[FXML-5890] Order tiling worklist

mlir/include/mlir/Dialect/SCF/Transforms/TileUsingInterface.h

@@ -10,6 +10,7 @@
 #define MLIR_DIALECT_SCF_TRANSFORMS_TILEUSINGINTERFACE_H
 
 #include "mlir/Dialect/SCF/IR/SCF.h"
+#include "mlir/Dialect/Tensor/IR/Tensor.h"
 #include "mlir/Dialect/Tensor/Transforms/Transforms.h"
 #include "mlir/IR/PatternMatch.h"
 #include "mlir/Interfaces/LoopLikeInterface.h"
@@ -194,6 +195,21 @@ struct SCFTileAndFuseOptions {
   /// before fusion. This will track deleted and newly inserted
   /// `tensor.extract_slice` ops and update the worklist.
   std::optional<FrozenRewritePatternSet> cleanupPatterns = std::nullopt;
+
+  /// A function to insert a tilable node into a list of nodes to be tiled.
+  /// This controls the order in which tiling and fusion happen.
+  using WorklistInsertFnTy = std::function<void(
+      tensor::ExtractSliceOp op, std::deque<tensor::ExtractSliceOp> &worklist)>;
+  /// By default, simply append the op at the end of the queue.
+  WorklistInsertFnTy worklistInsertFn =
+      [](tensor::ExtractSliceOp op,
+         std::deque<tensor::ExtractSliceOp> &worklist) {
+        worklist.push_back(op);
+      };
+  SCFTileAndFuseOptions &setWorklistInsertFn(WorklistInsertFnTy insertFn) {
+    worklistInsertFn = insertFn;
+    return *this;
+  }
 };
 
 /// Fuse the producer of the source of `candidateSliceOp` by computing the

mlir/lib/Dialect/SCF/Transforms/TileUsingInterface.cpp

@@ -1391,7 +1391,8 @@ namespace {
 class SliceTrackingListener : public RewriterBase::Listener {
 public:
   explicit SliceTrackingListener(
-      std::optional<FrozenRewritePatternSet> patterns);
+      std::optional<FrozenRewritePatternSet> patterns,
+      scf::SCFTileAndFuseOptions::WorklistInsertFnTy worklistInsertFn);
   SliceTrackingListener() = default;
 
   /// Adds the given list of operations to the worklist, and if present,
@@ -1421,18 +1422,22 @@ class SliceTrackingListener : public RewriterBase::Listener {
   /// Optional pattern set to apply when adding new operations to the
   /// worklist.
   std::optional<FrozenRewritePatternSet> patterns = std::nullopt;
+  scf::SCFTileAndFuseOptions::WorklistInsertFnTy worklistInsertFn;
 };
 
 SliceTrackingListener::SliceTrackingListener(
-    std::optional<FrozenRewritePatternSet> p) {
+    std::optional<FrozenRewritePatternSet> p,
+    scf::SCFTileAndFuseOptions::WorklistInsertFnTy w) {
   patterns = std::move(p);
+  worklistInsertFn = w;
 }
 
+/// Insert extract_slice ops into the worklist.
 LogicalResult
 SliceTrackingListener::insertAndApplyPatterns(ArrayRef<Operation *> ops) {
   for (Operation *op : ops) {
     if (auto slice = dyn_cast<tensor::ExtractSliceOp>(op))
-      worklist.push_back(slice);
+      worklistInsertFn(slice, worklist);
   }
 
   if (!patterns)
@@ -1444,12 +1449,14 @@ SliceTrackingListener::insertAndApplyPatterns(ArrayRef<Operation *> ops) {
   return applyOpPatternsGreedily(ops, patterns.value(), config);
 }
 
+/// Insert extract_slice ops created by cleanup patterns into the worklist.
+/// Triggered from applyOpPatternsAndFold() above.
 void SliceTrackingListener::notifyOperationInserted(
     Operation *op, OpBuilder::InsertPoint previous) {
   auto slice = dyn_cast<tensor::ExtractSliceOp>(op);
   if (!slice)
     return;
-  worklist.push_back(slice);
+  worklistInsertFn(slice, worklist);
 }
 
 // Scan the worklist for the given op and remove it if present. The
@@ -1580,7 +1587,7 @@ mlir::scf::tileConsumerAndFuseProducersUsingSCF(
   };
 
