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[mlir][linalg] set inbounds on xfer_read/writes for assumeDynamicDimsMatchVecSizes #160839

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[mlir][linalg] set inbounds on xfer_read/writes for assumeDynamicDimsMatchVecSizes #160839

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17 changes: 17 additions & 0 deletions mlir/lib/Dialect/Linalg/Transforms/Vectorization.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -524,6 +524,23 @@ VectorizationState::maskOperation(RewriterBase &rewriter, Operation *opToMask,

if (!mask) {
LDBG() << "No mask required";
if (assumeDynamicDimsMatchVecSizes) {
LDBG() << "Assuming dynamic dimensions match vector sizes!";
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I would move this inside the lambda. Otherwise it will be printed for every Op, which could be noise, no?

Suggested change
LDBG() << "Assuming dynamic dimensions match vector sizes!";
LDBG() << "Assuming dynamic dimensions match vector sizes, set in_bounds to true!";

// Set inbounds to all-true.
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This comment tells me what is happening, but that's also what the code says :) Could you instead clarify why we need this extra step? I would also update the LLDB message.

Basically,

  • xfer_read/xfer_write are special and hence this special treatment (this does not concern any other Ops)
  • We need to set in_bounds explicitly as otherwise things further down the line will assume "out-of-bouds".
Suggested change
// Set inbounds to all-true.
For vector.transfer_read and vector.transfer_write, there is also the `in-bounds` attribute that we need to set explicitly. Otherwise, "out-of-bounds" access will be assumed and masks will be generated.

llvm::TypeSwitch<Operation *>(opToMask)
.Case<vector::TransferReadOp, vector::TransferWriteOp>(
[&](auto xferOp) {
SmallVector<bool> inBoundsMap(xferOp.getInBounds().size(),
true);
Comment on lines +533 to +534
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Note, assumeDynamicDimsMatchVecSizes only applies to dynamic sizes ;-) Static should remain "out-of-bounds". IIRC, something else will later infer that it's in fact "in bounds" 🤞🏻

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Oh, completely missed that 🥲 Thanks!

rewriter.modifyOpInPlace(xferOp, [&]() {
xferOp.setInBoundsAttr(
rewriter.getBoolArrayAttr(inBoundsMap));
});
})
.Default([](Operation *op) {
// No-op if the operation is not an xfer read or write.
});
}
return opToMask;
}

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24 changes: 16 additions & 8 deletions mlir/test/Dialect/Linalg/vectorization/linalg-ops.mlir
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Expand Up @@ -918,12 +918,16 @@ func.func @mmt4d_scalable_with_assume(%A: memref<16x16x8x1xf32>, %B: memref<16x1
// CHECK-SAME: %[[B:.*]]: memref<16x16x?x1xf32>,
// CHECK-SAME: %[[C_IN:.*]]: memref<16x16x8x?xf32>) {
// CHECK-NOT: mask
// CHECK: %[[VEC_A:.*]] = vector.transfer_read %[[A]]{{.*}} : memref<16x16x8x1xf32>, vector<16x16x16x8x[4]x1xf32>
// CHECK: %[[VEC_B:.*]] = vector.transfer_read %[[B]]{{.*}} : memref<16x16x?x1xf32>, vector<16x16x16x8x[4]x1xf32>
// CHECK: %[[VEC_C:.*]] = vector.transfer_read %[[C_IN]]{{.*}} : memref<16x16x8x?xf32>, vector<16x16x8x[4]xf32>
// CHECK: %[[VEC_A:.*]] = vector.transfer_read %[[A]]
// CHECK-SAME: in_bounds = [true, true, true, true, true, true]{{.*}} : memref<16x16x8x1xf32>, vector<16x16x16x8x[4]x1xf32>
// CHECK: %[[VEC_B:.*]] = vector.transfer_read %[[B]]
// CHECK-SAME: in_bounds = [true, true, true, true, true, true]{{.*}} : memref<16x16x?x1xf32>, vector<16x16x16x8x[4]x1xf32>
// CHECK: %[[VEC_C:.*]] = vector.transfer_read %[[C_IN]]
// CHECK-SAME: in_bounds = [true, true, true, true]{{.*}} : memref<16x16x8x?xf32>, vector<16x16x8x[4]xf32>
// CHECK: %[[MUL:.*]] = arith.mulf %[[VEC_A]], %[[VEC_B]] : vector<16x16x16x8x[4]x1xf32>
// CHECK: %[[RED:.*]] = vector.multi_reduction <add>, %[[MUL]], %[[VEC_C]] [2, 5] : vector<16x16x16x8x[4]x1xf32> to vector<16x16x8x[4]xf32>
// CHECK: vector.transfer_write %[[RED]], %[[C_IN]]{{.*}} : vector<16x16x8x[4]xf32>, memref<16x16x8x?xf32>
// CHECK: vector.transfer_write %[[RED]], %[[C_IN]]
// CHECK-SAME: in_bounds = [true, true, true, true]{{.*}} : vector<16x16x8x[4]xf32>, memref<16x16x8x?xf32>

