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Jun 12, 2025
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[mlir][Vector] Tighten up application conditions in TransferReadAfter… #143869

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30 changes: 23 additions & 7 deletions mlir/lib/Dialect/Vector/IR/VectorOps.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -4668,12 +4668,15 @@ struct TransferReadAfterWriteToBroadcast

LogicalResult matchAndRewrite(TransferReadOp readOp,
PatternRewriter &rewriter) const override {
if (readOp.hasOutOfBoundsDim() ||
!llvm::isa<RankedTensorType>(readOp.getShapedType()))
return failure();
auto defWrite = readOp.getBase().getDefiningOp<vector::TransferWriteOp>();
if (!defWrite)
return failure();
// Bail if we need an alias analysis.
if (!readOp.hasPureTensorSemantics() || !defWrite.hasPureTensorSemantics())
return failure();
// Bail if we need a bounds analysis.
if (readOp.hasOutOfBoundsDim() || defWrite.hasOutOfBoundsDim())
return failure();
// TODO: If the written transfer chunk is a superset of the read transfer
// chunk we could do an extract_strided_slice.
if (readOp.getTransferChunkAccessed() !=
Expand All @@ -4684,15 +4687,28 @@ struct TransferReadAfterWriteToBroadcast
if (getUnusedDimsBitVector({readOp.getPermutationMap()}) !=
getUnusedDimsBitVector({defWrite.getPermutationMap()}))
return failure();
if (readOp.getIndices() != defWrite.getIndices() ||
readOp.getMask() != defWrite.getMask())
// This pattern should only catch the broadcast case, the non-broadcast case
// should be done separately to keep application conditions clean and
// separate.
AffineMap readMap = compressUnusedDims(readOp.getPermutationMap());
AffineMap writeMap = compressUnusedDims(defWrite.getPermutationMap());
bool bcast = !readMap.getBroadcastDims().empty() ||
!writeMap.getBroadcastDims().empty();
if (!bcast)
return failure();
// At this point, we know we have a bcast.
// Bail in the masked case (too complex atm and needed to properly account
// for padding).
if (readOp.getMask() || defWrite.getMask())
return failure();
// If indices are not the same a shift may be required, bail.
if (readOp.getIndices() != defWrite.getIndices())
return failure();

Value vec = defWrite.getVector();
// TODO: loop through the chain of transfer_write if we can prove that they
// don't overlap with the transfer_read. This requires improving
// `isDisjointTransferIndices` helper.
AffineMap readMap = compressUnusedDims(readOp.getPermutationMap());
AffineMap writeMap = compressUnusedDims(defWrite.getPermutationMap());
AffineMap map = readMap.compose(writeMap);
if (map.getNumResults() == 0)
return failure();
Expand Down
108 changes: 94 additions & 14 deletions mlir/test/Dialect/Vector/canonicalize.mlir
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Original file line number Diff line number Diff line change
Expand Up @@ -408,7 +408,7 @@ func.func @extract_strided_fold_insert(%a: vector<6x4xf32>, %b: vector<8x16xf32>
// -----

// Negative test where the extract is not a subset of the element inserted.
// CHECK-LABEL: extract_strided_fold_negative
// CHECK-LABEL: negative_extract_strided_fold
// CHECK-SAME: (%[[ARG0:.*]]: vector<4x4xf32>, %[[ARG1:.*]]: vector<8x16xf32>
// CHECK: %[[INS:.*]] = vector.insert_strided_slice %[[ARG0]], %[[ARG1]]
// CHECK-SAME: {offsets = [2, 2], strides = [1, 1]}
Expand All @@ -417,7 +417,7 @@ func.func @extract_strided_fold_insert(%a: vector<6x4xf32>, %b: vector<8x16xf32>
// CHECK-SAME: {offsets = [2, 2], sizes = [6, 4], strides = [1, 1]}
// CHECK-SAME: : vector<8x16xf32> to vector<6x4xf32>
// CHECK-NEXT: return %[[EXT]] : vector<6x4xf32>
func.func @extract_strided_fold_negative(%a: vector<4x4xf32>, %b: vector<8x16xf32>)
func.func @negative_extract_strided_fold(%a: vector<4x4xf32>, %b: vector<8x16xf32>)
-> (vector<6x4xf32>) {
%0 = vector.insert_strided_slice %a, %b {offsets = [2, 2], strides = [1, 1]}
: vector<4x4xf32> into vector<8x16xf32>
Expand Down Expand Up @@ -753,10 +753,10 @@ func.func @fold_extract_broadcast_0dvec_input_scalar_output(%a : vector<f32>,

