer");
DEBUG(dbgs() << "LV: Found an invalid PHI.\n");
return false;
}
InductionDescriptor ID;
if (InductionDescriptor::isInductionPHI(Phi, PSE.getSE(), ID)) {
Inductions[Phi] = ID;
// 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 (ID.getKind() == InductionDescriptor::IK_IntInduction &&
ID.getStepValue()->isOne() &&
isa<Constant>(ID.getStartValue()) &&
cast<Constant>(ID.getStartValue())->isNullValue()) {
// 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). We've checked that it begins at zero and
// steps by one, so this is a canonical induction variable.
if (!Induction || PhiTy == WidestIndTy)
Induction = Phi;
}
DEBUG(dbgs() << "LV: Found an induction variable.\n");
// Until we explicitly handle the case of an induction variable with
// an outside loop user we have to give up vectorizing this loop.
if (hasOutsideLoopUser(TheLoop, &*it, AllowedExit)) {
emitAnalysis(VectorizationReport(&*it) <<
"use of induction value outside of the "
"loop is not handled by vectorizer");
return false;
}
continue;
}
RecurrenceDescriptor RedDes;
if (RecurrenceDescriptor::isReductionPHI(Phi, TheLoop, RedDes)) {
if (RedDes.hasUnsafeAlgebra())
Requirements->addUnsafeAlgebraInst(RedDes.getUnsafeAlgebraInst());
AllowedExit.insert(RedDes.getLoopExitInstr());
Reductions[Phi] = RedDes;
continue;
}
emitAnalysis(VectorizationReport(&*it) <<
"value that could not be identified as "
"reduction is used outside the loop");
DEBUG(dbgs() << "LV: Found an unidentified PHI."<< *Phi <<"\n");
return false;
}// end of PHI handling
// We handle calls that:
// * Are debug info intrinsics.
// * Have a mapping to an IR intrinsic.
// * Have a vector version available.
CallInst *CI = dyn_cast<CallInst>(it);
if (CI && !getIntrinsicIDForCall(CI, TLI) && !isa<DbgInfoIntrinsic>(CI) &&
!(CI->getCalledFunction() && TLI &&
TLI->isFunctionVectorizable(CI->getCalledFunction()->getName()))) {
emitAnalysis(VectorizationReport(&*it)
<< "call instruction cannot be vectorized");
DEBUG(dbgs() << "LV: Found a non-intrinsic, non-libfunc callsite.\n");
return false;
}
// Intrinsics such as powi,cttz and ctlz are legal to vectorize if the
// second argument is the same (i.e. loop invariant)
if (CI &&
hasVectorInstrinsicScalarOpd(getIntrinsicIDForCall(CI, TLI), 1)) {
auto *SE = PSE.getSE();
if (!SE->isLoopInvariant(PSE.getSCEV(CI->getOperand(1)), TheLoop)) {
emitAnalysis(VectorizationReport(&*it)
<< "intrinsic instruction cannot be vectorized");
DEBUG(dbgs() << "LV: Found unvectorizable intrinsic " << *CI << "\n");
return false;
}
}
// Check that the instruction return type is vectorizable.
// Also, we can't vectorize extractelement instructions.
if ((!VectorType::isValidElementType(it->getType()) &&
!it->getType()->isVoidTy()) || isa<ExtractElementInst>(it)) {
emitAnalysis(VectorizationReport(&*it)
<< "instruction return type cannot be vectorized");
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)) {
emitAnalysis(VectorizationReport(ST) <<
"store instruction cannot be vectorized");
return false;
}
if (EnableMemAccessVersioning)
collectStridedAccess(ST);
}
if (EnableMemAccessVersioning)
if (LoadInst *LI = dyn_cast<LoadInst>(it))
collectStridedAccess(LI);
// Reduction instructions are allowed to have exit users.
// All other instructions must not have external users.
if (hasOutsideLoopUser(TheLoop, &*it, AllowedExit)) {
emitAnalysis(VectorizationReport(&*it) <<
"value cannot be used outside the loop");
return false;
}
} // next instr.
}
if (!Induction) {
DEBUG(dbgs() << "LV: Did not find one integer induction var.\n");
if (Inductions.empty()) {
emitAnalysis(VectorizationReport()
<< "loop induction variable could not be identified");
return false;
}
}
// Now we know the widest induction type, check if our found induction
// is the same size. If it's not, unset it here and InnerLoopVectorizer
// will create another.
if (Induction && WidestIndTy != Induction->getType())
Induction = nullptr;
return true;
}
void LoopVectorizationLegality::collectStridedAccess(Value *MemAccess) {
Value *Ptr = nullptr;
if (LoadInst *LI = dyn_cast<LoadInst>(MemAccess))
Ptr = LI->getPointerOperand();
else if (StoreInst *SI = dyn_cast<StoreInst>(MemAccess))
Ptr = SI->getPointerOperand();
else
return;
Value *Stride = getStrideFromPointer(Ptr, PSE.getSE(), TheLoop);
if (!Stride)
return;
DEBUG(dbgs() << "LV: Found a strided access that we can version");
DEBUG(dbgs() << " Ptr: " << *Ptr << " Stride: " << *Stride << "\n");
Strides[Ptr] = Stride;
StrideSet.insert(Stride);
}
void LoopVectorizationLegality::collectLoopUniforms() {
// We now know that the loop is vectorizable!
// Collect variables that will remain uniform after vectorization.
std::vector<Value*> Worklist;
BasicBlock *Latch = TheLoop->getLoopLatch();
// Start with the conditional branch and walk up the block.
Worklist.push_back(Latch->getTerminator()->getOperand(0));
// Also add all consecutive pointer values; these values will be uniform
// after vectorization (and subsequent cleanup) and, until revectorization is
// supported, all dependencies must also be uniform.
for (Loop::block_iterator B = TheLoop->block_begin(),
BE = TheLoop->block_end(); B != BE; ++B)
for (BasicBlock::iterator I = (*B)->begin(), IE = (*B)->end();
I != IE; ++I)
if (I->getType()->isPointerTy() && isConsecutivePtr(&*I))
Worklist.insert(Worklist.end(), I->op_begin(), I->op_end());
while (!Worklist.empty()) {
Instruction *I = dyn_cast<Instruction>(Worklist.back());
Worklist.pop_back();
// Look at instructions inside this loop.
// Stop when reaching PHI nodes.
// TODO: we need to follow values all over the loop, not only in this block.
if (!I || !TheLoop->contains(I) || isa<PHINode>(I))
continue;
// This is a known uniform.
Uniforms.insert(I);
// Insert all operands.