   SliceTrackingListener sliceTracker =
-      SliceTrackingListener(options.cleanupPatterns);
+      SliceTrackingListener(options.cleanupPatterns, options.worklistInsertFn);
 
   if (failed(
           sliceTracker.insertAndApplyPatterns(tilingResult->generatedSlices))) {
@@ -1596,6 +1603,8 @@ mlir::scf::tileConsumerAndFuseProducersUsingSCF(
                                           loops);
     if (!fusableProducer)
       continue;
+    LLVM_DEBUG(llvm::dbgs() << "worklist: producer is "
+                            << *(fusableProducer.getOwner()) << "\n");
 
     std::optional<SCFTileAndFuseOptions::ControlFnResult> controlFnResult =
         options.fusionControlFn(candidateSlice, fusableProducer,

mlir/test/Dialect/Linalg/tile-sort.mlir

@@ -0,0 +1,83 @@
+// RUN: mlir-opt %s -transform-interpreter -split-input-file -debug-only=tile-using-interface 2>&1 | FileCheck %s
+
+func.func @tile_order_ceil_then_negf(%arg: tensor<256xf32>) -> tensor<256xf32> {
+  // Ops are tiled by lower priority: linalg.powf, linalg.ceil (1st operand of powf, priority = 0),
+  // linalg.negf (2nd oprand of powf, priority = 1), linalg.ceil (operand of negf, priority = 0)
+  %empty = tensor.empty() : tensor<256xf32>
+  %0 = linalg.ceil {tiling_priority = 0 : i64} ins(%arg: tensor<256xf32>) outs(%empty: tensor<256xf32>) -> tensor<256xf32>
+  %empty1 = tensor.empty() : tensor<256xf32>
+  %1 = linalg.negf {tiling_priority = 1 : i64} ins(%0 : tensor<256xf32>) outs(%empty1: tensor<256xf32>) -> tensor<256xf32>
+  %empty2 = tensor.empty() : tensor<256xf32>
+  %2 = linalg.powf {tile} ins(%0, %1: tensor<256xf32>, tensor<256xf32>) outs(%empty2: tensor<256xf32>) -> tensor<256xf32>
+
+  // The order of these checks is the order in which the ops are actually tiled.
+  // CHECK: worklist: producer is %{{.*}} = linalg.ceil
+  // CHECK: worklist: producer is %{{.*}} = linalg.negf
+  // CHECK: worklist: producer is %{{.*}} = linalg.ceil
+
+  return %2 : tensor<256xf32>
+}
+
+module attributes {transform.with_named_sequence} {
+  transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
+    %0 = transform.structured.match ops{["linalg.powf"]} attributes {"tile"} in %arg1 : (!transform.any_op) -> !transform.any_op
+    %1, %loops = transform.test.tile_fuse_ordered %0 [32] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
+    transform.yield
+  }
+}
+
+// -----
+
+func.func @tile_negf_then_ceil(%arg: tensor<256xf32>) -> tensor<256xf32> {
+  // Ops are tiled by lower priority: linalg.powf, linalg.negf (2nd operand of powf, priority = 0),
+  // linalg.ceil (1st oprand of powf, priority = 1), linalg.ceil (operand of negf, priority = 1)
+  %empty = tensor.empty() : tensor<256xf32>
+  %0 = linalg.ceil {tiling_priority = 1 : i64} ins(%arg: tensor<256xf32>) outs(%empty: tensor<256xf32>) -> tensor<256xf32>
+  %empty1 = tensor.empty() : tensor<256xf32>
+  %1 = linalg.negf {tiling_priority = 0 : i64} ins(%0 : tensor<256xf32>) outs(%empty1: tensor<256xf32>) -> tensor<256xf32>
+  %empty2 = tensor.empty() : tensor<256xf32>
+  %2 = linalg.powf {tile} ins(%0, %1: tensor<256xf32>, tensor<256xf32>) outs(%empty2: tensor<256xf32>) -> tensor<256xf32>
+
+  // CHECK: worklist: producer is %{{.*}} = linalg.negf
+  // CHECK: worklist: producer is %{{.*}} = linalg.ceil
+  // CHECK: worklist: producer is %{{.*}} = linalg.ceil
+
+  return %2 : tensor<256xf32>
+}
+
+module attributes {transform.with_named_sequence} {
+  transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
+    %0 = transform.structured.match ops{["linalg.powf"]} attributes {"tile"} in %arg1 : (!transform.any_op) -> !transform.any_op
+    %1, %loops = transform.test.tile_fuse_ordered %0 [32] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
+    transform.yield
+  }
+}
+
+// -----
+
+func.func @tile_negf_then_ceil_swap_in_powf(%arg: tensor<256xf32>) -> tensor<256xf32> {
+  // This gives the same tiling order as above regardless of the operand order in the powf
+  // linalg.powf, linalg.negf (1st operand of powf, priority = 0),
+  // linalg.ceil (2nd oprand of powf, priority = 1), linalg.ceil (operand of negf, priority = 1)
+  %empty = tensor.empty() : tensor<256xf32>
+  %0 = linalg.ceil {tiling_priority = 1 : i64} ins(%arg: tensor<256xf32>) outs(%empty: tensor<256xf32>) -> tensor<256xf32>
+  %empty1 = tensor.empty() : tensor<256xf32>
+  %1 = linalg.negf {tiling_priority = 0 : i64} ins(%0 : tensor<256xf32>) outs(%empty1: tensor<256xf32>) -> tensor<256xf32>
+  %empty2 = tensor.empty() : tensor<256xf32>
+  %2 = linalg.powf {tile} ins(%1, %0: tensor<256xf32>, tensor<256xf32>) outs(%empty2: tensor<256xf32>) -> tensor<256xf32>
+
+  // CHECK: worklist: producer is %{{.*}} = linalg.negf
+  // CHECK: worklist: producer is %{{.*}} = linalg.ceil
+  // CHECK: worklist: producer is %{{.*}} = linalg.ceil
+
+  return %2 : tensor<256xf32>
+}
+
+module attributes {transform.with_named_sequence} {
+  transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
+    %0 = transform.structured.match ops{["linalg.powf"]} attributes {"tile"} in %arg1 : (!transform.any_op) -> !transform.any_op
+    %1, %loops = transform.test.tile_fuse_ordered %0 [32] : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
+    transform.yield
+  }
+}
+

