[VPlan] First step towards VPlan cost modeling.

llvm/lib/Transforms/Vectorize/LoopVectorizationPlanner.h

@@ -344,6 +344,16 @@ class LoopVectorizationPlanner {
   /// A builder used to construct the current plan.
   VPBuilder Builder;
 
+  /// Computes the cost of \p Plan for vectorization factor \p VF.
+  ///
+  /// The current implementation requires access to the
+  /// LoopVectorizationLegality to handle inductions and reductions, which is
+  /// why it is kept separate from the VPlan-only cost infrastructure.
+  ///
+  /// TODO: Move to VPlan::cost once the use of LoopVectorizationLegality has
+  /// been retired.
+  InstructionCost cost(VPlan &Plan, ElementCount VF) const;
+
 public:
   LoopVectorizationPlanner(
       Loop *L, LoopInfo *LI, DominatorTree *DT, const TargetLibraryInfo *TLI,
@@ -365,6 +375,9 @@ class LoopVectorizationPlanner {
   /// Return the best VPlan for \p VF.
   VPlan &getBestPlanFor(ElementCount VF) const;
 
+  /// Return the most profitable plan and fix its VF to the most profitable one.
+  VPlan &getBestPlan() const;
+
   /// Generate the IR code for the vectorized loop captured in VPlan \p BestPlan
   /// according to the best selected \p VF and  \p UF.
   ///
@@ -443,7 +456,9 @@ class LoopVectorizationPlanner {
                                   ElementCount MinVF);
 
   /// \return The most profitable vectorization factor and the cost of that VF.
-  /// This method checks every VF in \p CandidateVFs.
+  /// This method checks every VF in \p CandidateVFs. This is now only used to
+  /// verify the decisions by the new VPlan-based cost-model and will be retired
+  /// once the VPlan-based cost-model is stabilized.
   VectorizationFactor
   selectVectorizationFactor(const ElementCountSet &CandidateVFs);
 

llvm/lib/Transforms/Vectorize/LoopVectorize.cpp

@@ -290,7 +290,7 @@ static cl::opt<unsigned> ForceTargetMaxVectorInterleaveFactor(
     cl::desc("A flag that overrides the target's max interleave factor for "
              "vectorized loops."));
 
-static cl::opt<unsigned> ForceTargetInstructionCost(
+cl::opt<unsigned> ForceTargetInstructionCost(
     "force-target-instruction-cost", cl::init(0), cl::Hidden,
     cl::desc("A flag that overrides the target's expected cost for "
              "an instruction to a single constant value. Mostly "
@@ -412,14 +412,6 @@ static bool hasIrregularType(Type *Ty, const DataLayout &DL) {
   return DL.getTypeAllocSizeInBits(Ty) != DL.getTypeSizeInBits(Ty);
 }
 
-/// A helper function that returns the reciprocal of the block probability of
-/// predicated blocks. If we return X, we are assuming the predicated block
-/// will execute once for every X iterations of the loop header.
-///
-/// TODO: We should use actual block probability here, if available. Currently,
-///       we always assume predicated blocks have a 50% chance of executing.
-static unsigned getReciprocalPredBlockProb() { return 2; }
-
 /// Returns "best known" trip count for the specified loop \p L as defined by
 /// the following procedure:
 ///   1) Returns exact trip count if it is known.
@@ -1621,6 +1613,16 @@ class LoopVectorizationCostModel {
   /// \p VF is the vectorization factor chosen for the original loop.
   bool isEpilogueVectorizationProfitable(const ElementCount VF) const;
 
+  /// Return the cost of instructions in an inloop reduction pattern, if I is
+  /// part of that pattern.
+  std::optional<InstructionCost>
+  getReductionPatternCost(Instruction *I, ElementCount VF, Type *VectorTy,
+                          TTI::TargetCostKind CostKind) const;
+
+  /// Returns the execution time cost of an instruction for a given vector
+  /// width. Vector width of one means scalar.
+  VectorizationCostTy getInstructionCost(Instruction *I, ElementCount VF);
+
 private:
   unsigned NumPredStores = 0;
 
@@ -1646,21 +1648,11 @@ class LoopVectorizationCostModel {
   /// of elements.
   ElementCount getMaxLegalScalableVF(unsigned MaxSafeElements);
 
-  /// Returns the execution time cost of an instruction for a given vector
-  /// width. Vector width of one means scalar.
-  VectorizationCostTy getInstructionCost(Instruction *I, ElementCount VF);
-
   /// The cost-computation logic from getInstructionCost which provides
   /// the vector type as an output parameter.
   InstructionCost getInstructionCost(Instruction *I, ElementCount VF,
                                      Type *&VectorTy);
 
-  /// Return the cost of instructions in an inloop reduction pattern, if I is
-  /// part of that pattern.
-  std::optional<InstructionCost>
-  getReductionPatternCost(Instruction *I, ElementCount VF, Type *VectorTy,
-                          TTI::TargetCostKind CostKind) const;
-
   /// Calculate vectorization cost of memory instruction \p I.
   InstructionCost getMemoryInstructionCost(Instruction *I, ElementCount VF);
 