Worklist.insert(Worklist.end(), I->op_begin(), I->op_end());
}
}
bool LoopVectorizationLegality::canVectorizeMemory() {
LAI = &LAA->getInfo(TheLoop, Strides);
auto &OptionalReport = LAI->getReport();
if (OptionalReport)
emitAnalysis(VectorizationReport(*OptionalReport));
if (!LAI->canVectorizeMemory())
return false;
if (LAI->hasStoreToLoopInvariantAddress()) {
emitAnalysis(
VectorizationReport()
<< "write to a loop invariant address could not be vectorized");
DEBUG(dbgs() << "LV: We don't allow storing to uniform addresses\n");
return false;
}
Requirements->addRuntimePointerChecks(LAI->getNumRuntimePointerChecks());
PSE.addPredicate(LAI->PSE.getUnionPredicate());
return true;
}
bool LoopVectorizationLegality::isInductionVariable(const Value *V) {
Value *In0 = const_cast<Value*>(V);
PHINode *PN = dyn_cast_or_null<PHINode>(In0);
if (!PN)
return false;
return Inductions.count(PN);
}
bool LoopVectorizationLegality::blockNeedsPredication(BasicBlock *BB) {
return LoopAccessInfo::blockNeedsPredication(BB, TheLoop, DT);
}
bool LoopVectorizationLegality::blockCanBePredicated(BasicBlock *BB,
SmallPtrSetImpl<Value *> &SafePtrs) {
for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
// Check that we don't have a constant expression that can trap as operand.
for (Instruction::op_iterator OI = it->op_begin(), OE = it->op_end();
OI != OE; ++OI) {
if (Constant *C = dyn_cast<Constant>(*OI))
if (C->canTrap())
return false;
}
// We might be able to hoist the load.
if (it->mayReadFromMemory()) {
LoadInst *LI = dyn_cast<LoadInst>(it);
if (!LI)
return false;
if (!SafePtrs.count(LI->getPointerOperand())) {
if (isLegalMaskedLoad(LI->getType(), LI->getPointerOperand())) {
MaskedOp.insert(LI);
continue;
}
return false;
}
}
// We don't predicate stores at the moment.
if (it->mayWriteToMemory()) {
StoreInst *SI = dyn_cast<StoreInst>(it);
// We only support predication of stores in basic blocks with one
// predecessor.
if (!SI)
return false;
bool isSafePtr = (SafePtrs.count(SI->getPointerOperand()) != 0);
bool isSinglePredecessor = SI->getParent()->getSinglePredecessor();
if (++NumPredStores > NumberOfStoresToPredicate || !isSafePtr ||
!isSinglePredecessor) {
// Build a masked store if it is legal for the target, otherwise
// scalarize the block.
bool isLegalMaskedOp =
isLegalMaskedStore(SI->getValueOperand()->getType(),
SI->getPointerOperand());
if (isLegalMaskedOp) {
--NumPredStores;
MaskedOp.insert(SI);
continue;
}
return false;
}
}
if (it->mayThrow())
return false;
// The instructions below can trap.
switch (it->getOpcode()) {
default: continue;
case Instruction::UDiv:
case Instruction::SDiv:
case Instruction::URem:
case Instruction::SRem:
return false;
}
}
return true;
}
void InterleavedAccessInfo::collectConstStridedAccesses(
MapVector<Instruction *, StrideDescriptor> &StrideAccesses,
const ValueToValueMap &Strides) {
// Holds load/store instructions in program order.
SmallVector<Instruction *, 16> AccessList;
for (auto *BB : TheLoop->getBlocks()) {
bool IsPred = LoopAccessInfo::blockNeedsPredication(BB, TheLoop, DT);
for (auto &I : *BB) {
if (!isa<LoadInst>(&I) && !isa<StoreInst>(&I))
continue;
// FIXME: Currently we can't handle mixed accesses and predicated accesses
if (IsPred)
return;
AccessList.push_back(&I);
}
}
if (AccessList.empty())
return;
auto &DL = TheLoop->getHeader()->getModule()->getDataLayout();
for (auto I : AccessList) {
LoadInst *LI = dyn_cast<LoadInst>(I);
StoreInst *SI = dyn_cast<StoreInst>(I);
Value *Ptr = LI ? LI->getPointerOperand() : SI->getPointerOperand();
int Stride = isStridedPtr(PSE, Ptr, TheLoop, Strides);
// The factor of the corresponding interleave group.
unsigned Factor = std::abs(Stride);
// Ignore the access if the factor is too small or too large.
if (Factor < 2 || Factor > MaxInterleaveGroupFactor)
continue;
const SCEV *Scev = replaceSymbolicStrideSCEV(PSE, Strides, Ptr);
PointerType *PtrTy = dyn_cast<PointerType>(Ptr->getType());
unsigned Size = DL.getTypeAllocSize(PtrTy->getElementType());
// An alignment of 0 means target ABI alignment.
unsigned Align = LI ? LI->getAlignment() : SI->getAlignment();
if (!Align)
Align = DL.getABITypeAlignment(PtrTy->getElementType());
StrideAccesses[I] = StrideDescriptor(Stride, Scev, Size, Align);
}
}
// Analyze interleaved accesses and collect them into interleave groups.
//
// Notice that the vectorization on interleaved groups will change instruction
// orders and may break dependences. But the memory dependence check guarantees
// that there is no overlap between two pointers of different strides, element
// sizes or underlying bases.
//
// For pointers sharing the same stride, element size and underlying base, no
// need to worry about Read-After-Write dependences and Write-After-Read
// dependences.
//
// E.g. The RAW dependence: A[i] = a;
// b = A[i];
// This won't exist as it is a store-load forwarding conflict, which has
// already been checked and forbidden in the dependence check.
//
// E.g. The WAR dependence: a = A[i]; // (1)
// A[i] = b; // (2)
// The store group of (2) is always inserted at or below (2), and the load group
// of (1) is always inserted at or above (1). The dependence is safe.
void InterleavedAccessInfo::analyzeInterleaving(
const ValueToValueMap &Strides) {
DEBUG(dbgs() << "LV: Analyzing interleaved accesses...\n");
// Holds all the stride accesses.
MapVector<Instruction *, StrideDescriptor> StrideAccesses;
collectConstStridedAccesses(StrideAccesses, Strides);
if (StrideAccesses.empty())
return;
// Holds all interleaved store groups temporarily.
SmallSetVector<InterleaveGroup *, 4> StoreGroups;
// Search the load-load/write-write pair B-A in bottom-up order and try to
// insert B into the interleave group of A according to 3 rules:
// 1. A and B have the same stride.
// 2. A and B have the same memory object size.
// 3. B belongs to the group according to the distance.
//
// The bottom-up order can avoid breaking the Write-After-Write dependences
// between two pointers of the same base.
