[mlir][sparse] implementating stageSparseOpPass as an interface

mlir/include/mlir/Dialect/SparseTensor/IR/CMakeLists.txt

@@ -12,3 +12,9 @@ set(LLVM_TARGET_DEFINITIONS SparseTensorTypes.td)
 mlir_tablegen(SparseTensorTypes.h.inc -gen-typedef-decls)
 mlir_tablegen(SparseTensorTypes.cpp.inc -gen-typedef-defs)
 add_public_tablegen_target(MLIRSparseTensorTypesIncGen)
+
+set(LLVM_TARGET_DEFINITIONS SparseTensorInterfaces.td)
+mlir_tablegen(SparseTensorInterfaces.h.inc -gen-op-interface-decls)
+mlir_tablegen(SparseTensorInterfaces.cpp.inc -gen-op-interface-defs)
+add_public_tablegen_target(MLIRSparseTensorInterfacesIncGen)
+add_dependencies(mlir-headers MLIRSparseTensorInterfacesIncGen)

mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensor.h

@@ -11,6 +11,7 @@
 
 #include "mlir/Bytecode/BytecodeOpInterface.h"
 #include "mlir/Dialect/SparseTensor/IR/Enums.h"
+#include "mlir/Dialect/SparseTensor/IR/SparseTensorInterfaces.h"
 #include "mlir/IR/BuiltinTypes.h"
 #include "mlir/IR/Dialect.h"
 #include "mlir/IR/OpDefinition.h"

mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorInterfaces.h

@@ -0,0 +1,30 @@
+//===- SparseTensorInterface.h - sparse tensor operations interfaces-------===//
+//
+// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
+// See https://llvm.org/LICENSE.txt for license information.
+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+//
+//===----------------------------------------------------------------------===//
+
+#ifndef MLIR_DIALECT_SPARSETENSOR_IR_SPARSETENSORINTERFACES_H_
+#define MLIR_DIALECT_SPARSETENSOR_IR_SPARSETENSORINTERFACES_H_
+
+#include "mlir/IR/OpDefinition.h"
+
+namespace mlir {
+class PatternRewriter;
+
+namespace sparse_tensor {
+class StageWithSortSparseOp;
+
+namespace detail {
+LogicalResult stageWithSortImpl(sparse_tensor::StageWithSortSparseOp op,
+                                PatternRewriter &rewriter);
+} // namespace detail
+} // namespace sparse_tensor
+} // namespace mlir
+
+/// Include the generated interface declarations.
+#include "mlir/Dialect/SparseTensor/IR/SparseTensorInterfaces.h.inc"
+
+#endif // MLIR_DIALECT_SPARSETENSOR_IR_SPARSETENSORINTERFACES_H_

mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorInterfaces.td

@@ -0,0 +1,45 @@
+//===- SparseTensorInterfaces.td --------------------------*- tablegen -*-===//
+//
+// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
+// See https://llvm.org/LICENSE.txt for license information.
+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+//
+//===----------------------------------------------------------------------===//
+
+#ifndef SPARSETENSOR_IR_SPARSETENSORINTERFACES
+#define SPARSETENSOR_IR_SPARSETENSORINTERFACES
+
+include "mlir/IR/OpBase.td"
+
+def StageWithSortSparseOpInterface : OpInterface<"StageWithSortSparseOp"> {
+  let description = [{
+    A stage-with-sort sparse tensor operation is an operation that produces
+    unordered intermediate output. An extra sort is required to obtain the final
+    ordered result.
+
+    E.g., convert csr -> csc need to be implemented as
+          convert csr -> unordered coo -> sort by column -> csc; and
+          concatenate csr, csc -> csr can be staged into
+          concatenate csr, csr -> unordered coo -> sort by row -> csr.
+  }];
+  let cppNamespace = "::mlir::sparse_tensor";
+  let methods = [
+    InterfaceMethod<
+    /*desc=*/"Return true if the operation needs an extra sort to produce the final result.",
+    /*retTy=*/"bool",
+    /*methodName=*/"needExtraSort",
+    /*args=*/(ins),
+    /*methodBody=*/"">,
+    InterfaceMethod<
+    /*desc=*/"Stage the operation, return the final result value after staging.",
+    /*retTy=*/"::mlir::LogicalResult",
+    /*methodName=*/"stageWithSort",
+    /*args=*/(ins "::mlir::PatternRewriter &":$rewriter),
+    /*methodBody=*/[{
+        return detail::stageWithSortImpl($_op, rewriter);
+    }]>,
+  ];
+}
+
+
+#endif // SPARSETENSOR_IR_SPARSETENSORINTERFACES

mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorOps.td

@@ -12,6 +12,7 @@
 include "mlir/Dialect/SparseTensor/IR/SparseTensorAttrDefs.td"
 include "mlir/Dialect/SparseTensor/IR/SparseTensorBase.td"
 include "mlir/Dialect/SparseTensor/IR/SparseTensorTypes.td"
+include "mlir/Dialect/SparseTensor/IR/SparseTensorInterfaces.td"
 include "mlir/Interfaces/InferTypeOpInterface.td"
 include "mlir/Interfaces/SideEffectInterfaces.td"
 
@@ -153,7 +154,7 @@ def SparseTensor_DisassembleOp : SparseTensor_Op<"disassemble", [Pure, SameVaria
 }
 
 def SparseTensor_ConvertOp : SparseTensor_Op<"convert",
-  [Pure]>,
+  [Pure, StageWithSortSparseOpInterface]>,
     Arguments<(ins AnyTensor:$source)>,
     Results<(outs AnyTensor:$dest)> {
   string summary = "Converts between different tensor types";
@@ -197,9 +198,9 @@ def SparseTensor_ConvertOp : SparseTensor_Op<"convert",
   }];
 
   let extraClassDeclaration = [{
-     // Whether the convert can be done by a single step (either a sort or a foreach),
-     // or it would require a tmp buffer (sort, then foreach).
-     bool directConvertable();
+     // Whether the convert can be done by a single step or it would require
+     // an extra sort. Inherited from StageWithSortSparseOpInterface.
+     bool needExtraSort();
   }];
 
   let assemblyFormat = "$source attr-dict `:` type($source) `to` type($dest)";
@@ -334,7 +335,8 @@ def SparseTensor_NumberOfEntriesOp : SparseTensor_Op<"number_of_entries", [Pure]
   let assemblyFormat = "$tensor attr-dict `:` type($tensor)";
 }
 
-def SparseTensor_ConcatenateOp : SparseTensor_Op<"concatenate", [Pure]>,
+def SparseTensor_ConcatenateOp : SparseTensor_Op<"concatenate",
+                                 [Pure, StageWithSortSparseOpInterface]>,
     Arguments<(ins Variadic<AnyRankedTensor>:$inputs, DimensionAttr:$dimension)>,
     Results<(outs AnyRankedTensor:$result)> {
 
@@ -357,6 +359,12 @@ def SparseTensor_ConcatenateOp : SparseTensor_Op<"concatenate", [Pure]>,
      ```
    }];
 
+  let extraClassDeclaration = [{
+     // Whether the concatenate can be done by a single step or it would require
+     // an extra sort. Inherited from StageWithSortSparseOpInterface.
+     bool needExtraSort();
+  }];
+
   let assemblyFormat = "$inputs attr-dict `:` type($inputs) `to` type($result)";
   let hasVerifier = 1;
 }

mlir/lib/Dialect/SparseTensor/IR/CMakeLists.txt

@@ -29,6 +29,7 @@ endif()
 
 add_mlir_dialect_library(MLIRSparseTensorDialect
   SparseTensorDialect.cpp
+  SparseTensorInterfaces.cpp
   Detail/Var.cpp
   Detail/DimLvlMap.cpp
   Detail/LvlTypeParser.cpp

mlir/lib/Dialect/SparseTensor/IR/SparseTensorDialect.cpp

@@ -1065,18 +1065,18 @@ OpFoldResult ConvertOp::fold(FoldAdaptor adaptor) {
   return {};
 }
 
-bool ConvertOp::directConvertable() {
+bool ConvertOp::needExtraSort() {
   SparseTensorType srcStt = getSparseTensorType(getSource());
   SparseTensorType dstStt = getSparseTensorType(getDest());
 
-  // We can always directly convert to unordered sparse tensor or dense tensor
-  // since dense tensor support random access.
+  // We do not need an extra sort when returning unordered sparse tensors or
+  // dense tensor since dense tensor support random access.
   if (dstStt.isAllDense() || !dstStt.isAllOrdered())
-    return true;
+    return false;
 
   if (srcStt.isAllOrdered() && dstStt.isAllOrdered() &&
       srcStt.hasSameDimToLvl(dstStt)) {
-    return true;
+    return false;
   }
 