module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
Expand Down Expand Up @@ -1011,12 +1015,16 @@ func.func @batch_mmt4d_scalable_with_assume(%A: memref<2x16x16x8x1xf32>, %B: mem
// CHECK-SAME: %[[B:.*]]: memref<2x16x16x?x1xf32>,
// CHECK-SAME: %[[C_IN:.*]]: memref<2x16x16x8x?xf32>) {
// CHECK-NOT: mask
// CHECK: %[[VEC_A:.*]] = vector.transfer_read %[[A]]{{.*}} : memref<2x16x16x8x1xf32>, vector<2x16x16x16x8x[4]x1xf32>
// CHECK: %[[VEC_B:.*]] = vector.transfer_read %[[B]]{{.*}} : memref<2x16x16x?x1xf32>, vector<2x16x16x16x8x[4]x1xf32>
// CHECK: %[[VEC_C:.*]] = vector.transfer_read %[[C_IN]]{{.*}} : memref<2x16x16x8x?xf32>, vector<2x16x16x8x[4]xf32>
// CHECK: %[[VEC_A:.*]] = vector.transfer_read %[[A]]
// CHECK-SAME: in_bounds = [true, true, true, true, true, true, true]{{.*}} : memref<2x16x16x8x1xf32>, vector<2x16x16x16x8x[4]x1xf32>
// CHECK: %[[VEC_B:.*]] = vector.transfer_read %[[B]]
// CHECK-SAME: in_bounds = [true, true, true, true, true, true, true]{{.*}} : memref<2x16x16x?x1xf32>, vector<2x16x16x16x8x[4]x1xf32>
// CHECK: %[[VEC_C:.*]] = vector.transfer_read %[[C_IN]]
// CHECK-SAME: in_bounds = [true, true, true, true, true]{{.*}} : memref<2x16x16x8x?xf32>, vector<2x16x16x8x[4]xf32>
// CHECK: %[[MUL:.*]] = arith.mulf %[[VEC_A]], %[[VEC_B]] : vector<2x16x16x16x8x[4]x1xf32>
// CHECK: %[[RED:.*]] = vector.multi_reduction <add>, %[[MUL]], %[[VEC_C]] [3, 6] : vector<2x16x16x16x8x[4]x1xf32> to vector<2x16x16x8x[4]xf32>
// CHECK: vector.transfer_write %[[RED]], %[[C_IN]]{{.*}} : vector<2x16x16x8x[4]xf32>, memref<2x16x16x8x?xf32>
// CHECK: vector.transfer_write %[[RED]], %[[C_IN]]
// CHECK-SAME: in_bounds = [true, true, true, true, true]{{.*}} : vector<2x16x16x8x[4]xf32>, memref<2x16x16x8x?xf32>

module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
Expand Down