// E.g. A[i] = a; (1)
// A[i] = b; (2)
// A[i+1] = c (3)
// We form the group (2)+(3) in front, so (1) has to form groups with accesses
// above (1), which guarantees that (1) is always above (2).
for (auto I = StrideAccesses.rbegin(), E = StrideAccesses.rend(); I != E;
++I) {
Instruction *A = I->first;
StrideDescriptor DesA = I->second;
InterleaveGroup *Group = getInterleaveGroup(A);
if (!Group) {
DEBUG(dbgs() << "LV: Creating an interleave group with:" << *A << '\n');
Group = createInterleaveGroup(A, DesA.Stride, DesA.Align);
}
if (A->mayWriteToMemory())
StoreGroups.insert(Group);
for (auto II = std::next(I); II != E; ++II) {
Instruction *B = II->first;
StrideDescriptor DesB = II->second;
// Ignore if B is already in a group or B is a different memory operation.
if (isInterleaved(B) || A->mayReadFromMemory() != B->mayReadFromMemory())
continue;
// Check the rule 1 and 2.
if (DesB.Stride != DesA.Stride || DesB.Size != DesA.Size)
continue;
// Calculate the distance and prepare for the rule 3.
const SCEVConstant *DistToA = dyn_cast<SCEVConstant>(
PSE.getSE()->getMinusSCEV(DesB.Scev, DesA.Scev));
if (!DistToA)
continue;
int DistanceToA = DistToA->getAPInt().getSExtValue();
// Skip if the distance is not multiple of size as they are not in the
// same group.
if (DistanceToA % static_cast<int>(DesA.Size))
continue;
// The index of B is the index of A plus the related index to A.
int IndexB =
Group->getIndex(A) + DistanceToA / static_cast<int>(DesA.Size);
// Try to insert B into the group.
if (Group->insertMember(B, IndexB, DesB.Align)) {
DEBUG(dbgs() << "LV: Inserted:" << *B << '\n'
<< " into the interleave group with" << *A << '\n');
InterleaveGroupMap[B] = Group;
// Set the first load in program order as the insert position.
if (B->mayReadFromMemory())
Group->setInsertPos(B);
}
} // Iteration on instruction B
} // Iteration on instruction A
// Remove interleaved store groups with gaps.
for (InterleaveGroup *Group : StoreGroups)
if (Group->getNumMembers() != Group->getFactor())
releaseGroup(Group);
}
LoopVectorizationCostModel::VectorizationFactor
LoopVectorizationCostModel::selectVectorizationFactor(bool OptForSize) {
// Width 1 means no vectorize
VectorizationFactor Factor = { 1U, 0U };
if (OptForSize && Legal->getRuntimePointerChecking()->Need) {
emitAnalysis(VectorizationReport() <<
"runtime pointer checks needed. Enable vectorization of this "
"loop with '#pragma clang loop vectorize(enable)' when "
"compiling with -Os/-Oz");
DEBUG(dbgs() <<
"LV: Aborting. Runtime ptr check is required with -Os/-Oz.\n");
return Factor;
}
if (!EnableCondStoresVectorization && Legal->getNumPredStores()) {
emitAnalysis(VectorizationReport() <<
"store that is conditionally executed prevents vectorization");
DEBUG(dbgs() << "LV: No vectorization. There are conditional stores.\n");
return Factor;
}
// Find the trip count.
unsigned TC = PSE.getSE()->getSmallConstantTripCount(TheLoop);
DEBUG(dbgs() << "LV: Found trip count: " << TC << '\n');
MinBWs = computeMinimumValueSizes(TheLoop->getBlocks(), *DB, &TTI);
unsigned SmallestType, WidestType;
std::tie(SmallestType, WidestType) = getSmallestAndWidestTypes();
unsigned WidestRegister = TTI.getRegisterBitWidth(true);
unsigned MaxSafeDepDist = -1U;
if (Legal->getMaxSafeDepDistBytes() != -1U)
MaxSafeDepDist = Legal->getMaxSafeDepDistBytes() * 8;
WidestRegister = ((WidestRegister < MaxSafeDepDist) ?
WidestRegister : MaxSafeDepDist);
unsigned MaxVectorSize = WidestRegister / WidestType;
DEBUG(dbgs() << "LV: The Smallest and Widest types: " << SmallestType << " / "
<< 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 <= 64 && "Did not expect to pack so many elements"
" into one vector!");
unsigned VF = MaxVectorSize;
if (MaximizeBandwidth && !OptForSize) {
// Collect all viable vectorization factors.
SmallVector<unsigned, 8> VFs;
unsigned NewMaxVectorSize = WidestRegister / SmallestType;
for (unsigned VS = MaxVectorSize; VS <= NewMaxVectorSize; VS *= 2)
VFs.push_back(VS);
// For each VF calculate its register usage.
auto RUs = calculateRegisterUsage(VFs);
// Select the largest VF which doesn't require more registers than existing
// ones.
unsigned TargetNumRegisters = TTI.getNumberOfRegisters(true);
for (int i = RUs.size() - 1; i >= 0; --i) {
if (RUs[i].MaxLocalUsers <= TargetNumRegisters) {
VF = VFs[i];
break;
}
}
}
// If we optimize the program for size, avoid creating the tail loop.
if (OptForSize) {
// If we are unable to calculate the trip count then don't try to vectorize.
if (TC < 2) {
emitAnalysis
(VectorizationReport() <<
"unable to calculate the loop count due to complex control flow");
DEBUG(dbgs() << "LV: Aborting. A tail loop is required with -Os/-Oz.\n");
return Factor;
}
// Find the maximum SIMD width that can fit within the trip count.
VF = TC % MaxVectorSize;
if (VF == 0)
VF = MaxVectorSize;
else {
// If the trip count that we found modulo the vectorization factor is not
// zero then we require a tail.
emitAnalysis(VectorizationReport() <<
"cannot optimize for size and vectorize at the "
"same time. Enable vectorization of this loop "
"with '#pragma clang loop vectorize(enable)' "
"when compiling with -Os/-Oz");
DEBUG(dbgs() << "LV: Aborting. A tail loop is required with -Os/-Oz.\n");
return Factor;
}
}
int UserVF = Hints->getWidth();
if (UserVF != 0) {
assert(isPowerOf2_32(UserVF) && "VF needs to be a power of two");
DEBUG(dbgs() << "LV: Using user VF " << UserVF << ".\n");
Factor.Width = UserVF;
return Factor;
}
float Cost = expectedCost(1);
#ifndef NDEBUG
const float ScalarCost = Cost;
#endif /* NDEBUG */
unsigned Width = 1;
DEBUG(dbgs() << "LV: Scalar loop costs: " << (int)ScalarCost << ".\n");
bool ForceVectorization = Hints->getForce() == LoopVectorizeHints::FK_Enabled;
// Ignore scalar width, because the user explicitly wants vectorization.
if (ForceVectorization && VF > 1) {
Width = 2;
Cost = expectedCost(Width) / (float)Width;
}
for (unsigned i=2; i <= VF; i*=2) {
// Notice that the vector loop needs to be executed less times, so
// we need to divide the cost of the vector loops by the width of
// the vector elements.
