[mlir][linalg] Emit a warning when tile_using_forall generates non thread-safe code

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

@@ -1922,7 +1922,9 @@ def TileUsingForallOp :
 
     It is the user's responsibility to ensure that `num_threads/tile_sizes` is
     a valid tiling specification (i.e. that only tiles parallel dimensions,
-    e.g. in the Linalg case).
+    e.g. in the Linalg case). If the dimension is not parallelizable, a warning
+    is issued to notify the user that the generated code is not safe to
+    parallelize.
 
     If non-empty, the `mapping` is added as an attribute to the
     resulting `scf.forall`.

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

@@ -304,6 +304,28 @@ static void calculateTileOffsetsAndSizes(
   }
 }
 
+/// Returns a vector of bools representing if, for each axis, `op` can be tiled
+/// without incurring in a race condition and thus it is thread-safe to do the
+/// tiling. This is checked by iterating over numThreads and ensuring that the
+/// corresponding iterator type is "parallel". If it is not, then we know that
+/// such dimension is unsafe to tile.
+SmallVector<bool> safeToTileToForall(mlir::MLIRContext *ctx, LinalgOp linalgOp,
+                                     ArrayRef<OpFoldResult> numThreads) {
+  auto iterators = linalgOp.getIteratorTypesArray();
+  SmallVector<bool> safeToTile(numThreads.size(), true);
+
+  for (unsigned i = 0, e = numThreads.size(); i != e; i++) {
+    if (auto attr = llvm::dyn_cast_if_present<Attribute>(numThreads[i])) {
+      if (cast<IntegerAttr>(attr).getValue().getSExtValue() > 1) {
+        safeToTile[i] = iterators[i] == utils::IteratorType::parallel;
+      }
+    } else {
+      safeToTile[i] = iterators[i] == utils::IteratorType::parallel;
+    }
+  }
+  return safeToTile;
+}
+
 /// Rewrite a TilingInterface `op` to a tiled `scf.forall`. The
 /// tiling is specified by the number of tiles/threads `numThreads` and the
 /// optional nominal tile size `nominalTileSizes`. If `nominalTilSizes` is
@@ -314,8 +336,10 @@ static void calculateTileOffsetsAndSizes(
 /// size of data.
 /// It is the user's responsibility to ensure that `numThreads` is a valid
 /// tiling specification (i.e. that only tiles parallel dimensions, e.g. in the
-/// Linalg case). If `omitTileOffsetBoundsCheck` is true, then the function will
-/// assume that `tileSize[i] * (numThread[i] -1) <= dimSize[i]` holds.
+/// Linalg case). If the dimension is not parallelizable, a warning is issued to
+/// notify the user that the generated code is not safe to parallelize. If
+/// `omitTileOffsetBoundsCheck` is true, then the function will assume that
+/// `tileSize[i] * (numThread[i] -1) <= dimSize[i]` holds.
 static FailureOr<ForallTilingResult> tileToForallOpImpl(
     RewriterBase &b, TilingInterface op, ArrayRef<OpFoldResult> numThreads,
     std::optional<ArrayRef<OpFoldResult>> nominalTileSizes,
@@ -344,6 +368,16 @@ static FailureOr<ForallTilingResult> tileToForallOpImpl(
         return getValueOrCreateConstantIndexOp(b, loc, ofr);
       }));
 
+  LinalgOp linalgOp = dyn_cast<LinalgOp>(op.getOperation());
+  if (linalgOp) {
+    // Check if tiling is thread safe and print a warning if not.
+    SmallVector<bool> tilingSafety =
+        safeToTileToForall(b.getContext(), linalgOp, numThreads);
+    for (size_t i = 0; i < tilingSafety.size(); i++)
+      if (!tilingSafety[i])
+        op.emitWarning() << "tiling is not thread safe at axis #" << i;
+  }
+
   // 1. Create the ForallOp. We don't use the lambda body-builder
   // version because we require the use of RewriterBase in the body, so we
   // manually move the insertion point to the body below.

