[LV] Move getScalarizationOverhead and vector call cost computations to CM. (NFC)

[fhahn]

Summary

This reduces the number of parameters we need to pass in and they seem a
natural fit in LoopVectorizationCostModel. Also simplifies things for
D59995.

As a follow up refactoring, we could only expose a expose a
shouldUseVectorIntrinsic() helper in LoopVectorizationCostModel, instead
of calling getVectorCallCost/getVectorIntrinsicCost in
InnerLoopVectorizer/VPRecipeBuilder.

[rengolin]

looks obviously good to me. thanks!

llvm/lib/Transforms/Vectorize/LoopVectorize.cpp

6042

spurious new line?

6645

same here?

[fhahn]

Ran clang-format.

Thanks Renato! I'll wait with committing until D59995 is reviewed, in case
there are additional suggestions there.

llvm/lib/Transforms/Vectorize/LoopVectorize.cpp

public:
 
   /// Returns true if all loop blocks should be masked to fold tail loop.
   bool foldTailByMasking() const { return FoldTailByMasking; }
 
   bool blockNeedsPredication(BasicBlock *BB) {
     return foldTailByMasking() || Legal->blockNeedsPredication(BB);
   }
 
+  /// Estimate cost of an intrinsic call instruction CI if it were vectorized
+  /// with factor VF.  Return the cost of the instruction, including
+  /// scalarization overhead if it's needed.
+  unsigned getVectorIntrinsicCost(CallInst *CI, unsigned VF);
+
+  /// Estimate cost of a call instruction CI if it were vectorized with factor
+  /// VF. Return the cost of the instruction, including scalarization overhead
+  /// if it's needed. The flag NeedToScalarize shows if the call needs to be
+  /// scalarized -
+  // i.e. either vector version isn't available, or is too expensive.
+  unsigned getVectorCallCost(CallInst *CI, unsigned VF, bool &NeedToScalarize);
+
 private:
   unsigned NumPredStores = 0;
 
   /// \return An upper bound for the vectorization factor, larger than zero.
   /// One is returned if vectorization should best be avoided due to cost.
   unsigned computeFeasibleMaxVF(bool OptForSize, unsigned ConstTripCount);
 
   /// The vectorization cost is a combination of the cost itself and a boolean
private:
   unsigned getConsecutiveMemOpCost(Instruction *I, unsigned VF);
 
   /// The cost calculation for Load/Store instruction \p I with uniform pointer -
   /// Load: scalar load + broadcast.
   /// Store: scalar store + (loop invariant value stored? 0 : extract of last
   /// element)
   unsigned getUniformMemOpCost(Instruction *I, unsigned VF);
 
+  /// Estimate the overhead of scalarizing an instruction. This is a
+  /// convenience wrapper for the type-based getScalarizationOverhead API.
+  unsigned getScalarizationOverhead(Instruction *I, unsigned VF);
+
   /// Returns whether the instruction is a load or store and will be a emitted
   /// as a vector operation.
   bool isConsecutiveLoadOrStore(Instruction *I);
 
   /// Returns true if an artificially high cost for emulated masked memrefs
   /// should be used.
   bool useEmulatedMaskMemRefHack(Instruction *I);
 
if (Instruction *V = CSEMap.lookup(In)) {
       In->eraseFromParent();
       continue;
     }
 
     CSEMap[In] = In;
   }
 }
 
-/// Estimate the overhead of scalarizing an instruction. This is a
-/// convenience wrapper for the type-based getScalarizationOverhead API.
-static unsigned getScalarizationOverhead(Instruction *I, unsigned VF,
-                                         const TargetTransformInfo &TTI) {
-  if (VF == 1)
-    return 0;
-
-  unsigned Cost = 0;
-  Type *RetTy = ToVectorTy(I->getType(), VF);
-  if (!RetTy->isVoidTy() &&
-      (!isa<LoadInst>(I) ||
-       !TTI.supportsEfficientVectorElementLoadStore()))
-    Cost += TTI.getScalarizationOverhead(RetTy, true, false);
-
-  // Some targets keep addresses scalar.
-  if (isa<LoadInst>(I) && !TTI.prefersVectorizedAddressing())
-    return Cost;
-
-  if (CallInst *CI = dyn_cast<CallInst>(I)) {
-    SmallVector<const Value *, 4> Operands(CI->arg_operands());
-    Cost += TTI.getOperandsScalarizationOverhead(Operands, VF);
-  }
-  else if (!isa<StoreInst>(I) ||
-           !TTI.supportsEfficientVectorElementLoadStore()) {
-    SmallVector<const Value *, 4> Operands(I->operand_values());
-    Cost += TTI.getOperandsScalarizationOverhead(Operands, VF);
-  }
-
-  return Cost;
-}
-
-// Estimate cost of a call instruction CI if it were vectorized with factor VF.
-// Return the cost of the instruction, including scalarization overhead if it's
-// needed. The flag NeedToScalarize shows if the call needs to be scalarized -
-// i.e. either vector version isn't available, or is too expensive.
-static unsigned getVectorCallCost(CallInst *CI, unsigned VF,
-                                  const TargetTransformInfo &TTI,
-                                  const TargetLibraryInfo *TLI,
+unsigned LoopVectorizationCostModel::getVectorCallCost(CallInst *CI,
+                                                       unsigned VF,
                                                        bool &NeedToScalarize) {
   Function *F = CI->getCalledFunction();
   StringRef FnName = CI->getCalledFunction()->getName();
   Type *ScalarRetTy = CI->getType();
   SmallVector<Type *, 4> Tys, ScalarTys;
   for (auto &ArgOp : CI->arg_operands())
     ScalarTys.push_back(ArgOp->getType());
 