mlir/test/lib/Interfaces/TilingInterface/TestTilingInterfaceTransformOps.cpp

@@ -14,13 +14,18 @@
 #include "mlir/Dialect/Affine/IR/AffineOps.h"
 #include "mlir/Dialect/Index/IR/IndexDialect.h"
 #include "mlir/Dialect/SCF/Transforms/TileUsingInterface.h"
+#include "mlir/Dialect/Tensor/IR/Tensor.h"
 #include "mlir/Dialect/Transform/IR/TransformAttrs.h"
 #include "mlir/Dialect/Transform/IR/TransformDialect.h"
 #include "mlir/Dialect/Transform/Interfaces/TransformInterfaces.h"
 #include "mlir/Dialect/Utils/StaticValueUtils.h"
 #include "mlir/IR/Dominance.h"
+#include "mlir/IR/OpDefinition.h"
 #include "mlir/IR/OpImplementation.h"
 #include "mlir/Interfaces/TilingInterface.h"
+#include <deque>
+#include <functional>
+#include <string>
 
 #define GET_OP_CLASSES
 #include "TestTilingInterfaceTransformOps.h.inc"
@@ -54,12 +59,13 @@ static llvm::SmallDenseSet<Operation *> collectTiledAndFusedOps(Operation *op) {
 /// Apply a tile and fuse transformation to all payload ops and store both the
 /// tiled operation as well as the created tile loops.
 template <typename Range>
-static LogicalResult
-applyTileAndFuseToAll(RewriterBase &rewriter, Operation *transformOp,
-                      Range &&payloadOps, unsigned numLoops,
-                      ArrayRef<OpFoldResult> tileSizes,
-                      ArrayRef<int64_t> interchange, bool useForall,
-                      TransformResults &transformResults) {
+static LogicalResult applyTileAndFuseToAll(
+    RewriterBase &rewriter, Operation *transformOp, Range &&payloadOps,
+    unsigned numLoops, ArrayRef<OpFoldResult> tileSizes,
+    ArrayRef<int64_t> interchange, bool useForall,
+    TransformResults &transformResults,
+    std::optional<scf::SCFTileAndFuseOptions::WorklistInsertFnTy>
+        insertIntoWorklist) {
   SmallVector<Operation *> tiledOps;
   SmallVector<SmallVector<Operation *>> loopOps(numLoops);
 
