SLPVectorizer.cpp

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//===- SLPVectorizer.cpp - A bottom up SLP Vectorizer ---------------------===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
//
// This pass implements the Bottom Up SLP vectorizer. It detects consecutive
// stores that can be put together into vector-stores. Next, it attempts to
// construct vectorizable tree using the use-def chains. If a profitable tree
// was found, the SLP vectorizer performs vectorization on the tree.
//
// The pass is inspired by the work described in the paper:
//  "Loop-Aware SLP in GCC" by Ira Rosen, Dorit Nuzman, Ayal Zaks.
//
//===----------------------------------------------------------------------===//
 
#include "llvm/Transforms/Vectorize/SLPVectorizer.h"
#include "llvm/ADT/DenseMap.h"
#include "llvm/ADT/DenseSet.h"
#include "llvm/ADT/Optional.h"
#include "llvm/ADT/PostOrderIterator.h"
#include "llvm/ADT/STLExtras.h"
#include "llvm/ADT/SetVector.h"
#include "llvm/ADT/SmallBitVector.h"
#include "llvm/ADT/SmallPtrSet.h"
#include "llvm/ADT/SmallSet.h"
#include "llvm/ADT/SmallString.h"
#include "llvm/ADT/Statistic.h"
#include "llvm/ADT/iterator.h"
#include "llvm/ADT/iterator_range.h"
#include "llvm/Analysis/AliasAnalysis.h"
#include "llvm/Analysis/AssumptionCache.h"
#include "llvm/Analysis/CodeMetrics.h"
#include "llvm/Analysis/DemandedBits.h"
#include "llvm/Analysis/GlobalsModRef.h"
#include "llvm/Analysis/IVDescriptors.h"
#include "llvm/Analysis/LoopAccessAnalysis.h"
#include "llvm/Analysis/LoopInfo.h"
#include "llvm/Analysis/MemoryLocation.h"
#include "llvm/Analysis/OptimizationRemarkEmitter.h"
#include "llvm/Analysis/ScalarEvolution.h"
#include "llvm/Analysis/ScalarEvolutionExpressions.h"
#include "llvm/Analysis/TargetLibraryInfo.h"
#include "llvm/Analysis/TargetTransformInfo.h"
#include "llvm/Analysis/ValueTracking.h"
#include "llvm/Analysis/VectorUtils.h"
#include "llvm/IR/Attributes.h"
#include "llvm/IR/BasicBlock.h"
#include "llvm/IR/Constant.h"
#include "llvm/IR/Constants.h"
#include "llvm/IR/DataLayout.h"
#include "llvm/IR/DebugLoc.h"
#include "llvm/IR/DerivedTypes.h"
#include "llvm/IR/Dominators.h"
#include "llvm/IR/Function.h"
#include "llvm/IR/IRBuilder.h"
#include "llvm/IR/InstrTypes.h"
#include "llvm/IR/Instruction.h"
#include "llvm/IR/Instructions.h"
#include "llvm/IR/IntrinsicInst.h"
#include "llvm/IR/Intrinsics.h"
#include "llvm/IR/Module.h"
#include "llvm/IR/NoFolder.h"
#include "llvm/IR/Operator.h"
#include "llvm/IR/PatternMatch.h"
#include "llvm/IR/Type.h"
#include "llvm/IR/Use.h"
#include "llvm/IR/User.h"
#include "llvm/IR/Value.h"
#include "llvm/IR/ValueHandle.h"
#include "llvm/IR/Verifier.h"
#include "llvm/InitializePasses.h"
#include "llvm/Pass.h"
#include "llvm/Support/Casting.h"
#include "llvm/Support/CommandLine.h"
#include "llvm/Support/Compiler.h"
#include "llvm/Support/DOTGraphTraits.h"
#include "llvm/Support/Debug.h"
#include "llvm/Support/ErrorHandling.h"
#include "llvm/Support/GraphWriter.h"
#include "llvm/Support/InstructionCost.h"
#include "llvm/Support/KnownBits.h"
#include "llvm/Support/MathExtras.h"
#include "llvm/Support/raw_ostream.h"
#include "llvm/Transforms/Utils/InjectTLIMappings.h"
#include "llvm/Transforms/Utils/LoopUtils.h"
#include "llvm/Transforms/Vectorize.h"
#include <algorithm>
#include <cassert>
#include <cstdint>
#include <iterator>
#include <memory>
#include <set>
#include <string>
#include <tuple>
#include <utility>
#include <vector>
 
using namespace llvm;
using namespace llvm::PatternMatch;
using namespace slpvectorizer;
 
#define SV_NAME "slp-vectorizer"
#define DEBUG_TYPE "SLP"
 
STATISTIC(NumVectorInstructions, "Number of vector instructions generated");
 
cl::opt<bool> RunSLPVectorization("vectorize-slp", cl::init(true), cl::Hidden,
                                  cl::desc("Run the SLP vectorization passes"));
 
static cl::opt<int>
    SLPCostThreshold("slp-threshold", cl::init(0), cl::Hidden,
                     cl::desc("Only vectorize if you gain more than this "
                              "number "));
 
static cl::opt<bool>
ShouldVectorizeHor("slp-vectorize-hor", cl::init(true), cl::Hidden,
                   cl::desc("Attempt to vectorize horizontal reductions"));
 
static cl::opt<bool> ShouldStartVectorizeHorAtStore(
    "slp-vectorize-hor-store", cl::init(false), cl::Hidden,
    cl::desc(
        "Attempt to vectorize horizontal reductions feeding into a store"));
 
static cl::opt<int>
MaxVectorRegSizeOption("slp-max-reg-size", cl::init(128), cl::Hidden,
    cl::desc("Attempt to vectorize for this register size in bits"));
 
static cl::opt<unsigned>
MaxVFOption("slp-max-vf", cl::init(0), cl::Hidden,
    cl::desc("Maximum SLP vectorization factor (0=unlimited)"));
 
static cl::opt<int>
MaxStoreLookup("slp-max-store-lookup", cl::init(32), cl::Hidden,
    cl::desc("Maximum depth of the lookup for consecutive stores."));
 
/// Limits the size of scheduling regions in a block.
/// It avoid long compile times for _very_ large blocks where vector
/// instructions are spread over a wide range.
/// This limit is way higher than needed by real-world functions.
static cl::opt<int>
ScheduleRegionSizeBudget("slp-schedule-budget", cl::init(100000), cl::Hidden,
    cl::desc("Limit the size of the SLP scheduling region per block"));
 
static cl::opt<int> MinVectorRegSizeOption(
    "slp-min-reg-size", cl::init(128), cl::Hidden,
    cl::desc("Attempt to vectorize for this register size in bits"));
 
static cl::opt<unsigned> RecursionMaxDepth(
    "slp-recursion-max-depth", cl::init(12), cl::Hidden,
    cl::desc("Limit the recursion depth when building a vectorizable tree"));
 
static cl::opt<unsigned> MinTreeSize(
    "slp-min-tree-size", cl::init(3), cl::Hidden,
    cl::desc("Only vectorize small trees if they are fully vectorizable"));
 
// The maximum depth that the look-ahead score heuristic will explore.
// The higher this value, the higher the compilation time overhead.
static cl::opt<int> LookAheadMaxDepth(
    "slp-max-look-ahead-depth", cl::init(2), cl::Hidden,
    cl::desc("The maximum look-ahead depth for operand reordering scores"));
 
// The Look-ahead heuristic goes through the users of the bundle to calculate
// the users cost in getExternalUsesCost(). To avoid compilation time increase
// we limit the number of users visited to this value.
static cl::opt<unsigned> LookAheadUsersBudget(
    "slp-look-ahead-users-budget", cl::init(2), cl::Hidden,
    cl::desc("The maximum number of users to visit while visiting the "
             "predecessors. This prevents compilation time increase."));
 
static cl::opt<bool>
    ViewSLPTree("view-slp-tree", cl::Hidden,
                cl::desc("Display the SLP trees with Graphviz"));
 
// Limit the number of alias checks. The limit is chosen so that
// it has no negative effect on the llvm benchmarks.
static const unsigned AliasedCheckLimit = 10;
 
// Another limit for the alias checks: The maximum distance between load/store
// instructions where alias checks are done.
// This limit is useful for very large basic blocks.
static const unsigned MaxMemDepDistance = 160;
 
/// If the ScheduleRegionSizeBudget is exhausted, we allow small scheduling
/// regions to be handled.
static const int MinScheduleRegionSize = 16;
 
/// Predicate for the element types that the SLP vectorizer supports.
///
/// The most important thing to filter here are types which are invalid in LLVM
/// vectors. We also filter target specific types which have absolutely no
/// meaningful vectorization path such as x86_fp80 and ppc_f128. This just
/// avoids spending time checking the cost model and realizing that they will
/// be inevitably scalarized.
static bool isValidElementType(Type *Ty) {
  return VectorType::isValidElementType(Ty) && !Ty->isX86_FP80Ty() &&
         !Ty->isPPC_FP128Ty();
}
 
/// \returns true if all of the instructions in \p VL are in the same block or
/// false otherwise.
static bool allSameBlock(ArrayRef<Value *> VL) {
  Instruction *I0 = dyn_cast<Instruction>(VL[0]);
  if (!I0)
    return false;
  BasicBlock *BB = I0->getParent();
  for (int I = 1, E = VL.size(); I < E; I++) {
    auto *II = dyn_cast<Instruction>(VL[I]);
    if (!II)
      return false;
 
    if (BB != II->getParent())
      return false;
  }
  return true;
}
 
/// \returns True if all of the values in \p VL are constants (but not
/// globals/constant expressions).
static bool allConstant(ArrayRef<Value *> VL) {
  // Constant expressions and globals can't be vectorized like normal integer/FP
  // constants.
  for (Value *i : VL)
    if (!isa<Constant>(i) || isa<ConstantExpr>(i) || isa<GlobalValue>(i))
      return false;
  return true;
}
 
/// \returns True if all of the values in \p VL are identical.
static bool isSplat(ArrayRef<Value *> VL) {
  for (unsigned i = 1, e = VL.size(); i < e; ++i)
    if (VL[i] != VL[0])
      return false;
  return true;
}
 
/// \returns True if \p I is commutative, handles CmpInst and BinaryOperator.
static bool isCommutative(Instruction *I) {
  if (auto *Cmp = dyn_cast<CmpInst>(I))
    return Cmp->isCommutative();
  if (auto *BO = dyn_cast<BinaryOperator>(I))
    return BO->isCommutative();
  // TODO: This should check for generic Instruction::isCommutative(), but
  //       we need to confirm that the caller code correctly handles Intrinsics
  //       for example (does not have 2 operands).
  return false;
}
 
/// Checks if the vector of instructions can be represented as a shuffle, like:
/// %x0 = extractelement <4 x i8> %x, i32 0
/// %x3 = extractelement <4 x i8> %x, i32 3
/// %y1 = extractelement <4 x i8> %y, i32 1
/// %y2 = extractelement <4 x i8> %y, i32 2
/// %x0x0 = mul i8 %x0, %x0
/// %x3x3 = mul i8 %x3, %x3
/// %y1y1 = mul i8 %y1, %y1
/// %y2y2 = mul i8 %y2, %y2
/// %ins1 = insertelement <4 x i8> poison, i8 %x0x0, i32 0
/// %ins2 = insertelement <4 x i8> %ins1, i8 %x3x3, i32 1
/// %ins3 = insertelement <4 x i8> %ins2, i8 %y1y1, i32 2
/// %ins4 = insertelement <4 x i8> %ins3, i8 %y2y2, i32 3
/// ret <4 x i8> %ins4
/// can be transformed into:
/// %1 = shufflevector <4 x i8> %x, <4 x i8> %y, <4 x i32> <i32 0, i32 3, i32 5,
///                                                         i32 6>
/// %2 = mul <4 x i8> %1, %1
/// ret <4 x i8> %2
/// We convert this initially to something like:
/// %x0 = extractelement <4 x i8> %x, i32 0
/// %x3 = extractelement <4 x i8> %x, i32 3
/// %y1 = extractelement <4 x i8> %y, i32 1
/// %y2 = extractelement <4 x i8> %y, i32 2
/// %1 = insertelement <4 x i8> poison, i8 %x0, i32 0
/// %2 = insertelement <4 x i8> %1, i8 %x3, i32 1
/// %3 = insertelement <4 x i8> %2, i8 %y1, i32 2
/// %4 = insertelement <4 x i8> %3, i8 %y2, i32 3
/// %5 = mul <4 x i8> %4, %4
/// %6 = extractelement <4 x i8> %5, i32 0
/// %ins1 = insertelement <4 x i8> poison, i8 %6, i32 0
/// %7 = extractelement <4 x i8> %5, i32 1
/// %ins2 = insertelement <4 x i8> %ins1, i8 %7, i32 1
/// %8 = extractelement <4 x i8> %5, i32 2
/// %ins3 = insertelement <4 x i8> %ins2, i8 %8, i32 2
/// %9 = extractelement <4 x i8> %5, i32 3
/// %ins4 = insertelement <4 x i8> %ins3, i8 %9, i32 3
/// ret <4 x i8> %ins4
/// InstCombiner transforms this into a shuffle and vector mul
/// Mask will return the Shuffle Mask equivalent to the extracted elements.
/// TODO: Can we split off and reuse the shuffle mask detection from
/// TargetTransformInfo::getInstructionThroughput?
static Optional<TargetTransformInfo::ShuffleKind>
isShuffle(ArrayRef<Value *> VL, SmallVectorImpl<int> &Mask) {
  auto *EI0 = cast<ExtractElementInst>(VL[0]);
  unsigned Size =
      cast<FixedVectorType>(EI0->getVectorOperandType())->getNumElements();
  Value *Vec1 = nullptr;
  Value *Vec2 = nullptr;
  enum ShuffleMode { Unknown, Select, Permute };
  ShuffleMode CommonShuffleMode = Unknown;
  for (unsigned I = 0, E = VL.size(); I < E; ++I) {
    auto *EI = cast<ExtractElementInst>(VL[I]);
    auto *Vec = EI->getVectorOperand();
    // All vector operands must have the same number of vector elements.
    if (cast<FixedVectorType>(Vec->getType())->getNumElements() != Size)
      return None;
    auto *Idx = dyn_cast<ConstantInt>(EI->getIndexOperand());
    if (!Idx)
      return None;
    // Undefined behavior if Idx is negative or >= Size.
    if (Idx->getValue().uge(Size)) {
      Mask.push_back(UndefMaskElem);
      continue;
    }
    unsigned IntIdx = Idx->getValue().getZExtValue();
    Mask.push_back(IntIdx);
    // We can extractelement from undef or poison vector.
    if (isa<UndefValue>(Vec))
      continue;
    // For correct shuffling we have to have at most 2 different vector operands
    // in all extractelement instructions.
    if (!Vec1 || Vec1 == Vec)
      Vec1 = Vec;
    else if (!Vec2 || Vec2 == Vec)
      Vec2 = Vec;
    else
      return None;
    if (CommonShuffleMode == Permute)
      continue;
    // If the extract index is not the same as the operation number, it is a
    // permutation.
    if (IntIdx != I) {
      CommonShuffleMode = Permute;
      continue;
    }
    CommonShuffleMode = Select;
  }
  // If we're not crossing lanes in different vectors, consider it as blending.
  if (CommonShuffleMode == Select && Vec2)
    return TargetTransformInfo::SK_Select;
  // If Vec2 was never used, we have a permutation of a single vector, otherwise
  // we have permutation of 2 vectors.
  return Vec2 ? TargetTransformInfo::SK_PermuteTwoSrc
              : TargetTransformInfo::SK_PermuteSingleSrc;
}
 
namespace {
 
/// Main data required for vectorization of instructions.
struct InstructionsState {
  /// The very first instruction in the list with the main opcode.
  Value *OpValue = nullptr;
 
  /// The main/alternate instruction.
  Instruction *MainOp = nullptr;
  Instruction *AltOp = nullptr;
 
  /// The main/alternate opcodes for the list of instructions.
  unsigned getOpcode() const {
    return MainOp ? MainOp->getOpcode() : 0;
  }
 
  unsigned getAltOpcode() const {
    return AltOp ? AltOp->getOpcode() : 0;
  }
 
  /// Some of the instructions in the list have alternate opcodes.
  bool isAltShuffle() const { return getOpcode() != getAltOpcode(); }
 
  bool isOpcodeOrAlt(Instruction *I) const {
    unsigned CheckedOpcode = I->getOpcode();
    return getOpcode() == CheckedOpcode || getAltOpcode() == CheckedOpcode;
  }
 
  InstructionsState() = delete;
  InstructionsState(Value *OpValue, Instruction *MainOp, Instruction *AltOp)
      : OpValue(OpValue), MainOp(MainOp), AltOp(AltOp) {}
};
 
} // end anonymous namespace
 
/// Chooses the correct key for scheduling data. If \p Op has the same (or
/// alternate) opcode as \p OpValue, the key is \p Op. Otherwise the key is \p
/// OpValue.
static Value *isOneOf(const InstructionsState &S, Value *Op) {
  auto *I = dyn_cast<Instruction>(Op);
  if (I && S.isOpcodeOrAlt(I))
    return Op;
  return S.OpValue;
}
 
/// \returns true if \p Opcode is allowed as part of of the main/alternate
/// instruction for SLP vectorization.
///
/// Example of unsupported opcode is SDIV that can potentially cause UB if the
/// "shuffled out" lane would result in division by zero.
static bool isValidForAlternation(unsigned Opcode) {
  if (Instruction::isIntDivRem(Opcode))
    return false;
 
  return true;
}
 
/// \returns analysis of the Instructions in \p VL described in
/// InstructionsState, the Opcode that we suppose the whole list
/// could be vectorized even if its structure is diverse.
static InstructionsState getSameOpcode(ArrayRef<Value *> VL,
                                       unsigned BaseIndex = 0) {
  // Make sure these are all Instructions.
  if (llvm::any_of(VL, [](Value *V) { return !isa<Instruction>(V); }))
    return InstructionsState(VL[BaseIndex], nullptr, nullptr);
 
  bool IsCastOp = isa<CastInst>(VL[BaseIndex]);
  bool IsBinOp = isa<BinaryOperator>(VL[BaseIndex]);
  unsigned Opcode = cast<Instruction>(VL[BaseIndex])->getOpcode();
  unsigned AltOpcode = Opcode;
  unsigned AltIndex = BaseIndex;
 
  // Check for one alternate opcode from another BinaryOperator.
  // TODO - generalize to support all operators (types, calls etc.).
  for (int Cnt = 0, E = VL.size(); Cnt < E; Cnt++) {
    unsigned InstOpcode = cast<Instruction>(VL[Cnt])->getOpcode();
    if (IsBinOp && isa<BinaryOperator>(VL[Cnt])) {
      if (InstOpcode == Opcode || InstOpcode == AltOpcode)
        continue;
      if (Opcode == AltOpcode && isValidForAlternation(InstOpcode) &&
          isValidForAlternation(Opcode)) {
        AltOpcode = InstOpcode;
        AltIndex = Cnt;
        continue;
      }
    } else if (IsCastOp && isa<CastInst>(VL[Cnt])) {
      Type *Ty0 = cast<Instruction>(VL[BaseIndex])->getOperand(0)->getType();
      Type *Ty1 = cast<Instruction>(VL[Cnt])->getOperand(0)->getType();
      if (Ty0 == Ty1) {
        if (InstOpcode == Opcode || InstOpcode == AltOpcode)
          continue;
        if (Opcode == AltOpcode) {
          assert(isValidForAlternation(Opcode) &&
                 isValidForAlternation(InstOpcode) &&
                 "Cast isn't safe for alternation, logic needs to be updated!");
          AltOpcode = InstOpcode;
          AltIndex = Cnt;
          continue;
        }
      }
    } else if (InstOpcode == Opcode || InstOpcode == AltOpcode)
      continue;
    return InstructionsState(VL[BaseIndex], nullptr, nullptr);
  }
 
  return InstructionsState(VL[BaseIndex], cast<Instruction>(VL[BaseIndex]),
                           cast<Instruction>(VL[AltIndex]));
}
 
/// \returns true if all of the values in \p VL have the same type or false
/// otherwise.
static bool allSameType(ArrayRef<Value *> VL) {
  Type *Ty = VL[0]->getType();
  for (int i = 1, e = VL.size(); i < e; i++)
    if (VL[i]->getType() != Ty)
      return false;
 
  return true;
}
 
/// \returns True if Extract{Value,Element} instruction extracts element Idx.
static Optional<unsigned> getExtractIndex(Instruction *E) {
  unsigned Opcode = E->getOpcode();
  assert((Opcode == Instruction::ExtractElement ||
          Opcode == Instruction::ExtractValue) &&
         "Expected extractelement or extractvalue instruction.");
  if (Opcode == Instruction::ExtractElement) {
    auto *CI = dyn_cast<ConstantInt>(E->getOperand(1));
    if (!CI)
      return None;
    return CI->getZExtValue();
  }
  ExtractValueInst *EI = cast<ExtractValueInst>(E);
  if (EI->getNumIndices() != 1)
    return None;
  return *EI->idx_begin();
}
 
/// \returns True if in-tree use also needs extract. This refers to
/// possible scalar operand in vectorized instruction.
static bool InTreeUserNeedToExtract(Value *Scalar, Instruction *UserInst,
                                    TargetLibraryInfo *TLI) {
  unsigned Opcode = UserInst->getOpcode();
  switch (Opcode) {
  case Instruction::Load: {
    LoadInst *LI = cast<LoadInst>(UserInst);
    return (LI->getPointerOperand() == Scalar);
  }
  case Instruction::Store: {
    StoreInst *SI = cast<StoreInst>(UserInst);
    return (SI->getPointerOperand() == Scalar);
  }
  case Instruction::Call: {
    CallInst *CI = cast<CallInst>(UserInst);
    Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI);
    for (unsigned i = 0, e = CI->getNumArgOperands(); i != e; ++i) {
      if (hasVectorInstrinsicScalarOpd(ID, i))
        return (CI->getArgOperand(i) == Scalar);
    }
    LLVM_FALLTHROUGH;
  }
  default:
    return false;
  }
}
 
/// \returns the AA location that is being access by the instruction.
static MemoryLocation getLocation(Instruction *I, AAResults *AA) {
  if (StoreInst *SI = dyn_cast<StoreInst>(I))
    return MemoryLocation::get(SI);
  if (LoadInst *LI = dyn_cast<LoadInst>(I))
    return MemoryLocation::get(LI);
  return MemoryLocation();
}
 
/// \returns True if the instruction is not a volatile or atomic load/store.
static bool isSimple(Instruction *I) {
  if (LoadInst *LI = dyn_cast<LoadInst>(I))
    return LI->isSimple();
  if (StoreInst *SI = dyn_cast<StoreInst>(I))
    return SI->isSimple();
  if (MemIntrinsic *MI = dyn_cast<MemIntrinsic>(I))
    return !MI->isVolatile();
  return true;
}
 
namespace llvm {
 
static void inversePermutation(ArrayRef<unsigned> Indices,
                               SmallVectorImpl<int> &Mask) {
  Mask.clear();
  const unsigned E = Indices.size();
  Mask.resize(E, E + 1);
  for (unsigned I = 0; I < E; ++I)
    Mask[Indices[I]] = I;
}
 
namespace slpvectorizer {
 
/// Bottom Up SLP Vectorizer.
class BoUpSLP {
  struct TreeEntry;
  struct ScheduleData;
 
public:
  using ValueList = SmallVector<Value *, 8>;
  using InstrList = SmallVector<Instruction *, 16>;
  using ValueSet = SmallPtrSet<Value *, 16>;
  using StoreList = SmallVector<StoreInst *, 8>;
  using ExtraValueToDebugLocsMap =
      MapVector<Value *, SmallVector<Instruction *, 2>>;
  using OrdersType = SmallVector<unsigned, 4>;
 
  BoUpSLP(Function *Func, ScalarEvolution *Se, TargetTransformInfo *Tti,
          TargetLibraryInfo *TLi, AAResults *Aa, LoopInfo *Li,
          DominatorTree *Dt, AssumptionCache *AC, DemandedBits *DB,
          const DataLayout *DL, OptimizationRemarkEmitter *ORE)
      : F(Func), SE(Se), TTI(Tti), TLI(TLi), AA(Aa), LI(Li), DT(Dt), AC(AC),
        DB(DB), DL(DL), ORE(ORE), Builder(Se->getContext()) {
    CodeMetrics::collectEphemeralValues(F, AC, EphValues);
    // Use the vector register size specified by the target unless overridden
    // by a command-line option.
    // TODO: It would be better to limit the vectorization factor based on
    //       data type rather than just register size. For example, x86 AVX has
    //       256-bit registers, but it does not support integer operations
    //       at that width (that requires AVX2).
    if (MaxVectorRegSizeOption.getNumOccurrences())
      MaxVecRegSize = MaxVectorRegSizeOption;
    else
      MaxVecRegSize =
          TTI->getRegisterBitWidth(TargetTransformInfo::RGK_FixedWidthVector)
              .getFixedSize();
 
    if (MinVectorRegSizeOption.getNumOccurrences())
      MinVecRegSize = MinVectorRegSizeOption;
    else
      MinVecRegSize = TTI->getMinVectorRegisterBitWidth();
  }
 
  /// Vectorize the tree that starts with the elements in \p VL.
  /// Returns the vectorized root.
  Value *vectorizeTree();
 
  /// Vectorize the tree but with the list of externally used values \p
  /// ExternallyUsedValues. Values in this MapVector can be replaced but the
  /// generated extractvalue instructions.
  Value *vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues);
 
  /// \returns the cost incurred by unwanted spills and fills, caused by
  /// holding live values over call sites.
  InstructionCost getSpillCost() const;
 
  /// \returns the vectorization cost of the subtree that starts at \p VL.
  /// A negative number means that this is profitable.
  InstructionCost getTreeCost();
 
  /// Construct a vectorizable tree that starts at \p Roots, ignoring users for
  /// the purpose of scheduling and extraction in the \p UserIgnoreLst.
  void buildTree(ArrayRef<Value *> Roots,
                 ArrayRef<Value *> UserIgnoreLst = None);
 
  /// Construct a vectorizable tree that starts at \p Roots, ignoring users for
  /// the purpose of scheduling and extraction in the \p UserIgnoreLst taking
  /// into account (and updating it, if required) list of externally used
  /// values stored in \p ExternallyUsedValues.
  void buildTree(ArrayRef<Value *> Roots,
                 ExtraValueToDebugLocsMap &ExternallyUsedValues,
                 ArrayRef<Value *> UserIgnoreLst = None);
 