   // Source and dest tensors are ordered in different ways. We only do direct
@@ -1086,9 +1086,9 @@ bool ConvertOp::directConvertable() {
   // performance.
   if (auto constOp = getSource().getDefiningOp<arith::ConstantOp>())
     if (isa<SparseElementsAttr>(constOp.getValue()))
-      return true;
+      return false;
 
-  return false;
+  return true;
 }
 
 LogicalResult ToPositionsOp::verify() {
@@ -1248,6 +1248,23 @@ LogicalResult UnaryOp::verify() {
   return success();
 }
 
+bool ConcatenateOp::needExtraSort() {
+  SparseTensorType dstStt = getSparseTensorType(*this);
+  if (dstStt.isAllDense() || !dstStt.isAllOrdered())
+    return false;
+
+  bool allSameOrdered = llvm::all_of(getInputs(), [dstStt](Value op) {
+    return getSparseTensorType(op).hasSameDimToLvl(dstStt);
+  });
+  // TODO: When conDim != 0, as long as conDim corresponding to the first level
+  // in all input/output buffers, and all input/output buffers have the same
+  // dimToLvl, the tmp COO buffer is still unnecessary (e.g, concatenate
+  // CSC matrices along column).
+  bool directLowerable =
+      allSameOrdered && getDimension() == 0 && dstStt.isIdentity();
+  return !directLowerable;
+}
+
 LogicalResult ConcatenateOp::verify() {
   const auto dstTp = getSparseTensorType(*this);
   const Dimension concatDim = getDimension();

mlir/lib/Dialect/SparseTensor/IR/SparseTensorInterfaces.cpp

@@ -0,0 +1,55 @@
+//===- SparseTensorInterfaces.cpp - SparseTensor interfaces impl ----------===//
+//
+// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
+// See https://llvm.org/LICENSE.txt for license information.
+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+//
+//===----------------------------------------------------------------------===//
+
+#include "mlir/Dialect/SparseTensor/IR/SparseTensorInterfaces.h"
+#include "mlir/Dialect/SparseTensor/IR/SparseTensor.h"
+#include "mlir/Dialect/SparseTensor/IR/SparseTensorType.h"
+#include "mlir/IR/PatternMatch.h"
+
+using namespace mlir;
+using namespace mlir::sparse_tensor;
+
+#include "mlir/Dialect/SparseTensor/IR/SparseTensorInterfaces.cpp.inc"
+
+LogicalResult
+sparse_tensor::detail::stageWithSortImpl(StageWithSortSparseOp op,
+                                         PatternRewriter &rewriter) {
+  if (!op.needExtraSort())
+    return failure();
+
+  Location loc = op.getLoc();
+  Type finalTp = op->getOpResult(0).getType();
+  SparseTensorType dstStt(finalTp.cast<RankedTensorType>());
+
+  Type srcCOOTp = getCOOFromTypeWithOrdering(
+      dstStt.getRankedTensorType(), dstStt.getDimToLvl(), /*ordered=*/false);
+
+  // Clones the original operation but changing the output to an unordered COO.
+  Operation *cloned = rewriter.clone(*op.getOperation());
+  rewriter.updateRootInPlace(cloned, [cloned, srcCOOTp]() {
+    cloned->getOpResult(0).setType(srcCOOTp);
+  });
+  Value srcCOO = cloned->getOpResult(0);
+
+  // -> sort
+  Type dstCOOTp = getCOOFromTypeWithOrdering(
+      dstStt.getRankedTensorType(), dstStt.getDimToLvl(), /*ordered=*/true);
+  Value dstCOO = rewriter.create<ReorderCOOOp>(
+      loc, dstCOOTp, srcCOO, SparseTensorSortKind::HybridQuickSort);
+
+  // -> dest.
+  if (dstCOO.getType() == finalTp) {
+    rewriter.replaceOp(op, dstCOO);
+  } else {
+    // Need an extra conversion if the target type is not COO.
+    rewriter.replaceOpWithNewOp<ConvertOp>(op, finalTp, dstCOO);
+  }
+  // TODO: deallocate extra COOs, we should probably delegate it to buffer
+  // deallocation pass.
+  return success();
+}