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// RUN: mlir-opt %s -affine-super-vectorize="virtual-vector-size=128" -split-input-file | FileCheck %s
// Specific tests to check vectorization of uniform/divergent values.
// CHECK-LABEL: @uniform_arg
// CHECK-SAME: %[[in:.*]]: memref<512xf32>,
// CHECK-SAME: %[[uniform:.*]]: f32
func.func @uniform_arg(%in : memref<512xf32>, %uniform : f32) {
affine.for %i = 0 to 512 {
%ld = affine.load %in[%i] : memref<512xf32>
%add = arith.addf %ld, %uniform : f32
}
return
}
// CHECK-NEXT: %[[bcast:.*]] = vector.broadcast %[[uniform]] : f32 to vector<128xf32>
// CHECK-NEXT: affine.for
// CHECK: arith.addf %{{.*}}, %[[bcast]] : vector<128xf32>
// -----
// CHECK-LABEL: @multi_use_uniform_arg
// CHECK-SAME: %[[in:.*]]: memref<512xf32>
// CHECK-SAME: %[[uniform:.*]]: f32
func.func @multi_use_uniform_arg(%in : memref<512xf32>, %uniform : f32) {
affine.for %i = 0 to 512 {
%ld = affine.load %in[%i] : memref<512xf32>
%user0 = arith.addf %ld, %uniform : f32
%user1 = arith.addf %ld, %uniform : f32
}
return
}
// CHECK-NEXT: %[[bcast:.*]] = vector.broadcast %[[uniform]] : f32 to vector<128xf32>
// CHECK-NOT: vector.broadcast
// CHECK-NEXT: affine.for
// CHECK: arith.addf %{{.*}}, %[[bcast]] : vector<128xf32>
// CHECK: arith.addf %{{.*}}, %[[bcast]] : vector<128xf32>
// -----
// CHECK-LABEL: @uniform_load
func.func @uniform_load(%A : memref<?x?xf32>, %C : memref<?x?xf32>) {
%c0 = arith.constant 0 : index
%N = memref.dim %A, %c0 : memref<?x?xf32>
affine.for %i = 0 to %N {
%uniform_ld = affine.load %A[%i, %i] : memref<?x?xf32>
affine.for %j = 0 to %N {
%b = affine.load %A[%i, %j] : memref<?x?xf32>
%c = arith.addf %uniform_ld, %b : f32
}
}
return
}
// CHECK: affine.for
// CHECK-NEXT: %[[uniform_ld:.*]] = affine.load %{{.*}}[%{{.*}}, %{{.*}}] : memref<?x?xf32>
// CHECK-NEXT: %[[bcast:.*]] = vector.broadcast %[[uniform_ld]] : f32 to vector<128xf32>
// CHECK-NEXT: affine.for
// CHECK: arith.addf %[[bcast]], %{{.*}} : vector<128xf32>
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