[Mlir-commits] [mlir] [mlir][scf] Considering affine.apply when fusing scf::ParallelOp (PR #80145)
Hsiangkai Wang
llvmlistbot at llvm.org
Wed Jan 31 06:31:46 PST 2024
https://github.com/Hsiangkai created https://github.com/llvm/llvm-project/pull/80145
When checking the load indices of the second loop coincide with the store indices of the first loop, it only considers the index values are the same or not. However, there are some cases the index values come from affine.apply operator. In these cases, it will treat them as different even the affine map is the same and the affine operands are the same.
We already check if the iteration space is the same in isFusionLegal(). When checking affine.apply, we only need to consider the operands come from the same induction variables. If so, we know the results of affine.apply are the same.
>From 8127a756eebdd8b1073f712a2484e86d4c233f22 Mon Sep 17 00:00:00 2001
From: Hsiangkai Wang <hsiangkai.wang at arm.com>
Date: Wed, 31 Jan 2024 12:59:15 +0000
Subject: [PATCH] [mlir][scf] Considering affine.apply when fusing
scf::ParallelOp
When checking the load indices of the second loop coincide with the
store indices of the first loop, it only considers the index values are
the same or not. However, there are some cases the index values come
from affine.apply operator. In these cases, it will treat them as
different even the affine map is the same and the affine operands are
the same.
We already check if the iteration space is the same in isFusionLegal().
When checking affine.apply, we only need to consider the operands come
from the same induction variables. If so, we know the results of
affine.apply are the same.
---
.../SCF/Transforms/ParallelLoopFusion.cpp | 33 ++++++++++++-
.../Dialect/SCF/parallel-loop-fusion.mlir | 46 +++++++++++++++++++
2 files changed, 77 insertions(+), 2 deletions(-)
diff --git a/mlir/lib/Dialect/SCF/Transforms/ParallelLoopFusion.cpp b/mlir/lib/Dialect/SCF/Transforms/ParallelLoopFusion.cpp
index 8f2ab5f5e6dc1..0b7904b75e6d1 100644
--- a/mlir/lib/Dialect/SCF/Transforms/ParallelLoopFusion.cpp
+++ b/mlir/lib/Dialect/SCF/Transforms/ParallelLoopFusion.cpp
@@ -10,6 +10,7 @@
//
//===----------------------------------------------------------------------===//
+#include "mlir/Dialect/Affine/IR/AffineOps.h"
#include "mlir/Dialect/SCF/Transforms/Passes.h"
#include "mlir/Analysis/AliasAnalysis.h"
@@ -27,6 +28,7 @@ namespace mlir {
} // namespace mlir
using namespace mlir;
+using namespace mlir::affine;
using namespace mlir::scf;
/// Verify there are no nested ParallelOps.
@@ -54,6 +56,16 @@ static bool equalIterationSpaces(ParallelOp firstPloop,
matchOperands(firstPloop.getStep(), secondPloop.getStep());
}
+static int getInductionVarIndex(Value operand, ParallelOp loop) {
+ auto indVars = loop.getInductionVars();
+ auto it = std::find(indVars.begin(), indVars.end(), operand);
+
+ if (it != indVars.end())
+ return static_cast<int>(std::distance(indVars.begin(), it));
+
+ return -1;
+}
+
/// Checks if the parallel loops have mixed access to the same buffers. Returns
/// `true` if the first parallel loop writes to the same indices that the second
/// loop reads.
@@ -102,8 +114,25 @@ static bool haveNoReadsAfterWriteExceptSameIndex(
return WalkResult::interrupt();
for (int i = 0, e = storeIndices.size(); i < e; ++i) {
if (firstToSecondPloopIndices.lookupOrDefault(storeIndices[i]) !=
- loadIndices[i])
- return WalkResult::interrupt();
+ loadIndices[i]) {
+ auto storeIndexDef = storeIndices[i].getDefiningOp<AffineApplyOp>();
+ auto loadIndexDef = loadIndices[i].getDefiningOp<AffineApplyOp>();
+ if (storeIndexDef && loadIndexDef) {
+ // When two indices come from affine.apply, we check the results of
+ // these two affine.apply are the same or not.
