[llvm] 17b701c - [LV] Collect a list of all element types found in the loop (NFC)

[Kerry McLaughlin via llvm-commits]

Author: Kerry McLaughlin
Date: 2021-07-06T10:37:41+01:00
New Revision: 17b701c43ca6459db020bff075b119f33a4a8ec5

URL: https://github.com/llvm/llvm-project/commit/17b701c43ca6459db020bff075b119f33a4a8ec5
DIFF: https://github.com/llvm/llvm-project/commit/17b701c43ca6459db020bff075b119f33a4a8ec5.diff

LOG: [LV] Collect a list of all element types found in the loop (NFC)

Splits `getSmallestAndWidestTypes` into two functions, one of which now collects
a list of all element types found in the loop (`ElementTypesInLoop`). This ensures we do not
have to iterate over all instructions in the loop again in other places, such as in D102253
which disables scalable vectorization of a loop if any of the instructions use invalid types.

Reviewed By: sdesmalen

Differential Revision: https://reviews.llvm.org/D105437

Added: 
    

Modified: 
    llvm/lib/Transforms/Vectorize/LoopVectorize.cpp

Removed: 
    


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diff  --git a/llvm/lib/Transforms/Vectorize/LoopVectorize.cpp b/llvm/lib/Transforms/Vectorize/LoopVectorize.cpp
index 617300f07db0..f3e5b020e8b6 100644
--- a/llvm/lib/Transforms/Vectorize/LoopVectorize.cpp
+++ b/llvm/lib/Transforms/Vectorize/LoopVectorize.cpp
@@ -1305,6 +1305,9 @@ class LoopVectorizationCostModel {
   /// Collect values we want to ignore in the cost model.
   void collectValuesToIgnore();
 
+  /// Collect all element types in the loop for which widening is needed.
+  void collectElementTypesForWidening();
+
   /// Split reductions into those that happen in the loop, and those that happen
   /// outside. In loop reductions are collected into InLoopReductionChains.
   void collectInLoopReductions();
@@ -1890,6 +1893,9 @@ class LoopVectorizationCostModel {
   /// Values to ignore in the cost model when VF > 1.
   SmallPtrSet<const Value *, 16> VecValuesToIgnore;
 
+  /// All element types found in the loop.
+  SmallPtrSet<Type *, 16> ElementTypesInLoop;
+
   /// Profitable vector factors.
   SmallVector<VectorizationFactor, 8> ProfitableVFs;
 };
@@ -6246,7 +6252,17 @@ LoopVectorizationCostModel::getSmallestAndWidestTypes() {
   unsigned MinWidth = -1U;
   unsigned MaxWidth = 8;
   const DataLayout &DL = TheFunction->getParent()->getDataLayout();
+  for (Type *T : ElementTypesInLoop) {
+    MinWidth = std::min<unsigned>(
+        MinWidth, DL.getTypeSizeInBits(T->getScalarType()).getFixedSize());
+    MaxWidth = std::max<unsigned>(
+        MaxWidth, DL.getTypeSizeInBits(T->getScalarType()).getFixedSize());
+  }
+  return {MinWidth, MaxWidth};
+}
 
+void LoopVectorizationCostModel::collectElementTypesForWidening() {
+  ElementTypesInLoop.clear();
   // For each block.
   for (BasicBlock *BB : TheLoop->blocks()) {
     // For each instruction in the loop.
@@ -6292,14 +6308,9 @@ LoopVectorizationCostModel::getSmallestAndWidestTypes() {
           !isAccessInterleaved(&I) && !isLegalGatherOrScatter(&I))
         continue;
 
-      MinWidth = std::min(MinWidth,
-                          (unsigned)DL.getTypeSizeInBits(T->getScalarType()));
-      MaxWidth = std::max(MaxWidth,
-                          (unsigned)DL.getTypeSizeInBits(T->getScalarType()));
+      ElementTypesInLoop.insert(T);
     }
   }
-
-  return {MinWidth, MaxWidth};
 }
 
 unsigned LoopVectorizationCostModel::selectInterleaveCount(ElementCount VF,
@@ -9840,6 +9851,8 @@ static bool processLoopInVPlanNativePath(
   // Get user vectorization factor.
   ElementCount UserVF = Hints.getWidth();
 
+  CM.collectElementTypesForWidening();
+
   // Plan how to best vectorize, return the best VF and its cost.
   const VectorizationFactor VF = LVP.planInVPlanNativePath(UserVF);
 
@@ -10061,6 +10074,7 @@ bool LoopVectorizePass::processLoop(Loop *L) {
   LoopVectorizationCostModel CM(SEL, L, PSE, LI, &LVL, *TTI, TLI, DB, AC, ORE,
                                 F, &Hints, IAI);
   CM.collectValuesToIgnore();
+  CM.collectElementTypesForWidening();
 
   // Use the planner for vectorization.
   LoopVectorizationPlanner LVP(L, LI, TLI, TTI, &LVL, CM, IAI, PSE, Hints,