[Mlir-commits] [mlir] 299cc5d - [mlir][Linalg] Further improve codegen strategy and add a linalg.matmul_i8_i8_i32

Nicolas Vasilache llvmlistbot at llvm.org
Thu Jan 28 05:06:37 PST 2021


Author: Nicolas Vasilache
Date: 2021-01-28T13:02:42Z
New Revision: 299cc5da6df6be9f3c81c54e2e952c6d3519f63b

URL: https://github.com/llvm/llvm-project/commit/299cc5da6df6be9f3c81c54e2e952c6d3519f63b
DIFF: https://github.com/llvm/llvm-project/commit/299cc5da6df6be9f3c81c54e2e952c6d3519f63b.diff

LOG: [mlir][Linalg] Further improve codegen strategy and add a linalg.matmul_i8_i8_i32

This revision adds a layer of SFINAE to the composable codegen strategy so it does
not have to require statically defined ops but instead can also be used with OpInterfaces, Operation* and an op name string.

A linalg.matmul_i8_i8_i32 is added to the .tc spec to demonstrate how all this works end to end.

Differential Revision: https://reviews.llvm.org/D95600

Added: 
    mlir/integration_test/Dialect/Linalg/CPU/benchmark_matmul_i8_i8_i32.mlir

Modified: 
    mlir/include/mlir/Dialect/Linalg/IR/LinalgNamedStructuredOpsSpec.tc
    mlir/include/mlir/Dialect/Linalg/Transforms/CodegenStrategy.h
    mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h
    mlir/include/mlir/Dialect/StandardOps/EDSC/Intrinsics.h
    mlir/integration_test/Dialect/Linalg/CPU/benchmark_matmul.mlir
    mlir/integration_test/Dialect/Linalg/CPU/benchmark_matmul_column_major.mlir
    mlir/integration_test/Dialect/Linalg/CPU/benchmark_matmul_column_major_as_row_major.mlir
    mlir/lib/Dialect/Linalg/Transforms/CodegenStrategy.cpp
    mlir/lib/Dialect/Linalg/Transforms/Generalization.cpp
    mlir/lib/Dialect/Linalg/Transforms/Tiling.cpp
    mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp
    mlir/lib/Dialect/Linalg/Transforms/Vectorization.cpp
    mlir/test/lib/Transforms/TestLinalgCodegenStrategy.cpp
    mlir/test/lib/Transforms/TestLinalgFusionTransforms.cpp
    mlir/test/lib/Transforms/TestLinalgTransforms.cpp

Removed: 
    


################################################################################
diff  --git a/mlir/include/mlir/Dialect/Linalg/IR/LinalgNamedStructuredOpsSpec.tc b/mlir/include/mlir/Dialect/Linalg/IR/LinalgNamedStructuredOpsSpec.tc
index e6d1e1935367..fc09243b46fe 100644
--- a/mlir/include/mlir/Dialect/Linalg/IR/LinalgNamedStructuredOpsSpec.tc
+++ b/mlir/include/mlir/Dialect/Linalg/IR/LinalgNamedStructuredOpsSpec.tc
@@ -8,6 +8,13 @@ def matmul_column_major(A: f32(K, M), B: f32(N, K)) -> (C: f32(N, M)) {
   C(n, m) = std_addf<k>(std_mulf(A(k, m), B(n, k)));
 }
 
+ods_def<MatmulI8I8I32Op>:
+def matmul_i8_i8_i32(A: i8(M, K), B: i8(K, N)) -> (C: i32(M, N)) {
+  // TODO: ideally something closer to
+  //   C(m, n) += cast<i32>(A(m, k)) * cast<i32>(B(k, n))
+  C(m, n) = std_addi<k>(std_sexti32(std_muli(A(m, k), B(k, n))));
+}
+
 ods_def<MatvecOp>:
 def matvec(A: f32(M, N), y: f32(N)) -> (x: f32(M)) {
   x(m) = std_addf<n>(std_mulf(A(m, n), y(n)));

diff  --git a/mlir/include/mlir/Dialect/Linalg/Transforms/CodegenStrategy.h b/mlir/include/mlir/Dialect/Linalg/Transforms/CodegenStrategy.h
index 25a98e3187e1..21bad4acec7c 100644
--- a/mlir/include/mlir/Dialect/Linalg/Transforms/CodegenStrategy.h
+++ b/mlir/include/mlir/Dialect/Linalg/Transforms/CodegenStrategy.h
@@ -21,27 +21,63 @@ namespace linalg {
 /// Abstract Transformation class applied in a sequence that also handles state
 /// through markers.
 struct Transformation {
+  explicit Transformation(linalg::LinalgTransformationFilter::FilterFunction f)
+      : filter(f) {}
   virtual ~Transformation() = default;
   virtual OwningRewritePatternList
-  buildRewritePatterns(MLIRContext *context, linalg::LinalgMarker m) = 0;
-  linalg::LinalgMarker marker;
+  buildRewritePatterns(MLIRContext *context,
+                       linalg::LinalgTransformationFilter m) = 0;
+  linalg::LinalgTransformationFilter::FilterFunction filter = nullptr;
 };
 
+/// SFINAE: Enqueue helper for ConcreteOpType that have a `getOperationName`.
+template <template <typename> class PatternType, typename ConcreteOpType,
+          typename OptionsType,
+          typename std::enable_if<std::is_member_function_pointer<
+              decltype(&ConcreteOpType::getOperationName)>::value>>
+void sfinae_enqueue(OwningRewritePatternList &patterList, OptionsType options,
+                    MLIRContext *context, StringRef opName,
+                    linalg::LinalgTransformationFilter m) {
+  assert(opName.empty() ||
+         opName == ConcreteOpType::getOperationName() &&
+             "explicit name must match ConcreteOpType::getOperationName");
+  patterList.insert<PatternType<ConcreteOpType>>(context, options, m);
+}
+
+/// SFINAE: Enqueue helper for OpType that do not have a `getOperationName`
+/// (e.g. LinalgOp, other interfaces, Operation*).
+template <template <typename> class PatternType, typename OpType,
+          typename OptionsType>
+void sfinae_enqueue(OwningRewritePatternList &patterList, OptionsType options,
+                    MLIRContext *context, StringRef opName,
+                    linalg::LinalgTransformationFilter m) {
+  assert(!opName.empty() && "opName must not be empty");
+  patterList.insert<PatternType<OpType>>(opName, context, options, m);
+}
+
 /// Promotion transformation enqueues a particular stage-1 pattern for
 /// `Tile<LinalgOpType>`with the appropriate `options`.
 template <typename LinalgOpType>
 struct Tile : public Transformation {
-  explicit Tile(linalg::LinalgTilingOptions options) : options(options) {}
+  explicit Tile(linalg::LinalgTilingOptions options,
+                linalg::LinalgTransformationFilter::FilterFunction f = nullptr)
+      : Transformation(f), opName(""), options(options) {}
+
+  Tile(StringRef name, linalg::LinalgTilingOptions options,
+       linalg::LinalgTransformationFilter::FilterFunction f = nullptr)
+      : Transformation(f), opName(name), options(options) {}
 