  /// Clear the internal data structures that are created by 'buildTree'.
  void deleteTree() {
    VectorizableTree.clear();
    ScalarToTreeEntry.clear();
    MustGather.clear();
    ExternalUses.clear();
    NumOpsWantToKeepOrder.clear();
    NumOpsWantToKeepOriginalOrder = 0;
    for (auto &Iter : BlocksSchedules) {
      BlockScheduling *BS = Iter.second.get();
      BS->clear();
    }
    MinBWs.clear();
    InstrElementSize.clear();
  }
 
  unsigned getTreeSize() const { return VectorizableTree.size(); }
 
  /// Perform LICM and CSE on the newly generated gather sequences.
  void optimizeGatherSequence();
 
  /// \returns The best order of instructions for vectorization.
  Optional<ArrayRef<unsigned>> bestOrder() const {
    assert(llvm::all_of(
               NumOpsWantToKeepOrder,
               [this](const decltype(NumOpsWantToKeepOrder)::value_type &D) {
                 return D.getFirst().size() ==
                        VectorizableTree[0]->Scalars.size();
               }) &&
           "All orders must have the same size as number of instructions in "
           "tree node.");
    auto I = std::max_element(
        NumOpsWantToKeepOrder.begin(), NumOpsWantToKeepOrder.end(),
        [](const decltype(NumOpsWantToKeepOrder)::value_type &D1,
           const decltype(NumOpsWantToKeepOrder)::value_type &D2) {
          return D1.second < D2.second;
        });
    if (I == NumOpsWantToKeepOrder.end() ||
        I->getSecond() <= NumOpsWantToKeepOriginalOrder)
      return None;
 
    return makeArrayRef(I->getFirst());
  }
 
  /// Builds the correct order for root instructions.
  /// If some leaves have the same instructions to be vectorized, we may
  /// incorrectly evaluate the best order for the root node (it is built for the
  /// vector of instructions without repeated instructions and, thus, has less
  /// elements than the root node). This function builds the correct order for
  /// the root node.
  /// For example, if the root node is <a+b, a+c, a+d, f+e>, then the leaves
  /// are <a, a, a, f> and <b, c, d, e>. When we try to vectorize the first
  /// leaf, it will be shrink to <a, b>. If instructions in this leaf should
  /// be reordered, the best order will be <1, 0>. We need to extend this
  /// order for the root node. For the root node this order should look like
  /// <3, 0, 1, 2>. This function extends the order for the reused
  /// instructions.
  void findRootOrder(OrdersType &Order) {
    // If the leaf has the same number of instructions to vectorize as the root
    // - order must be set already.
    unsigned RootSize = VectorizableTree[0]->Scalars.size();
    if (Order.size() == RootSize)
      return;
    SmallVector<unsigned, 4> RealOrder(Order.size());
    std::swap(Order, RealOrder);
    SmallVector<int, 4> Mask;
    inversePermutation(RealOrder, Mask);
    Order.assign(Mask.begin(), Mask.end());
    // The leaf has less number of instructions - need to find the true order of
    // the root.
    // Scan the nodes starting from the leaf back to the root.
    const TreeEntry *PNode = VectorizableTree.back().get();
    SmallVector<const TreeEntry *, 4> Nodes(1, PNode);
    SmallPtrSet<const TreeEntry *, 4> Visited;
    while (!Nodes.empty() && Order.size() != RootSize) {
      const TreeEntry *PNode = Nodes.pop_back_val();
      if (!Visited.insert(PNode).second)
        continue;
      const TreeEntry &Node = *PNode;
      for (const EdgeInfo &EI : Node.UserTreeIndices)
        if (EI.UserTE)
          Nodes.push_back(EI.UserTE);
      if (Node.ReuseShuffleIndices.empty())
        continue;
      // Build the order for the parent node.
      OrdersType NewOrder(Node.ReuseShuffleIndices.size(), RootSize);
      SmallVector<unsigned, 4> OrderCounter(Order.size(), 0);
      // The algorithm of the order extension is:
      // 1. Calculate the number of the same instructions for the order.
      // 2. Calculate the index of the new order: total number of instructions
      // with order less than the order of the current instruction + reuse
      // number of the current instruction.
      // 3. The new order is just the index of the instruction in the original
      // vector of the instructions.
      for (unsigned I : Node.ReuseShuffleIndices)
        ++OrderCounter[Order[I]];
      SmallVector<unsigned, 4> CurrentCounter(Order.size(), 0);
      for (unsigned I = 0, E = Node.ReuseShuffleIndices.size(); I < E; ++I) {
        unsigned ReusedIdx = Node.ReuseShuffleIndices[I];
        unsigned OrderIdx = Order[ReusedIdx];
        unsigned NewIdx = 0;
        for (unsigned J = 0; J < OrderIdx; ++J)
          NewIdx += OrderCounter[J];
        NewIdx += CurrentCounter[OrderIdx];
        ++CurrentCounter[OrderIdx];
        assert(NewOrder[NewIdx] == RootSize &&
               "The order index should not be written already.");
        NewOrder[NewIdx] = I;
      }
      std::swap(Order, NewOrder);
    }
    assert(Order.size() == RootSize &&
           "Root node is expected or the size of the order must be the same as "
           "the number of elements in the root node.");
    assert(llvm::all_of(Order,
                        [RootSize](unsigned Val) { return Val != RootSize; }) &&
           "All indices must be initialized");
  }
 
  /// \return The vector element size in bits to use when vectorizing the
  /// expression tree ending at \p V. If V is a store, the size is the width of
  /// the stored value. Otherwise, the size is the width of the largest loaded
  /// value reaching V. This method is used by the vectorizer to calculate
  /// vectorization factors.
  unsigned getVectorElementSize(Value *V);
 
  /// Compute the minimum type sizes required to represent the entries in a
  /// vectorizable tree.
  void computeMinimumValueSizes();
 
  // \returns maximum vector register size as set by TTI or overridden by cl::opt.
  unsigned getMaxVecRegSize() const {
    return MaxVecRegSize;
  }
 
  // \returns minimum vector register size as set by cl::opt.
  unsigned getMinVecRegSize() const {
    return MinVecRegSize;
  }
 
  unsigned getMaximumVF(unsigned ElemWidth, unsigned Opcode) const {
    unsigned MaxVF = MaxVFOption.getNumOccurrences() ?
      MaxVFOption : TTI->getMaximumVF(ElemWidth, Opcode);
    return MaxVF ? MaxVF : UINT_MAX;
  }
 
  /// Check if homogeneous aggregate is isomorphic to some VectorType.
  /// Accepts homogeneous multidimensional aggregate of scalars/vectors like
  /// {[4 x i16], [4 x i16]}, { <2 x float>, <2 x float> },
  /// {{{i16, i16}, {i16, i16}}, {{i16, i16}, {i16, i16}}} and so on.
  ///
  /// \returns number of elements in vector if isomorphism exists, 0 otherwise.
  unsigned canMapToVector(Type *T, const DataLayout &DL) const;
 
  /// \returns True if the VectorizableTree is both tiny and not fully
  /// vectorizable. We do not vectorize such trees.
  bool isTreeTinyAndNotFullyVectorizable() const;
 
  /// Assume that a legal-sized 'or'-reduction of shifted/zexted loaded values
  /// can be load combined in the backend. Load combining may not be allowed in
  /// the IR optimizer, so we do not want to alter the pattern. For example,
  /// partially transforming a scalar bswap() pattern into vector code is
  /// effectively impossible for the backend to undo.
  /// TODO: If load combining is allowed in the IR optimizer, this analysis
  ///       may not be necessary.
  bool isLoadCombineReductionCandidate(RecurKind RdxKind) const;
 
  /// Assume that a vector of stores of bitwise-or/shifted/zexted loaded values
  /// can be load combined in the backend. Load combining may not be allowed in
  /// the IR optimizer, so we do not want to alter the pattern. For example,
  /// partially transforming a scalar bswap() pattern into vector code is
  /// effectively impossible for the backend to undo.
  /// TODO: If load combining is allowed in the IR optimizer, this analysis
  ///       may not be necessary.
  bool isLoadCombineCandidate() const;
 
  OptimizationRemarkEmitter *getORE() { return ORE; }
 
  /// This structure holds any data we need about the edges being traversed
  /// during buildTree_rec(). We keep track of:
  /// (i) the user TreeEntry index, and
  /// (ii) the index of the edge.
  struct EdgeInfo {
    EdgeInfo() = default;
    EdgeInfo(TreeEntry *UserTE, unsigned EdgeIdx)
        : UserTE(UserTE), EdgeIdx(EdgeIdx) {}
    /// The user TreeEntry.
    TreeEntry *UserTE = nullptr;
    /// The operand index of the use.
    unsigned EdgeIdx = UINT_MAX;
#ifndef NDEBUG
    friend inline raw_ostream &operator<<(raw_ostream &OS,
                                          const BoUpSLP::EdgeInfo &EI) {
      EI.dump(OS);
      return OS;
    }
    /// Debug print.
    void dump(raw_ostream &OS) const {
      OS << "{User:" << (UserTE ? std::to_string(UserTE->Idx) : "null")
         << " EdgeIdx:" << EdgeIdx << "}";
    }
    LLVM_DUMP_METHOD void dump() const { dump(dbgs()); }
#endif
  };
 
  /// A helper data structure to hold the operands of a vector of instructions.
  /// This supports a fixed vector length for all operand vectors.
  class VLOperands {
    /// For each operand we need (i) the value, and (ii) the opcode that it
    /// would be attached to if the expression was in a left-linearized form.
    /// This is required to avoid illegal operand reordering.
    /// For example:
    /// \verbatim
    ///                         0 Op1
    ///                         |/
    /// Op1 Op2   Linearized    + Op2
    ///   \ /     ---------->   |/
    ///    -                    -
    ///
    /// Op1 - Op2            (0 + Op1) - Op2
    /// \endverbatim
    ///
    /// Value Op1 is attached to a '+' operation, and Op2 to a '-'.
    ///
    /// Another way to think of this is to track all the operations across the
    /// path from the operand all the way to the root of the tree and to
    /// calculate the operation that corresponds to this path. For example, the
    /// path from Op2 to the root crosses the RHS of the '-', therefore the
    /// corresponding operation is a '-' (which matches the one in the
    /// linearized tree, as shown above).
    ///
    /// For lack of a better term, we refer to this operation as Accumulated
    /// Path Operation (APO).
    struct OperandData {
      OperandData() = default;
      OperandData(Value *V, bool APO, bool IsUsed)
          : V(V), APO(APO), IsUsed(IsUsed) {}
      /// The operand value.
      Value *V = nullptr;
      /// TreeEntries only allow a single opcode, or an alternate sequence of
      /// them (e.g, +, -). Therefore, we can safely use a boolean value for the
      /// APO. It is set to 'true' if 'V' is attached to an inverse operation
      /// in the left-linearized form (e.g., Sub/Div), and 'false' otherwise
      /// (e.g., Add/Mul)
      bool APO = false;
      /// Helper data for the reordering function.
      bool IsUsed = false;
    };
 
    /// During operand reordering, we are trying to select the operand at lane
    /// that matches best with the operand at the neighboring lane. Our
    /// selection is based on the type of value we are looking for. For example,
    /// if the neighboring lane has a load, we need to look for a load that is
    /// accessing a consecutive address. These strategies are summarized in the
    /// 'ReorderingMode' enumerator.
    enum class ReorderingMode {
      Load,     ///< Matching loads to consecutive memory addresses
      Opcode,   ///< Matching instructions based on opcode (same or alternate)
      Constant, ///< Matching constants
      Splat,    ///< Matching the same instruction multiple times (broadcast)
      Failed,   ///< We failed to create a vectorizable group
    };
 
    using OperandDataVec = SmallVector<OperandData, 2>;
 
    /// A vector of operand vectors.
    SmallVector<OperandDataVec, 4> OpsVec;
 
    const DataLayout &DL;
    ScalarEvolution &SE;
    const BoUpSLP &R;
 
    /// \returns the operand data at \p OpIdx and \p Lane.
    OperandData &getData(unsigned OpIdx, unsigned Lane) {
      return OpsVec[OpIdx][Lane];
    }
 
    /// \returns the operand data at \p OpIdx and \p Lane. Const version.
    const OperandData &getData(unsigned OpIdx, unsigned Lane) const {
      return OpsVec[OpIdx][Lane];
    }
 
    /// Clears the used flag for all entries.
    void clearUsed() {
      for (unsigned OpIdx = 0, NumOperands = getNumOperands();
           OpIdx != NumOperands; ++OpIdx)
        for (unsigned Lane = 0, NumLanes = getNumLanes(); Lane != NumLanes;
             ++Lane)
          OpsVec[OpIdx][Lane].IsUsed = false;
    }
 
    /// Swap the operand at \p OpIdx1 with that one at \p OpIdx2.
    void swap(unsigned OpIdx1, unsigned OpIdx2, unsigned Lane) {
      std::swap(OpsVec[OpIdx1][Lane], OpsVec[OpIdx2][Lane]);
    }
 
    // The hard-coded scores listed here are not very important. When computing
    // the scores of matching one sub-tree with another, we are basically
    // counting the number of values that are matching. So even if all scores
    // are set to 1, we would still get a decent matching result.
    // However, sometimes we have to break ties. For example we may have to
    // choose between matching loads vs matching opcodes. This is what these
    // scores are helping us with: they provide the order of preference.
 
    /// Loads from consecutive memory addresses, e.g. load(A[i]), load(A[i+1]).
    static const int ScoreConsecutiveLoads = 3;
    /// ExtractElementInst from same vector and consecutive indexes.
    static const int ScoreConsecutiveExtracts = 3;
    /// Constants.
    static const int ScoreConstants = 2;
    /// Instructions with the same opcode.
    static const int ScoreSameOpcode = 2;
    /// Instructions with alt opcodes (e.g, add + sub).
    static const int ScoreAltOpcodes = 1;
    /// Identical instructions (a.k.a. splat or broadcast).
    static const int ScoreSplat = 1;
    /// Matching with an undef is preferable to failing.
    static const int ScoreUndef = 1;
    /// Score for failing to find a decent match.
    static const int ScoreFail = 0;
    /// User exteranl to the vectorized code.
    static const int ExternalUseCost = 1;
    /// The user is internal but in a different lane.
    static const int UserInDiffLaneCost = ExternalUseCost;
 
    /// \returns the score of placing \p V1 and \p V2 in consecutive lanes.
    static int getShallowScore(Value *V1, Value *V2, const DataLayout &DL,
                               ScalarEvolution &SE) {
      auto *LI1 = dyn_cast<LoadInst>(V1);
      auto *LI2 = dyn_cast<LoadInst>(V2);
      if (LI1 && LI2) {
        if (LI1->getParent() != LI2->getParent())
          return VLOperands::ScoreFail;
 
        Optional<int> Dist =
            getPointersDiff(LI1->getPointerOperand(), LI2->getPointerOperand(),
                            DL, SE, /*StrictCheck=*/true);
        return (Dist && *Dist == 1) ? VLOperands::ScoreConsecutiveLoads
                                    : VLOperands::ScoreFail;
      }
 
      auto *C1 = dyn_cast<Constant>(V1);
      auto *C2 = dyn_cast<Constant>(V2);
      if (C1 && C2)
        return VLOperands::ScoreConstants;
 
      // Extracts from consecutive indexes of the same vector better score as
      // the extracts could be optimized away.
      Value *EV;
      ConstantInt *Ex1Idx, *Ex2Idx;
      if (match(V1, m_ExtractElt(m_Value(EV), m_ConstantInt(Ex1Idx))) &&
          match(V2, m_ExtractElt(m_Deferred(EV), m_ConstantInt(Ex2Idx))) &&
          Ex1Idx->getZExtValue() + 1 == Ex2Idx->getZExtValue())
        return VLOperands::ScoreConsecutiveExtracts;
 
      auto *I1 = dyn_cast<Instruction>(V1);
      auto *I2 = dyn_cast<Instruction>(V2);
      if (I1 && I2) {
        if (I1 == I2)
          return VLOperands::ScoreSplat;
        InstructionsState S = getSameOpcode({I1, I2});
        // Note: Only consider instructions with <= 2 operands to avoid
        // complexity explosion.
        if (S.getOpcode() && S.MainOp->getNumOperands() <= 2)
          return S.isAltShuffle() ? VLOperands::ScoreAltOpcodes
                                  : VLOperands::ScoreSameOpcode;
      }
 
      if (isa<UndefValue>(V2))
        return VLOperands::ScoreUndef;
 
      return VLOperands::ScoreFail;
    }
 
    /// Holds the values and their lane that are taking part in the look-ahead
    /// score calculation. This is used in the external uses cost calculation.
    SmallDenseMap<Value *, int> InLookAheadValues;
 
    /// \Returns the additinal cost due to uses of \p LHS and \p RHS that are
    /// either external to the vectorized code, or require shuffling.
    int getExternalUsesCost(const std::pair<Value *, int> &LHS,
                            const std::pair<Value *, int> &RHS) {
      int Cost = 0;
      std::array<std::pair<Value *, int>, 2> Values = {{LHS, RHS}};
      for (int Idx = 0, IdxE = Values.size(); Idx != IdxE; ++Idx) {
        Value *V = Values[Idx].first;
        if (isa<Constant>(V)) {
          // Since this is a function pass, it doesn't make semantic sense to
          // walk the users of a subclass of Constant. The users could be in
          // another function, or even another module that happens to be in
          // the same LLVMContext.
          continue;
        }
 
        // Calculate the absolute lane, using the minimum relative lane of LHS
        // and RHS as base and Idx as the offset.
        int Ln = std::min(LHS.second, RHS.second) + Idx;
        assert(Ln >= 0 && "Bad lane calculation");
        unsigned UsersBudget = LookAheadUsersBudget;
        for (User *U : V->users()) {
          if (const TreeEntry *UserTE = R.getTreeEntry(U)) {
            // The user is in the VectorizableTree. Check if we need to insert.
            auto It = llvm::find(UserTE->Scalars, U);
            assert(It != UserTE->Scalars.end() && "U is in UserTE");
            int UserLn = std::distance(UserTE->Scalars.begin(), It);
            assert(UserLn >= 0 && "Bad lane");
            if (UserLn != Ln)
              Cost += UserInDiffLaneCost;
          } else {
            // Check if the user is in the look-ahead code.
            auto It2 = InLookAheadValues.find(U);
            if (It2 != InLookAheadValues.end()) {
              // The user is in the look-ahead code. Check the lane.
              if (It2->second != Ln)
                Cost += UserInDiffLaneCost;
            } else {
              // The user is neither in SLP tree nor in the look-ahead code.
              Cost += ExternalUseCost;
            }
          }
          // Limit the number of visited uses to cap compilation time.
          if (--UsersBudget == 0)
            break;
        }
      }
      return Cost;
    }
 
    /// Go through the operands of \p LHS and \p RHS recursively until \p
    /// MaxLevel, and return the cummulative score. For example:
    /// \verbatim
    ///  A[0]  B[0]  A[1]  B[1]  C[0] D[0]  B[1] A[1]
    ///     \ /         \ /         \ /        \ /
    ///      +           +           +          +
    ///     G1          G2          G3         G4
    /// \endverbatim
    /// The getScoreAtLevelRec(G1, G2) function will try to match the nodes at
    /// each level recursively, accumulating the score. It starts from matching
    /// the additions at level 0, then moves on to the loads (level 1). The
    /// score of G1 and G2 is higher than G1 and G3, because {A[0],A[1]} and
    /// {B[0],B[1]} match with VLOperands::ScoreConsecutiveLoads, while
    /// {A[0],C[0]} has a score of VLOperands::ScoreFail.
    /// Please note that the order of the operands does not matter, as we
    /// evaluate the score of all profitable combinations of operands. In
    /// other words the score of G1 and G4 is the same as G1 and G2. This
    /// heuristic is based on ideas described in:
    ///   Look-ahead SLP: Auto-vectorization in the presence of commutative
    ///   operations, CGO 2018 by Vasileios Porpodas, Rodrigo C. O. Rocha,
    ///   Luís F. W. Góes
    int getScoreAtLevelRec(const std::pair<Value *, int> &LHS,
                           const std::pair<Value *, int> &RHS, int CurrLevel,
                           int MaxLevel) {
 
      Value *V1 = LHS.first;
      Value *V2 = RHS.first;
      // Get the shallow score of V1 and V2.
      int ShallowScoreAtThisLevel =
          std::max((int)ScoreFail, getShallowScore(V1, V2, DL, SE) -
                                       getExternalUsesCost(LHS, RHS));
      int Lane1 = LHS.second;
      int Lane2 = RHS.second;
 
      // If reached MaxLevel,
      //  or if V1 and V2 are not instructions,
      //  or if they are SPLAT,
      //  or if they are not consecutive, early return the current cost.
      auto *I1 = dyn_cast<Instruction>(V1);
      auto *I2 = dyn_cast<Instruction>(V2);
      if (CurrLevel == MaxLevel || !(I1 && I2) || I1 == I2 ||
          ShallowScoreAtThisLevel == VLOperands::ScoreFail ||
          (isa<LoadInst>(I1) && isa<LoadInst>(I2) && ShallowScoreAtThisLevel))
        return ShallowScoreAtThisLevel;
      assert(I1 && I2 && "Should have early exited.");
 
      // Keep track of in-tree values for determining the external-use cost.
      InLookAheadValues[V1] = Lane1;
      InLookAheadValues[V2] = Lane2;
 
      // Contains the I2 operand indexes that got matched with I1 operands.
      SmallSet<unsigned, 4> Op2Used;
 
      // Recursion towards the operands of I1 and I2. We are trying all possbile
      // operand pairs, and keeping track of the best score.
      for (unsigned OpIdx1 = 0, NumOperands1 = I1->getNumOperands();
           OpIdx1 != NumOperands1; ++OpIdx1) {
        // Try to pair op1I with the best operand of I2.
        int MaxTmpScore = 0;
        unsigned MaxOpIdx2 = 0;
        bool FoundBest = false;
        // If I2 is commutative try all combinations.
        unsigned FromIdx = isCommutative(I2) ? 0 : OpIdx1;
        unsigned ToIdx = isCommutative(I2)
                             ? I2->getNumOperands()
                             : std::min(I2->getNumOperands(), OpIdx1 + 1);
        assert(FromIdx <= ToIdx && "Bad index");
        for (unsigned OpIdx2 = FromIdx; OpIdx2 != ToIdx; ++OpIdx2) {
          // Skip operands already paired with OpIdx1.
          if (Op2Used.count(OpIdx2))
            continue;
          // Recursively calculate the cost at each level
          int TmpScore = getScoreAtLevelRec({I1->getOperand(OpIdx1), Lane1},
                                            {I2->getOperand(OpIdx2), Lane2},
                                            CurrLevel + 1, MaxLevel);
          // Look for the best score.
          if (TmpScore > VLOperands::ScoreFail && TmpScore > MaxTmpScore) {
            MaxTmpScore = TmpScore;
            MaxOpIdx2 = OpIdx2;
            FoundBest = true;
          }
        }
        if (FoundBest) {
          // Pair {OpIdx1, MaxOpIdx2} was found to be best. Never revisit it.
          Op2Used.insert(MaxOpIdx2);
          ShallowScoreAtThisLevel += MaxTmpScore;
        }
      }
      return ShallowScoreAtThisLevel;
    }
 
    /// \Returns the look-ahead score, which tells us how much the sub-trees
    /// rooted at \p LHS and \p RHS match, the more they match the higher the
    /// score. This helps break ties in an informed way when we cannot decide on
    /// the order of the operands by just considering the immediate
    /// predecessors.
    int getLookAheadScore(const std::pair<Value *, int> &LHS,
                          const std::pair<Value *, int> &RHS) {
      InLookAheadValues.clear();
      return getScoreAtLevelRec(LHS, RHS, 1, LookAheadMaxDepth);
    }
 
    // Search all operands in Ops[*][Lane] for the one that matches best
    // Ops[OpIdx][LastLane] and return its opreand index.
    // If no good match can be found, return None.
    Optional<unsigned>
    getBestOperand(unsigned OpIdx, int Lane, int LastLane,
                   ArrayRef<ReorderingMode> ReorderingModes) {
      unsigned NumOperands = getNumOperands();
 
      // The operand of the previous lane at OpIdx.
      Value *OpLastLane = getData(OpIdx, LastLane).V;
 
      // Our strategy mode for OpIdx.
      ReorderingMode RMode = ReorderingModes[OpIdx];
 
      // The linearized opcode of the operand at OpIdx, Lane.
      bool OpIdxAPO = getData(OpIdx, Lane).APO;
 
      // The best operand index and its score.
      // Sometimes we have more than one option (e.g., Opcode and Undefs), so we
      // are using the score to differentiate between the two.
      struct BestOpData {
        Optional<unsigned> Idx = None;
        unsigned Score = 0;
      } BestOp;
 
      // Iterate through all unused operands and look for the best.
      for (unsigned Idx = 0; Idx != NumOperands; ++Idx) {
        // Get the operand at Idx and Lane.
        OperandData &OpData = getData(Idx, Lane);
        Value *Op = OpData.V;
        bool OpAPO = OpData.APO;
 
        // Skip already selected operands.
        if (OpData.IsUsed)
          continue;
 
        // Skip if we are trying to move the operand to a position with a
        // different opcode in the linearized tree form. This would break the
        // semantics.
        if (OpAPO != OpIdxAPO)
          continue;
 
        // Look for an operand that matches the current mode.
        switch (RMode) {
        case ReorderingMode::Load:
        case ReorderingMode::Constant:
        case ReorderingMode::Opcode: {
          bool LeftToRight = Lane > LastLane;
          Value *OpLeft = (LeftToRight) ? OpLastLane : Op;
          Value *OpRight = (LeftToRight) ? Op : OpLastLane;
          unsigned Score =
              getLookAheadScore({OpLeft, LastLane}, {OpRight, Lane});
          if (Score > BestOp.Score) {
            BestOp.Idx = Idx;
            BestOp.Score = Score;
          }
          break;
        }
        case ReorderingMode::Splat:
          if (Op == OpLastLane)
            BestOp.Idx = Idx;
          break;
        case ReorderingMode::Failed:
          return None;
        }
      }
 
      if (BestOp.Idx) {
        getData(BestOp.Idx.getValue(), Lane).IsUsed = true;
        return BestOp.Idx;
      }
      // If we could not find a good match return None.
      return None;
    }
 
    /// Helper for reorderOperandVecs. \Returns the lane that we should start
    /// reordering from. This is the one which has the least number of operands
    /// that can freely move about.
    unsigned getBestLaneToStartReordering() const {
      unsigned BestLane = 0;
      unsigned Min = UINT_MAX;
      for (unsigned Lane = 0, NumLanes = getNumLanes(); Lane != NumLanes;
           ++Lane) {
        unsigned NumFreeOps = getMaxNumOperandsThatCanBeReordered(Lane);
        if (NumFreeOps < Min) {
          Min = NumFreeOps;
          BestLane = Lane;
        }
      }
      return BestLane;
    }
 
    /// \Returns the maximum number of operands that are allowed to be reordered
    /// for \p Lane. This is used as a heuristic for selecting the first lane to
    /// start operand reordering.
    unsigned getMaxNumOperandsThatCanBeReordered(unsigned Lane) const {
      unsigned CntTrue = 0;
      unsigned NumOperands = getNumOperands();
      // Operands with the same APO can be reordered. We therefore need to count
      // how many of them we have for each APO, like this: Cnt[APO] = x.
      // Since we only have two APOs, namely true and false, we can avoid using
      // a map. Instead we can simply count the number of operands that
      // correspond to one of them (in this case the 'true' APO), and calculate
      // the other by subtracting it from the total number of operands.
      for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx)
        if (getData(OpIdx, Lane).APO)
          ++CntTrue;
      unsigned CntFalse = NumOperands - CntTrue;
      return std::max(CntTrue, CntFalse);
    }
 
    /// Go through the instructions in VL and append their operands.
    void appendOperandsOfVL(ArrayRef<Value *> VL) {
      assert(!VL.empty() && "Bad VL");
      assert((empty() || VL.size() == getNumLanes()) &&
             "Expected same number of lanes");
      assert(isa<Instruction>(VL[0]) && "Expected instruction");
      unsigned NumOperands = cast<Instruction>(VL[0])->getNumOperands();
      OpsVec.resize(NumOperands);
      unsigned NumLanes = VL.size();
      for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) {
        OpsVec[OpIdx].resize(NumLanes);
        for (unsigned Lane = 0; Lane != NumLanes; ++Lane) {
          assert(isa<Instruction>(VL[Lane]) && "Expected instruction");
          // Our tree has just 3 nodes: the root and two operands.
          // It is therefore trivial to get the APO. We only need to check the
          // opcode of VL[Lane] and whether the operand at OpIdx is the LHS or
          // RHS operand. The LHS operand of both add and sub is never attached
          // to an inversese operation in the linearized form, therefore its APO
          // is false. The RHS is true only if VL[Lane] is an inverse operation.
 
