[mlir][linalg] Allow promotion to use the original subview size (#144334)

linalg promotion attempts to compute a constant upper bound for the
allocated buffer size. Only when failed to compute an upperbound it
fallbacks to the original subview size, which may be dynamic.

Adding a promotion option to use the original subview size by default,
thus minimizing the allocation size.
Fixes #144268.

mlir/include/mlir/Dialect/Linalg/TransformOps/LinalgTransformOps.td

@@ -1402,6 +1402,7 @@ def PromoteOp : Op<Transform_Dialect, "structured.promote",
                        DefaultValuedAttr<I64ArrayAttr, "{}">:$operands_to_promote,
                        DefaultValuedAttr<BoolArrayAttr, "{}">:$use_full_tile_buffers,
                        UnitAttr:$use_full_tiles_by_default,
+                       UnitAttr:$use_original_subview_size,
                        UnitAttr:$use_alloca,
                        OptionalAttr<AnyAttr>:$memory_space,
                        OptionalAttr<DeviceMappingArrayAttr>:$mapping,

mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h

@@ -422,6 +422,13 @@ struct LinalgPromotionOptions {
     useFullTileBuffersDefault = use;
     return *this;
   }
+  /// If true, buffers will be allocated with the original subview size. This
+  /// may result in more dynamic allocations, in case of dynamic sizes.
+  bool useOriginalSubviewSize = false;
+  LinalgPromotionOptions &setUseOriginalSubviewSize(bool originalSize) {
+    useOriginalSubviewSize = originalSize;
+    return *this;
+  }
   /// Alignment of promoted buffer. If `std::nullopt` do not specify alignment.
   std::optional<unsigned> alignment;
   LinalgPromotionOptions &setAlignment(unsigned align) {
@@ -796,7 +803,8 @@ FailureOr<LinalgOp> specializeGenericOp(RewriterBase &rewriter,
                                         GenericOp genericOp);
 
 /// Create a new buffer using the `allocationFn` provided. The size of this
-/// buffer is the smallest constant bounding size along each dimension that
+/// buffer is either the original subview size when 'useOriginalSubviewSize' is
+/// set to true or the smallest constant bounding size along each dimension that
 /// can be computed for the size of the result of `subView`. Returns the
 /// allocated buffer as `fullLocalView` and the view that matches the size of
 /// the result of subview operation as `partialLocalView`.
@@ -806,6 +814,7 @@ struct PromotionInfo {
 };
 FailureOr<PromotionInfo>
 promoteSubviewAsNewBuffer(OpBuilder &b, Location loc, memref::SubViewOp subView,
+                          bool useOriginalSubviewSize,
                           const AllocBufferCallbackFn &allocationFn,
                           DataLayout &layout);
 

mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp

@@ -2408,6 +2408,9 @@ transform::PromoteOp::applyToOne(transform::TransformRewriter &rewriter,
   if (getUseFullTilesByDefault())
     promotionOptions = promotionOptions.setUseFullTileBuffersByDefault(
         getUseFullTilesByDefault());
+  if (getUseOriginalSubviewSize())
+    promotionOptions =
+        promotionOptions.setUseOriginalSubviewSize(getUseOriginalSubviewSize());
   if (getUseAlloca())
     promotionOptions = promotionOptions.setUseAlloca(getUseAlloca());
   if (!getUseFullTileBuffers().empty())

mlir/lib/Dialect/Linalg/Transforms/Promotion.cpp

@@ -148,6 +148,9 @@ struct LinalgOpInstancePromotionOptions {
   llvm::SmallSet<int64_t, 4> operandsNumbersToCopyIn;
   /// True if the full view should be used for the promoted buffer.
   DenseMap<Value, bool> useFullTileBuffers;
+  /// True if the original subview size should be used. This means the full tile
+  /// buffer is the same size as the partial view.
+  bool useOriginalSubviewSize;
 
   /// Callback functions for allocation and deallocation of promoted buffers, as
   /// well as to copy the data into and out of these buffers.
@@ -170,6 +173,7 @@ LinalgOpInstancePromotionOptions::LinalgOpInstancePromotionOptions(
       options.useFullTileBuffers.value_or(llvm::SmallBitVector());
   vUseFullTileBuffers.resize(linalgOp->getNumOperands(),
                              options.useFullTileBuffersDefault);
+  useOriginalSubviewSize = options.useOriginalSubviewSize;
 