   // Estimate cost of scalarized vector call. The source operands are assumed
   // to be vectors, so we need to extract individual elements from there,
   // execute VF scalar calls, and then gather the result into the vector return
   // value.
   unsigned ScalarCallCost = TTI.getCallInstrCost(F, ScalarRetTy, ScalarTys);
   if (VF == 1)
     return ScalarCallCost;
 
   // Compute corresponding vector type for return value and arguments.
   Type *RetTy = ToVectorTy(ScalarRetTy, VF);
   for (Type *ScalarTy : ScalarTys)
     Tys.push_back(ToVectorTy(ScalarTy, VF));
 
   // Compute costs of unpacking argument values for the scalar calls and
   // packing the return values to a vector.
-  unsigned ScalarizationCost = getScalarizationOverhead(CI, VF, TTI);
+  unsigned ScalarizationCost = getScalarizationOverhead(CI, VF);
 
   unsigned Cost = ScalarCallCost * VF + ScalarizationCost;
 
   // If we can't emit a vector call for this function, then the currently found
   // cost is the cost we need to return.
   NeedToScalarize = true;
   if (!TLI || !TLI->isFunctionVectorizable(FnName, VF) || CI->isNoBuiltin())
     return Cost;
 
   // If the corresponding vector cost is cheaper, return its cost.
   unsigned VectorCallCost = TTI.getCallInstrCost(nullptr, RetTy, Tys);
   if (VectorCallCost < Cost) {
     NeedToScalarize = false;
     return VectorCallCost;
   }
   return Cost;
 }
 
-// Estimate cost of an intrinsic call instruction CI if it were vectorized with
-// factor VF.  Return the cost of the instruction, including scalarization
-// overhead if it's needed.
-static unsigned getVectorIntrinsicCost(CallInst *CI, unsigned VF,
-                                       const TargetTransformInfo &TTI,
-                                       const TargetLibraryInfo *TLI) {
+unsigned LoopVectorizationCostModel::getVectorIntrinsicCost(CallInst *CI,
+                                                            unsigned VF) {
   Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI);
   assert(ID && "Expected intrinsic call!");
 
   FastMathFlags FMF;
   if (auto *FPMO = dyn_cast<FPMathOperator>(CI))
     FMF = FPMO->getFastMathFlags();
 
   SmallVector<Value *, 4> Operands(CI->arg_operands());
for (Value *ArgOperand : CI->arg_operands())
       Tys.push_back(ToVectorTy(ArgOperand->getType(), VF));
 
     Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI);
 
     // The flag shows whether we use Intrinsic or a usual Call for vectorized
     // version of the instruction.
     // Is it beneficial to perform intrinsic call compared to lib call?
     bool NeedToScalarize;
-    unsigned CallCost = getVectorCallCost(CI, VF, *TTI, TLI, NeedToScalarize);
+    unsigned CallCost = Cost->getVectorCallCost(CI, VF, NeedToScalarize);
     bool UseVectorIntrinsic =
-        ID && getVectorIntrinsicCost(CI, VF, *TTI, TLI) <= CallCost;
+        ID && Cost->getVectorIntrinsicCost(CI, VF) <= CallCost;
     assert((UseVectorIntrinsic || !NeedToScalarize) &&
            "Instruction should be scalarized elsewhere.");
 
     for (unsigned Part = 0; Part < UF; ++Part) {
       SmallVector<Value *, 4> Args;
       for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i) {
         Value *Arg = CI->getArgOperand(i);
         // Some intrinsics have a scalar argument - don't replace it with a
unsigned LoopVectorizationCostModel::getMemInstScalarizationCost(Instruction *I,
   // Don't pass *I here, since it is scalar but will actually be part of a
   // vectorized loop where the user of it is a vectorized instruction.
   Cost += VF *
           TTI.getMemoryOpCost(I->getOpcode(), ValTy->getScalarType(), Alignment,
                               AS);
 