          // Since operand reordering is performed on groups of commutative
          // operations or alternating sequences (e.g., +, -), we can safely
          // tell the inverse operations by checking commutativity.
          bool IsInverseOperation = !isCommutative(cast<Instruction>(VL[Lane]));
          bool APO = (OpIdx == 0) ? false : IsInverseOperation;
          OpsVec[OpIdx][Lane] = {cast<Instruction>(VL[Lane])->getOperand(OpIdx),
                                 APO, false};
        }
      }
    }
 
    /// \returns the number of operands.
    unsigned getNumOperands() const { return OpsVec.size(); }
 
    /// \returns the number of lanes.
    unsigned getNumLanes() const { return OpsVec[0].size(); }
 
    /// \returns the operand value at \p OpIdx and \p Lane.
    Value *getValue(unsigned OpIdx, unsigned Lane) const {
      return getData(OpIdx, Lane).V;
    }
 
    /// \returns true if the data structure is empty.
    bool empty() const { return OpsVec.empty(); }
 
    /// Clears the data.
    void clear() { OpsVec.clear(); }
 
    /// \Returns true if there are enough operands identical to \p Op to fill
    /// the whole vector.
    /// Note: This modifies the 'IsUsed' flag, so a cleanUsed() must follow.
    bool shouldBroadcast(Value *Op, unsigned OpIdx, unsigned Lane) {
      bool OpAPO = getData(OpIdx, Lane).APO;
      for (unsigned Ln = 0, Lns = getNumLanes(); Ln != Lns; ++Ln) {
        if (Ln == Lane)
          continue;
        // This is set to true if we found a candidate for broadcast at Lane.
        bool FoundCandidate = false;
        for (unsigned OpI = 0, OpE = getNumOperands(); OpI != OpE; ++OpI) {
          OperandData &Data = getData(OpI, Ln);
          if (Data.APO != OpAPO || Data.IsUsed)
            continue;
          if (Data.V == Op) {
            FoundCandidate = true;
            Data.IsUsed = true;
            break;
          }
        }
        if (!FoundCandidate)
          return false;
      }
      return true;
    }
 
  public:
    /// Initialize with all the operands of the instruction vector \p RootVL.
    VLOperands(ArrayRef<Value *> RootVL, const DataLayout &DL,
               ScalarEvolution &SE, const BoUpSLP &R)
        : DL(DL), SE(SE), R(R) {
      // Append all the operands of RootVL.
      appendOperandsOfVL(RootVL);
    }
 
    /// \Returns a value vector with the operands across all lanes for the
    /// opearnd at \p OpIdx.
    ValueList getVL(unsigned OpIdx) const {
      ValueList OpVL(OpsVec[OpIdx].size());
      assert(OpsVec[OpIdx].size() == getNumLanes() &&
             "Expected same num of lanes across all operands");
      for (unsigned Lane = 0, Lanes = getNumLanes(); Lane != Lanes; ++Lane)
        OpVL[Lane] = OpsVec[OpIdx][Lane].V;
      return OpVL;
    }
 
    // Performs operand reordering for 2 or more operands.
    // The original operands are in OrigOps[OpIdx][Lane].
    // The reordered operands are returned in 'SortedOps[OpIdx][Lane]'.
    void reorder() {
      unsigned NumOperands = getNumOperands();
      unsigned NumLanes = getNumLanes();
      // Each operand has its own mode. We are using this mode to help us select
      // the instructions for each lane, so that they match best with the ones
      // we have selected so far.
      SmallVector<ReorderingMode, 2> ReorderingModes(NumOperands);
 
      // This is a greedy single-pass algorithm. We are going over each lane
      // once and deciding on the best order right away with no back-tracking.
      // However, in order to increase its effectiveness, we start with the lane
      // that has operands that can move the least. For example, given the
      // following lanes:
      //  Lane 0 : A[0] = B[0] + C[0]   // Visited 3rd
      //  Lane 1 : A[1] = C[1] - B[1]   // Visited 1st
      //  Lane 2 : A[2] = B[2] + C[2]   // Visited 2nd
      //  Lane 3 : A[3] = C[3] - B[3]   // Visited 4th
      // we will start at Lane 1, since the operands of the subtraction cannot
      // be reordered. Then we will visit the rest of the lanes in a circular
      // fashion. That is, Lanes 2, then Lane 0, and finally Lane 3.
 
      // Find the first lane that we will start our search from.
      unsigned FirstLane = getBestLaneToStartReordering();
 
      // Initialize the modes.
      for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) {
        Value *OpLane0 = getValue(OpIdx, FirstLane);
        // Keep track if we have instructions with all the same opcode on one
        // side.
        if (isa<LoadInst>(OpLane0))
          ReorderingModes[OpIdx] = ReorderingMode::Load;
        else if (isa<Instruction>(OpLane0)) {
          // Check if OpLane0 should be broadcast.
          if (shouldBroadcast(OpLane0, OpIdx, FirstLane))
            ReorderingModes[OpIdx] = ReorderingMode::Splat;
          else
            ReorderingModes[OpIdx] = ReorderingMode::Opcode;
        }
        else if (isa<Constant>(OpLane0))
          ReorderingModes[OpIdx] = ReorderingMode::Constant;
        else if (isa<Argument>(OpLane0))
          // Our best hope is a Splat. It may save some cost in some cases.
          ReorderingModes[OpIdx] = ReorderingMode::Splat;
        else
          // NOTE: This should be unreachable.
          ReorderingModes[OpIdx] = ReorderingMode::Failed;
      }
 
      // If the initial strategy fails for any of the operand indexes, then we
      // perform reordering again in a second pass. This helps avoid assigning
      // high priority to the failed strategy, and should improve reordering for
      // the non-failed operand indexes.
      for (int Pass = 0; Pass != 2; ++Pass) {
        // Skip the second pass if the first pass did not fail.
        bool StrategyFailed = false;
        // Mark all operand data as free to use.
        clearUsed();
        // We keep the original operand order for the FirstLane, so reorder the
        // rest of the lanes. We are visiting the nodes in a circular fashion,
        // using FirstLane as the center point and increasing the radius
        // distance.
        for (unsigned Distance = 1; Distance != NumLanes; ++Distance) {
          // Visit the lane on the right and then the lane on the left.
          for (int Direction : {+1, -1}) {
            int Lane = FirstLane + Direction * Distance;
            if (Lane < 0 || Lane >= (int)NumLanes)
              continue;
            int LastLane = Lane - Direction;
            assert(LastLane >= 0 && LastLane < (int)NumLanes &&
                   "Out of bounds");
            // Look for a good match for each operand.
            for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) {
              // Search for the operand that matches SortedOps[OpIdx][Lane-1].
              Optional<unsigned> BestIdx =
                  getBestOperand(OpIdx, Lane, LastLane, ReorderingModes);
              // By not selecting a value, we allow the operands that follow to
              // select a better matching value. We will get a non-null value in
              // the next run of getBestOperand().
              if (BestIdx) {
                // Swap the current operand with the one returned by
                // getBestOperand().
                swap(OpIdx, BestIdx.getValue(), Lane);
              } else {
                // We failed to find a best operand, set mode to 'Failed'.
                ReorderingModes[OpIdx] = ReorderingMode::Failed;
                // Enable the second pass.
                StrategyFailed = true;
              }
            }
          }
        }
        // Skip second pass if the strategy did not fail.
        if (!StrategyFailed)
          break;
      }
    }
 
#if !defined(NDEBUG) || defined(LLVM_ENABLE_DUMP)
    LLVM_DUMP_METHOD static StringRef getModeStr(ReorderingMode RMode) {
      switch (RMode) {
      case ReorderingMode::Load:
        return "Load";
      case ReorderingMode::Opcode:
        return "Opcode";
      case ReorderingMode::Constant:
        return "Constant";
      case ReorderingMode::Splat:
        return "Splat";
      case ReorderingMode::Failed:
        return "Failed";
      }
      llvm_unreachable("Unimplemented Reordering Type");
    }
 
    LLVM_DUMP_METHOD static raw_ostream &printMode(ReorderingMode RMode,
                                                   raw_ostream &OS) {
      return OS << getModeStr(RMode);
    }
 
    /// Debug print.
    LLVM_DUMP_METHOD static void dumpMode(ReorderingMode RMode) {
      printMode(RMode, dbgs());
    }
 
    friend raw_ostream &operator<<(raw_ostream &OS, ReorderingMode RMode) {
      return printMode(RMode, OS);
    }
 
    LLVM_DUMP_METHOD raw_ostream &print(raw_ostream &OS) const {
      const unsigned Indent = 2;
      unsigned Cnt = 0;
      for (const OperandDataVec &OpDataVec : OpsVec) {
        OS << "Operand " << Cnt++ << "\n";
        for (const OperandData &OpData : OpDataVec) {
          OS.indent(Indent) << "{";
          if (Value *V = OpData.V)
            OS << *V;
          else
            OS << "null";
          OS << ", APO:" << OpData.APO << "}\n";
        }
        OS << "\n";
      }
      return OS;
    }
 
    /// Debug print.
    LLVM_DUMP_METHOD void dump() const { print(dbgs()); }
#endif
  };
 
  /// Checks if the instruction is marked for deletion.
  bool isDeleted(Instruction *I) const { return DeletedInstructions.count(I); }
 
  /// Marks values operands for later deletion by replacing them with Undefs.
  void eraseInstructions(ArrayRef<Value *> AV);
 
  ~BoUpSLP();
 
private:
  /// Checks if all users of \p I are the part of the vectorization tree.
  bool areAllUsersVectorized(Instruction *I) const;
 
  /// \returns the cost of the vectorizable entry.
  InstructionCost getEntryCost(TreeEntry *E);
 
  /// This is the recursive part of buildTree.
  void buildTree_rec(ArrayRef<Value *> Roots, unsigned Depth,
                     const EdgeInfo &EI);
 
  /// \returns true if the ExtractElement/ExtractValue instructions in \p VL can
  /// be vectorized to use the original vector (or aggregate "bitcast" to a
  /// vector) and sets \p CurrentOrder to the identity permutation; otherwise
  /// returns false, setting \p CurrentOrder to either an empty vector or a
  /// non-identity permutation that allows to reuse extract instructions.
  bool canReuseExtract(ArrayRef<Value *> VL, Value *OpValue,
                       SmallVectorImpl<unsigned> &CurrentOrder) const;
 
  /// Vectorize a single entry in the tree.
  Value *vectorizeTree(TreeEntry *E);
 
  /// Vectorize a single entry in the tree, starting in \p VL.
  Value *vectorizeTree(ArrayRef<Value *> VL);
 
  /// \returns the scalarization cost for this type. Scalarization in this
  /// context means the creation of vectors from a group of scalars.
  InstructionCost
  getGatherCost(FixedVectorType *Ty,
                const DenseSet<unsigned> &ShuffledIndices) const;
 
  /// \returns the scalarization cost for this list of values. Assuming that
  /// this subtree gets vectorized, we may need to extract the values from the
  /// roots. This method calculates the cost of extracting the values.
  InstructionCost getGatherCost(ArrayRef<Value *> VL) const;
 
  /// Set the Builder insert point to one after the last instruction in
  /// the bundle
  void setInsertPointAfterBundle(TreeEntry *E);
 
  /// \returns a vector from a collection of scalars in \p VL.
  Value *gather(ArrayRef<Value *> VL);
 
  /// \returns whether the VectorizableTree is fully vectorizable and will
  /// be beneficial even the tree height is tiny.
  bool isFullyVectorizableTinyTree() const;
 
  /// Reorder commutative or alt operands to get better probability of
  /// generating vectorized code.
  static void reorderInputsAccordingToOpcode(ArrayRef<Value *> VL,
                                             SmallVectorImpl<Value *> &Left,
                                             SmallVectorImpl<Value *> &Right,
                                             const DataLayout &DL,
                                             ScalarEvolution &SE,
                                             const BoUpSLP &R);
  struct TreeEntry {
    using VecTreeTy = SmallVector<std::unique_ptr<TreeEntry>, 8>;
    TreeEntry(VecTreeTy &Container) : Container(Container) {}
 
    /// \returns true if the scalars in VL are equal to this entry.
    bool isSame(ArrayRef<Value *> VL) const {
      if (VL.size() == Scalars.size())
        return std::equal(VL.begin(), VL.end(), Scalars.begin());
      return VL.size() == ReuseShuffleIndices.size() &&
             std::equal(
                 VL.begin(), VL.end(), ReuseShuffleIndices.begin(),
                 [this](Value *V, int Idx) { return V == Scalars[Idx]; });
    }
 
    /// A vector of scalars.
    ValueList Scalars;
 
    /// The Scalars are vectorized into this value. It is initialized to Null.
    Value *VectorizedValue = nullptr;
 
    /// Do we need to gather this sequence or vectorize it
    /// (either with vector instruction or with scatter/gather
    /// intrinsics for store/load)?
    enum EntryState { Vectorize, ScatterVectorize, NeedToGather };
    EntryState State;
 
    /// Does this sequence require some shuffling?
    SmallVector<int, 4> ReuseShuffleIndices;
 
    /// Does this entry require reordering?
    SmallVector<unsigned, 4> ReorderIndices;
 
    /// Points back to the VectorizableTree.
    ///
    /// Only used for Graphviz right now.  Unfortunately GraphTrait::NodeRef has
    /// to be a pointer and needs to be able to initialize the child iterator.
    /// Thus we need a reference back to the container to translate the indices
    /// to entries.
    VecTreeTy &Container;
 
    /// The TreeEntry index containing the user of this entry.  We can actually
    /// have multiple users so the data structure is not truly a tree.
    SmallVector<EdgeInfo, 1> UserTreeIndices;
 
    /// The index of this treeEntry in VectorizableTree.
    int Idx = -1;
 
  private:
    /// The operands of each instruction in each lane Operands[op_index][lane].
    /// Note: This helps avoid the replication of the code that performs the
    /// reordering of operands during buildTree_rec() and vectorizeTree().
    SmallVector<ValueList, 2> Operands;
 
    /// The main/alternate instruction.
    Instruction *MainOp = nullptr;
    Instruction *AltOp = nullptr;
 
  public:
    /// Set this bundle's \p OpIdx'th operand to \p OpVL.
    void setOperand(unsigned OpIdx, ArrayRef<Value *> OpVL) {
      if (Operands.size() < OpIdx + 1)
        Operands.resize(OpIdx + 1);
      assert(Operands[OpIdx].size() == 0 && "Already resized?");
      Operands[OpIdx].resize(Scalars.size());
      for (unsigned Lane = 0, E = Scalars.size(); Lane != E; ++Lane)
        Operands[OpIdx][Lane] = OpVL[Lane];
    }
 
    /// Set the operands of this bundle in their original order.
    void setOperandsInOrder() {
      assert(Operands.empty() && "Already initialized?");
      auto *I0 = cast<Instruction>(Scalars[0]);
      Operands.resize(I0->getNumOperands());
      unsigned NumLanes = Scalars.size();
      for (unsigned OpIdx = 0, NumOperands = I0->getNumOperands();
           OpIdx != NumOperands; ++OpIdx) {
        Operands[OpIdx].resize(NumLanes);
        for (unsigned Lane = 0; Lane != NumLanes; ++Lane) {
          auto *I = cast<Instruction>(Scalars[Lane]);
          assert(I->getNumOperands() == NumOperands &&
                 "Expected same number of operands");
          Operands[OpIdx][Lane] = I->getOperand(OpIdx);
        }
      }
    }
 
    /// \returns the \p OpIdx operand of this TreeEntry.
    ValueList &getOperand(unsigned OpIdx) {
      assert(OpIdx < Operands.size() && "Off bounds");
      return Operands[OpIdx];
    }
 
    /// \returns the number of operands.
    unsigned getNumOperands() const { return Operands.size(); }
 
    /// \return the single \p OpIdx operand.
    Value *getSingleOperand(unsigned OpIdx) const {
      assert(OpIdx < Operands.size() && "Off bounds");
      assert(!Operands[OpIdx].empty() && "No operand available");
      return Operands[OpIdx][0];
    }
 
    /// Some of the instructions in the list have alternate opcodes.
    bool isAltShuffle() const {
      return getOpcode() != getAltOpcode();
    }
 
    bool isOpcodeOrAlt(Instruction *I) const {
      unsigned CheckedOpcode = I->getOpcode();
      return (getOpcode() == CheckedOpcode ||
              getAltOpcode() == CheckedOpcode);
    }
 
    /// Chooses the correct key for scheduling data. If \p Op has the same (or
    /// alternate) opcode as \p OpValue, the key is \p Op. Otherwise the key is
    /// \p OpValue.
    Value *isOneOf(Value *Op) const {
      auto *I = dyn_cast<Instruction>(Op);
      if (I && isOpcodeOrAlt(I))
        return Op;
      return MainOp;
    }
 
    void setOperations(const InstructionsState &S) {
      MainOp = S.MainOp;
      AltOp = S.AltOp;
    }
 
    Instruction *getMainOp() const {
      return MainOp;
    }
 
    Instruction *getAltOp() const {
      return AltOp;
    }
 
    /// The main/alternate opcodes for the list of instructions.
    unsigned getOpcode() const {
      return MainOp ? MainOp->getOpcode() : 0;
    }
 
    unsigned getAltOpcode() const {
      return AltOp ? AltOp->getOpcode() : 0;
    }
 
    /// Update operations state of this entry if reorder occurred.
    bool updateStateIfReorder() {
      if (ReorderIndices.empty())
        return false;
      InstructionsState S = getSameOpcode(Scalars, ReorderIndices.front());
      setOperations(S);
      return true;
    }
 
#ifndef NDEBUG
    /// Debug printer.
    LLVM_DUMP_METHOD void dump() const {
      dbgs() << Idx << ".\n";
      for (unsigned OpI = 0, OpE = Operands.size(); OpI != OpE; ++OpI) {
        dbgs() << "Operand " << OpI << ":\n";
        for (const Value *V : Operands[OpI])
          dbgs().indent(2) << *V << "\n";
      }
      dbgs() << "Scalars: \n";
      for (Value *V : Scalars)
        dbgs().indent(2) << *V << "\n";
      dbgs() << "State: ";
      switch (State) {
      case Vectorize:
        dbgs() << "Vectorize\n";
        break;
      case ScatterVectorize:
        dbgs() << "ScatterVectorize\n";
        break;
      case NeedToGather:
        dbgs() << "NeedToGather\n";
        break;
      }
      dbgs() << "MainOp: ";
      if (MainOp)
        dbgs() << *MainOp << "\n";
      else
        dbgs() << "NULL\n";
      dbgs() << "AltOp: ";
      if (AltOp)
        dbgs() << *AltOp << "\n";
      else
        dbgs() << "NULL\n";
      dbgs() << "VectorizedValue: ";
      if (VectorizedValue)
        dbgs() << *VectorizedValue << "\n";
      else
        dbgs() << "NULL\n";
      dbgs() << "ReuseShuffleIndices: ";
      if (ReuseShuffleIndices.empty())
        dbgs() << "Empty";
      else
        for (unsigned ReuseIdx : ReuseShuffleIndices)
          dbgs() << ReuseIdx << ", ";
      dbgs() << "\n";
      dbgs() << "ReorderIndices: ";
      for (unsigned ReorderIdx : ReorderIndices)
        dbgs() << ReorderIdx << ", ";
      dbgs() << "\n";
      dbgs() << "UserTreeIndices: ";
      for (const auto &EInfo : UserTreeIndices)
        dbgs() << EInfo << ", ";
      dbgs() << "\n";
    }
#endif
  };
 
#ifndef NDEBUG
  void dumpTreeCosts(TreeEntry *E, InstructionCost ReuseShuffleCost,
                     InstructionCost VecCost,
                     InstructionCost ScalarCost) const {
    dbgs() << "SLP: Calculated costs for Tree:\n"; E->dump();
    dbgs() << "SLP: Costs:\n";
    dbgs() << "SLP:     ReuseShuffleCost = " << ReuseShuffleCost << "\n";
    dbgs() << "SLP:     VectorCost = " << VecCost << "\n";
    dbgs() << "SLP:     ScalarCost = " << ScalarCost << "\n";
    dbgs() << "SLP:     ReuseShuffleCost + VecCost - ScalarCost = " <<
               ReuseShuffleCost + VecCost - ScalarCost << "\n";
  }
#endif
 
  /// Create a new VectorizableTree entry.
  TreeEntry *newTreeEntry(ArrayRef<Value *> VL, Optional<ScheduleData *> Bundle,
                          const InstructionsState &S,
                          const EdgeInfo &UserTreeIdx,
                          ArrayRef<unsigned> ReuseShuffleIndices = None,
                          ArrayRef<unsigned> ReorderIndices = None) {
    TreeEntry::EntryState EntryState =
        Bundle ? TreeEntry::Vectorize : TreeEntry::NeedToGather;
    return newTreeEntry(VL, EntryState, Bundle, S, UserTreeIdx,
                        ReuseShuffleIndices, ReorderIndices);
  }
 
  TreeEntry *newTreeEntry(ArrayRef<Value *> VL,
                          TreeEntry::EntryState EntryState,
                          Optional<ScheduleData *> Bundle,
                          const InstructionsState &S,
                          const EdgeInfo &UserTreeIdx,
                          ArrayRef<unsigned> ReuseShuffleIndices = None,
                          ArrayRef<unsigned> ReorderIndices = None) {
    assert(((!Bundle && EntryState == TreeEntry::NeedToGather) ||
            (Bundle && EntryState != TreeEntry::NeedToGather)) &&
           "Need to vectorize gather entry?");
    VectorizableTree.push_back(std::make_unique<TreeEntry>(VectorizableTree));
    TreeEntry *Last = VectorizableTree.back().get();
    Last->Idx = VectorizableTree.size() - 1;
    Last->Scalars.insert(Last->Scalars.begin(), VL.begin(), VL.end());
    Last->State = EntryState;
    Last->ReuseShuffleIndices.append(ReuseShuffleIndices.begin(),
                                     ReuseShuffleIndices.end());
    Last->ReorderIndices.append(ReorderIndices.begin(), ReorderIndices.end());
    Last->setOperations(S);
    if (Last->State != TreeEntry::NeedToGather) {
      for (Value *V : VL) {
        assert(!getTreeEntry(V) && "Scalar already in tree!");
        ScalarToTreeEntry[V] = Last;
      }
      // Update the scheduler bundle to point to this TreeEntry.
      unsigned Lane = 0;
      for (ScheduleData *BundleMember = Bundle.getValue(); BundleMember;
           BundleMember = BundleMember->NextInBundle) {
        BundleMember->TE = Last;
        BundleMember->Lane = Lane;
        ++Lane;
      }
      assert((!Bundle.getValue() || Lane == VL.size()) &&
             "Bundle and VL out of sync");
    } else {
      MustGather.insert(VL.begin(), VL.end());
    }
 
    if (UserTreeIdx.UserTE)
      Last->UserTreeIndices.push_back(UserTreeIdx);
 
    return Last;
  }
 
  /// -- Vectorization State --
  /// Holds all of the tree entries.
  TreeEntry::VecTreeTy VectorizableTree;
 
#ifndef NDEBUG
  /// Debug printer.
  LLVM_DUMP_METHOD void dumpVectorizableTree() const {
    for (unsigned Id = 0, IdE = VectorizableTree.size(); Id != IdE; ++Id) {
      VectorizableTree[Id]->dump();
      dbgs() << "\n";
    }
  }
#endif
 
  TreeEntry *getTreeEntry(Value *V) { return ScalarToTreeEntry.lookup(V); }
 
  const TreeEntry *getTreeEntry(Value *V) const {
    return ScalarToTreeEntry.lookup(V);
  }
 
  /// Maps a specific scalar to its tree entry.
  SmallDenseMap<Value*, TreeEntry *> ScalarToTreeEntry;
 
  /// Maps a value to the proposed vectorizable size.
  SmallDenseMap<Value *, unsigned> InstrElementSize;
 
  /// A list of scalars that we found that we need to keep as scalars.
  ValueSet MustGather;
 
  /// This POD struct describes one external user in the vectorized tree.
  struct ExternalUser {
    ExternalUser(Value *S, llvm::User *U, int L)
        : Scalar(S), User(U), Lane(L) {}
 
    // Which scalar in our function.
    Value *Scalar;
 
    // Which user that uses the scalar.
    llvm::User *User;
 