mlir/test/Dialect/Linalg/tile-to-forall.mlir

@@ -586,3 +586,144 @@ module attributes {transform.with_named_sequence} {
     transform.yield
   }
 }
+
+// -----
+
+#map = affine_map<(d0, d1) -> (d0, d1)>
+#map1 = affine_map<(d0, d1) -> (d0)>
+
+func.func @tile_thread_safety1(%arg0: tensor<100x300xf32>, %arg1: tensor<100xf32>) -> tensor<100xf32> {
+  // expected-warning@below {{tiling is not thread safe at axis #1}}
+  %0 = linalg.generic {indexing_maps = [#map, #map1], iterator_types = ["parallel", "reduction"]} ins(%arg0 : tensor<100x300xf32>) outs(%arg1 : tensor<100xf32>) {
+  ^bb0(%in: f32, %out: f32):
+    %1 = arith.addf %in, %out : f32
+    linalg.yield %1 : f32
+  } -> tensor<100xf32>
+  return %0 : tensor<100xf32>
+}
+
+module attributes {transform.with_named_sequence} {
+  transform.named_sequence @__transform_main(%arg0: !transform.any_op {transform.readonly}) {
+    %0 = transform.structured.match ops{["linalg.generic"]} in %arg0 : (!transform.any_op) -> !transform.any_op
+    %forall, %tiled_generic = transform.structured.tile_using_forall %0 num_threads [4, 2]
+          : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
+    transform.yield
+  }
+}
+
+// -----
+
+#map = affine_map<(d0, d1, d2) -> (d0, d1, d2)>
+#map1 = affine_map<(d0, d1, d2) -> (d1, d2)>
+
+func.func @tile_thread_safety2(%arg0: tensor<100x300x8xf32>, %arg1: tensor<300x8xf32>) -> tensor<300x8xf32> {
+  // expected-warning@below {{tiling is not thread safe at axis #0}}
+  %0 = linalg.generic {indexing_maps = [#map, #map1], iterator_types = ["reduction", "parallel", "parallel"]} ins(%arg0 : tensor<100x300x8xf32>) outs(%arg1 : tensor<300x8xf32>) {
+  ^bb0(%in: f32, %out: f32):
+    %1 = arith.addf %in, %out : f32
+    linalg.yield %1 : f32
+  } -> tensor<300x8xf32>
+  return %0 : tensor<300x8xf32>
+}
+
+module attributes {transform.with_named_sequence} {
+  transform.named_sequence @__transform_main(%arg0: !transform.any_op {transform.readonly}) {
+    %0 = transform.structured.match ops{["linalg.generic"]} in %arg0 : (!transform.any_op) -> !transform.any_op
+    %forall, %tiled_generic = transform.structured.tile_using_forall %0 num_threads [8]
+          : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
+    transform.yield
+  }
+}
+
+// -----
+
+#map = affine_map<(d0, d1, d2) -> (d0, d1, d2)>
+#map1 = affine_map<(d0, d1, d2) -> (d0, d2)>
+
+func.func @tile_thread_safety3(%arg0: tensor<100x300x8xf32>, %arg1: tensor<100x8xf32>) -> tensor<100x8xf32> {
+  // expected-warning@below {{tiling is not thread safe at axis #1}}
+  %0 = linalg.generic {indexing_maps = [#map, #map1], iterator_types = ["parallel", "reduction", "parallel"]} ins(%arg0 : tensor<100x300x8xf32>) outs(%arg1 : tensor<100x8xf32>) {
+  ^bb0(%in: f32, %out: f32):
+    %1 = arith.addf %in, %out : f32
+    linalg.yield %1 : f32
+  } -> tensor<100x8xf32>
+  return %0 : tensor<100x8xf32>
+}
+
+module attributes {transform.with_named_sequence} {
+  transform.named_sequence @__transform_main(%arg0: !transform.any_op {transform.readonly}) {
+    %0 = transform.structured.match ops{["linalg.generic"]} in %arg0 : (!transform.any_op) -> !transform.any_op
+    %forall, %tiled_generic = transform.structured.tile_using_forall %0 num_threads [8, 4, 2]
+          : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