   // Get the overhead of the extractelement and insertelement instructions
   // we might create due to scalarization.
-  Cost += getScalarizationOverhead(I, VF, TTI);
+  Cost += getScalarizationOverhead(I, VF);
 
   // If we have a predicated store, it may not be executed for each vector
   // lane. Scale the cost by the probability of executing the predicated
   // block.
   if (isPredicatedInst(I)) {
     Cost /= getReciprocalPredBlockProb();
 
     if (useEmulatedMaskMemRefHack(I))
LoopVectorizationCostModel::getInstructionCost(Instruction *I, unsigned VF) {
   Type *VectorTy;
   unsigned C = getInstructionCost(I, VF, VectorTy);
 
   bool TypeNotScalarized =
       VF > 1 && VectorTy->isVectorTy() && TTI.getNumberOfParts(VectorTy) < VF;
   return VectorizationCostTy(C, TypeNotScalarized);
 }
 
+unsigned LoopVectorizationCostModel::getScalarizationOverhead(Instruction *I,
+                                                              unsigned VF) {
+
+  if (VF == 1)
+    return 0;
+
+  unsigned Cost = 0;
+  Type *RetTy = ToVectorTy(I->getType(), VF);
+  if (!RetTy->isVoidTy() &&
+      (!isa<LoadInst>(I) || !TTI.supportsEfficientVectorElementLoadStore()))
+    Cost += TTI.getScalarizationOverhead(RetTy, true, false);
+
+  // Some targets keep addresses scalar.
+  if (isa<LoadInst>(I) && !TTI.prefersVectorizedAddressing())
+    return Cost;
+
+  if (CallInst *CI = dyn_cast<CallInst>(I)) {
+    SmallVector<const Value *, 4> Operands(CI->arg_operands());
+    Cost += TTI.getOperandsScalarizationOverhead(Operands, VF);
+  } else if (!isa<StoreInst>(I) ||
+             !TTI.supportsEfficientVectorElementLoadStore()) {
+    SmallVector<const Value *, 4> Operands(I->operand_values());
+    Cost += TTI.getOperandsScalarizationOverhead(Operands, VF);
+  }
+
+  return Cost;
+}
+
 void LoopVectorizationCostModel::setCostBasedWideningDecision(unsigned VF) {
   if (VF == 1)
     return;
   NumPredStores = 0;
   for (BasicBlock *BB : TheLoop->blocks()) {
     // For each instruction in the old loop.
     for (Instruction &I : *BB) {
       Value *Ptr =  getLoadStorePointerOperand(&I);
if (VF > 1 && isScalarWithPredication(I)) {
       // models a copy at the end of each predicated block.
       Cost += VF * TTI.getCFInstrCost(Instruction::PHI);
 
       // The cost of the non-predicated instruction.
       Cost += VF * TTI.getArithmeticInstrCost(I->getOpcode(), RetTy);
 
       // The cost of insertelement and extractelement instructions needed for
       // scalarization.
-      Cost += getScalarizationOverhead(I, VF, TTI);
+      Cost += getScalarizationOverhead(I, VF);
 
       // Scale the cost by the probability of executing the predicated blocks.
       // This assumes the predicated block for each vector lane is equally
       // likely.
       return Cost / getReciprocalPredBlockProb();
     }
     LLVM_FALLTHROUGH;
   case Instruction::Add:
case Instruction::BitCast: {
     }
 
     unsigned N = isScalarAfterVectorization(I, VF) ? VF : 1;
     return N * TTI.getCastInstrCost(I->getOpcode(), VectorTy, SrcVecTy, I);
   }
   case Instruction::Call: {
     bool NeedToScalarize;
     CallInst *CI = cast<CallInst>(I);
-    unsigned CallCost = getVectorCallCost(CI, VF, TTI, TLI, NeedToScalarize);
+    unsigned CallCost = getVectorCallCost(CI, VF, NeedToScalarize);
     if (getVectorIntrinsicIDForCall(CI, TLI))
-      return std::min(CallCost, getVectorIntrinsicCost(CI, VF, TTI, TLI));
+      return std::min(CallCost, getVectorIntrinsicCost(CI, VF));
     return CallCost;
   }
   default:
     // The cost of executing VF copies of the scalar instruction. This opcode
     // is unknown. Assume that it is the same as 'mul'.
     return VF * TTI.getArithmeticInstrCost(Instruction::Mul, VectorTy) +
-           getScalarizationOverhead(I, VF, TTI);
+           getScalarizationOverhead(I, VF);
   } // end of switch.
 }
 
 char LoopVectorize::ID = 0;
 
 static const char lv_name[] = "Loop Vectorization";
 