float VectorCost = expectedCost(i) / (float)i;
DEBUG(dbgs() << "LV: Vector loop of width " << i << " costs: " <<
(int)VectorCost << ".\n");
if (VectorCost < Cost) {
Cost = VectorCost;
Width = i;
}
}
DEBUG(if (ForceVectorization && Width > 1 && Cost >= ScalarCost) dbgs()
<< "LV: Vectorization seems to be not beneficial, "
<< "but was forced by a user.\n");
DEBUG(dbgs() << "LV: Selecting VF: "<< Width << ".\n");
Factor.Width = Width;
Factor.Cost = Width * Cost;
return Factor;
}
std::pair<unsigned, unsigned>
LoopVectorizationCostModel::getSmallestAndWidestTypes() {
unsigned MinWidth = -1U;
unsigned MaxWidth = 8;
const DataLayout &DL = TheFunction->getParent()->getDataLayout();
// 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();
// Skip ignored values.
if (ValuesToIgnore.count(&*it))
continue;
// Only examine Loads, Stores and PHINodes.
if (!isa<LoadInst>(it) && !isa<StoreInst>(it) && !isa<PHINode>(it))
continue;
// Examine PHI nodes that are reduction variables. Update the type to
// account for the recurrence type.
if (PHINode *PN = dyn_cast<PHINode>(it)) {
if (!Legal->isReductionVariable(PN))
continue;
RecurrenceDescriptor RdxDesc = (*Legal->getReductionVars())[PN];
T = RdxDesc.getRecurrenceType();
}
// 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;
MinWidth = std::min(MinWidth,
(unsigned)DL.getTypeSizeInBits(T->getScalarType()));
MaxWidth = std::max(MaxWidth,
(unsigned)DL.getTypeSizeInBits(T->getScalarType()));
}
}
return {MinWidth, MaxWidth};
}
unsigned LoopVectorizationCostModel::selectInterleaveCount(bool OptForSize,
unsigned VF,
unsigned LoopCost) {
// -- The interleave heuristics --
// We interleave 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 interleave count:
// 1. If the code has reductions, then we interleave to break the cross
// iteration dependency.
// 2. If the loop is really small, then we interleave to reduce the loop
// overhead.
// 3. We don't interleave if we think that we will spill registers to memory
// due to the increased register pressure.
// When we optimize for size, we don't interleave.
if (OptForSize)
return 1;
// We used the distance for the interleave count.
if (Legal->getMaxSafeDepDistBytes() != -1U)
return 1;
// Do not interleave loops with a relatively small trip count.
unsigned TC = PSE.getSE()->getSmallConstantTripCount(TheLoop);
if (TC > 1 && TC < TinyTripCountInterleaveThreshold)
return 1;
unsigned TargetNumRegisters = TTI.getNumberOfRegisters(VF > 1);
DEBUG(dbgs() << "LV: The target has " << TargetNumRegisters <<
" registers\n");
if (VF == 1) {
if (ForceTargetNumScalarRegs.getNumOccurrences() > 0)
TargetNumRegisters = ForceTargetNumScalarRegs;
} else {
if (ForceTargetNumVectorRegs.getNumOccurrences() > 0)
TargetNumRegisters = ForceTargetNumVectorRegs;
}
RegisterUsage R = calculateRegisterUsage({VF})[0];
// 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 interleave count using the following formula.
// Subtract the number of loop invariants from the number of available
// registers. These registers are used by all of the interleaved 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. All of this is rounded down if necessary to be
// a power of two. We want power of two interleave count to simplify any
// addressing operations or alignment considerations.
unsigned IC = PowerOf2Floor((TargetNumRegisters - R.LoopInvariantRegs) /
R.MaxLocalUsers);
// Don't count the induction variable as interleaved.
if (EnableIndVarRegisterHeur)
IC = PowerOf2Floor((TargetNumRegisters - R.LoopInvariantRegs - 1) /
std::max(1U, (R.MaxLocalUsers - 1)));
// Clamp the interleave ranges to reasonable counts.
unsigned MaxInterleaveCount = TTI.getMaxInterleaveFactor(VF);
// Check if the user has overridden the max.
if (VF == 1) {
if (ForceTargetMaxScalarInterleaveFactor.getNumOccurrences() > 0)
MaxInterleaveCount = ForceTargetMaxScalarInterleaveFactor;
} else {
if (ForceTargetMaxVectorInterleaveFactor.getNumOccurrences() > 0)
MaxInterleaveCount = ForceTargetMaxVectorInterleaveFactor;
}
// 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 IC to be between the 1 and the max interleave count
// that the target allows.
if (IC > MaxInterleaveCount)
IC = MaxInterleaveCount;
else if (IC < 1)
IC = 1;
// Interleave if we vectorized this loop and there is a reduction that could
// benefit from interleaving.
if (VF > 1 && Legal->getReductionVars()->size()) {
DEBUG(dbgs() << "LV: Interleaving because of reductions.\n");
return IC;
}
// Note that if we've already vectorized the loop we will have done the
// runtime check and so interleaving won't require further checks.
bool InterleavingRequiresRuntimePointerCheck =
(VF == 1 && Legal->getRuntimePointerChecking()->Need);
// We want to interleave small loops in order to reduce the loop overhead and
// potentially expose ILP opportunities.
DEBUG(dbgs() << "LV: Loop cost is " << LoopCost << '\n');
if (!InterleavingRequiresRuntimePointerCheck && LoopCost < SmallLoopCost) {
// We assume that the cost overhead is 1 and we use the cost model
// to estimate the cost of the loop and interleave until the cost of the
// loop overhead is about 5% of the cost of the loop.
unsigned SmallIC =
std::min(IC, (unsigned)PowerOf2Floor(SmallLoopCost / LoopCost));
// Interleave until store/load ports (estimated by max interleave count) are
// saturated.
unsigned NumStores = Legal->getNumStores();
unsigned NumLoads = Legal->getNumLoads();
unsigned StoresIC = IC / (NumStores ? NumStores : 1);
unsigned LoadsIC = IC / (NumLoads ? NumLoads : 1);
// If we have a scalar reduction (vector reductions are already dealt with
// by this point), we can increase the critical path length if the loop
// we're interleaving is inside another loop. Limit, by default to 2, so the
// critical path only gets increased by one reduction operation.
if (Legal->getReductionVars()->size() &&
TheLoop->getLoopDepth() > 1) {
unsigned F = static_cast<unsigned>(MaxNestedScalarReductionIC);
SmallIC = std::min(SmallIC, F);
StoresIC = std::min(StoresIC, F);
LoadsIC = std::min(LoadsIC, F);
}
if (EnableLoadStoreRuntimeInterleave &&
std::max(StoresIC, LoadsIC) > SmallIC) {
DEBUG(dbgs() << "LV: Interleaving to saturate store or load ports.\n");
return std::max(StoresIC, LoadsIC);
}
DEBUG(dbgs() << "LV: Interleaving to reduce branch cost.\n");
return SmallIC;
}
// Interleave if this is a large loop (small loops are already dealt with by
// this point) that could benefit from interleaving.
