[Mlir-commits] [mlir] 2d3b9fd - [mlir][Affine] Fix vectorizability check for multiple load/stores
Diego Caballero
llvmlistbot at llvm.org
Wed Dec 9 12:38:01 PST 2020
Author: Sergei Grechanik
Date: 2020-12-09T12:19:34-08:00
New Revision: 2d3b9fdc193fa835313f09f526b51bf6de3a54ef
URL: https://github.com/llvm/llvm-project/commit/2d3b9fdc193fa835313f09f526b51bf6de3a54ef
DIFF: https://github.com/llvm/llvm-project/commit/2d3b9fdc193fa835313f09f526b51bf6de3a54ef.diff
LOG: [mlir][Affine] Fix vectorizability check for multiple load/stores
This patch fixes a bug that allowed vectorizing of loops with loads and
stores having indexing functions varying along different memory
dimensions.
Reviewed By: aartbik, dcaballe
Differential Revision: https://reviews.llvm.org/D92702
Added:
Modified:
mlir/lib/Analysis/LoopAnalysis.cpp
mlir/test/Dialect/Affine/SuperVectorize/vectorize_1d.mlir
Removed:
################################################################################
diff --git a/mlir/lib/Analysis/LoopAnalysis.cpp b/mlir/lib/Analysis/LoopAnalysis.cpp
index 210b68eae3cb..932559cac197 100644
--- a/mlir/lib/Analysis/LoopAnalysis.cpp
+++ b/mlir/lib/Analysis/LoopAnalysis.cpp
@@ -327,11 +327,23 @@ isVectorizableLoopBodyWithOpCond(AffineForOp loop,
bool mlir::isVectorizableLoopBody(AffineForOp loop, int *memRefDim,
NestedPattern &vectorTransferMatcher) {
+ *memRefDim = -1;
VectorizableOpFun fun([memRefDim](AffineForOp loop, Operation &op) {
auto load = dyn_cast<AffineLoadOp>(op);
auto store = dyn_cast<AffineStoreOp>(op);
- return load ? isContiguousAccess(loop.getInductionVar(), load, memRefDim)
- : isContiguousAccess(loop.getInductionVar(), store, memRefDim);
+ int thisOpMemRefDim = -1;
+ bool isContiguous = load ? isContiguousAccess(loop.getInductionVar(), load,
+ &thisOpMemRefDim)
+ : isContiguousAccess(loop.getInductionVar(), store,
+ &thisOpMemRefDim);
+ if (thisOpMemRefDim != -1) {
+ // If memory accesses vary across
diff erent dimensions then the loop is
+ // not vectorizable.
+ if (*memRefDim != -1 && *memRefDim != thisOpMemRefDim)
+ return false;
+ *memRefDim = thisOpMemRefDim;
+ }
+ return isContiguous;
});
return isVectorizableLoopBodyWithOpCond(loop, fun, vectorTransferMatcher);
}
diff --git a/mlir/test/Dialect/Affine/SuperVectorize/vectorize_1d.mlir b/mlir/test/Dialect/Affine/SuperVectorize/vectorize_1d.mlir
index ca496b75432c..86749e2c7bab 100644
--- a/mlir/test/Dialect/Affine/SuperVectorize/vectorize_1d.mlir
+++ b/mlir/test/Dialect/Affine/SuperVectorize/vectorize_1d.mlir
@@ -397,6 +397,33 @@ func @vec_rejected_10(%A : memref<?x?xf32>, %B : memref<?x?x?xf32>) {
return
}
+// CHECK-LABEL: func @vec_rejected_11
+func @vec_rejected_11(%A : memref<?x?xf32>, %B : memref<?x?x?xf32>) {
+ // CHECK-DAG: %[[C0:.*]] = constant 0 : index
+ // CHECK-DAG: %[[C1:.*]] = constant 1 : index
+ // CHECK-DAG: %[[C2:.*]] = constant 2 : index
+ // CHECK-DAG: [[ARG_M:%[0-9]+]] = dim %{{.*}}, %[[C0]] : memref<?x?xf32>
+ // CHECK-DAG: [[ARG_N:%[0-9]+]] = dim %{{.*}}, %[[C1]] : memref<?x?xf32>
+ // CHECK-DAG: [[ARG_P:%[0-9]+]] = dim %{{.*}}, %[[C2]] : memref<?x?x?xf32>
+ %c0 = constant 0 : index
+ %c1 = constant 1 : index
+ %c2 = constant 2 : index
+ %M = dim %A, %c0 : memref<?x?xf32>
+ %N = dim %A, %c1 : memref<?x?xf32>
+ %P = dim %B, %c2 : memref<?x?x?xf32>
+
+ // CHECK: for [[IV10:%[arg0-9]*]] = 0 to %{{[0-9]*}} {
+ // CHECK: for [[IV11:%[arg0-9]*]] = 0 to %{{[0-9]*}} {
+ // This is similar to vec_rejected_5, but the order of indices is
diff erent.
+ affine.for %i10 = 0 to %M { // not vectorized
+ affine.for %i11 = 0 to %N { // not vectorized
+ %a11 = affine.load %A[%i11, %i10] : memref<?x?xf32>
+ affine.store %a11, %A[%i10, %i11] : memref<?x?xf32>
+ }
+ }
+ return
+}
+
// This should not vectorize due to the sequential dependence in the scf.
// CHECK-LABEL: @vec_rejected_sequential
func @vec_rejected_sequential(%A : memref<?xf32>) {
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