 INITIALIZE_PASS_BEGIN(LoopVectorize, LV_NAME, lv_name, false, false)
if (!isa<PHINode>(I) && (CM.isScalarAfterVectorization(I, VF) ||
       return false;
     if (CallInst *CI = dyn_cast<CallInst>(I)) {
       Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI);
       // The following case may be scalarized depending on the VF.
       // The flag shows whether we use Intrinsic or a usual Call for vectorized
       // version of the instruction.
       // Is it beneficial to perform intrinsic call compared to lib call?
       bool NeedToScalarize;
-      unsigned CallCost = getVectorCallCost(CI, VF, *TTI, TLI, NeedToScalarize);
+      unsigned CallCost = CM.getVectorCallCost(CI, VF, NeedToScalarize);
       bool UseVectorIntrinsic =
-          ID && getVectorIntrinsicCost(CI, VF, *TTI, TLI) <= CallCost;
+          ID && CM.getVectorIntrinsicCost(CI, VF) <= CallCost;
       return UseVectorIntrinsic || !NeedToScalarize;
     }
     if (isa<LoadInst>(I) || isa<StoreInst>(I)) {
       assert(CM.getWideningDecision(I, VF) ==
                  LoopVectorizationCostModel::CM_Scalarize &&
              "Memory widening decisions should have been taken care by now");
       return false;
     }
LoopVectorizationPlanner::buildVPlanWithVPRecipes(
 
   DenseMap<Instruction *, Instruction *> &SinkAfter = Legal->getSinkAfter();
   DenseMap<Instruction *, Instruction *> SinkAfterInverse;
 
   // Create a dummy pre-entry VPBasicBlock to start building the VPlan.
   VPBasicBlock *VPBB = new VPBasicBlock("Pre-Entry");
   auto Plan = llvm::make_unique<VPlan>(VPBB);
 
-  VPRecipeBuilder RecipeBuilder(OrigLoop, TLI, TTI, Legal, CM, Builder);
+  VPRecipeBuilder RecipeBuilder(OrigLoop, TLI, Legal, CM, Builder);
   // Represent values that will have defs inside VPlan.
   for (Value *V : NeedDef)
     Plan->addVPValue(V);
 
   // Scan the body of the loop in a topological order to visit each basic block
   // after having visited its predecessor basic blocks.
   LoopBlocksDFS DFS(OrigLoop);
   DFS.perform(LI);

llvm/lib/Transforms/Vectorize/VPRecipeBuilder.h

 /// Helper class to create VPRecipies from IR instructions.
 class VPRecipeBuilder {
   /// The loop that we evaluate.
   Loop *OrigLoop;
 
   /// Target Library Info.
   const TargetLibraryInfo *TLI;
 
-  /// Target Transform Info.
-  const TargetTransformInfo *TTI;
-
   /// The legality analysis.
   LoopVectorizationLegality *Legal;
 
   /// The profitablity analysis.
   LoopVectorizationCostModel &CM;
 
   VPBuilder &Builder;
 
public:
 
   /// Create a replicating region for instruction \p I that requires
   /// predication. \p PredRecipe is a VPReplicateRecipe holding \p I.
   VPRegionBlock *createReplicateRegion(Instruction *I, VPRecipeBase *PredRecipe,
                                        VPlanPtr &Plan);
 
 public:
   VPRecipeBuilder(Loop *OrigLoop, const TargetLibraryInfo *TLI,
-                  const TargetTransformInfo *TTI,
                   LoopVectorizationLegality *Legal,
                   LoopVectorizationCostModel &CM, VPBuilder &Builder)
-      : OrigLoop(OrigLoop), TLI(TLI), TTI(TTI), Legal(Legal), CM(CM),
-        Builder(Builder) {}
+      : OrigLoop(OrigLoop), TLI(TLI), Legal(Legal), CM(CM), Builder(Builder) {}
 
   /// Check if a recipe can be create for \p I withing the given VF \p Range.
   /// If a recipe can be created, it adds it to \p VPBB.
   bool tryToCreateRecipe(Instruction *Instr, VFRange &Range, VPlanPtr &Plan,
                          VPBasicBlock *VPBB);
 
   /// Build a VPReplicationRecipe for \p I and enclose it within a Region if it
   /// is predicated. \return \p VPBB augmented with this new recipe if \p I is