[Mlir-commits] [mlir] [mlir][vectorize] Support affine.apply in SuperVectorize (PR #77968)

[llvmlistbot at llvm.org]

llvmbot wrote:


<!--LLVM PR SUMMARY COMMENT-->

@llvm/pr-subscribers-mlir-affine

Author: Hsiangkai Wang (Hsiangkai)

<details>
<summary>Changes</summary>

We have no need to vectorize affine.apply inside the vectorizing loop. However, we still need to generate it in the original scalar form. We have to replace all its operands with the generated scalar operands in the vectorizing loop, e.g., induction variables.

---
Full diff: https://github.com/llvm/llvm-project/pull/77968.diff


2 Files Affected:

- (modified) mlir/lib/Dialect/Affine/Transforms/SuperVectorize.cpp (+27-4) 
- (added) mlir/test/Dialect/Affine/SuperVectorize/vectorize_affine_apply.mlir (+23) 


``````````diff
diff --git a/mlir/lib/Dialect/Affine/Transforms/SuperVectorize.cpp b/mlir/lib/Dialect/Affine/Transforms/SuperVectorize.cpp
index 6b7a157925fae1..3b70618fe151c5 100644
--- a/mlir/lib/Dialect/Affine/Transforms/SuperVectorize.cpp
+++ b/mlir/lib/Dialect/Affine/Transforms/SuperVectorize.cpp
@@ -721,8 +721,7 @@ struct VectorizationState {
   /// Example:
   ///   * 'replaced': induction variable of a loop to be vectorized.
   ///   * 'replacement': new induction variable in the new vector loop.
-  void registerValueScalarReplacement(BlockArgument replaced,
-                                      BlockArgument replacement);
+  void registerValueScalarReplacement(Value replaced, Value replacement);
 
   /// Registers the scalar replacement of a scalar result returned from a
   /// reduction loop. 'replacement' must be scalar.
@@ -854,8 +853,8 @@ void VectorizationState::registerValueVectorReplacementImpl(Value replaced,
 /// Example:
 ///   * 'replaced': induction variable of a loop to be vectorized.
 ///   * 'replacement': new induction variable in the new vector loop.
-void VectorizationState::registerValueScalarReplacement(
-    BlockArgument replaced, BlockArgument replacement) {
+void VectorizationState::registerValueScalarReplacement(Value replaced,
+                                                        Value replacement) {
   registerValueScalarReplacementImpl(replaced, replacement);
 }
 
@@ -978,6 +977,28 @@ static arith::ConstantOp vectorizeConstant(arith::ConstantOp constOp,
   return newConstOp;
 }
 
+/// We have no need to vectorize affine.apply. However, we still need to
+/// generate it and replace the operands with values in valueScalarReplacement.
+static Operation *vectorizeAffineApplyOp(AffineApplyOp applyOp,
+                                         VectorizationState &state) {
+  SmallVector<Value, 8> updatedOperands;
+  for (Value operand : applyOp.getOperands()) {
+    Value updatedOperand = operand;
+    if (state.valueScalarReplacement.contains(operand)) {
+      updatedOperand = state.valueScalarReplacement.lookupOrDefault(operand);
+    }
+    updatedOperands.push_back(updatedOperand);
+  }
+
+  auto newApplyOp = state.builder.create<AffineApplyOp>(
+      applyOp.getLoc(), applyOp.getAffineMap(), updatedOperands);
+
+  // Register the new affine.apply result.
+  state.registerValueScalarReplacement(applyOp.getResult(),
+                                       newApplyOp.getResult());
+  return newApplyOp;
+}
+
 /// Creates a constant vector filled with the neutral elements of the given
 /// reduction. The scalar type of vector elements will be taken from
 /// `oldOperand`.
@@ -1493,6 +1514,8 @@ static Operation *vectorizeOneOperation(Operation *op,
     return vectorizeAffineYieldOp(yieldOp, state);
   if (auto constant = dyn_cast<arith::ConstantOp>(op))
     return vectorizeConstant(constant, state);
+  if (auto applyOp = dyn_cast<AffineApplyOp>(op))
+    return vectorizeAffineApplyOp(applyOp, state);
 
   // Other ops with regions are not supported.
   if (op->getNumRegions() != 0)
diff --git a/mlir/test/Dialect/Affine/SuperVectorize/vectorize_affine_apply.mlir b/mlir/test/Dialect/Affine/SuperVectorize/vectorize_affine_apply.mlir
new file mode 100644
index 00000000000000..588663e1f97b61
--- /dev/null
+++ b/mlir/test/Dialect/Affine/SuperVectorize/vectorize_affine_apply.mlir
@@ -0,0 +1,23 @@
+// RUN: mlir-opt %s -affine-super-vectorize="virtual-vector-size=8 test-fastest-varying=0" -split-input-file | FileCheck %s
+
+// CHECK-DAG: #[[$map_id0:map[0-9a-zA-Z_]*]] = affine_map<(d0) -> (d0 mod 12)>
+// CHECK-DAG: #[[$map_id1:map[0-9a-zA-Z_]*]] = affine_map<(d0) -> (d0 mod 16)>
+
+// CHECK-LABEL: func @vec_affine_apply
+func.func @vec_affine_apply(%arg0: memref<8x12x16xf32>, %arg1: memref<8x24x48xf32>) {
+  affine.for %arg2 = 0 to 8 {
+// CHECK: affine.for %[[S0:.*]] = 0 to 24 {
+// CHECK-NEXT: affine.for %[[S1:.*]] = 0 to 48 step 8 {
+    affine.for %arg3 = 0 to 24 {
+      affine.for %arg4 = 0 to 48 {
+// CHECK-NEXT: affine.apply #[[$map_id0]](%[[S0]])
+// CHECK-NEXT: affine.apply #[[$map_id1]](%[[S1]])
+        %0 = affine.apply affine_map<(d0) -> (d0 mod 12)>(%arg3)
+        %1 = affine.apply affine_map<(d0) -> (d0 mod 16)>(%arg4)
+        %2 = affine.load %arg0[%arg2, %0, %1] : memref<8x12x16xf32>
+        affine.store %2, %arg1[%arg2, %arg3, %arg4] : memref<8x24x48xf32>
+      }
+    }
+  }
+  return
+}

``````````

</details>


https://github.com/llvm/llvm-project/pull/77968