    // Which lane does the scalar belong to.
    int Lane;
  };
  using UserList = SmallVector<ExternalUser, 16>;
 
  /// Checks if two instructions may access the same memory.
  ///
  /// \p Loc1 is the location of \p Inst1. It is passed explicitly because it
  /// is invariant in the calling loop.
  bool isAliased(const MemoryLocation &Loc1, Instruction *Inst1,
                 Instruction *Inst2) {
    // First check if the result is already in the cache.
    AliasCacheKey key = std::make_pair(Inst1, Inst2);
    Optional<bool> &result = AliasCache[key];
    if (result.hasValue()) {
      return result.getValue();
    }
    MemoryLocation Loc2 = getLocation(Inst2, AA);
    bool aliased = true;
    if (Loc1.Ptr && Loc2.Ptr && isSimple(Inst1) && isSimple(Inst2)) {
      // Do the alias check.
      aliased = !AA->isNoAlias(Loc1, Loc2);
    }
    // Store the result in the cache.
    result = aliased;
    return aliased;
  }
 
  using AliasCacheKey = std::pair<Instruction *, Instruction *>;
 
  /// Cache for alias results.
  /// TODO: consider moving this to the AliasAnalysis itself.
  DenseMap<AliasCacheKey, Optional<bool>> AliasCache;
 
  /// Removes an instruction from its block and eventually deletes it.
  /// It's like Instruction::eraseFromParent() except that the actual deletion
  /// is delayed until BoUpSLP is destructed.
  /// This is required to ensure that there are no incorrect collisions in the
  /// AliasCache, which can happen if a new instruction is allocated at the
  /// same address as a previously deleted instruction.
  void eraseInstruction(Instruction *I, bool ReplaceOpsWithUndef = false) {
    auto It = DeletedInstructions.try_emplace(I, ReplaceOpsWithUndef).first;
    It->getSecond() = It->getSecond() && ReplaceOpsWithUndef;
  }
 
  /// Temporary store for deleted instructions. Instructions will be deleted
  /// eventually when the BoUpSLP is destructed.
  DenseMap<Instruction *, bool> DeletedInstructions;
 
  /// A list of values that need to extracted out of the tree.
  /// This list holds pairs of (Internal Scalar : External User). External User
  /// can be nullptr, it means that this Internal Scalar will be used later,
  /// after vectorization.
  UserList ExternalUses;
 
  /// Values used only by @llvm.assume calls.
  SmallPtrSet<const Value *, 32> EphValues;
 
  /// Holds all of the instructions that we gathered.
  SetVector<Instruction *> GatherSeq;
 
  /// A list of blocks that we are going to CSE.
  SetVector<BasicBlock *> CSEBlocks;
 
  /// Contains all scheduling relevant data for an instruction.
  /// A ScheduleData either represents a single instruction or a member of an
  /// instruction bundle (= a group of instructions which is combined into a
  /// vector instruction).
  struct ScheduleData {
    // The initial value for the dependency counters. It means that the
    // dependencies are not calculated yet.
    enum { InvalidDeps = -1 };
 
    ScheduleData() = default;
 
    void init(int BlockSchedulingRegionID, Value *OpVal) {
      FirstInBundle = this;
      NextInBundle = nullptr;
      NextLoadStore = nullptr;
      IsScheduled = false;
      SchedulingRegionID = BlockSchedulingRegionID;
      UnscheduledDepsInBundle = UnscheduledDeps;
      clearDependencies();
      OpValue = OpVal;
      TE = nullptr;
      Lane = -1;
    }
 
    /// Returns true if the dependency information has been calculated.
    bool hasValidDependencies() const { return Dependencies != InvalidDeps; }
 
    /// Returns true for single instructions and for bundle representatives
    /// (= the head of a bundle).
    bool isSchedulingEntity() const { return FirstInBundle == this; }
 
    /// Returns true if it represents an instruction bundle and not only a
    /// single instruction.
    bool isPartOfBundle() const {
      return NextInBundle != nullptr || FirstInBundle != this;
    }
 
    /// Returns true if it is ready for scheduling, i.e. it has no more
    /// unscheduled depending instructions/bundles.
    bool isReady() const {
      assert(isSchedulingEntity() &&
             "can't consider non-scheduling entity for ready list");
      return UnscheduledDepsInBundle == 0 && !IsScheduled;
    }
 
    /// Modifies the number of unscheduled dependencies, also updating it for
    /// the whole bundle.
    int incrementUnscheduledDeps(int Incr) {
      UnscheduledDeps += Incr;
      return FirstInBundle->UnscheduledDepsInBundle += Incr;
    }
 
    /// Sets the number of unscheduled dependencies to the number of
    /// dependencies.
    void resetUnscheduledDeps() {
      incrementUnscheduledDeps(Dependencies - UnscheduledDeps);
    }
 
    /// Clears all dependency information.
    void clearDependencies() {
      Dependencies = InvalidDeps;
      resetUnscheduledDeps();
      MemoryDependencies.clear();
    }
 
    void dump(raw_ostream &os) const {
      if (!isSchedulingEntity()) {
        os << "/ " << *Inst;
      } else if (NextInBundle) {
        os << '[' << *Inst;
        ScheduleData *SD = NextInBundle;
        while (SD) {
          os << ';' << *SD->Inst;
          SD = SD->NextInBundle;
        }
        os << ']';
      } else {
        os << *Inst;
      }
    }
 
    Instruction *Inst = nullptr;
 
    /// Points to the head in an instruction bundle (and always to this for
    /// single instructions).
    ScheduleData *FirstInBundle = nullptr;
 
    /// Single linked list of all instructions in a bundle. Null if it is a
    /// single instruction.
    ScheduleData *NextInBundle = nullptr;
 
    /// Single linked list of all memory instructions (e.g. load, store, call)
    /// in the block - until the end of the scheduling region.
    ScheduleData *NextLoadStore = nullptr;
 
    /// The dependent memory instructions.
    /// This list is derived on demand in calculateDependencies().
    SmallVector<ScheduleData *, 4> MemoryDependencies;
 
    /// This ScheduleData is in the current scheduling region if this matches
    /// the current SchedulingRegionID of BlockScheduling.
    int SchedulingRegionID = 0;
 
    /// Used for getting a "good" final ordering of instructions.
    int SchedulingPriority = 0;
 
    /// The number of dependencies. Constitutes of the number of users of the
    /// instruction plus the number of dependent memory instructions (if any).
    /// This value is calculated on demand.
    /// If InvalidDeps, the number of dependencies is not calculated yet.
    int Dependencies = InvalidDeps;
 
    /// The number of dependencies minus the number of dependencies of scheduled
    /// instructions. As soon as this is zero, the instruction/bundle gets ready
    /// for scheduling.
    /// Note that this is negative as long as Dependencies is not calculated.
    int UnscheduledDeps = InvalidDeps;
 
    /// The sum of UnscheduledDeps in a bundle. Equals to UnscheduledDeps for
    /// single instructions.
    int UnscheduledDepsInBundle = InvalidDeps;
 
    /// True if this instruction is scheduled (or considered as scheduled in the
    /// dry-run).
    bool IsScheduled = false;
 
    /// Opcode of the current instruction in the schedule data.
    Value *OpValue = nullptr;
 
    /// The TreeEntry that this instruction corresponds to.
    TreeEntry *TE = nullptr;
 
    /// The lane of this node in the TreeEntry.
    int Lane = -1;
  };
 
#ifndef NDEBUG
  friend inline raw_ostream &operator<<(raw_ostream &os,
                                        const BoUpSLP::ScheduleData &SD) {
    SD.dump(os);
    return os;
  }
#endif
 
  friend struct GraphTraits<BoUpSLP *>;
  friend struct DOTGraphTraits<BoUpSLP *>;
 
  /// Contains all scheduling data for a basic block.
  struct BlockScheduling {
    BlockScheduling(BasicBlock *BB)
        : BB(BB), ChunkSize(BB->size()), ChunkPos(ChunkSize) {}
 
    void clear() {
      ReadyInsts.clear();
      ScheduleStart = nullptr;
      ScheduleEnd = nullptr;
      FirstLoadStoreInRegion = nullptr;
      LastLoadStoreInRegion = nullptr;
 
      // Reduce the maximum schedule region size by the size of the
      // previous scheduling run.
      ScheduleRegionSizeLimit -= ScheduleRegionSize;
      if (ScheduleRegionSizeLimit < MinScheduleRegionSize)
        ScheduleRegionSizeLimit = MinScheduleRegionSize;
      ScheduleRegionSize = 0;
 
      // Make a new scheduling region, i.e. all existing ScheduleData is not
      // in the new region yet.
      ++SchedulingRegionID;
    }
 
    ScheduleData *getScheduleData(Value *V) {
      ScheduleData *SD = ScheduleDataMap[V];
      if (SD && SD->SchedulingRegionID == SchedulingRegionID)
        return SD;
      return nullptr;
    }
 
    ScheduleData *getScheduleData(Value *V, Value *Key) {
      if (V == Key)
        return getScheduleData(V);
      auto I = ExtraScheduleDataMap.find(V);
      if (I != ExtraScheduleDataMap.end()) {
        ScheduleData *SD = I->second[Key];
        if (SD && SD->SchedulingRegionID == SchedulingRegionID)
          return SD;
      }
      return nullptr;
    }
 
    bool isInSchedulingRegion(ScheduleData *SD) const {
      return SD->SchedulingRegionID == SchedulingRegionID;
    }
 
    /// Marks an instruction as scheduled and puts all dependent ready
    /// instructions into the ready-list.
    template <typename ReadyListType>
    void schedule(ScheduleData *SD, ReadyListType &ReadyList) {
      SD->IsScheduled = true;
      LLVM_DEBUG(dbgs() << "SLP:   schedule " << *SD << "\n");
 
      ScheduleData *BundleMember = SD;
      while (BundleMember) {
        if (BundleMember->Inst != BundleMember->OpValue) {
          BundleMember = BundleMember->NextInBundle;
          continue;
        }
        // Handle the def-use chain dependencies.
 
        // Decrement the unscheduled counter and insert to ready list if ready.
        auto &&DecrUnsched = [this, &ReadyList](Instruction *I) {
          doForAllOpcodes(I, [&ReadyList](ScheduleData *OpDef) {
            if (OpDef && OpDef->hasValidDependencies() &&
                OpDef->incrementUnscheduledDeps(-1) == 0) {
              // There are no more unscheduled dependencies after
              // decrementing, so we can put the dependent instruction
              // into the ready list.
              ScheduleData *DepBundle = OpDef->FirstInBundle;
              assert(!DepBundle->IsScheduled &&
                     "already scheduled bundle gets ready");
              ReadyList.insert(DepBundle);
              LLVM_DEBUG(dbgs()
                         << "SLP:    gets ready (def): " << *DepBundle << "\n");
            }
          });
        };
 
        // If BundleMember is a vector bundle, its operands may have been
        // reordered duiring buildTree(). We therefore need to get its operands
        // through the TreeEntry.
        if (TreeEntry *TE = BundleMember->TE) {
          int Lane = BundleMember->Lane;
          assert(Lane >= 0 && "Lane not set");
 
          // Since vectorization tree is being built recursively this assertion
          // ensures that the tree entry has all operands set before reaching
          // this code. Couple of exceptions known at the moment are extracts
          // where their second (immediate) operand is not added. Since
          // immediates do not affect scheduler behavior this is considered
          // okay.
          auto *In = TE->getMainOp();
          assert(In &&
                 (isa<ExtractValueInst>(In) || isa<ExtractElementInst>(In) ||
                  In->getNumOperands() == TE->getNumOperands()) &&
                 "Missed TreeEntry operands?");
          (void)In; // fake use to avoid build failure when assertions disabled
 
          for (unsigned OpIdx = 0, NumOperands = TE->getNumOperands();
               OpIdx != NumOperands; ++OpIdx)
            if (auto *I = dyn_cast<Instruction>(TE->getOperand(OpIdx)[Lane]))
              DecrUnsched(I);
        } else {
          // If BundleMember is a stand-alone instruction, no operand reordering
          // has taken place, so we directly access its operands.
          for (Use &U : BundleMember->Inst->operands())
            if (auto *I = dyn_cast<Instruction>(U.get()))
              DecrUnsched(I);
        }
        // Handle the memory dependencies.
        for (ScheduleData *MemoryDepSD : BundleMember->MemoryDependencies) {
          if (MemoryDepSD->incrementUnscheduledDeps(-1) == 0) {
            // There are no more unscheduled dependencies after decrementing,
            // so we can put the dependent instruction into the ready list.
            ScheduleData *DepBundle = MemoryDepSD->FirstInBundle;
            assert(!DepBundle->IsScheduled &&
                   "already scheduled bundle gets ready");
            ReadyList.insert(DepBundle);
            LLVM_DEBUG(dbgs()
                       << "SLP:    gets ready (mem): " << *DepBundle << "\n");
          }
        }
        BundleMember = BundleMember->NextInBundle;
      }
    }
 
    void doForAllOpcodes(Value *V,
                         function_ref<void(ScheduleData *SD)> Action) {
      if (ScheduleData *SD = getScheduleData(V))
        Action(SD);
      auto I = ExtraScheduleDataMap.find(V);
      if (I != ExtraScheduleDataMap.end())
        for (auto &P : I->second)
          if (P.second->SchedulingRegionID == SchedulingRegionID)
            Action(P.second);
    }
 
    /// Put all instructions into the ReadyList which are ready for scheduling.
    template <typename ReadyListType>
    void initialFillReadyList(ReadyListType &ReadyList) {
      for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) {
        doForAllOpcodes(I, [&](ScheduleData *SD) {
          if (SD->isSchedulingEntity() && SD->isReady()) {
            ReadyList.insert(SD);
            LLVM_DEBUG(dbgs()
                       << "SLP:    initially in ready list: " << *I << "\n");
          }
        });
      }
    }
 
    /// Checks if a bundle of instructions can be scheduled, i.e. has no
    /// cyclic dependencies. This is only a dry-run, no instructions are
    /// actually moved at this stage.
    /// \returns the scheduling bundle. The returned Optional value is non-None
    /// if \p VL is allowed to be scheduled.
    Optional<ScheduleData *>
    tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP,
                      const InstructionsState &S);
 
    /// Un-bundles a group of instructions.
    void cancelScheduling(ArrayRef<Value *> VL, Value *OpValue);
 
    /// Allocates schedule data chunk.
    ScheduleData *allocateScheduleDataChunks();
 
    /// Extends the scheduling region so that V is inside the region.
    /// \returns true if the region size is within the limit.
    bool extendSchedulingRegion(Value *V, const InstructionsState &S);
 
    /// Initialize the ScheduleData structures for new instructions in the
    /// scheduling region.
    void initScheduleData(Instruction *FromI, Instruction *ToI,
                          ScheduleData *PrevLoadStore,
                          ScheduleData *NextLoadStore);
 
    /// Updates the dependency information of a bundle and of all instructions/
    /// bundles which depend on the original bundle.
    void calculateDependencies(ScheduleData *SD, bool InsertInReadyList,
                               BoUpSLP *SLP);
 
    /// Sets all instruction in the scheduling region to un-scheduled.
    void resetSchedule();
 
    BasicBlock *BB;
 
    /// Simple memory allocation for ScheduleData.
    std::vector<std::unique_ptr<ScheduleData[]>> ScheduleDataChunks;
 
    /// The size of a ScheduleData array in ScheduleDataChunks.
    int ChunkSize;
 
    /// The allocator position in the current chunk, which is the last entry
    /// of ScheduleDataChunks.
    int ChunkPos;
 
    /// Attaches ScheduleData to Instruction.
    /// Note that the mapping survives during all vectorization iterations, i.e.
    /// ScheduleData structures are recycled.
    DenseMap<Value *, ScheduleData *> ScheduleDataMap;
 
    /// Attaches ScheduleData to Instruction with the leading key.
    DenseMap<Value *, SmallDenseMap<Value *, ScheduleData *>>
        ExtraScheduleDataMap;
 
    struct ReadyList : SmallVector<ScheduleData *, 8> {
      void insert(ScheduleData *SD) { push_back(SD); }
    };
 
    /// The ready-list for scheduling (only used for the dry-run).
    ReadyList ReadyInsts;
 
    /// The first instruction of the scheduling region.
    Instruction *ScheduleStart = nullptr;
 
    /// The first instruction _after_ the scheduling region.
    Instruction *ScheduleEnd = nullptr;
 
    /// The first memory accessing instruction in the scheduling region
    /// (can be null).
    ScheduleData *FirstLoadStoreInRegion = nullptr;
 
    /// The last memory accessing instruction in the scheduling region
    /// (can be null).
    ScheduleData *LastLoadStoreInRegion = nullptr;
 
    /// The current size of the scheduling region.
    int ScheduleRegionSize = 0;
 
    /// The maximum size allowed for the scheduling region.
    int ScheduleRegionSizeLimit = ScheduleRegionSizeBudget;
 
    /// The ID of the scheduling region. For a new vectorization iteration this
    /// is incremented which "removes" all ScheduleData from the region.
    // Make sure that the initial SchedulingRegionID is greater than the
    // initial SchedulingRegionID in ScheduleData (which is 0).
    int SchedulingRegionID = 1;
  };
 
  /// Attaches the BlockScheduling structures to basic blocks.
  MapVector<BasicBlock *, std::unique_ptr<BlockScheduling>> BlocksSchedules;
 
  /// Performs the "real" scheduling. Done before vectorization is actually
  /// performed in a basic block.
  void scheduleBlock(BlockScheduling *BS);
 
  /// List of users to ignore during scheduling and that don't need extracting.
  ArrayRef<Value *> UserIgnoreList;
 
  /// A DenseMapInfo implementation for holding DenseMaps and DenseSets of
  /// sorted SmallVectors of unsigned.
  struct OrdersTypeDenseMapInfo {
    static OrdersType getEmptyKey() {
      OrdersType V;
      V.push_back(~1U);
      return V;
    }
 
    static OrdersType getTombstoneKey() {
      OrdersType V;
      V.push_back(~2U);
      return V;
    }
 
    static unsigned getHashValue(const OrdersType &V) {
      return static_cast<unsigned>(hash_combine_range(V.begin(), V.end()));
    }
 
    static bool isEqual(const OrdersType &LHS, const OrdersType &RHS) {
      return LHS == RHS;
    }
  };
 
  /// Contains orders of operations along with the number of bundles that have
  /// operations in this order. It stores only those orders that require
  /// reordering, if reordering is not required it is counted using \a
  /// NumOpsWantToKeepOriginalOrder.
  DenseMap<OrdersType, unsigned, OrdersTypeDenseMapInfo> NumOpsWantToKeepOrder;
  /// Number of bundles that do not require reordering.
  unsigned NumOpsWantToKeepOriginalOrder = 0;
 
  // Analysis and block reference.
  Function *F;
  ScalarEvolution *SE;
  TargetTransformInfo *TTI;
  TargetLibraryInfo *TLI;
  AAResults *AA;
  LoopInfo *LI;
  DominatorTree *DT;
  AssumptionCache *AC;
  DemandedBits *DB;
  const DataLayout *DL;
  OptimizationRemarkEmitter *ORE;
 
  unsigned MaxVecRegSize; // This is set by TTI or overridden by cl::opt.
  unsigned MinVecRegSize; // Set by cl::opt (default: 128).
 
  /// Instruction builder to construct the vectorized tree.
  IRBuilder<> Builder;
 
  /// A map of scalar integer values to the smallest bit width with which they
  /// can legally be represented. The values map to (width, signed) pairs,
  /// where "width" indicates the minimum bit width and "signed" is True if the
  /// value must be signed-extended, rather than zero-extended, back to its
  /// original width.
  MapVector<Value *, std::pair<uint64_t, bool>> MinBWs;
};
 
} // end namespace slpvectorizer
 
template <> struct GraphTraits<BoUpSLP *> {
  using TreeEntry = BoUpSLP::TreeEntry;
 
  /// NodeRef has to be a pointer per the GraphWriter.
  using NodeRef = TreeEntry *;
 
  using ContainerTy = BoUpSLP::TreeEntry::VecTreeTy;
 
  /// Add the VectorizableTree to the index iterator to be able to return
  /// TreeEntry pointers.
  struct ChildIteratorType
      : public iterator_adaptor_base<
            ChildIteratorType, SmallVector<BoUpSLP::EdgeInfo, 1>::iterator> {
    ContainerTy &VectorizableTree;
 
    ChildIteratorType(SmallVector<BoUpSLP::EdgeInfo, 1>::iterator W,
                      ContainerTy &VT)
        : ChildIteratorType::iterator_adaptor_base(W), VectorizableTree(VT) {}
 
    NodeRef operator*() { return I->UserTE; }
  };
 
  static NodeRef getEntryNode(BoUpSLP &R) {
    return R.VectorizableTree[0].get();
  }
 
  static ChildIteratorType child_begin(NodeRef N) {
    return {N->UserTreeIndices.begin(), N->Container};
  }
 
  static ChildIteratorType child_end(NodeRef N) {
    return {N->UserTreeIndices.end(), N->Container};
  }
 
  /// For the node iterator we just need to turn the TreeEntry iterator into a
  /// TreeEntry* iterator so that it dereferences to NodeRef.
  class nodes_iterator {
    using ItTy = ContainerTy::iterator;
    ItTy It;
 
  public:
    nodes_iterator(const ItTy &It2) : It(It2) {}
    NodeRef operator*() { return It->get(); }
    nodes_iterator operator++() {
      ++It;
      return *this;
    }
    bool operator!=(const nodes_iterator &N2) const { return N2.It != It; }
  };
 
  static nodes_iterator nodes_begin(BoUpSLP *R) {
    return nodes_iterator(R->VectorizableTree.begin());
  }
 
  static nodes_iterator nodes_end(BoUpSLP *R) {
    return nodes_iterator(R->VectorizableTree.end());
  }
 
  static unsigned size(BoUpSLP *R) { return R->VectorizableTree.size(); }
};
 
template <> struct DOTGraphTraits<BoUpSLP *> : public DefaultDOTGraphTraits {
  using TreeEntry = BoUpSLP::TreeEntry;
 
  DOTGraphTraits(bool isSimple = false) : DefaultDOTGraphTraits(isSimple) {}
 
  std::string getNodeLabel(const TreeEntry *Entry, const BoUpSLP *R) {
    std::string Str;
    raw_string_ostream OS(Str);
    if (isSplat(Entry->Scalars)) {
      OS << "<splat> " << *Entry->Scalars[0];
      return Str;
    }
    for (auto V : Entry->Scalars) {
      OS << *V;
      if (llvm::any_of(R->ExternalUses, [&](const BoUpSLP::ExternalUser &EU) {
            return EU.Scalar == V;
          }))
        OS << " <extract>";
      OS << "\n";
    }
    return Str;
  }
 
  static std::string getNodeAttributes(const TreeEntry *Entry,
                                       const BoUpSLP *) {
    if (Entry->State == TreeEntry::NeedToGather)
      return "color=red";
    return "";
  }
};
 
} // end namespace llvm
 
BoUpSLP::~BoUpSLP() {
  for (const auto &Pair : DeletedInstructions) {
    // Replace operands of ignored instructions with Undefs in case if they were
    // marked for deletion.
    if (Pair.getSecond()) {
      Value *Undef = UndefValue::get(Pair.getFirst()->getType());
      Pair.getFirst()->replaceAllUsesWith(Undef);
    }
    Pair.getFirst()->dropAllReferences();
  }
  for (const auto &Pair : DeletedInstructions) {
    assert(Pair.getFirst()->use_empty() &&
           "trying to erase instruction with users.");
    Pair.getFirst()->eraseFromParent();
  }
#ifdef EXPENSIVE_CHECKS
  // If we could guarantee that this call is not extremely slow, we could
  // remove the ifdef limitation (see PR47712).
  assert(!verifyFunction(*F, &dbgs()));
#endif
}
 
void BoUpSLP::eraseInstructions(ArrayRef<Value *> AV) {
  for (auto *V : AV) {
    if (auto *I = dyn_cast<Instruction>(V))
      eraseInstruction(I, /*ReplaceOpsWithUndef=*/true);
  };
}
 
void BoUpSLP::buildTree(ArrayRef<Value *> Roots,
                        ArrayRef<Value *> UserIgnoreLst) {
  ExtraValueToDebugLocsMap ExternallyUsedValues;
  buildTree(Roots, ExternallyUsedValues, UserIgnoreLst);
}
 
void BoUpSLP::buildTree(ArrayRef<Value *> Roots,
                        ExtraValueToDebugLocsMap &ExternallyUsedValues,
                        ArrayRef<Value *> UserIgnoreLst) {
  deleteTree();
  UserIgnoreList = UserIgnoreLst;
  if (!allSameType(Roots))
    return;
  buildTree_rec(Roots, 0, EdgeInfo());
 
  // Collect the values that we need to extract from the tree.
  for (auto &TEPtr : VectorizableTree) {
    TreeEntry *Entry = TEPtr.get();
 
    // No need to handle users of gathered values.
    if (Entry->State == TreeEntry::NeedToGather)
      continue;
 
    // For each lane:
    for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) {
      Value *Scalar = Entry->Scalars[Lane];
      int FoundLane = Lane;
      if (!Entry->ReuseShuffleIndices.empty()) {
        FoundLane =
            std::distance(Entry->ReuseShuffleIndices.begin(),
                          llvm::find(Entry->ReuseShuffleIndices, FoundLane));
      }
 
      // Check if the scalar is externally used as an extra arg.
      auto ExtI = ExternallyUsedValues.find(Scalar);
      if (ExtI != ExternallyUsedValues.end()) {
        LLVM_DEBUG(dbgs() << "SLP: Need to extract: Extra arg from lane "
                          << Lane << " from " << *Scalar << ".\n");
        ExternalUses.emplace_back(Scalar, nullptr, FoundLane);
      }
      for (User *U : Scalar->users()) {
        LLVM_DEBUG(dbgs() << "SLP: Checking user:" << *U << ".\n");
 
        Instruction *UserInst = dyn_cast<Instruction>(U);
        if (!UserInst)
          continue;
 
        // Skip in-tree scalars that become vectors
        if (TreeEntry *UseEntry = getTreeEntry(U)) {
          Value *UseScalar = UseEntry->Scalars[0];
          // Some in-tree scalars will remain as scalar in vectorized
          // instructions. If that is the case, the one in Lane 0 will
          // be used.
          if (UseScalar != U ||
              UseEntry->State == TreeEntry::ScatterVectorize ||
              !InTreeUserNeedToExtract(Scalar, UserInst, TLI)) {
            LLVM_DEBUG(dbgs() << "SLP: \tInternal user will be removed:" << *U
                              << ".\n");
            assert(UseEntry->State != TreeEntry::NeedToGather && "Bad state");
            continue;
          }
        }
 
        // Ignore users in the user ignore list.
        if (is_contained(UserIgnoreList, UserInst))
          continue;
 
        LLVM_DEBUG(dbgs() << "SLP: Need to extract:" << *U << " from lane "
                          << Lane << " from " << *Scalar << ".\n");
        ExternalUses.push_back(ExternalUser(Scalar, U, FoundLane));
      }
    }
  }
}
 
void BoUpSLP::buildTree_rec(ArrayRef<Value *> VL, unsigned Depth,
                            const EdgeInfo &UserTreeIdx) {
  assert((allConstant(VL) || allSameType(VL)) && "Invalid types!");
 
  InstructionsState S = getSameOpcode(VL);
  if (Depth == RecursionMaxDepth) {
    LLVM_DEBUG(dbgs() << "SLP: Gathering due to max recursion depth.\n");
    newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx);
    return;
  }
 
  // Don't handle vectors.
  if (S.OpValue->getType()->isVectorTy()) {
    LLVM_DEBUG(dbgs() << "SLP: Gathering due to vector type.\n");
    newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx);
    return;
  }
 
  if (StoreInst *SI = dyn_cast<StoreInst>(S.OpValue))
    if (SI->getValueOperand()->getType()->isVectorTy()) {
      LLVM_DEBUG(dbgs() << "SLP: Gathering due to store vector type.\n");
      newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx);
      return;
    }
 
  // If all of the operands are identical or constant we have a simple solution.
  if (allConstant(VL) || isSplat(VL) || !allSameBlock(VL) || !S.getOpcode()) {
    LLVM_DEBUG(dbgs() << "SLP: Gathering due to C,S,B,O. \n");
    newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx);
    return;
  }
 
  // We now know that this is a vector of instructions of the same type from
  // the same block.
 
