[Mlir-commits] [mlir] [MLIR][XeGPU] Switch to 1D representation for SIMT code (PR #135116)

[Igor Zamyatin]

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@@ -336,32 +337,30 @@ LogicalResult TensorDescType::verify(
 //        [n_distribution_units, lane_data_size]
 FailureOr<VectorType> TensorDescType::getDistributedVectorType() {
   auto layout = llvm::dyn_cast_if_present<LayoutAttr>(getLayout());
-  // If no layout is provided, tensor desc is not used in SIMT mode.
-  if (!layout)
+  // It only works for subgroup level layout, which only has lane_layout
+  // and lane_data, and is to distribute a SIMD code into SIMT code.
+  if (!layout || !layout.isSgLayout())
     return failure();
 
   SmallVector<int64_t> laneData(layout.getLaneData().asArrayRef());
   SmallVector<int64_t> laneLayout(layout.getLaneLayout().asArrayRef());
   auto tdescShape = getShape();
 
-  auto laneDataSize = 1, sgSize = 1;
-  for (auto [laneDim, laneDataDim] : llvm::zip_equal(laneLayout, laneData)) {
-    laneDataSize *= laneDataDim;
-    sgSize *= laneDim;
-  }
+  // compute sgSize by multiply elements of laneLayout
+  // e.g. for 2D layout, sgSize = laneLayout[0] * laneLayout[1]
+  // e.g. for 1D layout, sgSize = laneLayout[0]
+  auto sgSize = std::accumulate(laneLayout.begin(), laneLayout.end(), 1,
+                                std::multiplies<int64_t>());
 
   // Case 1: regular loads/stores
   auto scatterAttr = getEncodingAsScatterTensorDescAttr();
   if (scatterAttr) {
     auto chunkSize = scatterAttr.getChunkSize().getInt();
     // Verify if the first dimension of the tensor descriptor shape is
     // distributable.
-    assert(tdescShape[0] % (laneLayout[0]) == 0 &&
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Garra1980 wrote:

Not very clear why this change

https://github.com/llvm/llvm-project/pull/135116