   OwningRewritePatternList
-  buildRewritePatterns(MLIRContext *context, linalg::LinalgMarker m) override {
+  buildRewritePatterns(MLIRContext *context,
+                       linalg::LinalgTransformationFilter m) override {
     OwningRewritePatternList tilingPatterns;
-    tilingPatterns.insert<linalg::LinalgTilingPattern<LinalgOpType>>(
-        context, options, m);
+    sfinae_enqueue<linalg::LinalgTilingPattern, LinalgOpType>(
+        tilingPatterns, options, context, opName, m);
     return tilingPatterns;
   }
 
 private:
+  std::string opName;
   linalg::LinalgTilingOptions options;
 };
 
@@ -49,17 +85,26 @@ struct Tile : public Transformation {
 /// `Promote<LinalgOpType>`with the appropriate `options`.
 template <typename LinalgOpType>
 struct Promote : public Transformation {
-  explicit Promote(linalg::LinalgPromotionOptions options) : options(options) {}
+  explicit Promote(
+      linalg::LinalgPromotionOptions options,
+      linalg::LinalgTransformationFilter::FilterFunction f = nullptr)
+      : Transformation(f), opName(""), options(options) {}
+
+  Promote(StringRef name, linalg::LinalgPromotionOptions options,
+          linalg::LinalgTransformationFilter::FilterFunction f = nullptr)
+      : Transformation(f), opName(name), options(options) {}
 
   OwningRewritePatternList
-  buildRewritePatterns(MLIRContext *context, linalg::LinalgMarker m) override {
+  buildRewritePatterns(MLIRContext *context,
+                       linalg::LinalgTransformationFilter m) override {
     OwningRewritePatternList promotionPatterns;
-    promotionPatterns.insert<linalg::LinalgPromotionPattern<LinalgOpType>>(
-        context, options, m);
+    sfinae_enqueue<linalg::LinalgPromotionPattern, LinalgOpType>(
+        promotionPatterns, options, context, opName, m);
     return promotionPatterns;
   }
 
 private:
+  std::string opName;
   linalg::LinalgPromotionOptions options;
 };
 
@@ -68,25 +113,36 @@ struct Promote : public Transformation {
 /// transfer rewrite forwarding patterns.
 template <typename LinalgOpType>
 struct Vectorize : public Transformation {
+  explicit Vectorize(
+      linalg::LinalgVectorizationOptions options,
+      linalg::LinalgTransformationFilter::FilterFunction f = nullptr)
+      : Transformation(f), opName(""), options(options) {}
+
+  Vectorize(StringRef name, linalg::LinalgVectorizationOptions options,
+            linalg::LinalgTransformationFilter::FilterFunction f = nullptr)
+      : Transformation(f), opName(name), options(options) {}
+
   OwningRewritePatternList
-  buildRewritePatterns(MLIRContext *context, linalg::LinalgMarker m) override {
+  buildRewritePatterns(MLIRContext *context,
+                       linalg::LinalgTransformationFilter m) override {
     OwningRewritePatternList vectorizationPatterns;
-    // FillOp may interfere with forwarding patterns atm, so we bump up the
-    // priority of LinalgCopyVTRForwardingPattern /
-    // LinalgCopyVTWForwardingPattern.
-    vectorizationPatterns
-        .insert<linalg::LinalgVectorizationPattern<LinalgOpType>>(context, m);
+    sfinae_enqueue<linalg::LinalgVectorizationPattern, LinalgOpType>(
+        vectorizationPatterns, options, context, opName, m);
     vectorizationPatterns.insert<linalg::LinalgCopyVTRForwardingPattern,
                                  linalg::LinalgCopyVTWForwardingPattern>(
         context, /*benefit=*/2);
     return vectorizationPatterns;
   }
+
+private:
+  std::string opName;
+  linalg::LinalgVectorizationOptions options;
 };
 