  // Don't vectorize ephemeral values.
  for (Value *V : VL) {
    if (EphValues.count(V)) {
      LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V
                        << ") is ephemeral.\n");
      newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx);
      return;
    }
  }
 
  // Check if this is a duplicate of another entry.
  if (TreeEntry *E = getTreeEntry(S.OpValue)) {
    LLVM_DEBUG(dbgs() << "SLP: \tChecking bundle: " << *S.OpValue << ".\n");
    if (!E->isSame(VL)) {
      LLVM_DEBUG(dbgs() << "SLP: Gathering due to partial overlap.\n");
      newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx);
      return;
    }
    // Record the reuse of the tree node.  FIXME, currently this is only used to
    // properly draw the graph rather than for the actual vectorization.
    E->UserTreeIndices.push_back(UserTreeIdx);
    LLVM_DEBUG(dbgs() << "SLP: Perfect diamond merge at " << *S.OpValue
                      << ".\n");
    return;
  }
 
  // Check that none of the instructions in the bundle are already in the tree.
  for (Value *V : VL) {
    auto *I = dyn_cast<Instruction>(V);
    if (!I)
      continue;
    if (getTreeEntry(I)) {
      LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V
                        << ") is already in tree.\n");
      newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx);
      return;
    }
  }
 
  // If any of the scalars is marked as a value that needs to stay scalar, then
  // we need to gather the scalars.
  // The reduction nodes (stored in UserIgnoreList) also should stay scalar.
  for (Value *V : VL) {
    if (MustGather.count(V) || is_contained(UserIgnoreList, V)) {
      LLVM_DEBUG(dbgs() << "SLP: Gathering due to gathered scalar.\n");
      newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx);
      return;
    }
  }
 
  // Check that all of the users of the scalars that we want to vectorize are
  // schedulable.
  auto *VL0 = cast<Instruction>(S.OpValue);
  BasicBlock *BB = VL0->getParent();
 
  if (!DT->isReachableFromEntry(BB)) {
    // Don't go into unreachable blocks. They may contain instructions with
    // dependency cycles which confuse the final scheduling.
    LLVM_DEBUG(dbgs() << "SLP: bundle in unreachable block.\n");
    newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx);
    return;
  }
 
  // Check that every instruction appears once in this bundle.
  SmallVector<unsigned, 4> ReuseShuffleIndicies;
  SmallVector<Value *, 4> UniqueValues;
  DenseMap<Value *, unsigned> UniquePositions;
  for (Value *V : VL) {
    auto Res = UniquePositions.try_emplace(V, UniqueValues.size());
    ReuseShuffleIndicies.emplace_back(Res.first->second);
    if (Res.second)
      UniqueValues.emplace_back(V);
  }
  size_t NumUniqueScalarValues = UniqueValues.size();
  if (NumUniqueScalarValues == VL.size()) {
    ReuseShuffleIndicies.clear();
  } else {
    LLVM_DEBUG(dbgs() << "SLP: Shuffle for reused scalars.\n");
    if (NumUniqueScalarValues <= 1 ||
        !llvm::isPowerOf2_32(NumUniqueScalarValues)) {
      LLVM_DEBUG(dbgs() << "SLP: Scalar used twice in bundle.\n");
      newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx);
      return;
    }
    VL = UniqueValues;
  }
 
  auto &BSRef = BlocksSchedules[BB];
  if (!BSRef)
    BSRef = std::make_unique<BlockScheduling>(BB);
 
  BlockScheduling &BS = *BSRef.get();
 
  Optional<ScheduleData *> Bundle = BS.tryScheduleBundle(VL, this, S);
  if (!Bundle) {
    LLVM_DEBUG(dbgs() << "SLP: We are not able to schedule this bundle!\n");
    assert((!BS.getScheduleData(VL0) ||
            !BS.getScheduleData(VL0)->isPartOfBundle()) &&
           "tryScheduleBundle should cancelScheduling on failure");
    newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
                 ReuseShuffleIndicies);
    return;
  }
  LLVM_DEBUG(dbgs() << "SLP: We are able to schedule this bundle.\n");
 
  unsigned ShuffleOrOp = S.isAltShuffle() ?
                (unsigned) Instruction::ShuffleVector : S.getOpcode();
  switch (ShuffleOrOp) {
    case Instruction::PHI: {
      auto *PH = cast<PHINode>(VL0);
 
      // Check for terminator values (e.g. invoke).
      for (Value *V : VL)
        for (unsigned I = 0, E = PH->getNumIncomingValues(); I < E; ++I) {
          Instruction *Term = dyn_cast<Instruction>(
              cast<PHINode>(V)->getIncomingValueForBlock(
                  PH->getIncomingBlock(I)));
          if (Term && Term->isTerminator()) {
            LLVM_DEBUG(dbgs()
                       << "SLP: Need to swizzle PHINodes (terminator use).\n");
            BS.cancelScheduling(VL, VL0);
            newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
                         ReuseShuffleIndicies);
            return;
          }
        }
 
      TreeEntry *TE =
          newTreeEntry(VL, Bundle, S, UserTreeIdx, ReuseShuffleIndicies);
      LLVM_DEBUG(dbgs() << "SLP: added a vector of PHINodes.\n");
 
      // Keeps the reordered operands to avoid code duplication.
      SmallVector<ValueList, 2> OperandsVec;
      for (unsigned I = 0, E = PH->getNumIncomingValues(); I < E; ++I) {
        ValueList Operands;
        // Prepare the operand vector.
        for (Value *V : VL)
          Operands.push_back(cast<PHINode>(V)->getIncomingValueForBlock(
              PH->getIncomingBlock(I)));
        TE->setOperand(I, Operands);
        OperandsVec.push_back(Operands);
      }
      for (unsigned OpIdx = 0, OpE = OperandsVec.size(); OpIdx != OpE; ++OpIdx)
        buildTree_rec(OperandsVec[OpIdx], Depth + 1, {TE, OpIdx});
      return;
    }
    case Instruction::ExtractValue:
    case Instruction::ExtractElement: {
      OrdersType CurrentOrder;
      bool Reuse = canReuseExtract(VL, VL0, CurrentOrder);
      if (Reuse) {
        LLVM_DEBUG(dbgs() << "SLP: Reusing or shuffling extract sequence.\n");
        ++NumOpsWantToKeepOriginalOrder;
        newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
                     ReuseShuffleIndicies);
        // This is a special case, as it does not gather, but at the same time
        // we are not extending buildTree_rec() towards the operands.
        ValueList Op0;
        Op0.assign(VL.size(), VL0->getOperand(0));
        VectorizableTree.back()->setOperand(0, Op0);
        return;
      }
      if (!CurrentOrder.empty()) {
        LLVM_DEBUG({
          dbgs() << "SLP: Reusing or shuffling of reordered extract sequence "
                    "with order";
          for (unsigned Idx : CurrentOrder)
            dbgs() << " " << Idx;
          dbgs() << "\n";
        });
        // Insert new order with initial value 0, if it does not exist,
        // otherwise return the iterator to the existing one.
        newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
                     ReuseShuffleIndicies, CurrentOrder);
        findRootOrder(CurrentOrder);
        ++NumOpsWantToKeepOrder[CurrentOrder];
        // This is a special case, as it does not gather, but at the same time
        // we are not extending buildTree_rec() towards the operands.
        ValueList Op0;
        Op0.assign(VL.size(), VL0->getOperand(0));
        VectorizableTree.back()->setOperand(0, Op0);
        return;
      }
      LLVM_DEBUG(dbgs() << "SLP: Gather extract sequence.\n");
      newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
                   ReuseShuffleIndicies);
      BS.cancelScheduling(VL, VL0);
      return;
    }
    case Instruction::Load: {
      // Check that a vectorized load would load the same memory as a scalar
      // load. For example, we don't want to vectorize loads that are smaller
      // than 8-bit. Even though we have a packed struct {<i2, i2, i2, i2>} LLVM
      // treats loading/storing it as an i8 struct. If we vectorize loads/stores
      // from such a struct, we read/write packed bits disagreeing with the
      // unvectorized version.
      Type *ScalarTy = VL0->getType();
 
      if (DL->getTypeSizeInBits(ScalarTy) !=
          DL->getTypeAllocSizeInBits(ScalarTy)) {
        BS.cancelScheduling(VL, VL0);
        newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
                     ReuseShuffleIndicies);
        LLVM_DEBUG(dbgs() << "SLP: Gathering loads of non-packed type.\n");
        return;
      }
 
      // Make sure all loads in the bundle are simple - we can't vectorize
      // atomic or volatile loads.
      SmallVector<Value *, 4> PointerOps(VL.size());
      auto POIter = PointerOps.begin();
      for (Value *V : VL) {
        auto *L = cast<LoadInst>(V);
        if (!L->isSimple()) {
          BS.cancelScheduling(VL, VL0);
          newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
                       ReuseShuffleIndicies);
          LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple loads.\n");
          return;
        }
        *POIter = L->getPointerOperand();
        ++POIter;
      }
 
      OrdersType CurrentOrder;
      // Check the order of pointer operands.
      if (llvm::sortPtrAccesses(PointerOps, *DL, *SE, CurrentOrder)) {
        Value *Ptr0;
        Value *PtrN;
        if (CurrentOrder.empty()) {
          Ptr0 = PointerOps.front();
          PtrN = PointerOps.back();
        } else {
          Ptr0 = PointerOps[CurrentOrder.front()];
          PtrN = PointerOps[CurrentOrder.back()];
        }
        Optional<int> Diff = getPointersDiff(Ptr0, PtrN, *DL, *SE);
        // Check that the sorted loads are consecutive.
        if (static_cast<unsigned>(*Diff) == VL.size() - 1) {
          if (CurrentOrder.empty()) {
            // Original loads are consecutive and does not require reordering.
            ++NumOpsWantToKeepOriginalOrder;
            TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S,
                                         UserTreeIdx, ReuseShuffleIndicies);
            TE->setOperandsInOrder();
            LLVM_DEBUG(dbgs() << "SLP: added a vector of loads.\n");
          } else {
            // Need to reorder.
            TreeEntry *TE =
                newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
                             ReuseShuffleIndicies, CurrentOrder);
            TE->setOperandsInOrder();
            LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled loads.\n");
            findRootOrder(CurrentOrder);
            ++NumOpsWantToKeepOrder[CurrentOrder];
          }
          return;
        }
        // Vectorizing non-consecutive loads with `llvm.masked.gather`.
        TreeEntry *TE = newTreeEntry(VL, TreeEntry::ScatterVectorize, Bundle, S,
                                     UserTreeIdx, ReuseShuffleIndicies);
        TE->setOperandsInOrder();
        buildTree_rec(PointerOps, Depth + 1, {TE, 0});
        LLVM_DEBUG(dbgs() << "SLP: added a vector of non-consecutive loads.\n");
        return;
      }
 
      LLVM_DEBUG(dbgs() << "SLP: Gathering non-consecutive loads.\n");
      BS.cancelScheduling(VL, VL0);
      newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
                   ReuseShuffleIndicies);
      return;
    }
    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: {
      Type *SrcTy = VL0->getOperand(0)->getType();
      for (Value *V : VL) {
        Type *Ty = cast<Instruction>(V)->getOperand(0)->getType();
        if (Ty != SrcTy || !isValidElementType(Ty)) {
          BS.cancelScheduling(VL, VL0);
          newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
                       ReuseShuffleIndicies);
          LLVM_DEBUG(dbgs()
                     << "SLP: Gathering casts with different src types.\n");
          return;
        }
      }
      TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
                                   ReuseShuffleIndicies);
      LLVM_DEBUG(dbgs() << "SLP: added a vector of casts.\n");
 
      TE->setOperandsInOrder();
      for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) {
        ValueList Operands;
        // Prepare the operand vector.
        for (Value *V : VL)
          Operands.push_back(cast<Instruction>(V)->getOperand(i));
 
        buildTree_rec(Operands, Depth + 1, {TE, i});
      }
      return;
    }
    case Instruction::ICmp:
    case Instruction::FCmp: {
      // Check that all of the compares have the same predicate.
      CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate();
      CmpInst::Predicate SwapP0 = CmpInst::getSwappedPredicate(P0);
      Type *ComparedTy = VL0->getOperand(0)->getType();
      for (Value *V : VL) {
        CmpInst *Cmp = cast<CmpInst>(V);
        if ((Cmp->getPredicate() != P0 && Cmp->getPredicate() != SwapP0) ||
            Cmp->getOperand(0)->getType() != ComparedTy) {
          BS.cancelScheduling(VL, VL0);
          newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
                       ReuseShuffleIndicies);
          LLVM_DEBUG(dbgs()
                     << "SLP: Gathering cmp with different predicate.\n");
          return;
        }
      }
 
      TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
                                   ReuseShuffleIndicies);
      LLVM_DEBUG(dbgs() << "SLP: added a vector of compares.\n");
 
      ValueList Left, Right;
      if (cast<CmpInst>(VL0)->isCommutative()) {
        // Commutative predicate - collect + sort operands of the instructions
        // so that each side is more likely to have the same opcode.
        assert(P0 == SwapP0 && "Commutative Predicate mismatch");
        reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this);
      } else {
        // Collect operands - commute if it uses the swapped predicate.
        for (Value *V : VL) {
          auto *Cmp = cast<CmpInst>(V);
          Value *LHS = Cmp->getOperand(0);
          Value *RHS = Cmp->getOperand(1);
          if (Cmp->getPredicate() != P0)
            std::swap(LHS, RHS);
          Left.push_back(LHS);
          Right.push_back(RHS);
        }
      }
      TE->setOperand(0, Left);
      TE->setOperand(1, Right);
      buildTree_rec(Left, Depth + 1, {TE, 0});
      buildTree_rec(Right, Depth + 1, {TE, 1});
      return;
    }
    case Instruction::Select:
    case Instruction::FNeg:
    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: {
      TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
                                   ReuseShuffleIndicies);
      LLVM_DEBUG(dbgs() << "SLP: added a vector of un/bin op.\n");
 
      // Sort operands of the instructions so that each side is more likely to
      // have the same opcode.
      if (isa<BinaryOperator>(VL0) && VL0->isCommutative()) {
        ValueList Left, Right;
        reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this);
        TE->setOperand(0, Left);
        TE->setOperand(1, Right);
        buildTree_rec(Left, Depth + 1, {TE, 0});
        buildTree_rec(Right, Depth + 1, {TE, 1});
        return;
      }
 
      TE->setOperandsInOrder();
      for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) {
        ValueList Operands;
        // Prepare the operand vector.
        for (Value *V : VL)
          Operands.push_back(cast<Instruction>(V)->getOperand(i));
 
        buildTree_rec(Operands, Depth + 1, {TE, i});
      }
      return;
    }
    case Instruction::GetElementPtr: {
      // We don't combine GEPs with complicated (nested) indexing.
      for (Value *V : VL) {
        if (cast<Instruction>(V)->getNumOperands() != 2) {
          LLVM_DEBUG(dbgs() << "SLP: not-vectorizable GEP (nested indexes).\n");
          BS.cancelScheduling(VL, VL0);
          newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
                       ReuseShuffleIndicies);
          return;
        }
      }
 
      // We can't combine several GEPs into one vector if they operate on
      // different types.
      Type *Ty0 = VL0->getOperand(0)->getType();
      for (Value *V : VL) {
        Type *CurTy = cast<Instruction>(V)->getOperand(0)->getType();
        if (Ty0 != CurTy) {
          LLVM_DEBUG(dbgs()
                     << "SLP: not-vectorizable GEP (different types).\n");
          BS.cancelScheduling(VL, VL0);
          newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
                       ReuseShuffleIndicies);
          return;
        }
      }
 
      // We don't combine GEPs with non-constant indexes.
      Type *Ty1 = VL0->getOperand(1)->getType();
      for (Value *V : VL) {
        auto Op = cast<Instruction>(V)->getOperand(1);
        if (!isa<ConstantInt>(Op) ||
            (Op->getType() != Ty1 &&
             Op->getType()->getScalarSizeInBits() >
                 DL->getIndexSizeInBits(
                     V->getType()->getPointerAddressSpace()))) {
          LLVM_DEBUG(dbgs()
                     << "SLP: not-vectorizable GEP (non-constant indexes).\n");
          BS.cancelScheduling(VL, VL0);
          newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
                       ReuseShuffleIndicies);
          return;
        }
      }
 
      TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
                                   ReuseShuffleIndicies);
      LLVM_DEBUG(dbgs() << "SLP: added a vector of GEPs.\n");
      TE->setOperandsInOrder();
      for (unsigned i = 0, e = 2; i < e; ++i) {
        ValueList Operands;
        // Prepare the operand vector.
        for (Value *V : VL)
          Operands.push_back(cast<Instruction>(V)->getOperand(i));
 
        buildTree_rec(Operands, Depth + 1, {TE, i});
      }
      return;
    }
    case Instruction::Store: {
      // Check if the stores are consecutive or if we need to swizzle them.
      llvm::Type *ScalarTy = cast<StoreInst>(VL0)->getValueOperand()->getType();
      // Avoid types that are padded when being allocated as scalars, while
      // being packed together in a vector (such as i1).
      if (DL->getTypeSizeInBits(ScalarTy) !=
          DL->getTypeAllocSizeInBits(ScalarTy)) {
        BS.cancelScheduling(VL, VL0);
        newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
                     ReuseShuffleIndicies);
        LLVM_DEBUG(dbgs() << "SLP: Gathering stores of non-packed type.\n");
        return;
      }
      // Make sure all stores in the bundle are simple - we can't vectorize
      // atomic or volatile stores.
      SmallVector<Value *, 4> PointerOps(VL.size());
      ValueList Operands(VL.size());
      auto POIter = PointerOps.begin();
      auto OIter = Operands.begin();
      for (Value *V : VL) {
        auto *SI = cast<StoreInst>(V);
        if (!SI->isSimple()) {
          BS.cancelScheduling(VL, VL0);
          newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
                       ReuseShuffleIndicies);
          LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple stores.\n");
          return;
        }
        *POIter = SI->getPointerOperand();
        *OIter = SI->getValueOperand();
        ++POIter;
        ++OIter;
      }
 
      OrdersType CurrentOrder;
      // Check the order of pointer operands.
      if (llvm::sortPtrAccesses(PointerOps, *DL, *SE, CurrentOrder)) {
        Value *Ptr0;
        Value *PtrN;
        if (CurrentOrder.empty()) {
          Ptr0 = PointerOps.front();
          PtrN = PointerOps.back();
        } else {
          Ptr0 = PointerOps[CurrentOrder.front()];
          PtrN = PointerOps[CurrentOrder.back()];
        }
        Optional<int> Dist = getPointersDiff(Ptr0, PtrN, *DL, *SE);
        // Check that the sorted pointer operands are consecutive.
        if (static_cast<unsigned>(*Dist) == VL.size() - 1) {
          if (CurrentOrder.empty()) {
            // Original stores are consecutive and does not require reordering.
            ++NumOpsWantToKeepOriginalOrder;
            TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S,
                                         UserTreeIdx, ReuseShuffleIndicies);
            TE->setOperandsInOrder();
            buildTree_rec(Operands, Depth + 1, {TE, 0});
            LLVM_DEBUG(dbgs() << "SLP: added a vector of stores.\n");
          } else {
            TreeEntry *TE =
                newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
                             ReuseShuffleIndicies, CurrentOrder);
            TE->setOperandsInOrder();
            buildTree_rec(Operands, Depth + 1, {TE, 0});
            LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled stores.\n");
            findRootOrder(CurrentOrder);
            ++NumOpsWantToKeepOrder[CurrentOrder];
          }
          return;
        }
      }
 
      BS.cancelScheduling(VL, VL0);
      newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
                   ReuseShuffleIndicies);
      LLVM_DEBUG(dbgs() << "SLP: Non-consecutive store.\n");
      return;
    }
    case Instruction::Call: {
      // Check if the calls are all to the same vectorizable intrinsic or
      // library function.
      CallInst *CI = cast<CallInst>(VL0);
      Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI);
 
      VFShape Shape = VFShape::get(
          *CI, ElementCount::getFixed(static_cast<unsigned int>(VL.size())),
          false /*HasGlobalPred*/);
      Function *VecFunc = VFDatabase(*CI).getVectorizedFunction(Shape);
 
      if (!VecFunc && !isTriviallyVectorizable(ID)) {
        BS.cancelScheduling(VL, VL0);
        newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
                     ReuseShuffleIndicies);
        LLVM_DEBUG(dbgs() << "SLP: Non-vectorizable call.\n");
        return;
      }
      Function *F = CI->getCalledFunction();
      unsigned NumArgs = CI->getNumArgOperands();
      SmallVector<Value*, 4> ScalarArgs(NumArgs, nullptr);
      for (unsigned j = 0; j != NumArgs; ++j)
        if (hasVectorInstrinsicScalarOpd(ID, j))
          ScalarArgs[j] = CI->getArgOperand(j);
      for (Value *V : VL) {
        CallInst *CI2 = dyn_cast<CallInst>(V);
        if (!CI2 || CI2->getCalledFunction() != F ||
            getVectorIntrinsicIDForCall(CI2, TLI) != ID ||
            (VecFunc &&
             VecFunc != VFDatabase(*CI2).getVectorizedFunction(Shape)) ||
            !CI->hasIdenticalOperandBundleSchema(*CI2)) {
          BS.cancelScheduling(VL, VL0);
          newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
                       ReuseShuffleIndicies);
          LLVM_DEBUG(dbgs() << "SLP: mismatched calls:" << *CI << "!=" << *V
                            << "\n");
          return;
        }
        // Some intrinsics have scalar arguments and should be same in order for
        // them to be vectorized.
        for (unsigned j = 0; j != NumArgs; ++j) {
          if (hasVectorInstrinsicScalarOpd(ID, j)) {
            Value *A1J = CI2->getArgOperand(j);
            if (ScalarArgs[j] != A1J) {
              BS.cancelScheduling(VL, VL0);
              newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
                           ReuseShuffleIndicies);
              LLVM_DEBUG(dbgs() << "SLP: mismatched arguments in call:" << *CI
                                << " argument " << ScalarArgs[j] << "!=" << A1J
                                << "\n");
              return;
            }
          }
        }
        // Verify that the bundle operands are identical between the two calls.
        if (CI->hasOperandBundles() &&
            !std::equal(CI->op_begin() + CI->getBundleOperandsStartIndex(),
                        CI->op_begin() + CI->getBundleOperandsEndIndex(),
                        CI2->op_begin() + CI2->getBundleOperandsStartIndex())) {
          BS.cancelScheduling(VL, VL0);
          newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
                       ReuseShuffleIndicies);
          LLVM_DEBUG(dbgs() << "SLP: mismatched bundle operands in calls:"
                            << *CI << "!=" << *V << '\n');
          return;
        }
      }
 
      TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
                                   ReuseShuffleIndicies);
      TE->setOperandsInOrder();
      for (unsigned i = 0, e = CI->getNumArgOperands(); i != e; ++i) {
        ValueList Operands;
        // Prepare the operand vector.
        for (Value *V : VL) {
          auto *CI2 = cast<CallInst>(V);
          Operands.push_back(CI2->getArgOperand(i));
        }
        buildTree_rec(Operands, Depth + 1, {TE, i});
      }
      return;
    }
    case Instruction::ShuffleVector: {
      // If this is not an alternate sequence of opcode like add-sub
      // then do not vectorize this instruction.
      if (!S.isAltShuffle()) {
        BS.cancelScheduling(VL, VL0);
        newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
                     ReuseShuffleIndicies);
        LLVM_DEBUG(dbgs() << "SLP: ShuffleVector are not vectorized.\n");
        return;
      }
      TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
                                   ReuseShuffleIndicies);
      LLVM_DEBUG(dbgs() << "SLP: added a ShuffleVector op.\n");
 
      // Reorder operands if reordering would enable vectorization.
      if (isa<BinaryOperator>(VL0)) {
        ValueList Left, Right;
        reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this);
        TE->setOperand(0, Left);
        TE->setOperand(1, Right);
        buildTree_rec(Left, Depth + 1, {TE, 0});
        buildTree_rec(Right, Depth + 1, {TE, 1});
        return;
      }
 
