[Mlir-commits] [mlir] Revert [mlir][vector] Use vector.broadcast in place of vector.splat (PR #148937)

[James Newling]

https://github.com/newling updated https://github.com/llvm/llvm-project/pull/148937

>From e68369528c535e7c4910db615cb3b9f7b99f45ba Mon Sep 17 00:00:00 2001
From: James Newling <james.newling at gmail.com>
Date: Tue, 15 Jul 2025 12:24:13 -0700
Subject: [PATCH] Revert "[mlir][vector] Use vector.broadcast in place of
 vector.splat

This reverts commit a599e60aff0c9981c4173db69e01eada2091cc23.
---
 .../Dialect/Arith/Transforms/EmulateUnsupportedFloats.cpp   | 2 +-
 mlir/lib/Dialect/NVGPU/TransformOps/NVGPUTransformOps.cpp   | 2 +-
 mlir/lib/Dialect/XeGPU/Transforms/XeGPUUnroll.cpp           | 3 +--
 mlir/test/Dialect/NVGPU/transform-matmul-to-nvvm.mlir       | 6 +++---
 4 files changed, 6 insertions(+), 7 deletions(-)

diff --git a/mlir/lib/Dialect/Arith/Transforms/EmulateUnsupportedFloats.cpp b/mlir/lib/Dialect/Arith/Transforms/EmulateUnsupportedFloats.cpp
index 22dd3bd0ea98f..62022bfb7df1e 100644
--- a/mlir/lib/Dialect/Arith/Transforms/EmulateUnsupportedFloats.cpp
+++ b/mlir/lib/Dialect/Arith/Transforms/EmulateUnsupportedFloats.cpp
@@ -123,7 +123,7 @@ void mlir::arith::populateEmulateUnsupportedFloatsLegality(
       vector::FMAOp, vector::OuterProductOp, vector::MatmulOp, vector::ScanOp>(
       [&](Operation *op) { return converter.isLegal(op); });
   target.addLegalOp<arith::BitcastOp, arith::ExtFOp, arith::TruncFOp,
-                    arith::ConstantOp, vector::SplatOp, vector::BroadcastOp>();
+                    arith::ConstantOp, vector::SplatOp>();
 }
 
 void EmulateUnsupportedFloatsPass::runOnOperation() {
diff --git a/mlir/lib/Dialect/NVGPU/TransformOps/NVGPUTransformOps.cpp b/mlir/lib/Dialect/NVGPU/TransformOps/NVGPUTransformOps.cpp
index bcd62acf6b9ce..d2c94b124cdfb 100644
--- a/mlir/lib/Dialect/NVGPU/TransformOps/NVGPUTransformOps.cpp
+++ b/mlir/lib/Dialect/NVGPU/TransformOps/NVGPUTransformOps.cpp
@@ -688,7 +688,7 @@ Value MmaSyncBuilder::buildMmaSyncMemRefLoadOperand(
 
   Type elementType = getElementTypeOrSelf(memref.getType());
   auto vt = VectorType::get(vectorShape, elementType);
-  Value res = b.create<vector::BroadcastOp>(loc, vt, loads[0]);
+  Value res = b.create<vector::SplatOp>(loc, vt, loads[0]);
   foreachIndividualVectorElement(
       res,
       /*applyFn=*/
diff --git a/mlir/lib/Dialect/XeGPU/Transforms/XeGPUUnroll.cpp b/mlir/lib/Dialect/XeGPU/Transforms/XeGPUUnroll.cpp
index 39e484927052c..dc76441b27c02 100644
--- a/mlir/lib/Dialect/XeGPU/Transforms/XeGPUUnroll.cpp
+++ b/mlir/lib/Dialect/XeGPU/Transforms/XeGPUUnroll.cpp
@@ -434,8 +434,7 @@ struct UnrollCreateDescOp : public UnrollPattern<xegpu::CreateDescOp> {
           // Compute the offset
           Value inc = rewriter.create<arith::ConstantIndexOp>(
               loc, i * blockedChunkSize);
-          Value incVec =
-              rewriter.create<vector::BroadcastOp>(loc, indiceType, inc);
+          Value incVec = rewriter.create<vector::SplatOp>(loc, indiceType, inc);
           Value offsetIndice =
               rewriter.create<arith::AddIOp>(loc, indice, incVec);
 