 /// Codegen strategy controls how a Linalg op is progressively lowered.
 /// The application uses a 3-level staged patterns strategy which allows
-/// ordering transformations by using the Linalg `applyStagedPatterns` function,
-/// where:
+/// ordering transformations by using the Linalg `applyStagedPatterns`
+/// function, where:
 ///   1. The first stage consists of the successive `tile`, `promote` and
 ///   `vectorize` patterns, applied sequentially.
 ///   2. The second stage consists of common local canonicalization patterns
@@ -97,41 +153,112 @@ struct CodegenStrategy {
   /// Append a pattern to add a level of tiling for `LinalgOpType` with tiling
   /// `options`.
   template <typename LinalgOpType>
-  CodegenStrategy &tile(linalg::LinalgTilingOptions options) {
-    transformationSequence.emplace_back(new Tile<LinalgOpType>(options));
+  CodegenStrategy &
+  tile(linalg::LinalgTilingOptions options,
+       linalg::LinalgTransformationFilter::FilterFunction f = nullptr) {
+    transformationSequence.emplace_back(
+        std::make_unique<Tile<LinalgOpType>>(options, f));
+    return *this;
+  }
+  /// Append a pattern to add a level of tiling for `LinalgOpType` with tiling
+  /// `options`.
+  template <typename LinalgOpType>
+  CodegenStrategy &
+  tile(StringRef opName, linalg::LinalgTilingOptions options,
+       linalg::LinalgTransformationFilter::FilterFunction f = nullptr) {
+    transformationSequence.emplace_back(
+        std::make_unique<Tile<LinalgOpType>>(opName, options, f));
     return *this;
   }
-  /// Conditionally append a pattern to add a level of tiling for `LinalgOpType`
-  /// with tiling `options`.
+  /// Conditionally append a pattern to add a level of tiling for
+  /// `LinalgOpType` with tiling `options`.
   template <typename LinalgOpType>
-  CodegenStrategy &tileIf(bool b, linalg::LinalgTilingOptions options) {
+  CodegenStrategy &
+  tileIf(bool b, linalg::LinalgTilingOptions options,
+         linalg::LinalgTransformationFilter::FilterFunction f = nullptr) {
     return b ? tile<LinalgOpType>(options) : *this;
   }
+  /// Conditionally append a pattern to add a level of tiling for
+  /// `LinalgOpType` with tiling `options`.
+  template <typename LinalgOpType>
+  CodegenStrategy &
+  tileIf(bool b, StringRef opName, linalg::LinalgTilingOptions options,
+         linalg::LinalgTransformationFilter::FilterFunction f = nullptr) {
+    return b ? tile<LinalgOpType>(opName, options) : *this;
+  }
+  /// Append a pattern to add a level of promotion for `LinalgOpType` with
+  /// promotion `options`.
+  template <typename LinalgOpType>
+  CodegenStrategy &
+  promote(linalg::LinalgPromotionOptions options,
+          linalg::LinalgTransformationFilter::FilterFunction f = nullptr) {
+    transformationSequence.emplace_back(
+        std::make_unique<Promote<LinalgOpType>>(options, f));
+    return *this;
+  }
   /// Append a pattern to add a level of promotion for `LinalgOpType` with
   /// promotion `options`.
   template <typename LinalgOpType>
-  CodegenStrategy &promote(linalg::LinalgPromotionOptions options) {
-    transformationSequence.emplace_back(new Promote<LinalgOpType>(options));
+  CodegenStrategy &
+  promote(StringRef opName, linalg::LinalgPromotionOptions options,
+          linalg::LinalgTransformationFilter::FilterFunction f = nullptr) {
+    transformationSequence.emplace_back(
+        std::make_unique<Promote<LinalgOpType>>(opName, options, f));
+    return *this;
+  }
+  /// Conditionally append a pattern to add a level of promotion for
+  /// `LinalgOpType` with promotion `options`.
+  template <typename LinalgOpType>
+  CodegenStrategy &
+  promoteIf(bool b, StringRef opName, linalg::LinalgPromotionOptions options,
+            linalg::LinalgTransformationFilter::FilterFunction f = nullptr) {
+    return b ? promote<LinalgOpType>(opName, options, f) : *this;
     return *this;
   }
   /// Conditionally append a pattern to add a level of promotion for
   /// `LinalgOpType` with promotion `options`.
   template <typename LinalgOpType>
-  CodegenStrategy &promoteIf(bool b, linalg::LinalgPromotionOptions options) {
-    return b ? promote<LinalgOpType>(options) : *this;
+  CodegenStrategy &
+  promoteIf(bool b, linalg::LinalgPromotionOptions options,
+            linalg::LinalgTransformationFilter::FilterFunction f = nullptr) {
+    return b ? promote<LinalgOpType>(options, f) : *this;
+    return *this;
+  }
+  /// Append a pattern to rewrite `LinalgOpType` as a vector operation.
+  template <typename LinalgOpType>
+  CodegenStrategy &
+  vectorize(linalg::LinalgTransformationFilter::FilterFunction f = nullptr) {
+    transformationSequence.emplace_back(
+        std::make_unique<Vectorize<LinalgOpType>>(
+            linalg::LinalgVectorizationOptions(), f));
     return *this;
   }
   /// Append a pattern to rewrite `LinalgOpType` as a vector operation.
   template <typename LinalgOpType>
-  CodegenStrategy &vectorize() {
-    transformationSequence.emplace_back(new Vectorize<LinalgOpType>());
+  CodegenStrategy &
+  vectorize(StringRef opName,
+            linalg::LinalgTransformationFilter::FilterFunction f = nullptr) {
+    transformationSequence.emplace_back(
+        std::make_unique<Vectorize<LinalgOpType>>(
+            opName, linalg::LinalgVectorizationOptions(), f));
+    return *this;
+  }
+  /// Conditionally append a pattern to rewrite `LinalgOpType` as a vector
+  /// operation.
+  template <typename LinalgOpType>
+  CodegenStrategy &
+  vectorizeIf(bool b,
+              linalg::LinalgTransformationFilter::FilterFunction f = nullptr) {
+    return b ? vectorize<LinalgOpType>(f) : *this;
     return *this;
   }
   /// Conditionally append a pattern to rewrite `LinalgOpType` as a vector
   /// operation.
   template <typename LinalgOpType>
-  CodegenStrategy &vectorizeIf(bool b) {
-    return b ? vectorize<LinalgOpType>() : *this;
+  CodegenStrategy &
+  vectorizeIf(bool b, StringRef opName,
+              linalg::LinalgTransformationFilter::FilterFunction f = nullptr) {
+    return b ? vectorize<LinalgOpType>(opName, f) : *this;
     return *this;
   }
   /// Configure the post staged-patterns late vector transformations.
@@ -140,15 +267,22 @@ struct CodegenStrategy {
     vectorTransformsOptions = options;
     return *this;
   }
-  /// Configure the post staged-patterns late vector.transfer to scf conversion.
+  /// Configure the post staged-patterns late vector.transfer to scf
+  /// conversion.
   CodegenStrategy &
   setVectorTransferToSCFOptions(VectorTransferToSCFOptions options) {
     vectorToSCFOptions = options;
     return *this;
   }
+  /// Configure the post staged-patterns late vector.transfer to scf
+  /// conversion.
+  CodegenStrategy &setHoistInvariantCode(bool enableLICM) {
+    this->enableLICM = enableLICM;
+    return *this;
+  }
 
-  /// Apply the transformation patterns in sequence with cleanup transformations
-  /// interleaved.
+  /// Apply the transformation patterns in sequence with cleanup
+  /// transformations interleaved.
   void transform(FuncOp func) const;
 
 private:
@@ -157,6 +291,7 @@ struct CodegenStrategy {
   vector::VectorTransformsOptions vectorTransformsOptions;
   VectorTransferToSCFOptions vectorToSCFOptions;
   SmallVector<std::unique_ptr<Transformation>, 4> transformationSequence;
+  bool enableLICM = true;
 };
 