      TE->setOperandsInOrder();
      for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) {
        ValueList Operands;
        // Prepare the operand vector.
        for (Value *V : VL)
          Operands.push_back(cast<Instruction>(V)->getOperand(i));
 
        buildTree_rec(Operands, Depth + 1, {TE, i});
      }
      return;
    }
    default:
      BS.cancelScheduling(VL, VL0);
      newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx,
                   ReuseShuffleIndicies);
      LLVM_DEBUG(dbgs() << "SLP: Gathering unknown instruction.\n");
      return;
  }
}
 
unsigned BoUpSLP::canMapToVector(Type *T, const DataLayout &DL) const {
  unsigned N = 1;
  Type *EltTy = T;
 
  while (isa<StructType>(EltTy) || isa<ArrayType>(EltTy) ||
         isa<VectorType>(EltTy)) {
    if (auto *ST = dyn_cast<StructType>(EltTy)) {
      // Check that struct is homogeneous.
      for (const auto *Ty : ST->elements())
        if (Ty != *ST->element_begin())
          return 0;
      N *= ST->getNumElements();
      EltTy = *ST->element_begin();
    } else if (auto *AT = dyn_cast<ArrayType>(EltTy)) {
      N *= AT->getNumElements();
      EltTy = AT->getElementType();
    } else {
      auto *VT = cast<FixedVectorType>(EltTy);
      N *= VT->getNumElements();
      EltTy = VT->getElementType();
    }
  }
 
  if (!isValidElementType(EltTy))
    return 0;
  uint64_t VTSize = DL.getTypeStoreSizeInBits(FixedVectorType::get(EltTy, N));
  if (VTSize < MinVecRegSize || VTSize > MaxVecRegSize || VTSize != DL.getTypeStoreSizeInBits(T))
    return 0;
  return N;
}
 
bool BoUpSLP::canReuseExtract(ArrayRef<Value *> VL, Value *OpValue,
                              SmallVectorImpl<unsigned> &CurrentOrder) const {
  Instruction *E0 = cast<Instruction>(OpValue);
  assert(E0->getOpcode() == Instruction::ExtractElement ||
         E0->getOpcode() == Instruction::ExtractValue);
  assert(E0->getOpcode() == getSameOpcode(VL).getOpcode() && "Invalid opcode");
  // Check if all of the extracts come from the same vector and from the
  // correct offset.
  Value *Vec = E0->getOperand(0);
 
  CurrentOrder.clear();
 
  // We have to extract from a vector/aggregate with the same number of elements.
  unsigned NElts;
  if (E0->getOpcode() == Instruction::ExtractValue) {
    const DataLayout &DL = E0->getModule()->getDataLayout();
    NElts = canMapToVector(Vec->getType(), DL);
    if (!NElts)
      return false;
    // Check if load can be rewritten as load of vector.
    LoadInst *LI = dyn_cast<LoadInst>(Vec);
    if (!LI || !LI->isSimple() || !LI->hasNUses(VL.size()))
      return false;
  } else {
    NElts = cast<FixedVectorType>(Vec->getType())->getNumElements();
  }
 
  if (NElts != VL.size())
    return false;
 
  // Check that all of the indices extract from the correct offset.
  bool ShouldKeepOrder = true;
  unsigned E = VL.size();
  // Assign to all items the initial value E + 1 so we can check if the extract
  // instruction index was used already.
  // Also, later we can check that all the indices are used and we have a
  // consecutive access in the extract instructions, by checking that no
  // element of CurrentOrder still has value E + 1.
  CurrentOrder.assign(E, E + 1);
  unsigned I = 0;
  for (; I < E; ++I) {
    auto *Inst = cast<Instruction>(VL[I]);
    if (Inst->getOperand(0) != Vec)
      break;
    Optional<unsigned> Idx = getExtractIndex(Inst);
    if (!Idx)
      break;
    const unsigned ExtIdx = *Idx;
    if (ExtIdx != I) {
      if (ExtIdx >= E || CurrentOrder[ExtIdx] != E + 1)
        break;
      ShouldKeepOrder = false;
      CurrentOrder[ExtIdx] = I;
    } else {
      if (CurrentOrder[I] != E + 1)
        break;
      CurrentOrder[I] = I;
    }
  }
  if (I < E) {
    CurrentOrder.clear();
    return false;
  }
 
  return ShouldKeepOrder;
}
 
bool BoUpSLP::areAllUsersVectorized(Instruction *I) const {
  return I->hasOneUse() || llvm::all_of(I->users(), [this](User *U) {
           return ScalarToTreeEntry.count(U) > 0;
         });
}
 
static std::pair<InstructionCost, InstructionCost>
getVectorCallCosts(CallInst *CI, FixedVectorType *VecTy,
                   TargetTransformInfo *TTI, TargetLibraryInfo *TLI) {
  Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI);
 
  // Calculate the cost of the scalar and vector calls.
  SmallVector<Type *, 4> VecTys;
  for (Use &Arg : CI->args())
    VecTys.push_back(
        FixedVectorType::get(Arg->getType(), VecTy->getNumElements()));
  FastMathFlags FMF;
  if (auto *FPCI = dyn_cast<FPMathOperator>(CI))
    FMF = FPCI->getFastMathFlags();
  SmallVector<const Value *> Arguments(CI->arg_begin(), CI->arg_end());
  IntrinsicCostAttributes CostAttrs(ID, VecTy, Arguments, VecTys, FMF,
                                    dyn_cast<IntrinsicInst>(CI));
  auto IntrinsicCost =
    TTI->getIntrinsicInstrCost(CostAttrs, TTI::TCK_RecipThroughput);
 
  auto Shape = VFShape::get(*CI, ElementCount::getFixed(static_cast<unsigned>(
                                     VecTy->getNumElements())),
                            false /*HasGlobalPred*/);
  Function *VecFunc = VFDatabase(*CI).getVectorizedFunction(Shape);
  auto LibCost = IntrinsicCost;
  if (!CI->isNoBuiltin() && VecFunc) {
    // Calculate the cost of the vector library call.
    // If the corresponding vector call is cheaper, return its cost.
    LibCost = TTI->getCallInstrCost(nullptr, VecTy, VecTys,
                                    TTI::TCK_RecipThroughput);
  }
  return {IntrinsicCost, LibCost};
}
 
/// Compute the cost of creating a vector of type \p VecTy containing the
/// extracted values from \p VL.
static InstructionCost
computeExtractCost(ArrayRef<Value *> VL, FixedVectorType *VecTy,
                   TargetTransformInfo::ShuffleKind ShuffleKind,
                   ArrayRef<int> Mask, TargetTransformInfo &TTI) {
  unsigned NumOfParts = TTI.getNumberOfParts(VecTy);
 
  if (ShuffleKind != TargetTransformInfo::SK_PermuteSingleSrc || !NumOfParts ||
      VecTy->getNumElements() < NumOfParts)
    return TTI.getShuffleCost(ShuffleKind, VecTy, Mask);
 
  bool AllConsecutive = true;
  unsigned EltsPerVector = VecTy->getNumElements() / NumOfParts;
  unsigned Idx = -1;
  InstructionCost Cost = 0;
 
  // Process extracts in blocks of EltsPerVector to check if the source vector
  // operand can be re-used directly. If not, add the cost of creating a shuffle
  // to extract the values into a vector register.
  for (auto *V : VL) {
    ++Idx;
 
    // Reached the start of a new vector registers.
    if (Idx % EltsPerVector == 0) {
      AllConsecutive = true;
      continue;
    }
 
    // Check all extracts for a vector register on the target directly
    // extract values in order.
    unsigned CurrentIdx = *getExtractIndex(cast<Instruction>(V));
    unsigned PrevIdx = *getExtractIndex(cast<Instruction>(VL[Idx - 1]));
    AllConsecutive &= PrevIdx + 1 == CurrentIdx &&
                      CurrentIdx % EltsPerVector == Idx % EltsPerVector;
 
    if (AllConsecutive)
      continue;
 
    // Skip all indices, except for the last index per vector block.
    if ((Idx + 1) % EltsPerVector != 0 && Idx + 1 != VL.size())
      continue;
 
    // If we have a series of extracts which are not consecutive and hence
    // cannot re-use the source vector register directly, compute the shuffle
    // cost to extract the a vector with EltsPerVector elements.
    Cost += TTI.getShuffleCost(
        TargetTransformInfo::SK_PermuteSingleSrc,
        FixedVectorType::get(VecTy->getElementType(), EltsPerVector));
  }
  return Cost;
}
 
InstructionCost BoUpSLP::getEntryCost(TreeEntry *E) {
  ArrayRef<Value*> VL = E->Scalars;
 
  Type *ScalarTy = VL[0]->getType();
  if (StoreInst *SI = dyn_cast<StoreInst>(VL[0]))
    ScalarTy = SI->getValueOperand()->getType();
  else if (CmpInst *CI = dyn_cast<CmpInst>(VL[0]))
    ScalarTy = CI->getOperand(0)->getType();
  auto *VecTy = FixedVectorType::get(ScalarTy, VL.size());
  TTI::TargetCostKind CostKind = TTI::TCK_RecipThroughput;
 
  // If we have computed a smaller type for the expression, update VecTy so
  // that the costs will be accurate.
  if (MinBWs.count(VL[0]))
    VecTy = FixedVectorType::get(
        IntegerType::get(F->getContext(), MinBWs[VL[0]].first), VL.size());
 
  unsigned ReuseShuffleNumbers = E->ReuseShuffleIndices.size();
  bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty();
  InstructionCost ReuseShuffleCost = 0;
  if (NeedToShuffleReuses) {
    ReuseShuffleCost =
        TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, VecTy,
                            E->ReuseShuffleIndices);
  }
  if (E->State == TreeEntry::NeedToGather) {
    if (allConstant(VL))
      return 0;
    if (isSplat(VL)) {
      return ReuseShuffleCost +
             TTI->getShuffleCost(TargetTransformInfo::SK_Broadcast, VecTy, None,
                                 0);
    }
    if (E->getOpcode() == Instruction::ExtractElement &&
        allSameType(VL) && allSameBlock(VL)) {
      SmallVector<int> Mask;
      Optional<TargetTransformInfo::ShuffleKind> ShuffleKind =
          isShuffle(VL, Mask);
      if (ShuffleKind.hasValue()) {
        InstructionCost Cost =
            computeExtractCost(VL, VecTy, *ShuffleKind, Mask, *TTI);
        for (auto *V : VL) {
          // If all users of instruction are going to be vectorized and this
          // instruction itself is not going to be vectorized, consider this
          // instruction as dead and remove its cost from the final cost of the
          // vectorized tree.
          if (areAllUsersVectorized(cast<Instruction>(V)) &&
              !ScalarToTreeEntry.count(V)) {
            auto *IO = cast<ConstantInt>(
                cast<ExtractElementInst>(V)->getIndexOperand());
            Cost -= TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy,
                                            IO->getZExtValue());
          }
        }
        return ReuseShuffleCost + Cost;
      }
    }
    return ReuseShuffleCost + getGatherCost(VL);
  }
  assert((E->State == TreeEntry::Vectorize ||
          E->State == TreeEntry::ScatterVectorize) &&
         "Unhandled state");
  assert(E->getOpcode() && allSameType(VL) && allSameBlock(VL) && "Invalid VL");
  Instruction *VL0 = E->getMainOp();
  unsigned ShuffleOrOp =
      E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode();
  switch (ShuffleOrOp) {
    case Instruction::PHI:
      return 0;
 
    case Instruction::ExtractValue:
    case Instruction::ExtractElement: {
      // The common cost of removal ExtractElement/ExtractValue instructions +
      // the cost of shuffles, if required to resuffle the original vector.
      InstructionCost CommonCost = 0;
      if (NeedToShuffleReuses) {
        unsigned Idx = 0;
        for (unsigned I : E->ReuseShuffleIndices) {
          if (ShuffleOrOp == Instruction::ExtractElement) {
            auto *IO = cast<ConstantInt>(
                cast<ExtractElementInst>(VL[I])->getIndexOperand());
            Idx = IO->getZExtValue();
            ReuseShuffleCost -= TTI->getVectorInstrCost(
                Instruction::ExtractElement, VecTy, Idx);
          } else {
            ReuseShuffleCost -= TTI->getVectorInstrCost(
                Instruction::ExtractElement, VecTy, Idx);
            ++Idx;
          }
        }
        Idx = ReuseShuffleNumbers;
        for (Value *V : VL) {
          if (ShuffleOrOp == Instruction::ExtractElement) {
            auto *IO = cast<ConstantInt>(
                cast<ExtractElementInst>(V)->getIndexOperand());
            Idx = IO->getZExtValue();
          } else {
            --Idx;
          }
          ReuseShuffleCost +=
              TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, Idx);
        }
        CommonCost = ReuseShuffleCost;
      } else if (!E->ReorderIndices.empty()) {
        SmallVector<int> NewMask;
        inversePermutation(E->ReorderIndices, NewMask);
        CommonCost = TTI->getShuffleCost(
            TargetTransformInfo::SK_PermuteSingleSrc, VecTy, NewMask);
      }
      for (unsigned I = 0, E = VL.size(); I < E; ++I) {
        Instruction *EI = cast<Instruction>(VL[I]);
        // If all users are going to be vectorized, instruction can be
        // considered as dead.
        // The same, if have only one user, it will be vectorized for sure.
        if (areAllUsersVectorized(EI)) {
          // Take credit for instruction that will become dead.
          if (EI->hasOneUse()) {
            Instruction *Ext = EI->user_back();
            if ((isa<SExtInst>(Ext) || isa<ZExtInst>(Ext)) &&
                all_of(Ext->users(),
                       [](User *U) { return isa<GetElementPtrInst>(U); })) {
              // Use getExtractWithExtendCost() to calculate the cost of
              // extractelement/ext pair.
              CommonCost -= TTI->getExtractWithExtendCost(
                  Ext->getOpcode(), Ext->getType(), VecTy, I);
              // Add back the cost of s|zext which is subtracted separately.
              CommonCost += TTI->getCastInstrCost(
                  Ext->getOpcode(), Ext->getType(), EI->getType(),
                  TTI::getCastContextHint(Ext), CostKind, Ext);
              continue;
            }
          }
          CommonCost -=
              TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, I);
        }
      }
      return CommonCost;
    }
    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: {
      Type *SrcTy = VL0->getOperand(0)->getType();
      InstructionCost ScalarEltCost =
          TTI->getCastInstrCost(E->getOpcode(), ScalarTy, SrcTy,
                                TTI::getCastContextHint(VL0), CostKind, VL0);
      if (NeedToShuffleReuses) {
        ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost;
      }
 
      // Calculate the cost of this instruction.
      InstructionCost ScalarCost = VL.size() * ScalarEltCost;
 
      auto *SrcVecTy = FixedVectorType::get(SrcTy, VL.size());
      InstructionCost VecCost = 0;
      // Check if the values are candidates to demote.
      if (!MinBWs.count(VL0) || VecTy != SrcVecTy) {
        VecCost =
            ReuseShuffleCost +
            TTI->getCastInstrCost(E->getOpcode(), VecTy, SrcVecTy,
                                  TTI::getCastContextHint(VL0), CostKind, VL0);
      }
      LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost));
      return VecCost - ScalarCost;
    }
    case Instruction::FCmp:
    case Instruction::ICmp:
    case Instruction::Select: {
      // Calculate the cost of this instruction.
      InstructionCost ScalarEltCost =
          TTI->getCmpSelInstrCost(E->getOpcode(), ScalarTy, Builder.getInt1Ty(),
                                  CmpInst::BAD_ICMP_PREDICATE, CostKind, VL0);
      if (NeedToShuffleReuses) {
        ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost;
      }
      auto *MaskTy = FixedVectorType::get(Builder.getInt1Ty(), VL.size());
      InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost;
 
      // Check if all entries in VL are either compares or selects with compares
      // as condition that have the same predicates.
      CmpInst::Predicate VecPred = CmpInst::BAD_ICMP_PREDICATE;
      bool First = true;
      for (auto *V : VL) {
        CmpInst::Predicate CurrentPred;
        auto MatchCmp = m_Cmp(CurrentPred, m_Value(), m_Value());
        if ((!match(V, m_Select(MatchCmp, m_Value(), m_Value())) &&
             !match(V, MatchCmp)) ||
            (!First && VecPred != CurrentPred)) {
          VecPred = CmpInst::BAD_ICMP_PREDICATE;
          break;
        }
        First = false;
        VecPred = CurrentPred;
      }
 
      InstructionCost VecCost = TTI->getCmpSelInstrCost(
          E->getOpcode(), VecTy, MaskTy, VecPred, CostKind, VL0);
      // Check if it is possible and profitable to use min/max for selects in
      // VL.
      //
      auto IntrinsicAndUse = canConvertToMinOrMaxIntrinsic(VL);
      if (IntrinsicAndUse.first != Intrinsic::not_intrinsic) {
        IntrinsicCostAttributes CostAttrs(IntrinsicAndUse.first, VecTy,
                                          {VecTy, VecTy});
        InstructionCost IntrinsicCost =
            TTI->getIntrinsicInstrCost(CostAttrs, CostKind);
        // If the selects are the only uses of the compares, they will be dead
        // and we can adjust the cost by removing their cost.
        if (IntrinsicAndUse.second)
          IntrinsicCost -=
              TTI->getCmpSelInstrCost(Instruction::ICmp, VecTy, MaskTy,
                                      CmpInst::BAD_ICMP_PREDICATE, CostKind);
        VecCost = std::min(VecCost, IntrinsicCost);
      }
      LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost));
      return ReuseShuffleCost + VecCost - ScalarCost;
    }
    case Instruction::FNeg:
    case Instruction::Add:
    case Instruction::FAdd:
    case Instruction::Sub:
    case Instruction::FSub:
    case Instruction::Mul:
    case Instruction::FMul:
    case Instruction::UDiv:
    case Instruction::SDiv:
    case Instruction::FDiv:
    case Instruction::URem:
    case Instruction::SRem:
    case Instruction::FRem:
    case Instruction::Shl:
    case Instruction::LShr:
    case Instruction::AShr:
    case Instruction::And:
    case Instruction::Or:
    case Instruction::Xor: {
      // Certain instructions can be cheaper to vectorize if they have a
      // constant second vector operand.
      TargetTransformInfo::OperandValueKind Op1VK =
          TargetTransformInfo::OK_AnyValue;
      TargetTransformInfo::OperandValueKind Op2VK =
          TargetTransformInfo::OK_UniformConstantValue;
      TargetTransformInfo::OperandValueProperties Op1VP =
          TargetTransformInfo::OP_None;
      TargetTransformInfo::OperandValueProperties Op2VP =
          TargetTransformInfo::OP_PowerOf2;
 
      // If all operands are exactly the same ConstantInt then set the
      // operand kind to OK_UniformConstantValue.
      // If instead not all operands are constants, then set the operand kind
      // to OK_AnyValue. If all operands are constants but not the same,
      // then set the operand kind to OK_NonUniformConstantValue.
      ConstantInt *CInt0 = nullptr;
      for (unsigned i = 0, e = VL.size(); i < e; ++i) {
        const Instruction *I = cast<Instruction>(VL[i]);
        unsigned OpIdx = isa<BinaryOperator>(I) ? 1 : 0;
        ConstantInt *CInt = dyn_cast<ConstantInt>(I->getOperand(OpIdx));
        if (!CInt) {
          Op2VK = TargetTransformInfo::OK_AnyValue;
          Op2VP = TargetTransformInfo::OP_None;
          break;
        }
        if (Op2VP == TargetTransformInfo::OP_PowerOf2 &&
            !CInt->getValue().isPowerOf2())
          Op2VP = TargetTransformInfo::OP_None;
        if (i == 0) {
          CInt0 = CInt;
          continue;
        }
        if (CInt0 != CInt)
          Op2VK = TargetTransformInfo::OK_NonUniformConstantValue;
      }
 
      SmallVector<const Value *, 4> Operands(VL0->operand_values());
      InstructionCost ScalarEltCost =
          TTI->getArithmeticInstrCost(E->getOpcode(), ScalarTy, CostKind, Op1VK,
                                      Op2VK, Op1VP, Op2VP, Operands, VL0);
      if (NeedToShuffleReuses) {
        ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost;
      }
      InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost;
      InstructionCost VecCost =
          TTI->getArithmeticInstrCost(E->getOpcode(), VecTy, CostKind, Op1VK,
                                      Op2VK, Op1VP, Op2VP, Operands, VL0);
      LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost));
      return ReuseShuffleCost + VecCost - ScalarCost;
    }
    case Instruction::GetElementPtr: {
      TargetTransformInfo::OperandValueKind Op1VK =
          TargetTransformInfo::OK_AnyValue;
      TargetTransformInfo::OperandValueKind Op2VK =
          TargetTransformInfo::OK_UniformConstantValue;
 
      InstructionCost ScalarEltCost = TTI->getArithmeticInstrCost(
          Instruction::Add, ScalarTy, CostKind, Op1VK, Op2VK);
      if (NeedToShuffleReuses) {
        ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost;
      }
      InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost;
      InstructionCost VecCost = TTI->getArithmeticInstrCost(
          Instruction::Add, VecTy, CostKind, Op1VK, Op2VK);
      LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost));
      return ReuseShuffleCost + VecCost - ScalarCost;
    }
    case Instruction::Load: {
      // Cost of wide load - cost of scalar loads.
      Align alignment = cast<LoadInst>(VL0)->getAlign();
      InstructionCost ScalarEltCost = TTI->getMemoryOpCost(
          Instruction::Load, ScalarTy, alignment, 0, CostKind, VL0);
      if (NeedToShuffleReuses) {
        ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost;
      }
      InstructionCost ScalarLdCost = VecTy->getNumElements() * ScalarEltCost;
      InstructionCost VecLdCost;
      if (E->State == TreeEntry::Vectorize) {
        VecLdCost = TTI->getMemoryOpCost(Instruction::Load, VecTy, alignment, 0,
                                         CostKind, VL0);
      } else {
        assert(E->State == TreeEntry::ScatterVectorize && "Unknown EntryState");
        VecLdCost = TTI->getGatherScatterOpCost(
            Instruction::Load, VecTy, cast<LoadInst>(VL0)->getPointerOperand(),
            /*VariableMask=*/false, alignment, CostKind, VL0);
      }
      if (!NeedToShuffleReuses && !E->ReorderIndices.empty()) {
        SmallVector<int> NewMask;
        inversePermutation(E->ReorderIndices, NewMask);
        VecLdCost += TTI->getShuffleCost(
            TargetTransformInfo::SK_PermuteSingleSrc, VecTy, NewMask);
      }
      LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecLdCost, ScalarLdCost));
      return ReuseShuffleCost + VecLdCost - ScalarLdCost;
    }
    case Instruction::Store: {
      // We know that we can merge the stores. Calculate the cost.
      bool IsReorder = !E->ReorderIndices.empty();
      auto *SI =
          cast<StoreInst>(IsReorder ? VL[E->ReorderIndices.front()] : VL0);
      Align Alignment = SI->getAlign();
      InstructionCost ScalarEltCost = TTI->getMemoryOpCost(
          Instruction::Store, ScalarTy, Alignment, 0, CostKind, VL0);
      InstructionCost ScalarStCost = VecTy->getNumElements() * ScalarEltCost;
      InstructionCost VecStCost = TTI->getMemoryOpCost(
          Instruction::Store, VecTy, Alignment, 0, CostKind, VL0);
      if (IsReorder) {
        SmallVector<int> NewMask;
        inversePermutation(E->ReorderIndices, NewMask);
        VecStCost += TTI->getShuffleCost(
            TargetTransformInfo::SK_PermuteSingleSrc, VecTy, NewMask);
      }
      LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecStCost, ScalarStCost));
      return VecStCost - ScalarStCost;
    }
    case Instruction::Call: {
      CallInst *CI = cast<CallInst>(VL0);
      Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI);
 
      // Calculate the cost of the scalar and vector calls.
      IntrinsicCostAttributes CostAttrs(ID, *CI, 1);
      InstructionCost ScalarEltCost =
          TTI->getIntrinsicInstrCost(CostAttrs, CostKind);
      if (NeedToShuffleReuses) {
        ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost;
      }
      InstructionCost ScalarCallCost = VecTy->getNumElements() * ScalarEltCost;
 
      auto VecCallCosts = getVectorCallCosts(CI, VecTy, TTI, TLI);
      InstructionCost VecCallCost =
          std::min(VecCallCosts.first, VecCallCosts.second);
 
      LLVM_DEBUG(dbgs() << "SLP: Call cost " << VecCallCost - ScalarCallCost
                        << " (" << VecCallCost << "-" << ScalarCallCost << ")"
                        << " for " << *CI << "\n");
 
      return ReuseShuffleCost + VecCallCost - ScalarCallCost;
    }
    case Instruction::ShuffleVector: {
      assert(E->isAltShuffle() &&
             ((Instruction::isBinaryOp(E->getOpcode()) &&
               Instruction::isBinaryOp(E->getAltOpcode())) ||
              (Instruction::isCast(E->getOpcode()) &&
               Instruction::isCast(E->getAltOpcode()))) &&
             "Invalid Shuffle Vector Operand");
      InstructionCost ScalarCost = 0;
      if (NeedToShuffleReuses) {
        for (unsigned Idx : E->ReuseShuffleIndices) {
          Instruction *I = cast<Instruction>(VL[Idx]);
          ReuseShuffleCost -= TTI->getInstructionCost(I, CostKind);
        }
        for (Value *V : VL) {
          Instruction *I = cast<Instruction>(V);
          ReuseShuffleCost += TTI->getInstructionCost(I, CostKind);
        }
      }
      for (Value *V : VL) {
        Instruction *I = cast<Instruction>(V);
        assert(E->isOpcodeOrAlt(I) && "Unexpected main/alternate opcode");
        ScalarCost += TTI->getInstructionCost(I, CostKind);
      }
      // VecCost is equal to sum of the cost of creating 2 vectors
      // and the cost of creating shuffle.
      InstructionCost VecCost = 0;
      if (Instruction::isBinaryOp(E->getOpcode())) {
        VecCost = TTI->getArithmeticInstrCost(E->getOpcode(), VecTy, CostKind);
        VecCost += TTI->getArithmeticInstrCost(E->getAltOpcode(), VecTy,
                                               CostKind);
      } else {
        Type *Src0SclTy = E->getMainOp()->getOperand(0)->getType();
        Type *Src1SclTy = E->getAltOp()->getOperand(0)->getType();
        auto *Src0Ty = FixedVectorType::get(Src0SclTy, VL.size());
        auto *Src1Ty = FixedVectorType::get(Src1SclTy, VL.size());
        VecCost = TTI->getCastInstrCost(E->getOpcode(), VecTy, Src0Ty,
                                        TTI::CastContextHint::None, CostKind);
        VecCost += TTI->getCastInstrCost(E->getAltOpcode(), VecTy, Src1Ty,
                                         TTI::CastContextHint::None, CostKind);
      }
 