bool HasReductions = (Legal->getReductionVars()->size() > 0);
if (TTI.enableAggressiveInterleaving(HasReductions)) {
DEBUG(dbgs() << "LV: Interleaving to expose ILP.\n");
return IC;
}
DEBUG(dbgs() << "LV: Not Interleaving.\n");
return 1;
}
SmallVector<LoopVectorizationCostModel::RegisterUsage, 8>
LoopVectorizationCostModel::calculateRegisterUsage(
const SmallVector<unsigned, 8> &VFs) {
// 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 RU;
RU.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) {
RU.NumInstructions += (*bb)->size();
for (Instruction &I : **bb) {
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;
// Get the size of the widest register.
unsigned MaxSafeDepDist = -1U;
if (Legal->getMaxSafeDepDistBytes() != -1U)
MaxSafeDepDist = Legal->getMaxSafeDepDistBytes() * 8;
unsigned WidestRegister =
std::min(TTI.getRegisterBitWidth(true), MaxSafeDepDist);
const DataLayout &DL = TheFunction->getParent()->getDataLayout();
SmallVector<RegisterUsage, 8> RUs(VFs.size());
SmallVector<unsigned, 8> MaxUsages(VFs.size(), 0);
DEBUG(dbgs() << "LV(REG): Calculating max register usage:\n");
// A lambda that gets the register usage for the given type and VF.
auto GetRegUsage = [&DL, WidestRegister](Type *Ty, unsigned VF) {
unsigned TypeSize = DL.getTypeSizeInBits(Ty->getScalarType());
return std::max<unsigned>(1, VF * TypeSize / WidestRegister);
};
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]);
// Skip ignored values.
if (ValuesToIgnore.count(I))
continue;
// For each VF find the maximum usage of registers.
for (unsigned j = 0, e = VFs.size(); j < e; ++j) {
if (VFs[j] == 1) {
MaxUsages[j] = std::max(MaxUsages[j], OpenIntervals.size());
continue;
}
// Count the number of live intervals.
unsigned RegUsage = 0;
for (auto Inst : OpenIntervals) {
// Skip ignored values for VF > 1.
if (VecValuesToIgnore.count(Inst))
continue;
RegUsage += GetRegUsage(Inst->getType(), VFs[j]);
}
MaxUsages[j] = std::max(MaxUsages[j], RegUsage);
}
DEBUG(dbgs() << "LV(REG): At #" << i << " Interval # "
<< OpenIntervals.size() << '\n');
// Add the current instruction to the list of open intervals.
OpenIntervals.insert(I);
}
for (unsigned i = 0, e = VFs.size(); i < e; ++i) {
unsigned Invariant = 0;
if (VFs[i] == 1)
Invariant = LoopInvariants.size();
else {
for (auto Inst : LoopInvariants)
Invariant += GetRegUsage(Inst->getType(), VFs[i]);
}
DEBUG(dbgs() << "LV(REG): VF = " << VFs[i] << '\n');
DEBUG(dbgs() << "LV(REG): Found max usage: " << MaxUsages[i] << '\n');
DEBUG(dbgs() << "LV(REG): Found invariant usage: " << Invariant << '\n');
DEBUG(dbgs() << "LV(REG): LoopSize: " << RU.NumInstructions << '\n');
RU.LoopInvariantRegs = Invariant;
RU.MaxLocalUsers = MaxUsages[i];
RUs[i] = RU;
}
return RUs;
}
unsigned LoopVectorizationCostModel::expectedCost(unsigned VF) {
unsigned Cost = 0;
// For each block.
for (Loop::block_iterator bb = TheLoop->block_begin(),
be = TheLoop->block_end(); bb != be; ++bb) {
unsigned BlockCost = 0;
BasicBlock *BB = *bb;
// For each instruction in the old loop.
for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
// Skip dbg intrinsics.
if (isa<DbgInfoIntrinsic>(it))
continue;
// Skip ignored values.
if (ValuesToIgnore.count(&*it))
continue;
unsigned C = getInstructionCost(&*it, VF);
// Check if we should override the cost.
if (ForceTargetInstructionCost.getNumOccurrences() > 0)
C = ForceTargetInstructionCost;
BlockCost += C;
DEBUG(dbgs() << "LV: Found an estimated cost of " << C << " for VF " <<
VF << " For instruction: " << *it << '\n');
}
// We assume that if-converted blocks have a 50% chance of being executed.
// When the code is scalar then some of the blocks are avoided due to CF.
// When the code is vectorized we execute all code paths.
if (VF == 1 && Legal->blockNeedsPredication(*bb))
BlockCost /= 2;
Cost += BlockCost;
}
return Cost;
}
/// \brief Check whether the address computation for a non-consecutive memory
/// access looks like an unlikely candidate for being merged into the indexing
/// mode.
///
/// We look for a GEP which has one index that is an induction variable and all
/// other indices are loop invariant. If the stride of this access is also
/// within a small bound we decide that this address computation can likely be
/// merged into the addressing mode.
/// In all other cases, we identify the address computation as complex.
static bool isLikelyComplexAddressComputation(Value *Ptr,
LoopVectorizationLegality *Legal,
ScalarEvolution *SE,
const Loop *TheLoop) {
GetElementPtrInst *Gep = dyn_cast<GetElementPtrInst>(Ptr);
if (!Gep)
return true;
// We are looking for a gep with all loop invariant indices except for one
// which should be an induction variable.
unsigned NumOperands = Gep->getNumOperands();
for (unsigned i = 1; i < NumOperands; ++i) {
Value *Opd = Gep->getOperand(i);
if (!SE->isLoopInvariant(SE->getSCEV(Opd), TheLoop) &&
!Legal->isInductionVariable(Opd))
return true;
}
// Now we know we have a GEP ptr, %inv, %ind, %inv. Make sure that the step
// can likely be merged into the address computation.
unsigned MaxMergeDistance = 64;
const SCEVAddRecExpr *AddRec = dyn_cast<SCEVAddRecExpr>(SE->getSCEV(Ptr));
if (!AddRec)
return true;
// Check the step is constant.
const SCEV *Step = AddRec->getStepRecurrence(*SE);
// Calculate the pointer stride and check if it is consecutive.
const SCEVConstant *C = dyn_cast<SCEVConstant>(Step);
if (!C)
return true;
const APInt &APStepVal = C->getAPInt();
// Huge step value - give up.