+ if (storeIndexDef.getAffineMap() != loadIndexDef.getAffineMap())
+ return WalkResult::interrupt();
+ if (storeIndexDef.getNumOperands() != loadIndexDef.getNumOperands())
+ return WalkResult::interrupt();
+ for (unsigned i = 0; i < storeIndexDef.getNumOperands(); ++i) {
+ if (getInductionVarIndex(storeIndexDef.getOperand(i), firstPloop) !=
+ getInductionVarIndex(loadIndexDef.getOperand(i), secondPloop))
+ return WalkResult::interrupt();
+ }
+ } else {
+ return WalkResult::interrupt();
+ }
+ }
}
return WalkResult::advance();
});
diff --git a/mlir/test/Dialect/SCF/parallel-loop-fusion.mlir b/mlir/test/Dialect/SCF/parallel-loop-fusion.mlir
index 110168ba6eca5..49cce745a8ce7 100644
--- a/mlir/test/Dialect/SCF/parallel-loop-fusion.mlir
+++ b/mlir/test/Dialect/SCF/parallel-loop-fusion.mlir
@@ -480,3 +480,49 @@ func.func @do_not_fuse_multiple_stores_on_diff_indices(
// CHECK: scf.reduce
// CHECK: }
// CHECK: memref.dealloc [[SUM]]
+
+// -----
+
+func.func @fuse_same_indices_by_affine_apply(
+ %A: memref<2x2xf32>, %B: memref<2x2xf32>) {
+ %c0 = arith.constant 0 : index
+ %c1 = arith.constant 1 : index
+ %c2 = arith.constant 2 : index
+ %sum = memref.alloc() : memref<2x3xf32>
+ scf.parallel (%i, %j) = (%c0, %c0) to (%c2, %c2) step (%c1, %c1) {
+ %B_elem = memref.load %B[%i, %j] : memref<2x2xf32>
+ %1 = affine.apply affine_map<(d0, d1) -> (d0 + d1)>(%i, %j)
+ memref.store %B_elem, %sum[%i, %1] : memref<2x3xf32>
+ scf.reduce
+ }
+ scf.parallel (%i, %j) = (%c0, %c0) to (%c2, %c2) step (%c1, %c1) {
+ %1 = affine.apply affine_map<(d0, d1) -> (d0 + d1)>(%i, %j)
+ %sum_elem = memref.load %sum[%i, %1] : memref<2x3xf32>
+ %A_elem = memref.load %A[%i, %j] : memref<2x2xf32>
+ %product = arith.mulf %sum_elem, %A_elem : f32
+ memref.store %product, %B[%i, %j] : memref<2x2xf32>
+ scf.reduce
+ }
+ memref.dealloc %sum : memref<2x3xf32>
+ return
+}
+// CHECK: #[[$MAP:.+]] = affine_map<(d0, d1) -> (d0 + d1)>
+// CHECK-LABEL: fuse_same_indices_by_affine_apply
+// CHECK-SAME: (%[[ARG0:.+]]: memref<2x2xf32>, %[[ARG1:.+]]: memref<2x2xf32>) {
+// CHECK-DAG: %[[C0:.+]] = arith.constant 0 : index
+// CHECK-DAG: %[[C1:.+]] = arith.constant 1 : index
+// CHECK-DAG: %[[C2:.+]] = arith.constant 2 : index
+// CHECK: %[[ALLOC:.+]] = memref.alloc() : memref<2x3xf32>
+// CHECK-NEXT: scf.parallel (%[[ARG2:.+]], %[[ARG3:.+]]) = (%[[C0]], %[[C0]]) to (%[[C2]], %[[C2]]) step (%[[C1]], %[[C1]]) {
+// CHECK-NEXT: %[[S0:.+]] = memref.load %[[ARG1]][%[[ARG2]], %[[ARG3]]] : memref<2x2xf32>
+// CHECK-NEXT: %[[S1:.+]] = affine.apply #[[$MAP]](%[[ARG2]], %[[ARG3]])
+// CHECK-NEXT: memref.store %[[S0]], %[[ALLOC]][%[[ARG2]], %[[S1]]] : memref<2x3xf32>
+// CHECK-NEXT: %[[S2:.+]] = affine.apply #[[$MAP]](%[[ARG2]], %[[ARG3]])
+// CHECK-NEXT: %[[S3:.+]] = memref.load %[[ALLOC]][%[[ARG2]], %[[S2]]] : memref<2x3xf32>
+// CHECK-NEXT: %[[S4:.+]] = memref.load %[[ARG0]][%[[ARG2]], %[[ARG3]]] : memref<2x2xf32>
+// CHECK-NEXT: %[[S5:.+]] = arith.mulf %[[S3]], %[[S4]] : f32
+// CHECK-NEXT: memref.store %[[S5]], %[[ARG1]][%[[ARG2]], %[[ARG3]]] : memref<2x2xf32>
+// CHECK-NEXT: scf.reduce
+// CHECK-NEXT: }
+// CHECK-NEXT: memref.dealloc %[[ALLOC]] : memref<2x3xf32>
+// CHECK-NEXT: return
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