      SmallVector<int> Mask(E->Scalars.size());
      for (unsigned I = 0, End = E->Scalars.size(); I < End; ++I) {
        auto *OpInst = cast<Instruction>(E->Scalars[I]);
        assert(E->isOpcodeOrAlt(OpInst) && "Unexpected main/alternate opcode");
        Mask[I] = I + (OpInst->getOpcode() == E->getAltOpcode() ? End : 0);
      }
      VecCost +=
          TTI->getShuffleCost(TargetTransformInfo::SK_Select, VecTy, Mask, 0);
      LLVM_DEBUG(dumpTreeCosts(E, ReuseShuffleCost, VecCost, ScalarCost));
      return ReuseShuffleCost + VecCost - ScalarCost;
    }
    default:
      llvm_unreachable("Unknown instruction");
  }
}
 
bool BoUpSLP::isFullyVectorizableTinyTree() const {
  LLVM_DEBUG(dbgs() << "SLP: Check whether the tree with height "
                    << VectorizableTree.size() << " is fully vectorizable .\n");
 
  // We only handle trees of heights 1 and 2.
  if (VectorizableTree.size() == 1 &&
      VectorizableTree[0]->State == TreeEntry::Vectorize)
    return true;
 
  if (VectorizableTree.size() != 2)
    return false;
 
  // Handle splat and all-constants stores.
  if (VectorizableTree[0]->State == TreeEntry::Vectorize &&
      (allConstant(VectorizableTree[1]->Scalars) ||
       isSplat(VectorizableTree[1]->Scalars)))
    return true;
 
  // Gathering cost would be too much for tiny trees.
  if (VectorizableTree[0]->State == TreeEntry::NeedToGather ||
      VectorizableTree[1]->State == TreeEntry::NeedToGather)
    return false;
 
  return true;
}
 
static bool isLoadCombineCandidateImpl(Value *Root, unsigned NumElts,
                                       TargetTransformInfo *TTI) {
  // Look past the root to find a source value. Arbitrarily follow the
  // path through operand 0 of any 'or'. Also, peek through optional
  // shift-left-by-multiple-of-8-bits.
  Value *ZextLoad = Root;
  const APInt *ShAmtC;
  while (!isa<ConstantExpr>(ZextLoad) &&
         (match(ZextLoad, m_Or(m_Value(), m_Value())) ||
          (match(ZextLoad, m_Shl(m_Value(), m_APInt(ShAmtC))) &&
           ShAmtC->urem(8) == 0)))
    ZextLoad = cast<BinaryOperator>(ZextLoad)->getOperand(0);
 
  // Check if the input is an extended load of the required or/shift expression.
  Value *LoadPtr;
  if (ZextLoad == Root || !match(ZextLoad, m_ZExt(m_Load(m_Value(LoadPtr)))))
    return false;
 
  // Require that the total load bit width is a legal integer type.
  // For example, <8 x i8> --> i64 is a legal integer on a 64-bit target.
  // But <16 x i8> --> i128 is not, so the backend probably can't reduce it.
  Type *SrcTy = LoadPtr->getType()->getPointerElementType();
  unsigned LoadBitWidth = SrcTy->getIntegerBitWidth() * NumElts;
  if (!TTI->isTypeLegal(IntegerType::get(Root->getContext(), LoadBitWidth)))
    return false;
 
  // Everything matched - assume that we can fold the whole sequence using
  // load combining.
  LLVM_DEBUG(dbgs() << "SLP: Assume load combining for tree starting at "
             << *(cast<Instruction>(Root)) << "\n");
 
  return true;
}
 
bool BoUpSLP::isLoadCombineReductionCandidate(RecurKind RdxKind) const {
  if (RdxKind != RecurKind::Or)
    return false;
 
  unsigned NumElts = VectorizableTree[0]->Scalars.size();
  Value *FirstReduced = VectorizableTree[0]->Scalars[0];
  return isLoadCombineCandidateImpl(FirstReduced, NumElts, TTI);
}
 
bool BoUpSLP::isLoadCombineCandidate() const {
  // Peek through a final sequence of stores and check if all operations are
  // likely to be load-combined.
  unsigned NumElts = VectorizableTree[0]->Scalars.size();
  for (Value *Scalar : VectorizableTree[0]->Scalars) {
    Value *X;
    if (!match(Scalar, m_Store(m_Value(X), m_Value())) ||
        !isLoadCombineCandidateImpl(X, NumElts, TTI))
      return false;
  }
  return true;
}
 
bool BoUpSLP::isTreeTinyAndNotFullyVectorizable() const {
  // We can vectorize the tree if its size is greater than or equal to the
  // minimum size specified by the MinTreeSize command line option.
  if (VectorizableTree.size() >= MinTreeSize)
    return false;
 
  // If we have a tiny tree (a tree whose size is less than MinTreeSize), we
  // can vectorize it if we can prove it fully vectorizable.
  if (isFullyVectorizableTinyTree())
    return false;
 
  assert(VectorizableTree.empty()
             ? ExternalUses.empty()
             : true && "We shouldn't have any external users");
 
  // Otherwise, we can't vectorize the tree. It is both tiny and not fully
  // vectorizable.
  return true;
}
 
InstructionCost BoUpSLP::getSpillCost() const {
  // Walk from the bottom of the tree to the top, tracking which values are
  // live. When we see a call instruction that is not part of our tree,
  // query TTI to see if there is a cost to keeping values live over it
  // (for example, if spills and fills are required).
  unsigned BundleWidth = VectorizableTree.front()->Scalars.size();
  InstructionCost Cost = 0;
 
  SmallPtrSet<Instruction*, 4> LiveValues;
  Instruction *PrevInst = nullptr;
 
  // The entries in VectorizableTree are not necessarily ordered by their
  // position in basic blocks. Collect them and order them by dominance so later
  // instructions are guaranteed to be visited first. For instructions in
  // different basic blocks, we only scan to the beginning of the block, so
  // their order does not matter, as long as all instructions in a basic block
  // are grouped together. Using dominance ensures a deterministic order.
  SmallVector<Instruction *, 16> OrderedScalars;
  for (const auto &TEPtr : VectorizableTree) {
    Instruction *Inst = dyn_cast<Instruction>(TEPtr->Scalars[0]);
    if (!Inst)
      continue;
    OrderedScalars.push_back(Inst);
  }
  llvm::stable_sort(OrderedScalars, [this](Instruction *A, Instruction *B) {
    return DT->dominates(B, A);
  });
 
  for (Instruction *Inst : OrderedScalars) {
    if (!PrevInst) {
      PrevInst = Inst;
      continue;
    }
 
    // Update LiveValues.
    LiveValues.erase(PrevInst);
    for (auto &J : PrevInst->operands()) {
      if (isa<Instruction>(&*J) && getTreeEntry(&*J))
        LiveValues.insert(cast<Instruction>(&*J));
    }
 
    LLVM_DEBUG({
      dbgs() << "SLP: #LV: " << LiveValues.size();
      for (auto *X : LiveValues)
        dbgs() << " " << X->getName();
      dbgs() << ", Looking at ";
      Inst->dump();
    });
 
    // Now find the sequence of instructions between PrevInst and Inst.
    unsigned NumCalls = 0;
    BasicBlock::reverse_iterator InstIt = ++Inst->getIterator().getReverse(),
                                 PrevInstIt =
                                     PrevInst->getIterator().getReverse();
    while (InstIt != PrevInstIt) {
      if (PrevInstIt == PrevInst->getParent()->rend()) {
        PrevInstIt = Inst->getParent()->rbegin();
        continue;
      }
 
      // Debug information does not impact spill cost.
      if ((isa<CallInst>(&*PrevInstIt) &&
           !isa<DbgInfoIntrinsic>(&*PrevInstIt)) &&
          &*PrevInstIt != PrevInst)
        NumCalls++;
 
      ++PrevInstIt;
    }
 
    if (NumCalls) {
      SmallVector<Type*, 4> V;
      for (auto *II : LiveValues)
        V.push_back(FixedVectorType::get(II->getType(), BundleWidth));
      Cost += NumCalls * TTI->getCostOfKeepingLiveOverCall(V);
    }
 
    PrevInst = Inst;
  }
 
  return Cost;
}
 
InstructionCost BoUpSLP::getTreeCost() {
  InstructionCost Cost = 0;
  LLVM_DEBUG(dbgs() << "SLP: Calculating cost for tree of size "
                    << VectorizableTree.size() << ".\n");
 
  unsigned BundleWidth = VectorizableTree[0]->Scalars.size();
 
  for (unsigned I = 0, E = VectorizableTree.size(); I < E; ++I) {
    TreeEntry &TE = *VectorizableTree[I].get();
 
    // We create duplicate tree entries for gather sequences that have multiple
    // uses. However, we should not compute the cost of duplicate sequences.
    // For example, if we have a build vector (i.e., insertelement sequence)
    // that is used by more than one vector instruction, we only need to
    // compute the cost of the insertelement instructions once. The redundant
    // instructions will be eliminated by CSE.
    //
    // We should consider not creating duplicate tree entries for gather
    // sequences, and instead add additional edges to the tree representing
    // their uses. Since such an approach results in fewer total entries,
    // existing heuristics based on tree size may yield different results.
    //
    if (TE.State == TreeEntry::NeedToGather &&
        std::any_of(std::next(VectorizableTree.begin(), I + 1),
                    VectorizableTree.end(),
                    [TE](const std::unique_ptr<TreeEntry> &EntryPtr) {
                      return EntryPtr->State == TreeEntry::NeedToGather &&
                             EntryPtr->isSame(TE.Scalars);
                    }))
      continue;
 
    InstructionCost C = getEntryCost(&TE);
    Cost += C;
    LLVM_DEBUG(dbgs() << "SLP: Adding cost " << C
                      << " for bundle that starts with " << *TE.Scalars[0]
                      << ".\n"
                      << "SLP: Current total cost = " << Cost << "\n");
  }
 
  SmallPtrSet<Value *, 16> ExtractCostCalculated;
  InstructionCost ExtractCost = 0;
  for (ExternalUser &EU : ExternalUses) {
    // We only add extract cost once for the same scalar.
    if (!ExtractCostCalculated.insert(EU.Scalar).second)
      continue;
 
    // Uses by ephemeral values are free (because the ephemeral value will be
    // removed prior to code generation, and so the extraction will be
    // removed as well).
    if (EphValues.count(EU.User))
      continue;
 
    // If we plan to rewrite the tree in a smaller type, we will need to sign
    // extend the extracted value back to the original type. Here, we account
    // for the extract and the added cost of the sign extend if needed.
    auto *VecTy = FixedVectorType::get(EU.Scalar->getType(), BundleWidth);
    auto *ScalarRoot = VectorizableTree[0]->Scalars[0];
    if (MinBWs.count(ScalarRoot)) {
      auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first);
      auto Extend =
          MinBWs[ScalarRoot].second ? Instruction::SExt : Instruction::ZExt;
      VecTy = FixedVectorType::get(MinTy, BundleWidth);
      ExtractCost += TTI->getExtractWithExtendCost(Extend, EU.Scalar->getType(),
                                                   VecTy, EU.Lane);
    } else {
      ExtractCost +=
          TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, EU.Lane);
    }
  }
 
  InstructionCost SpillCost = getSpillCost();
  Cost += SpillCost + ExtractCost;
 
#ifndef NDEBUG
  SmallString<256> Str;
  {
    raw_svector_ostream OS(Str);
    OS << "SLP: Spill Cost = " << SpillCost << ".\n"
       << "SLP: Extract Cost = " << ExtractCost << ".\n"
       << "SLP: Total Cost = " << Cost << ".\n";
  }
  LLVM_DEBUG(dbgs() << Str);
  if (ViewSLPTree)
    ViewGraph(this, "SLP" + F->getName(), false, Str);
#endif
 
  return Cost;
}
 
InstructionCost
BoUpSLP::getGatherCost(FixedVectorType *Ty,
                       const DenseSet<unsigned> &ShuffledIndices) const {
  unsigned NumElts = Ty->getNumElements();
  APInt DemandedElts = APInt::getNullValue(NumElts);
  for (unsigned I = 0; I < NumElts; ++I)
    if (!ShuffledIndices.count(I))
      DemandedElts.setBit(I);
  InstructionCost Cost =
      TTI->getScalarizationOverhead(Ty, DemandedElts, /*Insert*/ true,
                                    /*Extract*/ false);
  if (!ShuffledIndices.empty())
    Cost += TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, Ty);
  return Cost;
}
 
InstructionCost BoUpSLP::getGatherCost(ArrayRef<Value *> VL) const {
  // Find the type of the operands in VL.
  Type *ScalarTy = VL[0]->getType();
  if (StoreInst *SI = dyn_cast<StoreInst>(VL[0]))
    ScalarTy = SI->getValueOperand()->getType();
  auto *VecTy = FixedVectorType::get(ScalarTy, VL.size());
  // Find the cost of inserting/extracting values from the vector.
  // Check if the same elements are inserted several times and count them as
  // shuffle candidates.
  DenseSet<unsigned> ShuffledElements;
  DenseSet<Value *> UniqueElements;
  // Iterate in reverse order to consider insert elements with the high cost.
  for (unsigned I = VL.size(); I > 0; --I) {
    unsigned Idx = I - 1;
    if (!UniqueElements.insert(VL[Idx]).second)
      ShuffledElements.insert(Idx);
  }
  return getGatherCost(VecTy, ShuffledElements);
}
 
// Perform operand reordering on the instructions in VL and return the reordered
// operands in Left and Right.
void BoUpSLP::reorderInputsAccordingToOpcode(ArrayRef<Value *> VL,
                                             SmallVectorImpl<Value *> &Left,
                                             SmallVectorImpl<Value *> &Right,
                                             const DataLayout &DL,
                                             ScalarEvolution &SE,
                                             const BoUpSLP &R) {
  if (VL.empty())
    return;
  VLOperands Ops(VL, DL, SE, R);
  // Reorder the operands in place.
  Ops.reorder();
  Left = Ops.getVL(0);
  Right = Ops.getVL(1);
}
 
void BoUpSLP::setInsertPointAfterBundle(TreeEntry *E) {
  // Get the basic block this bundle is in. All instructions in the bundle
  // should be in this block.
  auto *Front = E->getMainOp();
  auto *BB = Front->getParent();
  assert(llvm::all_of(E->Scalars, [=](Value *V) -> bool {
    auto *I = cast<Instruction>(V);
    return !E->isOpcodeOrAlt(I) || I->getParent() == BB;
  }));
 
  // The last instruction in the bundle in program order.
  Instruction *LastInst = nullptr;
 
  // Find the last instruction. The common case should be that BB has been
  // scheduled, and the last instruction is VL.back(). So we start with
  // VL.back() and iterate over schedule data until we reach the end of the
  // bundle. The end of the bundle is marked by null ScheduleData.
  if (BlocksSchedules.count(BB)) {
    auto *Bundle =
        BlocksSchedules[BB]->getScheduleData(E->isOneOf(E->Scalars.back()));
    if (Bundle && Bundle->isPartOfBundle())
      for (; Bundle; Bundle = Bundle->NextInBundle)
        if (Bundle->OpValue == Bundle->Inst)
          LastInst = Bundle->Inst;
  }
 
  // LastInst can still be null at this point if there's either not an entry
  // for BB in BlocksSchedules or there's no ScheduleData available for
  // VL.back(). This can be the case if buildTree_rec aborts for various
  // reasons (e.g., the maximum recursion depth is reached, the maximum region
  // size is reached, etc.). ScheduleData is initialized in the scheduling
  // "dry-run".
  //
  // If this happens, we can still find the last instruction by brute force. We
  // iterate forwards from Front (inclusive) until we either see all
  // instructions in the bundle or reach the end of the block. If Front is the
  // last instruction in program order, LastInst will be set to Front, and we
  // will visit all the remaining instructions in the block.
  //
  // One of the reasons we exit early from buildTree_rec is to place an upper
  // bound on compile-time. Thus, taking an additional compile-time hit here is
  // not ideal. However, this should be exceedingly rare since it requires that
  // we both exit early from buildTree_rec and that the bundle be out-of-order
  // (causing us to iterate all the way to the end of the block).
  if (!LastInst) {
    SmallPtrSet<Value *, 16> Bundle(E->Scalars.begin(), E->Scalars.end());
    for (auto &I : make_range(BasicBlock::iterator(Front), BB->end())) {
      if (Bundle.erase(&I) && E->isOpcodeOrAlt(&I))
        LastInst = &I;
      if (Bundle.empty())
        break;
    }
  }
  assert(LastInst && "Failed to find last instruction in bundle");
 
  // Set the insertion point after the last instruction in the bundle. Set the
  // debug location to Front.
  Builder.SetInsertPoint(BB, ++LastInst->getIterator());
  Builder.SetCurrentDebugLocation(Front->getDebugLoc());
}
 
Value *BoUpSLP::gather(ArrayRef<Value *> VL) {
  Value *Val0 =
      isa<StoreInst>(VL[0]) ? cast<StoreInst>(VL[0])->getValueOperand() : VL[0];
  FixedVectorType *VecTy = FixedVectorType::get(Val0->getType(), VL.size());
  Value *Vec = PoisonValue::get(VecTy);
  unsigned InsIndex = 0;
  for (Value *Val : VL) {
    Vec = Builder.CreateInsertElement(Vec, Val, Builder.getInt32(InsIndex++));
    auto *InsElt = dyn_cast<InsertElementInst>(Vec);
    if (!InsElt)
      continue;
    GatherSeq.insert(InsElt);
    CSEBlocks.insert(InsElt->getParent());
    // Add to our 'need-to-extract' list.
    if (TreeEntry *Entry = getTreeEntry(Val)) {
      // Find which lane we need to extract.
      unsigned FoundLane = std::distance(Entry->Scalars.begin(),
                                         find(Entry->Scalars, Val));
      assert(FoundLane < Entry->Scalars.size() && "Couldn't find extract lane");
      if (!Entry->ReuseShuffleIndices.empty()) {
        FoundLane = std::distance(Entry->ReuseShuffleIndices.begin(),
                                  find(Entry->ReuseShuffleIndices, FoundLane));
      }
      ExternalUses.push_back(ExternalUser(Val, InsElt, FoundLane));
    }
  }
 
  return Vec;
}
 
Value *BoUpSLP::vectorizeTree(ArrayRef<Value *> VL) {
  InstructionsState S = getSameOpcode(VL);
  if (S.getOpcode()) {
    if (TreeEntry *E = getTreeEntry(S.OpValue)) {
      if (E->isSame(VL)) {
        Value *V = vectorizeTree(E);
        if (VL.size() == E->Scalars.size() && !E->ReuseShuffleIndices.empty()) {
          // Reshuffle to get only unique values.
          // If some of the scalars are duplicated in the vectorization tree
          // entry, we do not vectorize them but instead generate a mask for the
          // reuses. But if there are several users of the same entry, they may
          // have different vectorization factors. This is especially important
          // for PHI nodes. In this case, we need to adapt the resulting
          // instruction for the user vectorization factor and have to reshuffle
          // it again to take only unique elements of the vector. Without this
          // code the function incorrectly returns reduced vector instruction
          // with the same elements, not with the unique ones.
          // block:
          // %phi = phi <2 x > { .., %entry} {%shuffle, %block}
          // %2 = shuffle <2 x > %phi, %poison, <4 x > <0, 0, 1, 1>
          // ... (use %2)
          // %shuffle = shuffle <2 x> %2, poison, <2 x> {0, 2}
          // br %block
          SmallVector<int, 4> UniqueIdxs;
          SmallSet<int, 4> UsedIdxs;
          int Pos = 0;
          for (int Idx : E->ReuseShuffleIndices) {
            if (UsedIdxs.insert(Idx).second)
              UniqueIdxs.emplace_back(Pos);
            ++Pos;
          }
          V = Builder.CreateShuffleVector(V, UniqueIdxs, "shrink.shuffle");
        }
        return V;
      }
    }
  }
 
  // Check that every instruction appears once in this bundle.
  SmallVector<int, 4> ReuseShuffleIndicies;
  SmallVector<Value *, 4> UniqueValues;
  if (VL.size() > 2) {
    DenseMap<Value *, unsigned> UniquePositions;
    for (Value *V : VL) {
      auto Res = UniquePositions.try_emplace(V, UniqueValues.size());
      ReuseShuffleIndicies.emplace_back(Res.first->second);
      if (Res.second || isa<Constant>(V))
        UniqueValues.emplace_back(V);
    }
    // Do not shuffle single element or if number of unique values is not power
    // of 2.
    if (UniqueValues.size() == VL.size() || UniqueValues.size() <= 1 ||
        !llvm::isPowerOf2_32(UniqueValues.size()))
      ReuseShuffleIndicies.clear();
    else
      VL = UniqueValues;
  }
 
  Value *Vec = gather(VL);
  if (!ReuseShuffleIndicies.empty()) {
    Vec = Builder.CreateShuffleVector(Vec, ReuseShuffleIndicies, "shuffle");
    if (auto *I = dyn_cast<Instruction>(Vec)) {
      GatherSeq.insert(I);
      CSEBlocks.insert(I->getParent());
    }
  }
  return Vec;
}
 
namespace {
/// Merges shuffle masks and emits final shuffle instruction, if required.
class ShuffleInstructionBuilder {
  IRBuilderBase &Builder;
  bool IsFinalized = false;
  SmallVector<int, 4> Mask;
 
public:
  ShuffleInstructionBuilder(IRBuilderBase &Builder) : Builder(Builder) {}
 
  /// Adds a mask, inverting it before applying.
  void addInversedMask(ArrayRef<unsigned> SubMask) {
    if (SubMask.empty())
      return;
    SmallVector<int, 4> NewMask;
    inversePermutation(SubMask, NewMask);
    addMask(NewMask);
  }
 
  /// Functions adds masks, merging them into  single one.
  void addMask(ArrayRef<unsigned> SubMask) {
    SmallVector<int, 4> NewMask(SubMask.begin(), SubMask.end());
    addMask(NewMask);
  }
 
  void addMask(ArrayRef<int> SubMask) {
    if (SubMask.empty())
      return;
    if (Mask.empty()) {
      Mask.append(SubMask.begin(), SubMask.end());
      return;
    }
    SmallVector<int, 4> NewMask(SubMask.size(), SubMask.size());
    int TermValue = std::min(Mask.size(), SubMask.size());
    for (int I = 0, E = SubMask.size(); I < E; ++I) {
      if (SubMask[I] >= TermValue || Mask[SubMask[I]] >= TermValue) {
        NewMask[I] = E;
        continue;
      }
      NewMask[I] = Mask[SubMask[I]];
    }
    Mask.swap(NewMask);
  }
 
  Value *finalize(Value *V) {
    IsFinalized = true;
    if (Mask.empty())
      return V;
    return Builder.CreateShuffleVector(V, Mask, "shuffle");
  }
 
  ~ShuffleInstructionBuilder() {
    assert((IsFinalized || Mask.empty()) &&
           "Shuffle construction must be finalized.");
  }
};
} // namespace
 
Value *BoUpSLP::vectorizeTree(TreeEntry *E) {
  IRBuilder<>::InsertPointGuard Guard(Builder);
 
  if (E->VectorizedValue) {
    LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *E->Scalars[0] << ".\n");
    return E->VectorizedValue;
  }
 
  ShuffleInstructionBuilder ShuffleBuilder(Builder);
  bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty();
  if (E->State == TreeEntry::NeedToGather) {
    setInsertPointAfterBundle(E);
    Value *Vec = gather(E->Scalars);
    if (NeedToShuffleReuses) {
      ShuffleBuilder.addMask(E->ReuseShuffleIndices);
      Vec = ShuffleBuilder.finalize(Vec);
      if (auto *I = dyn_cast<Instruction>(Vec)) {
        GatherSeq.insert(I);
        CSEBlocks.insert(I->getParent());
      }
    }
    E->VectorizedValue = Vec;
    return Vec;
  }
 
  assert((E->State == TreeEntry::Vectorize ||
          E->State == TreeEntry::ScatterVectorize) &&
         "Unhandled state");
  unsigned ShuffleOrOp =
      E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode();
  Instruction *VL0 = E->getMainOp();
  Type *ScalarTy = VL0->getType();
  if (auto *Store = dyn_cast<StoreInst>(VL0))
    ScalarTy = Store->getValueOperand()->getType();
  auto *VecTy = FixedVectorType::get(ScalarTy, E->Scalars.size());
  switch (ShuffleOrOp) {
    case Instruction::PHI: {
      auto *PH = cast<PHINode>(VL0);
      Builder.SetInsertPoint(PH->getParent()->getFirstNonPHI());
      Builder.SetCurrentDebugLocation(PH->getDebugLoc());
      PHINode *NewPhi = Builder.CreatePHI(VecTy, PH->getNumIncomingValues());
      Value *V = NewPhi;
      if (NeedToShuffleReuses)
        V = Builder.CreateShuffleVector(V, E->ReuseShuffleIndices, "shuffle");
 
      E->VectorizedValue = V;
 
      // PHINodes may have multiple entries from the same block. We want to
      // visit every block once.
      SmallPtrSet<BasicBlock*, 4> VisitedBBs;
 
      for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) {
        ValueList Operands;
        BasicBlock *IBB = PH->getIncomingBlock(i);
 
        if (!VisitedBBs.insert(IBB).second) {
          NewPhi->addIncoming(NewPhi->getIncomingValueForBlock(IBB), IBB);
          continue;
        }
 
        Builder.SetInsertPoint(IBB->getTerminator());
        Builder.SetCurrentDebugLocation(PH->getDebugLoc());
        Value *Vec = vectorizeTree(E->getOperand(i));
        NewPhi->addIncoming(Vec, IBB);
      }
 
      assert(NewPhi->getNumIncomingValues() == PH->getNumIncomingValues() &&
             "Invalid number of incoming values");
      return V;
    }
 
    case Instruction::ExtractElement: {
      Value *V = E->getSingleOperand(0);
      Builder.SetInsertPoint(VL0);
      ShuffleBuilder.addInversedMask(E->ReorderIndices);
      ShuffleBuilder.addMask(E->ReuseShuffleIndices);
      V = ShuffleBuilder.finalize(V);
      E->VectorizedValue = V;
      return V;
    }
    case Instruction::ExtractValue: {
      auto *LI = cast<LoadInst>(E->getSingleOperand(0));
      Builder.SetInsertPoint(LI);
      auto *PtrTy = PointerType::get(VecTy, LI->getPointerAddressSpace());
      Value *Ptr = Builder.CreateBitCast(LI->getOperand(0), PtrTy);
      LoadInst *V = Builder.CreateAlignedLoad(VecTy, Ptr, LI->getAlign());
      Value *NewV = propagateMetadata(V, E->Scalars);
      ShuffleBuilder.addInversedMask(E->ReorderIndices);
      ShuffleBuilder.addMask(E->ReuseShuffleIndices);
      NewV = ShuffleBuilder.finalize(NewV);
      E->VectorizedValue = NewV;
      return NewV;
    }
    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: {
      setInsertPointAfterBundle(E);
 