@@ -87,6 +93,9 @@ applyTileAndFuseToAll(RewriterBase &rewriter, Operation *transformOp,
     }
 
     scf::SCFTileAndFuseOptions tileAndFuseOptions;
+    if (insertIntoWorklist.has_value()) {
+      tileAndFuseOptions.setWorklistInsertFn(*insertIntoWorklist);
+    }
     tileAndFuseOptions.setTilingOptions(tilingOptions);
 
     scf::SCFTileAndFuseOptions::ControlFnTy controlFn =
@@ -157,7 +166,65 @@ transform::TestFuseAndYieldOp::apply(TransformRewriter &rewriter,
   LogicalResult result = applyTileAndFuseToAll(
       rewriter, getOperation(), state.getPayloadOps(getTarget()),
       tileSizes.size() - llvm::count(tileSizes, 0), tileSizesOfr,
-      tileInterchange, getUseForall(), transformResults);
+      tileInterchange, getUseForall(), transformResults, {});
+  return failed(result) ? DiagnosedSilenceableFailure::definiteFailure()
+                        : DiagnosedSilenceableFailure::success();
+}
+
+//===----------------------------------------------------------------------===//
+// TestFuseOrderedOp
+//===----------------------------------------------------------------------===//
+
+static std::optional<int64_t>
+getProducerTilingPriority(tensor::ExtractSliceOp op) {
+  auto *producer = op.getSource().getDefiningOp();
+  if (!producer)
+    return {};
+
+  if (!producer->hasAttrOfType<IntegerAttr>("tiling_priority"))
+    return {};
+
+  auto attr = producer->getAttrOfType<IntegerAttr>("tiling_priority");
+  return attr.getInt();
+}
+
+static void
+insertIntoWorklistOrdered(tensor::ExtractSliceOp op,
+                          std::deque<tensor::ExtractSliceOp> &worklist) {
+  std::optional<int64_t> opTilingOrder = getProducerTilingPriority(op);
+  if (!opTilingOrder) {
+    worklist.push_back(op);
+    return;
+  }
+
+  auto iterator = worklist.begin();
+  for (; iterator != worklist.end(); ++iterator) {
+    std::optional<int64_t> otherOpTilingOrder =
+        getProducerTilingPriority(*iterator);
+    if (!otherOpTilingOrder || *otherOpTilingOrder > *opTilingOrder)
+      break;
+  }
+  worklist.insert(iterator, op);
+}
+
+DiagnosedSilenceableFailure
+transform::TestFuseOrderedOp::apply(TransformRewriter &rewriter,
+                                    TransformResults &transformResults,
+                                    TransformState &state) {
+  SmallVector<int64_t> tileSizes =
+      extractFromIntegerArrayAttr<int64_t>(getTileSizes());
+  SmallVector<int64_t> tileInterchange;
+  for (size_t i = 0; i < tileSizes.size(); ++i) {
+    tileInterchange.push_back(i);
+  }
+
+  SmallVector<OpFoldResult> tileSizesOfr =
+      getAsIndexOpFoldResult(rewriter.getContext(), tileSizes);
+
+  LogicalResult result = applyTileAndFuseToAll(
+      rewriter, getOperation(), state.getPayloadOps(getTarget()),
+      tileSizes.size() - llvm::count(tileSizes, 0), tileSizesOfr, {}, false,
+      transformResults, insertIntoWorklistOrdered);
   return failed(result) ? DiagnosedSilenceableFailure::definiteFailure()
                         : DiagnosedSilenceableFailure::success();
 }

mlir/test/lib/Interfaces/TilingInterface/TestTilingInterfaceTransformOps.td

@@ -49,6 +49,29 @@ def TestFuseAndYieldOp : Op<Transform_Dialect, "test.fuse_and_yield",
   }];
 }
 
+def TestFuseOrderedOp : Op<Transform_Dialect, "test.tile_fuse_ordered",
+  [FunctionalStyleTransformOpTrait, MemoryEffectsOpInterface,
+   DeclareOpInterfaceMethods<TransformOpInterface>,
+   ReportTrackingListenerFailuresOpTrait]> {
+  let description = [{
+    Applies tiling and fusion to the operations pointed to by the target handle,
+    following the order given by each operation's tiling_priority attribute.
+
+    On success returns the tiled operations as well as generated loops. Emits
+    a definite failure if tiling fails.
+  }];
+
+  let arguments =
+    (ins TransformHandleTypeInterface:$target,
+        DefaultValuedAttr<I64ArrayAttr, "{}">:$tile_sizes);
+  let results = (outs TransformHandleTypeInterface:$transfomed,
+      Variadic<TransformHandleTypeInterface>:$loops);
+
+  let assemblyFormat = [{
+    $target ($tile_sizes^)? attr-dict `:` functional-type(operands, results)
+  }];
+}
+
 def TestFuseConsumerOp : Op<Transform_Dialect, "test.fuse_consumer",
        [DeclareOpInterfaceMethods<TransformOpInterface>,
         DeclareOpInterfaceMethods<MemoryEffectsOpInterface>,