if (APStepVal.getBitWidth() > 64)
return true;
int64_t StepVal = APStepVal.getSExtValue();
return StepVal > MaxMergeDistance;
}
static bool isStrideMul(Instruction *I, LoopVectorizationLegality *Legal) {
return Legal->hasStride(I->getOperand(0)) ||
Legal->hasStride(I->getOperand(1));
}
unsigned
LoopVectorizationCostModel::getInstructionCost(Instruction *I, unsigned VF) {
// If we know that this instruction will remain uniform, check the cost of
// the scalar version.
if (Legal->isUniformAfterVectorization(I))
VF = 1;
Type *RetTy = I->getType();
if (VF > 1 && MinBWs.count(I))
RetTy = IntegerType::get(RetTy->getContext(), MinBWs[I]);
Type *VectorTy = ToVectorTy(RetTy, VF);
auto SE = PSE.getSE();
// TODO: We need to estimate the cost of intrinsic calls.
switch (I->getOpcode()) {
case Instruction::GetElementPtr:
// We mark this instruction as zero-cost because the cost of GEPs in
// vectorized code depends on whether the corresponding memory instruction
// is scalarized or not. Therefore, we handle GEPs with the memory
// instruction cost.
return 0;
case Instruction::Br: {
return TTI.getCFInstrCost(I->getOpcode());
}
case Instruction::PHI:
//TODO: IF-converted IFs become selects.
return 0;
case Instruction::Add:
case Instruction::FAdd:
case Instruction::Sub:
case Instruction::FSub:
case Instruction::Mul:
case Instruction::FMul:
case Instruction::UDiv:
case Instruction::SDiv:
case Instruction::FDiv:
case Instruction::URem:
case Instruction::SRem:
case Instruction::FRem:
case Instruction::Shl:
case Instruction::LShr:
case Instruction::AShr:
case Instruction::And:
case Instruction::Or:
case Instruction::Xor: {
// Since we will replace the stride by 1 the multiplication should go away.
if (I->getOpcode() == Instruction::Mul && isStrideMul(I, Legal))
return 0;
// 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;
TargetTransformInfo::OperandValueProperties Op1VP =
TargetTransformInfo::OP_None;
TargetTransformInfo::OperandValueProperties Op2VP =
TargetTransformInfo::OP_None;
Value *Op2 = I->getOperand(1);
// Check for a splat of a constant or for a non uniform vector of constants.
if (isa<ConstantInt>(Op2)) {
ConstantInt *CInt = cast<ConstantInt>(Op2);
if (CInt && CInt->getValue().isPowerOf2())
Op2VP = TargetTransformInfo::OP_PowerOf2;
Op2VK = TargetTransformInfo::OK_UniformConstantValue;
} else if (isa<ConstantVector>(Op2) || isa<ConstantDataVector>(Op2)) {
Op2VK = TargetTransformInfo::OK_NonUniformConstantValue;
Constant *SplatValue = cast<Constant>(Op2)->getSplatValue();
if (SplatValue) {
ConstantInt *CInt = dyn_cast<ConstantInt>(SplatValue);
if (CInt && CInt->getValue().isPowerOf2())
Op2VP = TargetTransformInfo::OP_PowerOf2;
Op2VK = TargetTransformInfo::OK_UniformConstantValue;
}
}
return TTI.getArithmeticInstrCost(I->getOpcode(), VectorTy, Op1VK, Op2VK,
Op1VP, Op2VP);
}
case Instruction::Select: {
SelectInst *SI = cast<SelectInst>(I);
const SCEV *CondSCEV = SE->getSCEV(SI->getCondition());
bool ScalarCond = (SE->isLoopInvariant(CondSCEV, TheLoop));
Type *CondTy = SI->getCondition()->getType();
if (!ScalarCond)
CondTy = VectorType::get(CondTy, VF);
return TTI.getCmpSelInstrCost(I->getOpcode(), VectorTy, CondTy);
}
case Instruction::ICmp:
case Instruction::FCmp: {
Type *ValTy = I->getOperand(0)->getType();
Instruction *Op0AsInstruction = dyn_cast<Instruction>(I->getOperand(0));
auto It = MinBWs.find(Op0AsInstruction);
if (VF > 1 && It != MinBWs.end())
ValTy = IntegerType::get(ValTy->getContext(), It->second);
VectorTy = ToVectorTy(ValTy, VF);
return TTI.getCmpSelInstrCost(I->getOpcode(), VectorTy);
}
case Instruction::Store:
case Instruction::Load: {
StoreInst *SI = dyn_cast<StoreInst>(I);
LoadInst *LI = dyn_cast<LoadInst>(I);
Type *ValTy = (SI ? SI->getValueOperand()->getType() :
LI->getType());
VectorTy = ToVectorTy(ValTy, VF);
unsigned Alignment = SI ? SI->getAlignment() : LI->getAlignment();
unsigned AS = SI ? SI->getPointerAddressSpace() :
LI->getPointerAddressSpace();
Value *Ptr = SI ? SI->getPointerOperand() : LI->getPointerOperand();
// We add the cost of address computation here instead of with the gep
// instruction because only here we know whether the operation is
// scalarized.
if (VF == 1)
return TTI.getAddressComputationCost(VectorTy) +
TTI.getMemoryOpCost(I->getOpcode(), VectorTy, Alignment, AS);
// For an interleaved access, calculate the total cost of the whole
// interleave group.
if (Legal->isAccessInterleaved(I)) {
auto Group = Legal->getInterleavedAccessGroup(I);
assert(Group && "Fail to get an interleaved access group.");
// Only calculate the cost once at the insert position.
if (Group->getInsertPos() != I)
return 0;
unsigned InterleaveFactor = Group->getFactor();
Type *WideVecTy =
VectorType::get(VectorTy->getVectorElementType(),
VectorTy->getVectorNumElements() * InterleaveFactor);
// Holds the indices of existing members in an interleaved load group.
// An interleaved store group doesn't need this as it dones't allow gaps.
SmallVector<unsigned, 4> Indices;
if (LI) {
for (unsigned i = 0; i < InterleaveFactor; i++)
if (Group->getMember(i))
Indices.push_back(i);
}
// Calculate the cost of the whole interleaved group.
unsigned Cost = TTI.getInterleavedMemoryOpCost(
I->getOpcode(), WideVecTy, Group->getFactor(), Indices,
Group->getAlignment(), AS);
if (Group->isReverse())
Cost +=
Group->getNumMembers() *
TTI.getShuffleCost(TargetTransformInfo::SK_Reverse, VectorTy, 0);
// FIXME: The interleaved load group with a huge gap could be even more
// expensive than scalar operations. Then we could ignore such group and
// use scalar operations instead.
return Cost;
}
// Scalarized loads/stores.
int ConsecutiveStride = Legal->isConsecutivePtr(Ptr);
bool Reverse = ConsecutiveStride < 0;
const DataLayout &DL = I->getModule()->getDataLayout();
unsigned ScalarAllocatedSize = DL.getTypeAllocSize(ValTy);
unsigned VectorElementSize = DL.getTypeStoreSize(VectorTy) / VF;
if (!ConsecutiveStride || ScalarAllocatedSize != VectorElementSize) {
bool IsComplexComputation =
isLikelyComplexAddressComputation(Ptr, Legal, SE, TheLoop);
unsigned Cost = 0;
// The cost of extracting from the value vector and pointer vector.