@@ -7288,7 +7280,10 @@ LoopVectorizationPlanner::plan(ElementCount UserVF, unsigned UserIC) {
   if (!MaxFactors.hasVector())
     return VectorizationFactor::Disabled();
 
-  // Select the optimal vectorization factor.
+  // Select the optimal vectorization factor according to the legacy cost-model.
+  // This is now only used to verify the decisions by the new VPlan-based
+  // cost-model and will be retired once the VPlan-based cost-model is
+  // stabilized.
   VectorizationFactor VF = selectVectorizationFactor(VFCandidates);
   assert((VF.Width.isScalar() || VF.ScalarCost > 0) && "when vectorizing, the scalar cost must be non-zero.");
   if (!hasPlanWithVF(VF.Width)) {
@@ -7299,6 +7294,166 @@ LoopVectorizationPlanner::plan(ElementCount UserVF, unsigned UserIC) {
   return VF;
 }
 
+InstructionCost VPCostContext::getLegacyCost(Instruction *UI,
+                                             ElementCount VF) const {
+  return CM.getInstructionCost(UI, VF).first;
+}
+
+bool VPCostContext::skipCostComputation(Instruction *UI, bool IsVector) const {
+  return (IsVector && CM.VecValuesToIgnore.contains(UI)) ||
+         SkipCostComputation.contains(UI);
+}
+
+InstructionCost LoopVectorizationPlanner::cost(VPlan &Plan,
+                                               ElementCount VF) const {
+  InstructionCost Cost = 0;
+  LLVMContext &LLVMCtx = OrigLoop->getHeader()->getContext();
+  VPCostContext CostCtx(CM.TTI, Legal->getWidestInductionType(), LLVMCtx, CM);
+
+  // Cost modeling for inductions is inaccurate in the legacy cost model
+  // compared to the recipes that are generated. To match here initially during
+  // VPlan cost model bring up directly use the induction costs from the legacy
+  // cost model. Note that we do this as pre-processing; the VPlan may not have
+  // any recipes associated with the original induction increment instruction.
+  // We precompute the cost of both induction increment instructions that are
+  // represented by recipes and those that are not, to avoid distinguishing
+  // between them here, and skip all recipes that represent induction increments
+  // (the former case) later on, if they exist, to avoid counting them twice.
+  // TODO: Switch to more accurate costing based on VPlan.
+  for (const auto &[IV, _] : Legal->getInductionVars()) {
+    Instruction *IVInc = cast<Instruction>(
+        IV->getIncomingValueForBlock(OrigLoop->getLoopLatch()));
+    assert(!CostCtx.SkipCostComputation.contains(IVInc) &&
+           "Same IV increment for multiple inductions?");
+    CostCtx.SkipCostComputation.insert(IVInc);
+    InstructionCost InductionCost = CostCtx.getLegacyCost(IVInc, VF);
+    LLVM_DEBUG({
+      dbgs() << "Cost of " << InductionCost << " for VF " << VF
+             << ":\n induction increment " << *IVInc << "\n";
+      IVInc->dump();
+    });
+    Cost += InductionCost;
+  }
+
+  /// Compute the cost of all exiting conditions of the loop using the legacy
+  /// cost model. This is to match the legacy behavior, which adds the cost of
+  /// all exit conditions. Note that this over-estimates the cost, as there will
+  /// be a single condition to control the vector loop.
+  SmallVector<BasicBlock *> Exiting;
+  CM.TheLoop->getExitingBlocks(Exiting);
+  // Add the cost of all exit conditions.
+  for (BasicBlock *EB : Exiting) {
+    auto *Term = dyn_cast<BranchInst>(EB->getTerminator());
+    if (!Term)
+      continue;
+    if (auto *CondI = dyn_cast<Instruction>(Term->getOperand(0))) {
+      assert(!CostCtx.SkipCostComputation.contains(CondI) &&
+             "Condition already skipped?");
+      CostCtx.SkipCostComputation.insert(CondI);
+      Cost += CostCtx.getLegacyCost(CondI, VF);
+    }
+  }
+
+  // The legacy cost model has special logic to compute the cost of in-loop
+  // reductions, which may be smaller than the sum of all instructions involved
+  // in the reduction. For AnyOf reductions, VPlan codegen may remove the select
+  // which the legacy cost model uses to assign cost. Pre-compute their costs
+  // for now.
+  // TODO: Switch to costing based on VPlan once the logic has been ported.
+  for (const auto &[RedPhi, RdxDesc] : Legal->getReductionVars()) {
+    if (!CM.isInLoopReduction(RedPhi) &&
+        !RecurrenceDescriptor::isAnyOfRecurrenceKind(
+            RdxDesc.getRecurrenceKind()))
+      continue;
+
+    // AnyOf reduction codegen may remove the select. To match the legacy cost
+    // model, pre-compute the cost for AnyOf reductions here.