// -----

// CHECK-LABEL: fold_extract_broadcast_negative
// CHECK-LABEL: negative_fold_extract_broadcast
// CHECK: vector.broadcast %{{.*}} : vector<1x1xf32> to vector<1x1x4xf32>
// CHECK: vector.extract %{{.*}}[0, 0] : vector<4xf32> from vector<1x1x4xf32>
func.func @fold_extract_broadcast_negative(%a : vector<1x1xf32>) -> vector<4xf32> {
func.func @negative_fold_extract_broadcast(%a : vector<1x1xf32>) -> vector<4xf32> {
%b = vector.broadcast %a : vector<1x1xf32> to vector<1x1x4xf32>
%r = vector.extract %b[0, 0] : vector<4xf32> from vector<1x1x4xf32>
return %r : vector<4xf32>
Expand Down Expand Up @@ -895,11 +895,11 @@ func.func @fold_extract_shapecast_0d_source(%arg0 : vector<f32>) -> f32 {

// -----

// CHECK-LABEL: fold_extract_shapecast_negative
// CHECK-LABEL: negative_fold_extract_shapecast
// CHECK: %[[V:.*]] = vector.shape_cast %{{.*}} : vector<16xf32> to vector<2x4x2xf32>
// CHECK: %[[R:.*]] = vector.extract %[[V]][1] : vector<4x2xf32> from vector<2x4x2xf32>
// CHECK: return %[[R]] : vector<4x2xf32>
func.func @fold_extract_shapecast_negative(%arg0 : vector<16xf32>) -> vector<4x2xf32> {
func.func @negative_fold_extract_shapecast(%arg0 : vector<16xf32>) -> vector<4x2xf32> {
%0 = vector.shape_cast %arg0 : vector<16xf32> to vector<2x4x2xf32>
%r = vector.extract %0[1] : vector<4x2xf32> from vector<2x4x2xf32>
return %r : vector<4x2xf32>
Expand Down Expand Up @@ -1460,11 +1460,11 @@ func.func @store_after_load_tensor(%arg0 : tensor<4x4xf32>) -> tensor<4x4xf32> {

// -----

// CHECK-LABEL: func @store_after_load_tensor_negative
// CHECK-LABEL: func @negative_store_after_load_tensor
// CHECK: vector.transfer_read
// CHECK: vector.transfer_write
// CHECK: return
func.func @store_after_load_tensor_negative(%arg0 : tensor<4x4xf32>) -> tensor<4x4xf32> {
func.func @negative_store_after_load_tensor(%arg0 : tensor<4x4xf32>) -> tensor<4x4xf32> {
%c1 = arith.constant 1 : index
%c0 = arith.constant 0 : index
%cf0 = arith.constant 0.0 : f32
Expand Down Expand Up @@ -1499,12 +1499,12 @@ func.func @store_to_load_tensor(%arg0 : tensor<4x4xf32>,

// -----

// CHECK-LABEL: func @store_to_load_negative_tensor
// CHECK-LABEL: func @negative_store_to_load_tensor
// CHECK: vector.transfer_write
// CHECK: vector.transfer_write
// CHECK: %[[V:.*]] = vector.transfer_read
// CHECK: return %[[V]] : vector<1x4xf32>
func.func @store_to_load_negative_tensor(%arg0 : tensor<4x4xf32>,
func.func @negative_store_to_load_tensor(%arg0 : tensor<4x4xf32>,
%v0 : vector<1x4xf32>, %v1 : vector<1x4xf32>, %i : index) -> vector<1x4xf32> {
%c1 = arith.constant 1 : index
%c2 = arith.constant 2 : index
Expand Down Expand Up @@ -1540,6 +1540,86 @@ func.func @store_to_load_tensor_broadcast(%arg0 : tensor<4x4xf32>,

// -----

// CHECK-LABEL: func @negative_store_to_load_tensor_memref
// CHECK-NOT: vector.broadcast
// CHECK-NOT: vector.transpose
// CHECK: vector.transfer_write
// CHECK: vector.transfer_read
func.func @negative_store_to_load_tensor_memref(
%arg0 : tensor<?x?xf32>,
%arg1 : memref<?x?xf32>,
%v0 : vector<4x2xf32>
) -> vector<4x2xf32>
{
%c0 = arith.constant 0 : index
%cf0 = arith.constant 0.0 : f32
vector.transfer_write %v0, %arg1[%c0, %c0] {in_bounds = [true, true]} :
vector<4x2xf32>, memref<?x?xf32>
%0 = vector.transfer_read %arg0[%c0, %c0], %cf0 {in_bounds = [true, true]} :
tensor<?x?xf32>, vector<4x2xf32>
return %0 : vector<4x2xf32>
}