Type *PtrTy = ToVectorTy(Ptr->getType(), VF);
for (unsigned i = 0; i < VF; ++i) {
// The cost of extracting the pointer operand.
Cost += TTI.getVectorInstrCost(Instruction::ExtractElement, PtrTy, i);
// In case of STORE, the cost of ExtractElement from the vector.
// In case of LOAD, the cost of InsertElement into the returned
// vector.
Cost += TTI.getVectorInstrCost(SI ? Instruction::ExtractElement :
Instruction::InsertElement,
VectorTy, i);
}
// The cost of the scalar loads/stores.
Cost += VF * TTI.getAddressComputationCost(PtrTy, IsComplexComputation);
Cost += VF * TTI.getMemoryOpCost(I->getOpcode(), ValTy->getScalarType(),
Alignment, AS);
return Cost;
}
// Wide load/stores.
unsigned Cost = TTI.getAddressComputationCost(VectorTy);
if (Legal->isMaskRequired(I))
Cost += TTI.getMaskedMemoryOpCost(I->getOpcode(), VectorTy, Alignment,
AS);
else
Cost += TTI.getMemoryOpCost(I->getOpcode(), VectorTy, Alignment, AS);
if (Reverse)
Cost += TTI.getShuffleCost(TargetTransformInfo::SK_Reverse,
VectorTy, 0);
return Cost;
}
case Instruction::ZExt:
case Instruction::SExt:
case Instruction::FPToUI:
case Instruction::FPToSI:
case Instruction::FPExt:
case Instruction::PtrToInt:
case Instruction::IntToPtr:
case Instruction::SIToFP:
case Instruction::UIToFP:
case Instruction::Trunc:
case Instruction::FPTrunc:
case Instruction::BitCast: {
// We optimize the truncation of induction variable.
// The cost of these is the same as the scalar operation.
if (I->getOpcode() == Instruction::Trunc &&
Legal->isInductionVariable(I->getOperand(0)))
return TTI.getCastInstrCost(I->getOpcode(), I->getType(),
I->getOperand(0)->getType());
Type *SrcScalarTy = I->getOperand(0)->getType();
Type *SrcVecTy = ToVectorTy(SrcScalarTy, VF);
if (VF > 1 && MinBWs.count(I)) {
// This cast is going to be shrunk. This may remove the cast or it might
// turn it into slightly different cast. For example, if MinBW == 16,
// "zext i8 %1 to i32" becomes "zext i8 %1 to i16".
//
// Calculate the modified src and dest types.
Type *MinVecTy = VectorTy;
if (I->getOpcode() == Instruction::Trunc) {
SrcVecTy = smallestIntegerVectorType(SrcVecTy, MinVecTy);
VectorTy = largestIntegerVectorType(ToVectorTy(I->getType(), VF),
MinVecTy);
} else if (I->getOpcode() == Instruction::ZExt ||
I->getOpcode() == Instruction::SExt) {
SrcVecTy = largestIntegerVectorType(SrcVecTy, MinVecTy);
VectorTy = smallestIntegerVectorType(ToVectorTy(I->getType(), VF),
MinVecTy);
}
}
return TTI.getCastInstrCost(I->getOpcode(), VectorTy, SrcVecTy);
}
case Instruction::Call: {
bool NeedToScalarize;
CallInst *CI = cast<CallInst>(I);
unsigned CallCost = getVectorCallCost(CI, VF, TTI, TLI, NeedToScalarize);
if (getIntrinsicIDForCall(CI, TLI))
return std::min(CallCost, getVectorIntrinsicCost(CI, VF, TTI, TLI));
return CallCost;
}
default: {
// We are scalarizing the instruction. Return the cost of the scalar
// instruction, plus the cost of insert and extract into vector
// elements, times the vector width.
unsigned Cost = 0;
if (!RetTy->isVoidTy() && VF != 1) {
unsigned InsCost = TTI.getVectorInstrCost(Instruction::InsertElement,
VectorTy);
unsigned ExtCost = TTI.getVectorInstrCost(Instruction::ExtractElement,
VectorTy);
// The cost of inserting the results plus extracting each one of the
// operands.
Cost += VF * (InsCost + ExtCost * I->getNumOperands());
}
// The cost of executing VF copies of the scalar instruction. This opcode
// is unknown. Assume that it is the same as 'mul'.
Cost += VF * TTI.getArithmeticInstrCost(Instruction::Mul, VectorTy);
return Cost;
}
}// end of switch.
}
char LoopVectorize::ID = 0;
static const char lv_name[] = "Loop Vectorization";
INITIALIZE_PASS_BEGIN(LoopVectorize, LV_NAME, lv_name, false, false)
INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass)
INITIALIZE_PASS_DEPENDENCY(BasicAAWrapperPass)
INITIALIZE_PASS_DEPENDENCY(AAResultsWrapperPass)
INITIALIZE_PASS_DEPENDENCY(GlobalsAAWrapperPass)
INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker)
INITIALIZE_PASS_DEPENDENCY(BlockFrequencyInfoWrapperPass)
INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass)
INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass)
INITIALIZE_PASS_DEPENDENCY(LCSSA)
INITIALIZE_PASS_DEPENDENCY(LoopInfoWrapperPass)
INITIALIZE_PASS_DEPENDENCY(LoopSimplify)
INITIALIZE_PASS_DEPENDENCY(LoopAccessAnalysis)
INITIALIZE_PASS_DEPENDENCY(DemandedBits)
INITIALIZE_PASS_END(LoopVectorize, LV_NAME, lv_name, false, false)
namespace llvm {
Pass *createLoopVectorizePass(bool NoUnrolling, bool AlwaysVectorize) {
return new LoopVectorize(NoUnrolling, AlwaysVectorize);
}
}
bool LoopVectorizationCostModel::isConsecutiveLoadOrStore(Instruction *Inst) {
// Check for a store.
if (StoreInst *ST = dyn_cast<StoreInst>(Inst))
return Legal->isConsecutivePtr(ST->getPointerOperand()) != 0;
// Check for a load.
if (LoadInst *LI = dyn_cast<LoadInst>(Inst))
return Legal->isConsecutivePtr(LI->getPointerOperand()) != 0;
return false;
}
void LoopVectorizationCostModel::collectValuesToIgnore() {
// Ignore ephemeral values.