      Value *InVec = vectorizeTree(E->getOperand(0));
 
      if (E->VectorizedValue) {
        LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
        return E->VectorizedValue;
      }
 
      auto *CI = cast<CastInst>(VL0);
      Value *V = Builder.CreateCast(CI->getOpcode(), InVec, VecTy);
      ShuffleBuilder.addMask(E->ReuseShuffleIndices);
      V = ShuffleBuilder.finalize(V);
 
      E->VectorizedValue = V;
      ++NumVectorInstructions;
      return V;
    }
    case Instruction::FCmp:
    case Instruction::ICmp: {
      setInsertPointAfterBundle(E);
 
      Value *L = vectorizeTree(E->getOperand(0));
      Value *R = vectorizeTree(E->getOperand(1));
 
      if (E->VectorizedValue) {
        LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
        return E->VectorizedValue;
      }
 
      CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate();
      Value *V = Builder.CreateCmp(P0, L, R);
      propagateIRFlags(V, E->Scalars, VL0);
      ShuffleBuilder.addMask(E->ReuseShuffleIndices);
      V = ShuffleBuilder.finalize(V);
 
      E->VectorizedValue = V;
      ++NumVectorInstructions;
      return V;
    }
    case Instruction::Select: {
      setInsertPointAfterBundle(E);
 
      Value *Cond = vectorizeTree(E->getOperand(0));
      Value *True = vectorizeTree(E->getOperand(1));
      Value *False = vectorizeTree(E->getOperand(2));
 
      if (E->VectorizedValue) {
        LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
        return E->VectorizedValue;
      }
 
      Value *V = Builder.CreateSelect(Cond, True, False);
      ShuffleBuilder.addMask(E->ReuseShuffleIndices);
      V = ShuffleBuilder.finalize(V);
 
      E->VectorizedValue = V;
      ++NumVectorInstructions;
      return V;
    }
    case Instruction::FNeg: {
      setInsertPointAfterBundle(E);
 
      Value *Op = vectorizeTree(E->getOperand(0));
 
      if (E->VectorizedValue) {
        LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
        return E->VectorizedValue;
      }
 
      Value *V = Builder.CreateUnOp(
          static_cast<Instruction::UnaryOps>(E->getOpcode()), Op);
      propagateIRFlags(V, E->Scalars, VL0);
      if (auto *I = dyn_cast<Instruction>(V))
        V = propagateMetadata(I, E->Scalars);
 
      ShuffleBuilder.addMask(E->ReuseShuffleIndices);
      V = ShuffleBuilder.finalize(V);
 
      E->VectorizedValue = V;
      ++NumVectorInstructions;
 
      return V;
    }
    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: {
      setInsertPointAfterBundle(E);
 
      Value *LHS = vectorizeTree(E->getOperand(0));
      Value *RHS = vectorizeTree(E->getOperand(1));
 
      if (E->VectorizedValue) {
        LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
        return E->VectorizedValue;
      }
 
      Value *V = Builder.CreateBinOp(
          static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS,
          RHS);
      propagateIRFlags(V, E->Scalars, VL0);
      if (auto *I = dyn_cast<Instruction>(V))
        V = propagateMetadata(I, E->Scalars);
 
      ShuffleBuilder.addMask(E->ReuseShuffleIndices);
      V = ShuffleBuilder.finalize(V);
 
      E->VectorizedValue = V;
      ++NumVectorInstructions;
 
      return V;
    }
    case Instruction::Load: {
      // Loads are inserted at the head of the tree because we don't want to
      // sink them all the way down past store instructions.
      bool IsReorder = E->updateStateIfReorder();
      if (IsReorder)
        VL0 = E->getMainOp();
      setInsertPointAfterBundle(E);
 
      LoadInst *LI = cast<LoadInst>(VL0);
      Instruction *NewLI;
      unsigned AS = LI->getPointerAddressSpace();
      Value *PO = LI->getPointerOperand();
      if (E->State == TreeEntry::Vectorize) {
 
        Value *VecPtr = Builder.CreateBitCast(PO, VecTy->getPointerTo(AS));
 
        // The pointer operand uses an in-tree scalar so we add the new BitCast
        // to ExternalUses list to make sure that an extract will be generated
        // in the future.
        if (getTreeEntry(PO))
          ExternalUses.emplace_back(PO, cast<User>(VecPtr), 0);
 
        NewLI = Builder.CreateAlignedLoad(VecTy, VecPtr, LI->getAlign());
      } else {
        assert(E->State == TreeEntry::ScatterVectorize && "Unhandled state");
        Value *VecPtr = vectorizeTree(E->getOperand(0));
        // Use the minimum alignment of the gathered loads.
        Align CommonAlignment = LI->getAlign();
        for (Value *V : E->Scalars)
          CommonAlignment =
              commonAlignment(CommonAlignment, cast<LoadInst>(V)->getAlign());
        NewLI = Builder.CreateMaskedGather(VecPtr, CommonAlignment);
      }
      Value *V = propagateMetadata(NewLI, E->Scalars);
 
      ShuffleBuilder.addInversedMask(E->ReorderIndices);
      ShuffleBuilder.addMask(E->ReuseShuffleIndices);
      V = ShuffleBuilder.finalize(V);
      E->VectorizedValue = V;
      ++NumVectorInstructions;
      return V;
    }
    case Instruction::Store: {
      bool IsReorder = !E->ReorderIndices.empty();
      auto *SI = cast<StoreInst>(
          IsReorder ? E->Scalars[E->ReorderIndices.front()] : VL0);
      unsigned AS = SI->getPointerAddressSpace();
 
      setInsertPointAfterBundle(E);
 
      Value *VecValue = vectorizeTree(E->getOperand(0));
      ShuffleBuilder.addMask(E->ReorderIndices);
      VecValue = ShuffleBuilder.finalize(VecValue);
 
      Value *ScalarPtr = SI->getPointerOperand();
      Value *VecPtr = Builder.CreateBitCast(
          ScalarPtr, VecValue->getType()->getPointerTo(AS));
      StoreInst *ST = Builder.CreateAlignedStore(VecValue, VecPtr,
                                                 SI->getAlign());
 
      // The pointer operand uses an in-tree scalar, so add the new BitCast to
      // ExternalUses to make sure that an extract will be generated in the
      // future.
      if (getTreeEntry(ScalarPtr))
        ExternalUses.push_back(ExternalUser(ScalarPtr, cast<User>(VecPtr), 0));
 
      Value *V = propagateMetadata(ST, E->Scalars);
 
      E->VectorizedValue = V;
      ++NumVectorInstructions;
      return V;
    }
    case Instruction::GetElementPtr: {
      setInsertPointAfterBundle(E);
 
      Value *Op0 = vectorizeTree(E->getOperand(0));
 
      std::vector<Value *> OpVecs;
      for (int j = 1, e = cast<GetElementPtrInst>(VL0)->getNumOperands(); j < e;
           ++j) {
        ValueList &VL = E->getOperand(j);
        // Need to cast all elements to the same type before vectorization to
        // avoid crash.
        Type *VL0Ty = VL0->getOperand(j)->getType();
        Type *Ty = llvm::all_of(
                       VL, [VL0Ty](Value *V) { return VL0Ty == V->getType(); })
                       ? VL0Ty
                       : DL->getIndexType(cast<GetElementPtrInst>(VL0)
                                              ->getPointerOperandType()
                                              ->getScalarType());
        for (Value *&V : VL) {
          auto *CI = cast<ConstantInt>(V);
          V = ConstantExpr::getIntegerCast(CI, Ty,
                                           CI->getValue().isSignBitSet());
        }
        Value *OpVec = vectorizeTree(VL);
        OpVecs.push_back(OpVec);
      }
 
      Value *V = Builder.CreateGEP(
          cast<GetElementPtrInst>(VL0)->getSourceElementType(), Op0, OpVecs);
      if (Instruction *I = dyn_cast<Instruction>(V))
        V = propagateMetadata(I, E->Scalars);
 
      ShuffleBuilder.addMask(E->ReuseShuffleIndices);
      V = ShuffleBuilder.finalize(V);
 
      E->VectorizedValue = V;
      ++NumVectorInstructions;
 
      return V;
    }
    case Instruction::Call: {
      CallInst *CI = cast<CallInst>(VL0);
      setInsertPointAfterBundle(E);
 
      Intrinsic::ID IID  = Intrinsic::not_intrinsic;
      if (Function *FI = CI->getCalledFunction())
        IID = FI->getIntrinsicID();
 
      Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI);
 
      auto VecCallCosts = getVectorCallCosts(CI, VecTy, TTI, TLI);
      bool UseIntrinsic = ID != Intrinsic::not_intrinsic &&
                          VecCallCosts.first <= VecCallCosts.second;
 
      Value *ScalarArg = nullptr;
      std::vector<Value *> OpVecs;
      for (int j = 0, e = CI->getNumArgOperands(); j < e; ++j) {
        ValueList OpVL;
        // Some intrinsics have scalar arguments. This argument should not be
        // vectorized.
        if (UseIntrinsic && hasVectorInstrinsicScalarOpd(IID, j)) {
          CallInst *CEI = cast<CallInst>(VL0);
          ScalarArg = CEI->getArgOperand(j);
          OpVecs.push_back(CEI->getArgOperand(j));
          continue;
        }
 
        Value *OpVec = vectorizeTree(E->getOperand(j));
        LLVM_DEBUG(dbgs() << "SLP: OpVec[" << j << "]: " << *OpVec << "\n");
        OpVecs.push_back(OpVec);
      }
 
      Function *CF;
      if (!UseIntrinsic) {
        VFShape Shape =
            VFShape::get(*CI, ElementCount::getFixed(static_cast<unsigned>(
                                  VecTy->getNumElements())),
                         false /*HasGlobalPred*/);
        CF = VFDatabase(*CI).getVectorizedFunction(Shape);
      } else {
        Type *Tys[] = {FixedVectorType::get(CI->getType(), E->Scalars.size())};
        CF = Intrinsic::getDeclaration(F->getParent(), ID, Tys);
      }
 
      SmallVector<OperandBundleDef, 1> OpBundles;
      CI->getOperandBundlesAsDefs(OpBundles);
      Value *V = Builder.CreateCall(CF, OpVecs, OpBundles);
 
      // The scalar argument uses an in-tree scalar so we add the new vectorized
      // call to ExternalUses list to make sure that an extract will be
      // generated in the future.
      if (ScalarArg && getTreeEntry(ScalarArg))
        ExternalUses.push_back(ExternalUser(ScalarArg, cast<User>(V), 0));
 
      propagateIRFlags(V, E->Scalars, VL0);
      ShuffleBuilder.addMask(E->ReuseShuffleIndices);
      V = ShuffleBuilder.finalize(V);
 
      E->VectorizedValue = V;
      ++NumVectorInstructions;
      return V;
    }
    case Instruction::ShuffleVector: {
      assert(E->isAltShuffle() &&
             ((Instruction::isBinaryOp(E->getOpcode()) &&
               Instruction::isBinaryOp(E->getAltOpcode())) ||
              (Instruction::isCast(E->getOpcode()) &&
               Instruction::isCast(E->getAltOpcode()))) &&
             "Invalid Shuffle Vector Operand");
 
      Value *LHS = nullptr, *RHS = nullptr;
      if (Instruction::isBinaryOp(E->getOpcode())) {
        setInsertPointAfterBundle(E);
        LHS = vectorizeTree(E->getOperand(0));
        RHS = vectorizeTree(E->getOperand(1));
      } else {
        setInsertPointAfterBundle(E);
        LHS = vectorizeTree(E->getOperand(0));
      }
 
      if (E->VectorizedValue) {
        LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
        return E->VectorizedValue;
      }
 
      Value *V0, *V1;
      if (Instruction::isBinaryOp(E->getOpcode())) {
        V0 = Builder.CreateBinOp(
            static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, RHS);
        V1 = Builder.CreateBinOp(
            static_cast<Instruction::BinaryOps>(E->getAltOpcode()), LHS, RHS);
      } else {
        V0 = Builder.CreateCast(
            static_cast<Instruction::CastOps>(E->getOpcode()), LHS, VecTy);
        V1 = Builder.CreateCast(
            static_cast<Instruction::CastOps>(E->getAltOpcode()), LHS, VecTy);
      }
 
      // Create shuffle to take alternate operations from the vector.
      // Also, gather up main and alt scalar ops to propagate IR flags to
      // each vector operation.
      ValueList OpScalars, AltScalars;
      unsigned e = E->Scalars.size();
      SmallVector<int, 8> Mask(e);
      for (unsigned i = 0; i < e; ++i) {
        auto *OpInst = cast<Instruction>(E->Scalars[i]);
        assert(E->isOpcodeOrAlt(OpInst) && "Unexpected main/alternate opcode");
        if (OpInst->getOpcode() == E->getAltOpcode()) {
          Mask[i] = e + i;
          AltScalars.push_back(E->Scalars[i]);
        } else {
          Mask[i] = i;
          OpScalars.push_back(E->Scalars[i]);
        }
      }
 
      propagateIRFlags(V0, OpScalars);
      propagateIRFlags(V1, AltScalars);
 
      Value *V = Builder.CreateShuffleVector(V0, V1, Mask);
      if (Instruction *I = dyn_cast<Instruction>(V))
        V = propagateMetadata(I, E->Scalars);
      ShuffleBuilder.addMask(E->ReuseShuffleIndices);
      V = ShuffleBuilder.finalize(V);
 
      E->VectorizedValue = V;
      ++NumVectorInstructions;
 
      return V;
    }
    default:
    llvm_unreachable("unknown inst");
  }
  return nullptr;
}
 
Value *BoUpSLP::vectorizeTree() {
  ExtraValueToDebugLocsMap ExternallyUsedValues;
  return vectorizeTree(ExternallyUsedValues);
}
 
Value *
BoUpSLP::vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues) {
  // All blocks must be scheduled before any instructions are inserted.
  for (auto &BSIter : BlocksSchedules) {
    scheduleBlock(BSIter.second.get());
  }
 
  Builder.SetInsertPoint(&F->getEntryBlock().front());
  auto *VectorRoot = vectorizeTree(VectorizableTree[0].get());
 
  // If the vectorized tree can be rewritten in a smaller type, we truncate the
  // vectorized root. InstCombine will then rewrite the entire expression. We
  // sign extend the extracted values below.
  auto *ScalarRoot = VectorizableTree[0]->Scalars[0];
  if (MinBWs.count(ScalarRoot)) {
    if (auto *I = dyn_cast<Instruction>(VectorRoot)) {
      // If current instr is a phi and not the last phi, insert it after the
      // last phi node.
      if (isa<PHINode>(I))
        Builder.SetInsertPoint(&*I->getParent()->getFirstInsertionPt());
      else
        Builder.SetInsertPoint(&*++BasicBlock::iterator(I));
    }
    auto BundleWidth = VectorizableTree[0]->Scalars.size();
    auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first);
    auto *VecTy = FixedVectorType::get(MinTy, BundleWidth);
    auto *Trunc = Builder.CreateTrunc(VectorRoot, VecTy);
    VectorizableTree[0]->VectorizedValue = Trunc;
  }
 
  LLVM_DEBUG(dbgs() << "SLP: Extracting " << ExternalUses.size()
                    << " values .\n");
 
  // If necessary, sign-extend or zero-extend ScalarRoot to the larger type
  // specified by ScalarType.
  auto extend = [&](Value *ScalarRoot, Value *Ex, Type *ScalarType) {
    if (!MinBWs.count(ScalarRoot))
      return Ex;
    if (MinBWs[ScalarRoot].second)
      return Builder.CreateSExt(Ex, ScalarType);
    return Builder.CreateZExt(Ex, ScalarType);
  };
 
  // Extract all of the elements with the external uses.
  for (const auto &ExternalUse : ExternalUses) {
    Value *Scalar = ExternalUse.Scalar;
    llvm::User *User = ExternalUse.User;
 
    // Skip users that we already RAUW. This happens when one instruction
    // has multiple uses of the same value.
    if (User && !is_contained(Scalar->users(), User))
      continue;
    TreeEntry *E = getTreeEntry(Scalar);
    assert(E && "Invalid scalar");
    assert(E->State != TreeEntry::NeedToGather &&
           "Extracting from a gather list");
 
    Value *Vec = E->VectorizedValue;
    assert(Vec && "Can't find vectorizable value");
 
    Value *Lane = Builder.getInt32(ExternalUse.Lane);
    // If User == nullptr, the Scalar is used as extra arg. Generate
    // ExtractElement instruction and update the record for this scalar in
    // ExternallyUsedValues.
    if (!User) {
      assert(ExternallyUsedValues.count(Scalar) &&
             "Scalar with nullptr as an external user must be registered in "
             "ExternallyUsedValues map");
      if (auto *VecI = dyn_cast<Instruction>(Vec)) {
        Builder.SetInsertPoint(VecI->getParent(),
                               std::next(VecI->getIterator()));
      } else {
        Builder.SetInsertPoint(&F->getEntryBlock().front());
      }
      Value *Ex = Builder.CreateExtractElement(Vec, Lane);
      Ex = extend(ScalarRoot, Ex, Scalar->getType());
      CSEBlocks.insert(cast<Instruction>(Scalar)->getParent());
      auto &Locs = ExternallyUsedValues[Scalar];
      ExternallyUsedValues.insert({Ex, Locs});
      ExternallyUsedValues.erase(Scalar);
      // Required to update internally referenced instructions.
      Scalar->replaceAllUsesWith(Ex);
      continue;
    }
 
    // Generate extracts for out-of-tree users.
    // Find the insertion point for the extractelement lane.
    if (auto *VecI = dyn_cast<Instruction>(Vec)) {
      if (PHINode *PH = dyn_cast<PHINode>(User)) {
        for (int i = 0, e = PH->getNumIncomingValues(); i != e; ++i) {
          if (PH->getIncomingValue(i) == Scalar) {
            Instruction *IncomingTerminator =
                PH->getIncomingBlock(i)->getTerminator();
            if (isa<CatchSwitchInst>(IncomingTerminator)) {
              Builder.SetInsertPoint(VecI->getParent(),
                                     std::next(VecI->getIterator()));
            } else {
              Builder.SetInsertPoint(PH->getIncomingBlock(i)->getTerminator());
            }
            Value *Ex = Builder.CreateExtractElement(Vec, Lane);
            Ex = extend(ScalarRoot, Ex, Scalar->getType());
            CSEBlocks.insert(PH->getIncomingBlock(i));
            PH->setOperand(i, Ex);
          }
        }
      } else {
        Builder.SetInsertPoint(cast<Instruction>(User));
        Value *Ex = Builder.CreateExtractElement(Vec, Lane);
        Ex = extend(ScalarRoot, Ex, Scalar->getType());
        CSEBlocks.insert(cast<Instruction>(User)->getParent());
        User->replaceUsesOfWith(Scalar, Ex);
      }
    } else {
      Builder.SetInsertPoint(&F->getEntryBlock().front());
      Value *Ex = Builder.CreateExtractElement(Vec, Lane);
      Ex = extend(ScalarRoot, Ex, Scalar->getType());
      CSEBlocks.insert(&F->getEntryBlock());
      User->replaceUsesOfWith(Scalar, Ex);
    }
 
    LLVM_DEBUG(dbgs() << "SLP: Replaced:" << *User << ".\n");
  }
 
  // For each vectorized value:
  for (auto &TEPtr : VectorizableTree) {
    TreeEntry *Entry = TEPtr.get();
 
    // No need to handle users of gathered values.
    if (Entry->State == TreeEntry::NeedToGather)
      continue;
 
    assert(Entry->VectorizedValue && "Can't find vectorizable value");
 
    // For each lane:
    for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) {
      Value *Scalar = Entry->Scalars[Lane];
 
#ifndef NDEBUG
      Type *Ty = Scalar->getType();
      if (!Ty->isVoidTy()) {
        for (User *U : Scalar->users()) {
          LLVM_DEBUG(dbgs() << "SLP: \tvalidating user:" << *U << ".\n");
 
          // It is legal to delete users in the ignorelist.
          assert((getTreeEntry(U) || is_contained(UserIgnoreList, U)) &&
                 "Deleting out-of-tree value");
        }
      }
#endif
      LLVM_DEBUG(dbgs() << "SLP: \tErasing scalar:" << *Scalar << ".\n");
      eraseInstruction(cast<Instruction>(Scalar));
    }
  }
 
  Builder.ClearInsertionPoint();
  InstrElementSize.clear();
 
  return VectorizableTree[0]->VectorizedValue;
}
 
void BoUpSLP::optimizeGatherSequence() {
  LLVM_DEBUG(dbgs() << "SLP: Optimizing " << GatherSeq.size()
                    << " gather sequences instructions.\n");
  // LICM InsertElementInst sequences.
  for (Instruction *I : GatherSeq) {
    if (isDeleted(I))
      continue;
 
    // Check if this block is inside a loop.
    Loop *L = LI->getLoopFor(I->getParent());
    if (!L)
      continue;
 
    // Check if it has a preheader.
    BasicBlock *PreHeader = L->getLoopPreheader();
    if (!PreHeader)
      continue;
 
    // If the vector or the element that we insert into it are
    // instructions that are defined in this basic block then we can't
    // hoist this instruction.
    auto *Op0 = dyn_cast<Instruction>(I->getOperand(0));
    auto *Op1 = dyn_cast<Instruction>(I->getOperand(1));
    if (Op0 && L->contains(Op0))
      continue;
    if (Op1 && L->contains(Op1))
      continue;
 
    // We can hoist this instruction. Move it to the pre-header.
    I->moveBefore(PreHeader->getTerminator());
  }
 
  // Make a list of all reachable blocks in our CSE queue.
  SmallVector<const DomTreeNode *, 8> CSEWorkList;
  CSEWorkList.reserve(CSEBlocks.size());
  for (BasicBlock *BB : CSEBlocks)
    if (DomTreeNode *N = DT->getNode(BB)) {
      assert(DT->isReachableFromEntry(N));
      CSEWorkList.push_back(N);
    }
 
  // Sort blocks by domination. This ensures we visit a block after all blocks
  // dominating it are visited.
  llvm::stable_sort(CSEWorkList,
                    [this](const DomTreeNode *A, const DomTreeNode *B) {
                      return DT->properlyDominates(A, B);
                    });
 
  // Perform O(N^2) search over the gather sequences and merge identical
  // instructions. TODO: We can further optimize this scan if we split the
  // instructions into different buckets based on the insert lane.
  SmallVector<Instruction *, 16> Visited;
  for (auto I = CSEWorkList.begin(), E = CSEWorkList.end(); I != E; ++I) {
    assert(*I &&
           (I == CSEWorkList.begin() || !DT->dominates(*I, *std::prev(I))) &&
           "Worklist not sorted properly!");
    BasicBlock *BB = (*I)->getBlock();
    // For all instructions in blocks containing gather sequences:
    for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e;) {
      Instruction *In = &*it++;
      if (isDeleted(In))
        continue;
      if (!isa<InsertElementInst>(In) && !isa<ExtractElementInst>(In))
        continue;
 
      // Check if we can replace this instruction with any of the
      // visited instructions.
      for (Instruction *v : Visited) {
        if (In->isIdenticalTo(v) &&
            DT->dominates(v->getParent(), In->getParent())) {
          In->replaceAllUsesWith(v);
          eraseInstruction(In);
          In = nullptr;
          break;
        }
      }
      if (In) {
        assert(!is_contained(Visited, In));
        Visited.push_back(In);
      }
    }
  }
  CSEBlocks.clear();
  GatherSeq.clear();
}
 
// Groups the instructions to a bundle (which is then a single scheduling entity)
// and schedules instructions until the bundle gets ready.
Optional<BoUpSLP::ScheduleData *>
BoUpSLP::BlockScheduling::tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP,
                                            const InstructionsState &S) {
  if (isa<PHINode>(S.OpValue))
    return nullptr;
 
  // Initialize the instruction bundle.
  Instruction *OldScheduleEnd = ScheduleEnd;
  ScheduleData *PrevInBundle = nullptr;
  ScheduleData *Bundle = nullptr;
  bool ReSchedule = false;
  LLVM_DEBUG(dbgs() << "SLP:  bundle: " << *S.OpValue << "\n");
 
  auto &&TryScheduleBundle = [this, OldScheduleEnd, SLP](bool ReSchedule,
                                                         ScheduleData *Bundle) {
    // The scheduling region got new instructions at the lower end (or it is a
    // new region for the first bundle). This makes it necessary to
    // recalculate all dependencies.
    // It is seldom that this needs to be done a second time after adding the
    // initial bundle to the region.
    if (ScheduleEnd != OldScheduleEnd) {
      for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode())
        doForAllOpcodes(I, [](ScheduleData *SD) { SD->clearDependencies(); });
      ReSchedule = true;
    }
    if (ReSchedule) {
      resetSchedule();
      initialFillReadyList(ReadyInsts);
    }
    if (Bundle) {
      LLVM_DEBUG(dbgs() << "SLP: try schedule bundle " << *Bundle
                        << " in block " << BB->getName() << "\n");
      calculateDependencies(Bundle, /*InsertInReadyList=*/true, SLP);
    }
 
    // Now try to schedule the new bundle or (if no bundle) just calculate
    // dependencies. As soon as the bundle is "ready" it means that there are no
    // cyclic dependencies and we can schedule it. Note that's important that we
    // don't "schedule" the bundle yet (see cancelScheduling).
    while (((!Bundle && ReSchedule) || (Bundle && !Bundle->isReady())) &&
           !ReadyInsts.empty()) {
      ScheduleData *Picked = ReadyInsts.pop_back_val();
      if (Picked->isSchedulingEntity() && Picked->isReady())
        schedule(Picked, ReadyInsts);
    }
  };
 
  // Make sure that the scheduling region contains all
  // instructions of the bundle.
  for (Value *V : VL) {
    if (!extendSchedulingRegion(V, S)) {
      // If the scheduling region got new instructions at the lower end (or it
      // is a new region for the first bundle). This makes it necessary to
      // recalculate all dependencies.
      // Otherwise the compiler may crash trying to incorrectly calculate
      // dependencies and emit instruction in the wrong order at the actual
      // scheduling.
      TryScheduleBundle(/*ReSchedule=*/false, nullptr);
      return None;
    }
  }
 
  for (Value *V : VL) {
    ScheduleData *BundleMember = getScheduleData(V);
    assert(BundleMember &&
           "no ScheduleData for bundle member (maybe not in same basic block)");
    if (BundleMember->IsScheduled) {
      // A bundle member was scheduled as single instruction before and now
      // needs to be scheduled as part of the bundle. We just get rid of the
      // existing schedule.
      LLVM_DEBUG(dbgs() &