 } // namespace linalg

diff  --git a/mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h b/mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h
index f359992e5ff1..18cb91e3200a 100644
--- a/mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h
+++ b/mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h
@@ -316,16 +316,32 @@ struct LinalgTransforms {
   static const StringLiteral kLinalgTransformMarker;
 };
 
-/// Helper class to control common attribute matching and setting behavior.
-struct LinalgMarker {
-  explicit LinalgMarker(ArrayRef<Identifier> matchDisjunction = {},
-                        Optional<Identifier> replacement = None);
-  LinalgMarker(LinalgMarker &&) = default;
-  LinalgMarker(const LinalgMarker &) = default;
+/// Helper class to control application of linalg transformation patterns.
+/// Control comes in 2 forms:
+///   1. attribute matching and setting behavior using the attribute named
+///      `kLinalgTransformMarker`. This can be used to build a state machine
+///      using attributes and incrementally applying patterns to advance states.
+///   2. filter function, which is a simple lambda on the Operation* that
+///      returns a LogicalResult.
+struct LinalgTransformationFilter {
+  using FilterFunction = std::function<LogicalResult(Operation *)>;
+
+  explicit LinalgTransformationFilter(
+      ArrayRef<Identifier> matchDisjunction = {},
+      Optional<Identifier> replacement = None);
+
+  explicit LinalgTransformationFilter(
+      FilterFunction f, ArrayRef<Identifier> matchDisjunction = {},
+      Optional<Identifier> replacement = None);
+
+  LinalgTransformationFilter(LinalgTransformationFilter &&) = default;
+  LinalgTransformationFilter(const LinalgTransformationFilter &) = default;
   LogicalResult checkAndNotify(PatternRewriter &rewriter, Operation *op) const;
-  void replaceLinalgMarker(PatternRewriter &rewriter, Operation *op) const;
+  void replaceLinalgTransformationFilter(PatternRewriter &rewriter,
+                                         Operation *op) const;
 
 private:
+  FilterFunction filter;
   SmallVector<Identifier, 4> matchDisjunction;
   Optional<Identifier> replacement;
 };
@@ -425,31 +441,44 @@ void populateLinalgTilingCanonicalizationPatterns(
 ///      and some operand shape cannot be bounded statically.
 struct LinalgBaseTilingPattern : public RewritePattern {
   // Entry point to match any LinalgOp OpInterface.
-  LinalgBaseTilingPattern(LinalgTilingOptions options,
-                          LinalgMarker marker = LinalgMarker(),
-                          PatternBenefit benefit = 1);
+  LinalgBaseTilingPattern(
+      LinalgTilingOptions options,
+      LinalgTransformationFilter marker = LinalgTransformationFilter(),
+      PatternBenefit benefit = 1);
   // Entry point to match a specific Linalg op.
-  LinalgBaseTilingPattern(StringRef opName, MLIRContext *context,
-                          LinalgTilingOptions options,
-                          LinalgMarker marker = LinalgMarker(),
-                          PatternBenefit benefit = 1);
+  LinalgBaseTilingPattern(
+      StringRef opName, MLIRContext *context, LinalgTilingOptions options,
+      LinalgTransformationFilter marker = LinalgTransformationFilter(),
+      PatternBenefit benefit = 1);
   LogicalResult matchAndRewriteBase(Operation *op, PatternRewriter &rewriter,
                                     TiledLinalgOp &result) const;
 
 private:
   /// LinalgTransformMarker handles special attribute manipulations.
-  LinalgMarker marker;
+  LinalgTransformationFilter marker;
   /// Options to control tiling;
   LinalgTilingOptions options;
 };
 
 template <typename OpTy>
 struct LinalgTilingPattern : public LinalgBaseTilingPattern {
-  LinalgTilingPattern(MLIRContext *context, LinalgTilingOptions options,
-                      LinalgMarker marker = LinalgMarker(),
-                      PatternBenefit benefit = 1)
-      : LinalgBaseTilingPattern(OpTy::getOperationName(), context, options,
-                                marker, benefit) {}
+  /// SFINAE: This constructor can only trigger for concrete ops that have a
+  /// static `getOperationName` method.
+  template <typename ConcreateOpTy = OpTy>
+  LinalgTilingPattern(
+      MLIRContext *context, LinalgTilingOptions options,
+      LinalgTransformationFilter marker = LinalgTransformationFilter(),
+      PatternBenefit benefit = 1)
+      : LinalgBaseTilingPattern(ConcreateOpTy::getOperationName(), context,
+                                options, marker, benefit) {}
+
+  /// This constructor is available to anyone.
+  LinalgTilingPattern(
+      StringRef opName, MLIRContext *context, LinalgTilingOptions options,
+      LinalgTransformationFilter marker = LinalgTransformationFilter(),
+      PatternBenefit benefit = 1)
+      : LinalgBaseTilingPattern(opName, context, options, marker, benefit) {}
+
   LogicalResult matchAndRewrite(Operation *op,
                                 PatternRewriter &rewriter) const override {
     TiledLinalgOp tiledLinalgOp;
@@ -474,14 +503,15 @@ struct LinalgFusionOptions {
 };
 
 struct LinalgBaseTileAndFusePattern : public RewritePattern {
-  LinalgBaseTileAndFusePattern(StringRef opName, MLIRContext *context,
-                               const LinalgDependenceGraph &dependenceGraph,
-                               LinalgTilingOptions tilingOptions,
-                               LinalgFusionOptions fusionOptions,
-                               LinalgMarker marker = LinalgMarker(),
-                               LinalgMarker fusedOpMarker = LinalgMarker(),
-                               LinalgMarker originalOpMarker = LinalgMarker(),
-                               PatternBenefit benefit = 1);
+  LinalgBaseTileAndFusePattern(
+      StringRef opName, MLIRContext *context,
+      const LinalgDependenceGraph &dependenceGraph,
+      LinalgTilingOptions tilingOptions, LinalgFusionOptions fusionOptions,
+      LinalgTransformationFilter marker = LinalgTransformationFilter(),
+      LinalgTransformationFilter fusedOpMarker = LinalgTransformationFilter(),
+      LinalgTransformationFilter originalOpMarker =
+          LinalgTransformationFilter(),
+      PatternBenefit benefit = 1);
   LogicalResult matchAndRewrite(Operation *op,
                                 PatternRewriter &rewriter) const override;
 