// -----

// CHECK-LABEL: func @negative_store_to_load_tensor_no_actual_broadcast
// CHECK-NOT: vector.broadcast
// CHECK-NOT: vector.transpose
// CHECK: vector.transfer_write
// CHECK: vector.transfer_read
func.func @negative_store_to_load_tensor_no_actual_broadcast(%arg0 : tensor<?x?xf32>,
%v0 : vector<4x2xf32>) -> vector<4x2xf32> {
%c0 = arith.constant 0 : index
%cf0 = arith.constant 0.0 : f32
%w0 = vector.transfer_write %v0, %arg0[%c0, %c0] :
vector<4x2xf32>, tensor<?x?xf32>
%0 = vector.transfer_read %w0[%c0, %c0], %cf0 {in_bounds = [true, true]} :
tensor<?x?xf32>, vector<4x2xf32>
return %0 : vector<4x2xf32>
}

// -----

// CHECK-LABEL: func @negative_store_to_load_tensor_broadcast_out_of_bounds
// CHECK-NOT: vector.broadcast
// CHECK-NOT: vector.transpose
// CHECK: vector.transfer_write
// CHECK: vector.transfer_read
func.func @negative_store_to_load_tensor_broadcast_out_of_bounds(%arg0 : tensor<?x?xf32>,
%v0 : vector<4x2xf32>) -> vector<4x2x6xf32> {
%c0 = arith.constant 0 : index
%cf0 = arith.constant 0.0 : f32
%w0 = vector.transfer_write %v0, %arg0[%c0, %c0] :
vector<4x2xf32>, tensor<?x?xf32>
%0 = vector.transfer_read %w0[%c0, %c0], %cf0 {in_bounds = [true, true, true],
permutation_map = affine_map<(d0, d1) -> (d0, d1, 0)>} :
tensor<?x?xf32>, vector<4x2x6xf32>
return %0 : vector<4x2x6xf32>
}

// -----

// CHECK-LABEL: func @negative_store_to_load_tensor_broadcast_masked
// CHECK-NOT: vector.broadcast
// CHECK-NOT: vector.transpose
// CHECK: vector.transfer_write
// CHECK: vector.transfer_read
func.func @negative_store_to_load_tensor_broadcast_masked(
%arg0 : tensor<?x?xf32>, %v0 : vector<4x2xf32>, %mask : vector<4x2xi1>)
-> vector<4x2x6xf32>
{
%c0 = arith.constant 0 : index
%cf0 = arith.constant 0.0 : f32
%w0 = vector.transfer_write %v0, %arg0[%c0, %c0], %mask {in_bounds = [true, true]} :
vector<4x2xf32>, tensor<?x?xf32>
%0 = vector.transfer_read %w0[%c0, %c0], %cf0 {in_bounds = [true, true, true],
permutation_map = affine_map<(d0, d1) -> (d0, d1, 0)>} :
tensor<?x?xf32>, vector<4x2x6xf32>
return %0 : vector<4x2x6xf32>
}

// -----

// CHECK-LABEL: func @store_to_load_tensor_broadcast_scalable
// CHECK-SAME: (%[[ARG:.*]]: tensor<?xf32>, %[[V0:.*]]: vector<[4]xf32>)
// CHECK: %[[B:.*]] = vector.broadcast %[[V0]] : vector<[4]xf32> to vector<6x[4]xf32>
Expand Down Expand Up @@ -1604,15 +1684,15 @@ func.func @dead_store_tensor(%arg0 : tensor<4x4xf32>,

// -----

// CHECK-LABEL: func @dead_store_tensor_negative
// CHECK-LABEL: func @negative_dead_store_tensor
// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index
// CHECK: vector.transfer_write
// CHECK: vector.transfer_write
// CHECK: vector.transfer_read
// CHECK: %[[VTW:.*]] = vector.transfer_write {{.*}}, {{.*}}[%[[C1]], %[[C0]]]
// CHECK: return %[[VTW]] : tensor<4x4xf32>
func.func @dead_store_tensor_negative(%arg0 : tensor<4x4xf32>,
func.func @negative_dead_store_tensor(%arg0 : tensor<4x4xf32>,
%v0 : vector<1x4xf32>, %v1 : vector<1x4xf32>, %i : index) -> tensor<4x4xf32> {
%c1 = arith.constant 1 : index
%c2 = arith.constant 2 : index
Expand Down Expand Up @@ -2063,10 +2143,10 @@ func.func @extract_insert_rank_reduce(%a: vector<4xf32>, %b: vector<8x16xf32>)

// -----

// CHECK-LABEL: extract_insert_negative
// CHECK-LABEL: negative_extract_insert
// CHECK: vector.insert_strided_slice
// CHECK: vector.extract
func.func @extract_insert_negative(%a: vector<2x15xf32>, %b: vector<12x8x16xf32>)
func.func @negative_extract_insert(%a: vector<2x15xf32>, %b: vector<12x8x16xf32>)
-> vector<16xf32> {
%0 = vector.insert_strided_slice %a, %b {offsets = [4, 2, 0], strides = [1, 1]}
: vector<2x15xf32> into vector<12x8x16xf32>
Expand Down