CodeMetrics::collectEphemeralValues(TheLoop, AC, ValuesToIgnore);
// Ignore type-promoting instructions we identified during reduction
// detection.
for (auto &Reduction : *Legal->getReductionVars()) {
RecurrenceDescriptor &RedDes = Reduction.second;
SmallPtrSetImpl<Instruction *> &Casts = RedDes.getCastInsts();
VecValuesToIgnore.insert(Casts.begin(), Casts.end());
}
// Ignore induction phis that are only used in either GetElementPtr or ICmp
// instruction to exit loop. Induction variables usually have large types and
// can have big impact when estimating register usage.
// This is for when VF > 1.
for (auto &Induction : *Legal->getInductionVars()) {
auto *PN = Induction.first;
auto *UpdateV = PN->getIncomingValueForBlock(TheLoop->getLoopLatch());
// Check that the PHI is only used by the induction increment (UpdateV) or
// by GEPs. Then check that UpdateV is only used by a compare instruction or
// the loop header PHI.
// FIXME: Need precise def-use analysis to determine if this instruction
// variable will be vectorized.
if (std::all_of(PN->user_begin(), PN->user_end(),
[&](const User *U) -> bool {
return U == UpdateV || isa<GetElementPtrInst>(U);
}) &&
std::all_of(UpdateV->user_begin(), UpdateV->user_end(),
[&](const User *U) -> bool {
return U == PN || isa<ICmpInst>(U);
})) {
VecValuesToIgnore.insert(PN);
VecValuesToIgnore.insert(UpdateV);
}
}
// Ignore instructions that will not be vectorized.
// This is for when VF > 1.
for (auto bb = TheLoop->block_begin(), be = TheLoop->block_end(); bb != be;
++bb) {
for (auto &Inst : **bb) {
switch (Inst.getOpcode()) {
case Instruction::GetElementPtr: {
// Ignore GEP if its last operand is an induction variable so that it is
// a consecutive load/store and won't be vectorized as scatter/gather
// pattern.
GetElementPtrInst *Gep = cast<GetElementPtrInst>(&Inst);
unsigned NumOperands = Gep->getNumOperands();
unsigned InductionOperand = getGEPInductionOperand(Gep);
bool GepToIgnore = true;
// Check that all of the gep indices are uniform except for the
// induction operand.
for (unsigned i = 0; i != NumOperands; ++i) {
if (i != InductionOperand &&
!PSE.getSE()->isLoopInvariant(PSE.getSCEV(Gep->getOperand(i)),
TheLoop)) {
GepToIgnore = false;
break;
}
}
if (GepToIgnore)
VecValuesToIgnore.insert(&Inst);
break;
}
}
}
}
}
void InnerLoopUnroller::scalarizeInstruction(Instruction *Instr,
bool IfPredicateStore) {
assert(!Instr->getType()->isAggregateType() && "Can't handle vectors");
// Holds vector parameters or scalars, in case of uniform vals.
SmallVector<VectorParts, 4> Params;
setDebugLocFromInst(Builder, Instr);
// Find all of the vectorized parameters.
for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) {
Value *SrcOp = Instr->getOperand(op);
// If we are accessing the old induction variable, use the new one.
if (SrcOp == OldInduction) {
Params.push_back(getVectorValue(SrcOp));
continue;
}
// Try using previously calculated values.
Instruction *SrcInst = dyn_cast<Instruction>(SrcOp);
// If the src is an instruction that appeared earlier in the basic block
// then it should already be vectorized.
if (SrcInst && OrigLoop->contains(SrcInst)) {
assert(WidenMap.has(SrcInst) && "Source operand is unavailable");
// The parameter is a vector value from earlier.
Params.push_back(WidenMap.get(SrcInst));
} else {
// The parameter is a scalar from outside the loop. Maybe even a constant.
VectorParts Scalars;
Scalars.append(UF, SrcOp);
Params.push_back(Scalars);
}
}
assert(Params.size() == Instr->getNumOperands() &&
"Invalid number of operands");
// Does this instruction return a value ?
bool IsVoidRetTy = Instr->getType()->isVoidTy();
Value *UndefVec = IsVoidRetTy ? nullptr :
UndefValue::get(Instr->getType());
// Create a new entry in the WidenMap and initialize it to Undef or Null.
VectorParts &VecResults = WidenMap.splat(Instr, UndefVec);
VectorParts Cond;
if (IfPredicateStore) {
assert(Instr->getParent()->getSinglePredecessor() &&
"Only support single predecessor blocks");
Cond = createEdgeMask(Instr->getParent()->getSinglePredecessor(),
Instr->getParent());
}
// For each vector unroll 'part':
for (unsigned Part = 0; Part < UF; ++Part) {
// For each scalar that we create:
// Start an "if (pred) a[i] = ..." block.
Value *Cmp = nullptr;
if (IfPredicateStore) {
if (Cond[Part]->getType()->isVectorTy())
Cond[Part] =
Builder.CreateExtractElement(Cond[Part], Builder.getInt32(0));
Cmp = Builder.CreateICmp(ICmpInst::ICMP_EQ, Cond[Part],
ConstantInt::get(Cond[Part]->getType(), 1));
}
Instruction *Cloned = Instr->clone();
if (!IsVoidRetTy)
Cloned->setName(Instr->getName() + ".cloned");
// Replace the operands of the cloned instructions with extracted scalars.
for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) {
Value *Op = Params[op][Part];
Cloned->setOperand(op, Op);
}
// Place the cloned scalar in the new loop.
Builder.Insert(Cloned);
// If the original scalar returns a value we need to place it in a vector
// so that future users will be able to use it.
if (!IsVoidRetTy)
VecResults[Part] = Cloned;
// End if-block.
if (IfPredicateStore)
PredicatedStores.push_back(std::make_pair(cast<StoreInst>(Cloned),
Cmp));
}
}
void InnerLoopUnroller::vectorizeMemoryInstruction(Instruction *Instr) {
StoreInst *SI = dyn_cast<StoreInst>(Instr);
bool IfPredicateStore = (SI && Legal->blockNeedsPredication(SI->getParent()));
return scalarizeInstruction(Instr, IfPredicateStore);
}
Value *InnerLoopUnroller::reverseVector(Value *Vec) {
return Vec;
}
Value *InnerLoopUnroller::getBroadcastInstrs(Value *V) {
return V;
}
Value *InnerLoopUnroller::getStepVector(Value *Val, int StartIdx, Value *Step) {
// When unrolling and the VF is 1, we only need to add a simple scalar.
Type *ITy = Val->getType();
assert(!ITy->isVectorTy() && "Val must be a scalar");
Constant *C = ConstantInt::get(ITy, StartIdx);
return Builder.CreateAdd(Val, Builder.CreateMul(C, Step), "induction");
}
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