@@ -493,27 +523,27 @@ struct LinalgBaseTileAndFusePattern : public RewritePattern {
   /// Options to control fusion.
   LinalgFusionOptions fusionOptions;
   /// Marker to control application of the pattern.
-  LinalgMarker marker;
+  LinalgTransformationFilter marker;
   /// Marker set on the fused op after tile and fuse.
-  LinalgMarker fusedOpMarker;
+  LinalgTransformationFilter fusedOpMarker;
   /// The dependenceGraph is not modifiable, i.e. if the Linalg operations used
   /// to build the dependence graph changes then the dependenceGraph needs to be
   /// recomputed right now. To not invalidate the dependenceGraph as
   /// transformation happens, the original producer can be tagged with a marker
   /// that can be later used to delete the original operations.
-  LinalgMarker originalOpMarker;
+  LinalgTransformationFilter originalOpMarker;
 };
 
 template <typename OpTy>
 struct LinalgTileAndFusePattern : public LinalgBaseTileAndFusePattern {
-  LinalgTileAndFusePattern(MLIRContext *context,
-                           const LinalgDependenceGraph &dependenceGraph,
-                           LinalgTilingOptions tilingOptions,
-                           LinalgFusionOptions fusionOptions,
-                           LinalgMarker marker = LinalgMarker(),
-                           LinalgMarker fusedOpMarker = LinalgMarker(),
-                           LinalgMarker originalOpMarker = LinalgMarker(),
-                           PatternBenefit benefit = 1)
+  LinalgTileAndFusePattern(
+      MLIRContext *context, const LinalgDependenceGraph &dependenceGraph,
+      LinalgTilingOptions tilingOptions, LinalgFusionOptions fusionOptions,
+      LinalgTransformationFilter marker = LinalgTransformationFilter(),
+      LinalgTransformationFilter fusedOpMarker = LinalgTransformationFilter(),
+      LinalgTransformationFilter originalOpMarker =
+          LinalgTransformationFilter(),
+      PatternBenefit benefit = 1)
       : LinalgBaseTileAndFusePattern(
             OpTy::getOperationName(), context, dependenceGraph, tilingOptions,
             fusionOptions, marker, fusedOpMarker, originalOpMarker, benefit) {}
@@ -526,26 +556,27 @@ struct LinalgTileAndFusePattern : public LinalgBaseTileAndFusePattern {
 /// `marker` controls LinalgTransformMarker matching and update when specified.
 /// See `interchange` for more details.
 struct LinalgBaseInterchangePattern : public RewritePattern {
-  LinalgBaseInterchangePattern(StringRef opName, MLIRContext *context,
-                               ArrayRef<unsigned> interchangeVector,
-                               LinalgMarker marker = LinalgMarker(),
-                               PatternBenefit benefit = 1);
+  LinalgBaseInterchangePattern(
+      StringRef opName, MLIRContext *context,
+      ArrayRef<unsigned> interchangeVector,
+      LinalgTransformationFilter marker = LinalgTransformationFilter(),
+      PatternBenefit benefit = 1);
   LogicalResult matchAndRewrite(Operation *op,
                                 PatternRewriter &rewriter) const override;
 
 private:
   /// LinalgTransformMarker handles special attribute manipulations.
-  LinalgMarker marker;
+  LinalgTransformationFilter marker;
   /// The interchange vector to reorder the iterators and indexing_maps dims.
   SmallVector<unsigned, 8> interchangeVector;
 };
 
 template <typename OpTy>
 struct LinalgInterchangePattern : public LinalgBaseInterchangePattern {
-  LinalgInterchangePattern(MLIRContext *context,
-                           ArrayRef<unsigned> interchangeVector,
-                           LinalgMarker marker = LinalgMarker(),
-                           PatternBenefit benefit = 1)
+  LinalgInterchangePattern(
+      MLIRContext *context, ArrayRef<unsigned> interchangeVector,
+      LinalgTransformationFilter marker = LinalgTransformationFilter(),
+      PatternBenefit benefit = 1)
       : LinalgBaseInterchangePattern(OpTy::getOperationName(), context,
                                      interchangeVector, marker, benefit) {}
 };
@@ -557,27 +588,38 @@ struct LinalgInterchangePattern : public LinalgBaseInterchangePattern {
 /// `marker` controls LinalgTransformMarker matching and update when specified.
 /// See `promoteSubViews` for more details.
 struct LinalgBasePromotionPattern : public RewritePattern {
-  LinalgBasePromotionPattern(StringRef opName, MLIRContext *context,
-                             LinalgPromotionOptions options,
-                             LinalgMarker marker = LinalgMarker(),
-                             PatternBenefit benefit = 1);
+  LinalgBasePromotionPattern(
+      StringRef opName, MLIRContext *context, LinalgPromotionOptions options,
+      LinalgTransformationFilter marker = LinalgTransformationFilter(),
+      PatternBenefit benefit = 1);
+
   LogicalResult matchAndRewrite(Operation *op,
                                 PatternRewriter &rewriter) const override;
 
 private:
   /// LinalgTransformMarker handles special attribute manipulations.
-  LinalgMarker marker;
+  LinalgTransformationFilter marker;
   /// Promotion options.
   LinalgPromotionOptions options;
 };
 
 template <typename OpTy>
 struct LinalgPromotionPattern : public LinalgBasePromotionPattern {
-  LinalgPromotionPattern(MLIRContext *context, LinalgPromotionOptions options,
-                         LinalgMarker marker = LinalgMarker(),
-                         PatternBenefit benefit = 1)
+  /// SFINAE: This constructor can only trigger for concrete ops that have a
+  /// static `getOperationName` method.
+  template <typename ConcreateOpTy = OpTy>
+  LinalgPromotionPattern(
+      MLIRContext *context, LinalgPromotionOptions options,
+      LinalgTransformationFilter marker = LinalgTransformationFilter(),
+      PatternBenefit benefit = 1)
       : LinalgBasePromotionPattern(OpTy::getOperationName(), context, options,
                                    marker, benefit) {}
+  /// This constructor is available to anyone.
+  LinalgPromotionPattern(
+      StringRef opName, MLIRContext *context, LinalgPromotionOptions options,
+      LinalgTransformationFilter marker = LinalgTransformationFilter(),
+      PatternBenefit benefit = 1)
+      : LinalgBasePromotionPattern(opName, context, options, marker, benefit) {}
 };
 