+    transform.yield
+  }
+}
+
+// -----
+
+#map = affine_map<(d0, d1, d2) -> (d0, d1, d2)>
+#map1 = affine_map<(d0, d1, d2) -> (d0, d2)>
+#map2 = affine_map<(d0, d1, d2) -> (d2)>
+
+func.func @tile_thread_safety4(%arg0: tensor<100x300x8xf32>, %arg1: tensor<100x8xf32>, %arg2 : tensor<8xf32>) -> (tensor<100x8xf32>, tensor<8xf32>) {
+  // expected-warning@+2 {{tiling is not thread safe at axis #0}}
+  // expected-warning@below {{tiling is not thread safe at axis #1}}
+  %0:2 = linalg.generic {indexing_maps = [#map, #map1, #map2], iterator_types = ["reduction", "reduction", "parallel"]} ins(%arg0 : tensor<100x300x8xf32>) outs(%arg1, %arg2 : tensor<100x8xf32>, tensor<8xf32>) {
+  ^bb0(%in: f32, %out1: f32, %out2: f32):
+    %1 = arith.addf %in, %out1 : f32
+    %2 = arith.addf %in, %out2 : f32
+    linalg.yield %1, %2 : f32, f32
+  } -> (tensor<100x8xf32>, tensor<8xf32>)
+  return %0#0, %0#1 : tensor<100x8xf32>, tensor<8xf32>
+}
+
+module attributes {transform.with_named_sequence} {
+  transform.named_sequence @__transform_main(%arg0: !transform.any_op {transform.readonly}) {
+    %0 = transform.structured.match ops{["linalg.generic"]} in %arg0 : (!transform.any_op) -> !transform.any_op
+    %forall, %tiled_generic = transform.structured.tile_using_forall %0 num_threads [8, 4, 2]
+          : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
+    transform.yield
+  }
+}
+
+// -----
+
+#map = affine_map<(d0, d1) -> (d0, d1)>
+#map1 = affine_map<(d0, d1) -> (d0)>
+
+func.func @tile_thread_safety5(%arg0: tensor<100x300xf32>, %arg1: tensor<100xf32>) -> tensor<100xf32> {
+  // expected-warning@below {{tiling is not thread safe at axis #1}}
+  %0 = linalg.generic {indexing_maps = [#map, #map1], iterator_types = ["parallel", "reduction"]} ins(%arg0 : tensor<100x300xf32>) outs(%arg1 : tensor<100xf32>) {
+  ^bb0(%in: f32, %out: f32):
+    %1 = arith.addf %in, %out : f32
+    linalg.yield %1 : f32
+  } -> tensor<100xf32>
+  return %0 : tensor<100xf32>
+}
+
+module attributes {transform.with_named_sequence} {
+  transform.named_sequence @__transform_main(%arg0: !transform.any_op {transform.readonly}) {
+    %0 = transform.structured.match ops{["linalg.generic"]} in %arg0 : (!transform.any_op) -> !transform.any_op
+    %forall, %tiled_generic = transform.structured.tile_using_forall %0 tile_sizes [10, 1]
+          : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
+    transform.yield
+  }
+}
+
+// -----
+
+func.func @tile_thread_safety6(%A: tensor<?x?xf32>, %B: tensor<?x?xf32>, %C: tensor<?x?xf32>) -> tensor<?x?xf32> {
+  // expected-warning@below {{tiling is not thread safe at axis #2}}
+  %0 = linalg.matmul ins(%A, %B : tensor<?x?xf32>, tensor<?x?xf32>)
+                    outs(%C : tensor<?x?xf32>) -> (tensor<?x?xf32>)
+  return %0 : tensor<?x?xf32>
+}
+
+module attributes {transform.with_named_sequence} {
+  transform.named_sequence @__transform_main(%arg0: !transform.any_op {transform.readonly}) {
+    %0 = transform.structured.match ops{["linalg.matmul"]} in %arg0 : (!transform.any_op) -> !transform.any_op
+    %forall, %tiled_generic = transform.structured.tile_using_forall %0 num_threads [2, 0, 8]
+          : (!transform.any_op) -> (!transform.any_op, !transform.any_op)
+    transform.yield
+  }
+}