diff --git a/mlir/test/Dialect/NVGPU/transform-matmul-to-nvvm.mlir b/mlir/test/Dialect/NVGPU/transform-matmul-to-nvvm.mlir
index bbe27fe1b99d9..07e03f3b8473d 100644
--- a/mlir/test/Dialect/NVGPU/transform-matmul-to-nvvm.mlir
+++ b/mlir/test/Dialect/NVGPU/transform-matmul-to-nvvm.mlir
@@ -20,14 +20,14 @@ func.func @matmul_16x8x4xf32_global(
 // CHECK:           %[[VAL_7:.*]] = affine.apply #[[$div4p8]]()[%[[TIDX]]]
 // CHECK:           %[[VAL_8:.*]] = affine.apply #[[$mod4]]()[%[[TIDX]]]
 // CHECK:           %[[VAL_9:.*]] = memref.load %[[VAL_0]][%[[VAL_7]], %[[VAL_8]]] : memref<16x4xf32>
-// CHECK:           %[[VAL_10:.*]] = vector.broadcast %[[VAL_6]] : f32 to vector<2x1xf32>
+// CHECK:           %[[VAL_10:.*]] = vector.splat %[[VAL_6]] : vector<2x1xf32>
 // CHECK:           %[[VAL_11:.*]] = vector.insert %[[VAL_6]], %[[VAL_10]] [0, 0] : f32 into vector<2x1xf32>
 // CHECK:           %[[LHS:.*]] = vector.insert %[[VAL_9]], %[[VAL_11]] [1, 0] : f32 into vector<2x1xf32>
 //
 // CHECK:           %[[VAL_13:.*]] = affine.apply #[[$mod4]]()[%[[TIDX]]]
 // CHECK:           %[[VAL_14:.*]] = affine.apply #[[$div4]]()[%[[TIDX]]]
 // CHECK:           %[[VAL_15:.*]] = memref.load %[[VAL_1]][%[[VAL_13]], %[[VAL_14]]] : memref<4x8xf32>
-// CHECK:           %[[VAL_16:.*]] = vector.broadcast %[[VAL_15]] : f32 to vector<1x1xf32>
+// CHECK:           %[[VAL_16:.*]] = vector.splat %[[VAL_15]] : vector<1x1xf32>
 // CHECK:           %[[RHS:.*]] = vector.insert %[[VAL_15]], %[[VAL_16]] [0, 0] : f32 into vector<1x1xf32>
 //
 // CHECK:           %[[VAL_18:.*]] = affine.apply #[[$div4]]()[%[[TIDX]]]
@@ -42,7 +42,7 @@ func.func @matmul_16x8x4xf32_global(
 // CHECK:           %[[VAL_27:.*]] = affine.apply #[[$div4p8]]()[%[[TIDX]]]
 // CHECK:           %[[VAL_28:.*]] = affine.apply #[[$map4]]()[%[[TIDX]]]
 // CHECK:           %[[VAL_29:.*]] = memref.load %[[VAL_2]][%[[VAL_27]], %[[VAL_28]]] : memref<16x8xf32>
-// CHECK:           %[[VAL_30:.*]] = vector.broadcast %[[VAL_20]] : f32 to vector<2x2xf32>
+// CHECK:           %[[VAL_30:.*]] = vector.splat %[[VAL_20]] : vector<2x2xf32>
 // CHECK:           %[[VAL_31:.*]] = vector.insert %[[VAL_20]], %[[VAL_30]] [0, 0] : f32 into vector<2x2xf32>
 // CHECK:           %[[VAL_32:.*]] = vector.insert %[[VAL_23]], %[[VAL_31]] [0, 1] : f32 into vector<2x2xf32>
 // CHECK:           %[[VAL_33:.*]] = vector.insert %[[VAL_26]], %[[VAL_32]] [1, 0] : f32 into vector<2x2xf32>