 ///
@@ -586,25 +628,42 @@ struct LinalgPromotionPattern : public LinalgBasePromotionPattern {
 /// Apply the `vectorizeLinalgOp` transformation as a pattern.
 /// `marker` controls LinalgTransformMarker matching and update when specified.
 /// See `vectorizeLinalgOp` for more details.
+
+/// Empty for now, used for SFINAE purposes only.
+struct LinalgVectorizationOptions {};
+
 struct LinalgBaseVectorizationPattern : public RewritePattern {
-  LinalgBaseVectorizationPattern(StringRef opName, MLIRContext *context,
-                                 LinalgMarker marker = LinalgMarker(),
-                                 PatternBenefit benefit = 1);
+  LinalgBaseVectorizationPattern(
+      StringRef opName, MLIRContext *context,
+      LinalgTransformationFilter marker = LinalgTransformationFilter(),
+      PatternBenefit benefit = 1);
   LogicalResult matchAndRewrite(Operation *op,
                                 PatternRewriter &rewriter) const override;
 
 private:
   /// LinalgTransformMarker handles special attribute manipulations.
-  LinalgMarker marker;
+  LinalgTransformationFilter marker;
 };
 
 template <typename OpTy>
 struct LinalgVectorizationPattern : public LinalgBaseVectorizationPattern {
-  LinalgVectorizationPattern(MLIRContext *context,
-                             LinalgMarker marker = LinalgMarker(),
-                             PatternBenefit benefit = 1)
+  /// SFINAE: This constructor can only trigger for concrete ops that have a
+  /// static `getOperationName` method.
+  template <typename ConcreateOpTy = OpTy>
+  LinalgVectorizationPattern(
+      MLIRContext *context,
+      LinalgVectorizationOptions options = LinalgVectorizationOptions(),
+      LinalgTransformationFilter marker = LinalgTransformationFilter(),
+      PatternBenefit benefit = 1)
       : LinalgBaseVectorizationPattern(OpTy::getOperationName(), context,
                                        marker, benefit) {}
+  /// This constructor is available to anyone.
+  LinalgVectorizationPattern(
+      StringRef opName, MLIRContext *context,
+      LinalgVectorizationOptions options = LinalgVectorizationOptions(),
+      LinalgTransformationFilter marker = LinalgTransformationFilter(),
+      PatternBenefit benefit = 1)
+      : LinalgBaseVectorizationPattern(opName, context, marker, benefit) {}
 };
 
 ///
@@ -622,10 +681,10 @@ enum class LinalgLoweringType {
 
 template <typename OpTy>
 struct LinalgLoweringPattern : public RewritePattern {
-  LinalgLoweringPattern(MLIRContext *context, LinalgLoweringType loweringType,
-                        LinalgMarker marker = LinalgMarker(),
-                        ArrayRef<unsigned> interchangeVector = {},
-                        PatternBenefit benefit = 1)
+  LinalgLoweringPattern(
+      MLIRContext *context, LinalgLoweringType loweringType,
+      LinalgTransformationFilter marker = LinalgTransformationFilter(),
+      ArrayRef<unsigned> interchangeVector = {}, PatternBenefit benefit = 1)
       : RewritePattern(OpTy::getOperationName(), {}, benefit, context),
         marker(marker), loweringType(loweringType),
         interchangeVector(interchangeVector.begin(), interchangeVector.end()) {}
@@ -663,7 +722,7 @@ struct LinalgLoweringPattern : public RewritePattern {
 
 private:
   /// LinalgTransformMarker handles special attribute manipulations.
-  LinalgMarker marker;
+  LinalgTransformationFilter marker;
   /// Controls whether the pattern lowers to library calls, scf.for, affine.for
   /// or scf.parallel.
   LinalgLoweringType loweringType;
@@ -677,13 +736,13 @@ struct LinalgLoweringPattern : public RewritePattern {
 /// linalg.generic ops.
 void populateLinalgNamedOpsGeneralizationPatterns(
     MLIRContext *context, OwningRewritePatternList &patterns,
-    LinalgMarker marker = LinalgMarker());
+    LinalgTransformationFilter marker = LinalgTransformationFilter());
 
 /// Populates `patterns` with patterns to convert linalg.conv ops to
 /// linalg.generic ops.
 void populateLinalgConvGeneralizationPatterns(
     MLIRContext *context, OwningRewritePatternList &patterns,
-    LinalgMarker marker = LinalgMarker());
+    LinalgTransformationFilter marker = LinalgTransformationFilter());
 
 //===----------------------------------------------------------------------===//
 // Op-specific patterns.

diff  --git a/mlir/include/mlir/Dialect/StandardOps/EDSC/Intrinsics.h b/mlir/include/mlir/Dialect/StandardOps/EDSC/Intrinsics.h
index 5d4668d7b5fc..ae5d5ad357f5 100644
--- a/mlir/include/mlir/Dialect/StandardOps/EDSC/Intrinsics.h
+++ b/mlir/include/mlir/Dialect/StandardOps/EDSC/Intrinsics.h
@@ -38,6 +38,7 @@ using std_ret = OperationBuilder<ReturnOp>;
 using std_rsqrt = ValueBuilder<RsqrtOp>;
 using std_select = ValueBuilder<SelectOp>;
 using std_load = ValueBuilder<LoadOp>;
+using std_sign_extendi = ValueBuilder<SignExtendIOp>;
 using std_splat = ValueBuilder<SplatOp>;
 using std_store = OperationBuilder<StoreOp>;
 using std_subf = ValueBuilder<SubFOp>;
@@ -48,9 +49,19 @@ using std_tensor_load = ValueBuilder<TensorLoadOp>;
 using std_tensor_store = OperationBuilder<TensorStoreOp>;
 using std_view = ValueBuilder<ViewOp>;
 using std_zero_extendi = ValueBuilder<ZeroExtendIOp>;
-using std_sign_extendi = ValueBuilder<SignExtendIOp>;
 using tensor_extract = ValueBuilder<tensor::ExtractOp>;
 