+    if (RecurrenceDescriptor::isAnyOfRecurrenceKind(
+            RdxDesc.getRecurrenceKind())) {
+      auto *Select = cast<SelectInst>(*find_if(
+          RedPhi->users(), [](User *U) { return isa<SelectInst>(U); }));
+      assert(!CostCtx.SkipCostComputation.contains(Select) &&
+             "reduction op visited multiple times");
+      CostCtx.SkipCostComputation.insert(Select);
+      auto ReductionCost = CostCtx.getLegacyCost(Select, VF);
+      LLVM_DEBUG(dbgs() << "Cost of " << ReductionCost << " for VF " << VF
+                        << ":\n any-of reduction " << *Select << "\n");
+      Cost += ReductionCost;
+      continue;
+    }
+
+    const auto &ChainOps = RdxDesc.getReductionOpChain(RedPhi, OrigLoop);
+    SetVector<Instruction *> ChainOpsAndOperands(ChainOps.begin(),
+                                                 ChainOps.end());
+    // Also include the operands of instructions in the chain, as the cost-model
+    // may mark extends as free.
+    for (auto *ChainOp : ChainOps) {
+      for (Value *Op : ChainOp->operands()) {
+        if (auto *I = dyn_cast<Instruction>(Op))
+          ChainOpsAndOperands.insert(I);
+      }
+    }
+
+    // Pre-compute the cost for I, if it has a reduction pattern cost.
+    for (Instruction *I : ChainOpsAndOperands) {
+      auto ReductionCost = CM.getReductionPatternCost(
+          I, VF, ToVectorTy(I->getType(), VF), TTI::TCK_RecipThroughput);
+      if (!ReductionCost)
+        continue;
+
+      assert(!CostCtx.SkipCostComputation.contains(I) &&
+             "reduction op visited multiple times");
+      CostCtx.SkipCostComputation.insert(I);
+      LLVM_DEBUG(dbgs() << "Cost of " << ReductionCost << " for VF " << VF
+                        << ":\n in-loop reduction " << *I << "\n");
+      Cost += *ReductionCost;
+    }
+  }
+
+  // Now compute and add the VPlan-based cost.
+  Cost += Plan.cost(VF, CostCtx);
+  LLVM_DEBUG(dbgs() << "Cost for VF " << VF << ": " << Cost << "\n");
+  return Cost;
+}
+
+VPlan &LoopVectorizationPlanner::getBestPlan() const {
+  // If there is a single VPlan with a single VF, return it directly.
+  VPlan &FirstPlan = *VPlans[0];
+  if (VPlans.size() == 1 && size(FirstPlan.vectorFactors()) == 1)
+    return FirstPlan;
+
+  VPlan *BestPlan = &FirstPlan;
+  ElementCount ScalarVF = ElementCount::getFixed(1);
+  assert(hasPlanWithVF(ScalarVF) &&
+         "More than a single plan/VF w/o any plan having scalar VF");
+
+  InstructionCost ScalarCost = cost(getBestPlanFor(ScalarVF), ScalarVF);
+  VectorizationFactor BestFactor(ScalarVF, ScalarCost, ScalarCost);
+
+  bool ForceVectorization = Hints.getForce() == LoopVectorizeHints::FK_Enabled;
+  if (ForceVectorization) {
+    // Ignore scalar width, because the user explicitly wants vectorization.
+    // Initialize cost to max so that VF = 2 is, at least, chosen during cost
+    // evaluation.
+    BestFactor.Cost = InstructionCost::getMax();
+  }
+
+  for (auto &P : VPlans) {
+    for (ElementCount VF : P->vectorFactors()) {
+      if (VF.isScalar())
+        continue;
+      InstructionCost Cost = cost(*P, VF);
+      VectorizationFactor CurrentFactor(VF, Cost, ScalarCost);
+      if (isMoreProfitable(CurrentFactor, BestFactor)) {
+        BestFactor = CurrentFactor;
+        BestPlan = &*P;
+      }
+    }
+  }
+  BestPlan->setVF(BestFactor.Width);
+  return *BestPlan;
+}
+
 VPlan &LoopVectorizationPlanner::getBestPlanFor(ElementCount VF) const {
   assert(count_if(VPlans,
                   [VF](const VPlanPtr &Plan) { return Plan->hasVF(VF); }) ==
@@ -10157,8 +10312,15 @@ bool LoopVectorizePass::processLoop(Loop *L) {
                                VF.MinProfitableTripCount, IC, &LVL, &CM, BFI,
                                PSI, Checks);
 
-        VPlan &BestPlan = LVP.getBestPlanFor(VF.Width);
-        LVP.executePlan(VF.Width, IC, BestPlan, LB, DT, false);
+        VPlan &BestPlan = LVP.getBestPlan();
+        assert(size(BestPlan.vectorFactors()) == 1 &&
+               "Plan should have a single VF");
+        ElementCount Width = *BestPlan.vectorFactors().begin();
+        LLVM_DEBUG(dbgs() << "VF picked by VPlan cost model: " << Width
+                          << "\n");
+        assert(VF.Width == Width &&
+               "VPlan cost model and legacy cost model disagreed");
+        LVP.executePlan(Width, IC, BestPlan, LB, DT, false);
         ++LoopsVectorized;
 
         // Add metadata to disable runtime unrolling a scalar loop when there