[Mlir-commits] [mlir] [MLIR][XeGPU] Add blocking and subgroup to lane distribution support for ConvertLayout operation (PR #183837)

[Charitha Saumya]

================
@@ -1032,15 +1032,59 @@ struct UnrollStoreMatrixOp : public UnrollPattern<xegpu::StoreMatrixOp> {
   }
 };
 
+struct UnrollConvertLayoutOp : public UnrollPattern<xegpu::ConvertLayoutOp> {
+  using UnrollPattern<xegpu::ConvertLayoutOp>::UnrollPattern;
+  LogicalResult matchAndRewrite(xegpu::ConvertLayoutOp op,
+                                PatternRewriter &rewriter) const override {
+    Location loc = op.getLoc();
+    VectorType valueTy = llvm::dyn_cast<VectorType>(op.getType());
+    assert(valueTy && "the value type must be vector type!");
+
+    std::optional<SmallVector<int64_t>> targetShape = getTargetShape(op);
+    if (!targetShape || targetShape->size() != (size_t)valueTy.getRank())
+      return failure();
+
+    xegpu::DistributeLayoutAttr inputLayout = op.getInputLayoutAttr();
+    xegpu::DistributeLayoutAttr targetLayout = op.getTargetLayoutAttr();
+    if (!inputLayout || !targetLayout)
+      return rewriter.notifyMatchFailure(op, "missing layout attributes.");
+
+    if (inputLayout.getEffectiveInstDataAsInt().empty() ||
+        targetLayout.getEffectiveInstDataAsInt().empty())
+      return rewriter.notifyMatchFailure(op, "Not a target ConvertLayoutOp.");
+
+    inputLayout = inputLayout.dropInstData();
+    targetLayout = targetLayout.dropInstData();
+
+    Value newSource = op.getSource();
+    SmallVector<Value> newOps;
+    if (inputLayout && targetLayout) {
+      SmallVector<Type> convertedValTypes =
+          getUnrolledTypes(valueTy, *targetShape);
+      SmallVector<Value> convertedValues =
+          pack(op.getOperand(), convertedValTypes, *targetShape, loc, rewriter);
+      for (auto [v, t] : llvm::zip(convertedValues, convertedValTypes)) {
+        auto newOp = xegpu::ConvertLayoutOp::create(rewriter, op.getLoc(), t, v,
+                                                    inputLayout, targetLayout);
+        newOps.push_back(newOp);
+      }
+      newSource = unpack(newOps, op.getType(), *targetShape, loc, rewriter);
+    }
+
+    rewriter.replaceOp(op, newSource);
+    return success();
+  }
+};
+
 } // namespace
 
 void mlir::xegpu::populateXeGPUUnrollPatterns(
     RewritePatternSet &patterns, const xegpu::UnrollOptions &options) {
-  patterns
-      .add<UnrollCreateNdOp, UnrollUpdateNdOffsetOp, UnrollPrefetchNdOp,
-           UnrollLoadNdOp, UnrollStoreNdOp, UnrollDpasOp, UnrollCreateDescOp,
-           UnrollLoadGatherOp, UnrollStoreScatterOp, UnrollPrefetchOp,
-           UnrollUpdateOffsetOp, UnrollLoadMatrixOp, UnrollStoreMatrixOp,
-           UnrollLoadGatherOpWithOffset, UnrollStoreScatterOpWithOffsets>(
-          patterns.getContext(), options);
+  patterns.add<UnrollCreateNdOp, UnrollUpdateNdOffsetOp, UnrollPrefetchNdOp,
+               UnrollLoadNdOp, UnrollStoreNdOp, UnrollDpasOp,
+               UnrollCreateDescOp, UnrollLoadGatherOp, UnrollStoreScatterOp,
+               UnrollPrefetchOp, UnrollUpdateOffsetOp, UnrollLoadMatrixOp,
+               UnrollStoreMatrixOp, UnrollLoadGatherOpWithOffset,
+               UnrollStoreScatterOpWithOffsets, UnrollConvertLayoutOp>(
----------------
charithaintc wrote:

I would fuse them together. could be a different PR.

It seems like there are 2 patterns for a single op type in the same pattern application. What happens if the order of application changes? 

https://github.com/llvm/llvm-project/pull/183837