+template <int N>
+struct SExtiValueBuilder : public ValueBuilder<SignExtendIOp> {
+  using ValueBuilder<SignExtendIOp>::ValueBuilder;
+  template <typename... Args>
+  SExtiValueBuilder(Args... args)
+      : ValueBuilder<SignExtendIOp>(ScopedContext::getBuilderRef().getI32Type(),
+                                    args...) {}
+};
+
+using std_sexti32 = SExtiValueBuilder<32>;
+
 /// Branches into `block` with `operands`.
 BranchOp std_br(Block *block, ValueRange operands);
 

diff  --git a/mlir/integration_test/Dialect/Linalg/CPU/benchmark_matmul.mlir b/mlir/integration_test/Dialect/Linalg/CPU/benchmark_matmul.mlir
index 3c589d163857..3e7560ef0867 100644
--- a/mlir/integration_test/Dialect/Linalg/CPU/benchmark_matmul.mlir
+++ b/mlir/integration_test/Dialect/Linalg/CPU/benchmark_matmul.mlir
@@ -14,9 +14,12 @@
 // RUN: tee -a /dev/stderr | FileCheck %s
 
 
-!row_major_A = type memref<${M}x${K}xf32>
-!row_major_B = type memref<${K}x${N}xf32>
-!row_major_C = type memref<${M}x${N}xf32>
+!elem_type_a = type f32
+!elem_type_b = type f32
+!elem_type_c = type f32
+!row_major_A = type memref<${M}x${K}x!elem_type_a>
+!row_major_B = type memref<${K}x${N}x!elem_type_b>
+!row_major_C = type memref<${M}x${N}x!elem_type_c>
 
 func @matmul(%a: !row_major_A, %b: !row_major_B, %c: !row_major_C)
 // TODO: activate manually for now.
@@ -48,16 +51,16 @@ func @print_perf(%iters: index, %total_time: f64) {
 }
 
 func @main() {
-  %f0 = constant 0.0 : f32
-  %f1 = constant 1.0 : f32
+  %v0 = constant 0.0 : !elem_type_a
+  %v1 = constant 1.0 : !elem_type_a
 
   %A = alloc() : !row_major_A
   %B = alloc() : !row_major_B
   %C = alloc() : !row_major_C
 
-  linalg.fill(%A, %f1) : !row_major_A, f32
-  linalg.fill(%B, %f1) : !row_major_B, f32
-  linalg.fill(%C, %f0) : !row_major_C, f32
+  linalg.fill(%A, %v1) : !row_major_A, !elem_type_a
+  linalg.fill(%B, %v1) : !row_major_B, !elem_type_b
+  linalg.fill(%C, %v0) : !row_major_C, !elem_type_c
 
   %c0 = constant 0: index
   %c1 = constant 1: index
@@ -66,7 +69,8 @@ func @main() {
   /// Run and dump performance for matmul.
   /// Preheating run:
   scf.for %arg0 = %c0 to %iters step %c1 {
-    linalg.fill(%C, %f0) : !row_major_C, f32
+    %z = constant 0.0 : !elem_type_c
+    linalg.fill(%C, %z) : !row_major_C, !elem_type_c
     call @matmul(%A, %B, %C) : (!row_major_A, !row_major_B, !row_major_C) -> ()
   }
   %t_start_matmul = call @rtclock() : () -> f64
@@ -75,7 +79,8 @@ func @main() {
     // This is accounts for about 10-15% perf hit on small sizes.
     // Once linalg on tensors is ready, fusing fill at teh register level will
     // be easy.
-    linalg.fill(%C, %f0) : !row_major_C, f32
+    %z = constant 0.0 : !elem_type_c
+    linalg.fill(%C, %z) : !row_major_C, !elem_type_c
     call @matmul(%A, %B, %C) : (!row_major_A, !row_major_B, !row_major_C) -> ()
   }
   %t_end_matmul = call @rtclock() : () -> f64

diff  --git a/mlir/integration_test/Dialect/Linalg/CPU/benchmark_matmul_column_major.mlir b/mlir/integration_test/Dialect/Linalg/CPU/benchmark_matmul_column_major.mlir
index a71643fde480..03e51b4b1a91 100644
--- a/mlir/integration_test/Dialect/Linalg/CPU/benchmark_matmul_column_major.mlir
+++ b/mlir/integration_test/Dialect/Linalg/CPU/benchmark_matmul_column_major.mlir
@@ -15,12 +15,15 @@
 // Use tee to both print to stderr and FileCheck
 // RUN: tee -a /dev/stderr | FileCheck %s
 
-!row_major_A = type memref<${M}x${K}xf32>
-!row_major_B = type memref<${K}x${N}xf32>
-!row_major_C = type memref<${M}x${N}xf32>
-!column_major_A = type memref<${K}x${M}xf32>
-!column_major_B = type memref<${N}x${K}xf32>
-!column_major_C = type memref<${N}x${M}xf32>
+!elem_type_a = type f32
+!elem_type_b = type f32
+!elem_type_c = type f32
+!row_major_A = type memref<${M}x${K}x!elem_type_a>
+!row_major_B = type memref<${K}x${N}x!elem_type_b>
+!row_major_C = type memref<${M}x${N}x!elem_type_c>
+!column_major_A = type memref<${K}x${M}x!elem_type_a>
+!column_major_B = type memref<${N}x${K}x!elem_type_b>
+!column_major_C = type memref<${N}x${M}x!elem_type_c>
 
 func @matmul_column_major(%a: !column_major_A, %b: !column_major_B, %c: !column_major_C)
 // TODO: activate manually for now.
@@ -52,16 +55,16 @@ func @print_perf(%iters: index, %total_time: f64) {
 }
 
 func @main() {
-  %f0 = constant 0.0 : f32
-  %f1 = constant 1.0 : f32
+  %f0 = constant 0.0 : !elem_type_c
+  %f1 = constant 1.0 : !elem_type_a
 
   %cA = alloc() : !column_major_A
   %cB = alloc() : !column_major_B
   %cC = alloc() : !column_major_C
 
-  linalg.fill(%cA, %f1) : !column_major_A, f32
-  linalg.fill(%cB, %f1) : !column_major_B, f32
-  linalg.fill(%cC, %f0) : !column_major_C, f32
+  linalg.fill(%cA, %f1) : !column_major_A, !elem_type_a
+  linalg.fill(%cB, %f1) : !column_major_B, !elem_type_b
+  linalg.fill(%cC, %f0) : !column_major_C, !elem_type_c
 