   for (OpOperand &opOperand : linalgOp->getOpOperands()) {
     int64_t operandNumber = opOperand.getOperandNumber();
@@ -237,7 +241,8 @@ LinalgOpInstancePromotionOptions::LinalgOpInstancePromotionOptions(
 // by a partial `copy` op.
 FailureOr<PromotionInfo> mlir::linalg::promoteSubviewAsNewBuffer(
     OpBuilder &b, Location loc, memref::SubViewOp subView,
-    const AllocBufferCallbackFn &allocationFn, DataLayout &layout) {
+    bool useOriginalSubviewSize, const AllocBufferCallbackFn &allocationFn,
+    DataLayout &layout) {
   auto viewType = subView.getType();
   auto rank = viewType.getRank();
   SmallVector<Value, 4> fullSizes;
@@ -254,7 +259,8 @@ FailureOr<PromotionInfo> mlir::linalg::promoteSubviewAsNewBuffer(
     // to look for the bound.
     LLVM_DEBUG(llvm::dbgs() << "Extract tightest: " << rangeValue.size << "\n");
     Value size;
-    if (auto attr = llvm::dyn_cast_if_present<Attribute>(rangeValue.size)) {
+    if (llvm::isa_and_present<Attribute>(rangeValue.size) ||
+        useOriginalSubviewSize) {
       size = getValueOrCreateConstantIndexOp(b, loc, rangeValue.size);
     } else {
       FailureOr<int64_t> upperBound =
@@ -295,7 +301,8 @@ promoteSubViews(ImplicitLocOpBuilder &b,
     memref::SubViewOp subView =
         cast<memref::SubViewOp>(v.second.getDefiningOp());
     auto promotionInfo = promoteSubviewAsNewBuffer(
-        b, b.getLoc(), subView, options.allocationFn, layout);
+        b, b.getLoc(), subView, options.useOriginalSubviewSize,
+        options.allocationFn, layout);
     if (failed(promotionInfo))
       return failure();
     promotionInfoMap[v.first] = *promotionInfo;

mlir/test/Dialect/Linalg/promotion_options.mlir

@@ -42,3 +42,59 @@ module attributes {transform.with_named_sequence} {
     transform.yield
   }
 }
+
+// -----
+
+func.func @matmul_f32(%A: memref<512x256xf32>, %B: memref<256x512xf32>, %C: memref<256x256xf32>, %s0: index, %s1: index, %s2: index) {
+  %c0 = arith.constant 0 : index
+  %c256 = arith.constant 256 : index
+  %c512 = arith.constant 512 : index
+  scf.for %arg4 = %c0 to %c512 step %s0 {
+    scf.for %arg5 = %c0 to %c512 step %s1 {
+      scf.for %arg6 = %c0 to %c256 step %s2 {
+        %i0 = affine.min affine_map<(d0)[s0] -> (-d0 + 512, s0)>(%arg4)[%s0]
+        %i1 = affine.min affine_map<(d0)[s0] -> (-d0 + 512, s0)>(%arg5)[%s1]
+        %i2 = affine.min affine_map<(d0)[s0] -> (-d0 + 256, s0)>(%arg6)[%s2]
+        %0 = memref.subview %A[%arg4, %arg6][%i0, %i2][1, 1] : memref<512x256xf32> to memref<?x?xf32, strided<[256, 1], offset: ?>>
+        %1 = memref.subview %B[%arg6, %arg5][%i2, %i1][1, 1] : memref<256x512xf32> to memref<?x?xf32, strided<[512, 1], offset: ?>>
+        %2 = memref.subview %C[%arg4, %arg5][%i0, %i1][1, 1] : memref<256x256xf32> to memref<?x?xf32, strided<[256, 1], offset: ?>>
+        linalg.matmul
+          ins(%0, %1: memref<?x?xf32, strided<[256, 1], offset: ?>>,
+                      memref<?x?xf32, strided<[512, 1], offset: ?>>)
+          outs(%2: memref<?x?xf32, strided<[256, 1], offset: ?>>)
+      }
+    }
+  }
+  return
+}
+
+// CHECK-LABEL:   func.func @matmul_f32(
+// CHECK-SAME:      %[[ARG0:.*]]: memref<512x256xf32>
+// CHECK-SAME:      %[[ARG1:.*]]: memref<256x512xf32>
+// CHECK-SAME:      %[[ARG2:.*]]: memref<256x256xf32>
+// CHECK-SAME:      %[[ARG3:.*]]: index, %[[ARG4:.*]]: index, %[[ARG5:.*]]: index
+// CHECK:           %[[C4:.*]] = arith.constant 4 : index
+
+// CHECK:                 %[[i0:.*]] = affine.min
+// CHECK:                 %[[i1:.*]] = affine.min
+// CHECK:                 %[[i2:.*]] = affine.min
+
+// CHECK:                 %[[VAL_13:.*]] = arith.muli %[[i0]], %[[i2]] : index
+// CHECK:                 %[[VAL_14:.*]] = arith.muli %[[VAL_13]], %[[C4]] : index
+// CHECK:                 %[[VAL_15:.*]] = memref.alloc(%[[VAL_14]]) : memref<?xi8>
+
+// CHECK:                 %[[VAL_18:.*]] = arith.muli %[[i2]], %[[i1]] : index
+// CHECK:                 %[[VAL_19:.*]] = arith.muli %[[VAL_18]], %[[C4]] : index
+// CHECK:                 %[[VAL_20:.*]] = memref.alloc(%[[VAL_19]]) : memref<?xi8>
+
+// CHECK:                 %[[VAL_23:.*]] = arith.muli %[[i0]], %[[i1]] : index
+// CHECK:                 %[[VAL_24:.*]] = arith.muli %[[VAL_23]], %[[C4]] : index
+// CHECK:                 %[[VAL_25:.*]] = memref.alloc(%[[VAL_24]]) : memref<?xi8>
+
+module attributes {transform.with_named_sequence} {
+  transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
+    %0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
+    %1 = transform.structured.promote %0 { use_original_subview_size } : (!transform.any_op) -> !transform.any_op
+    transform.yield
+  }
+}