Address reviewer comments.

Author: silee2

mlir/lib/Conversion/XeGPUToXeVM/XeGPUToXeVM.cpp

@@ -882,6 +882,9 @@ struct ConvertXeGPUToXeVMPass
       return {};
     };
 
+    // If result type of original op is single element vector and lowered type
+    // is scalar. This materialization cast creates a single element vector by
+    // broadcasting the scalar value.
     auto singleElementVectorMaterializationCast =
         [](OpBuilder &builder, Type type, ValueRange inputs,
            Location loc) -> Value {

mlir/test/Conversion/XeGPUToXeVM/loadstoreprefetch.mlir

@@ -27,16 +27,20 @@ gpu.func @load_gather_i64_src_value_offset(%src: i64, %offset: vector<1xindex>)
 }
 
 // -----
-module @test {
+gpu.module @test {
 // CHECK-LABEL: @source_materialize_single_elem_vec
-func.func @source_materialize_single_elem_vec(%src: i64, %offset: vector<1xindex>) -> vector<1xf16> {
+// CHECK-SAME: %[[ARG0:.*]]: i64, %[[ARG1:.*]]: vector<1xindex>, %[[ARG2:.*]]: memref<1xf16>
+gpu.func @source_materialize_single_elem_vec(%src: i64, %offset: vector<1xindex>, %dst: memref<1xf16>) {
   %1 = arith.constant dense<1>: vector<1xi1>
   %3 = xegpu.load %src[%offset], %1 <{l1_hint = #xegpu.cache_hint<cached>, l2_hint = #xegpu.cache_hint<uncached>}>
       : i64, vector<1xindex>, vector<1xi1> -> vector<1xf16>
   // CHECK: %[[VAR_IF:.*]] = scf.if
   // CHECK: %[[VAR_RET:.*]] = vector.broadcast %[[VAR_IF]] : f16 to vector<1xf16>
-  // CHECK: return %[[VAR_RET]] : vector<1xf16>
-  return %3 : vector<1xf16>
+  // CHECK: %[[C0:.*]] = arith.constant 0 : index
+  // CHECK: vector.store %[[VAR_RET]], %[[ARG2]][%[[C0]]] : memref<1xf16>, vector<1xf16>
+  %c0 = arith.constant 0 : index
+  vector.store %3, %dst[%c0] : memref<1xf16>, vector<1xf16>
+  gpu.return
 }
 }