   %c0 = constant 0: index
   %c1 = constant 1: index
@@ -74,7 +77,7 @@ func @main() {
     // This is accounts for about 10-15% perf hit on small sizes.
     // Once linalg on tensors is ready, fusing fill at teh register level will
     // be easy.
-    linalg.fill(%cC, %f0) : !column_major_C, f32
+    linalg.fill(%cC, %f0) : !column_major_C, !elem_type_c
     call @matmul_column_major(%cA, %cB, %cC) : (!column_major_A, !column_major_B, !column_major_C) -> ()
   }
   %t_end_matmul_column_major = call @rtclock() : () -> f64
@@ -83,7 +86,7 @@ func @main() {
 
   %res = load %cC[%c0, %c0]: !column_major_C
   // CHECK: 64
-  vector.print %res: f32
+  vector.print %res: !elem_type_c
 
   dealloc %cA : !column_major_A
   dealloc %cB : !column_major_B

diff  --git a/mlir/integration_test/Dialect/Linalg/CPU/benchmark_matmul_column_major_as_row_major.mlir b/mlir/integration_test/Dialect/Linalg/CPU/benchmark_matmul_column_major_as_row_major.mlir
index c8f3fe4b95d4..f672829ac432 100644
--- a/mlir/integration_test/Dialect/Linalg/CPU/benchmark_matmul_column_major_as_row_major.mlir
+++ b/mlir/integration_test/Dialect/Linalg/CPU/benchmark_matmul_column_major_as_row_major.mlir
@@ -16,12 +16,15 @@
 // Use tee to both print to stderr and FileCheck
 // RUN: tee -a /dev/stderr | FileCheck %s
 
-!row_major_A = type memref<${M}x${K}xf32>
-!row_major_B = type memref<${K}x${N}xf32>
-!row_major_C = type memref<${M}x${N}xf32>
-!column_major_A = type memref<${K}x${M}xf32>
-!column_major_B = type memref<${N}x${K}xf32>
-!column_major_C = type memref<${N}x${M}xf32>
+!elem_type_a = type f32
+!elem_type_b = type f32
+!elem_type_c = type f32
+!row_major_A = type memref<${M}x${K}x!elem_type_a>
+!row_major_B = type memref<${K}x${N}x!elem_type_b>
+!row_major_C = type memref<${M}x${N}x!elem_type_c>
+!column_major_A = type memref<${K}x${M}x!elem_type_a>
+!column_major_B = type memref<${N}x${K}x!elem_type_b>
+!column_major_C = type memref<${N}x${M}x!elem_type_c>
 
 func @matmul_column_major_as_row_major(
   %ca: !column_major_A, %cb: !column_major_B, %cc: !column_major_C,
@@ -58,16 +61,16 @@ func @print_perf(%iters: index, %total_time: f64) {
 }
 
 func @main() {
-  %f0 = constant 0.0 : f32
-  %f1 = constant 1.0 : f32
+  %f0 = constant 0.0 : !elem_type_c
+  %f1 = constant 1.0 : !elem_type_a
 
   %cA = alloc() : !column_major_A
   %cB = alloc() : !column_major_B
   %cC = alloc() : !column_major_C
 
-  linalg.fill(%cA, %f1) : !column_major_A, f32
-  linalg.fill(%cB, %f1) : !column_major_B, f32
-  linalg.fill(%cC, %f0) : !column_major_C, f32
+  linalg.fill(%cA, %f1) : !column_major_A, !elem_type_a
+  linalg.fill(%cB, %f1) : !column_major_B, !elem_type_b
+  linalg.fill(%cC, %f0) : !column_major_C, !elem_type_c
 
   %c0 = constant 0: index
   %c1 = constant 1: index
@@ -83,7 +86,7 @@ func @main() {
     // This is accounts for about 10-15% perf hit on small sizes.
     // Once linalg on tensors is ready, fusing fill at teh register level will
     // be easy.
-    linalg.fill(%C, %f0) : !row_major_C, f32
+    linalg.fill(%C, %f0) : !row_major_C, !elem_type_c
     call @matmul_column_major_as_row_major(%cA, %cB, %cC, %A, %B, %C) :
       (!column_major_A, !column_major_B, !column_major_C,
        !row_major_A, !row_major_B, !row_major_C) -> ()
@@ -94,10 +97,10 @@ func @main() {
 
   %res = load %cC[%c0, %c0]: !column_major_C
   // CHECK: 64
-  vector.print %res: f32
+  vector.print %res: !elem_type_c
   %res2 = load %C[%c0, %c0]: !row_major_C
   // CHECK: 64
-  vector.print %res2: f32
+  vector.print %res2: !elem_type_c
 
   dealloc %A : !row_major_A
   dealloc %B : !row_major_B

diff  --git a/mlir/integration_test/Dialect/Linalg/CPU/benchmark_matmul_i8_i8_i32.mlir b/mlir/integration_test/Dialect/Linalg/CPU/benchmark_matmul_i8_i8_i32.mlir
new file mode 100644
index 000000000000..9243ebbae4eb
--- /dev/null
+++ b/mlir/integration_test/Dialect/Linalg/CPU/benchmark_matmul_i8_i8_i32.mlir
@@ -0,0 +1,103 @@
+// RUN: export M=24 && export K=64 && export N=192 && export ITERS=10 && \
+// RUN: cat %s | sed 's@${M}@'"$M"'@g'| sed 's@${K}@'"$K"'@g' | sed 's@${N}@'"$N"'@g'| sed 's@${ITERS}@'"$ITERS"'@g'| \
+// TODO: extend vectorization with interfaces so that it works with sexti
+// RUN: mlir-opt -test-linalg-codegen-strategy="anchor-op=linalg.matmul_i8_i8_i32 register-tile-sizes=12,32,16" | \
+// RUN: mlir-opt -test-linalg-codegen-strategy="anchor-op=linalg.fill register-tile-sizes=4,32 vectorize" | \
+// RUN: mlir-opt -test-linalg-codegen-strategy="anchor-op=linalg.copy register-tile-sizes=4,32 vectorize" | \
+// RUN: mlir-opt -canonicalize -convert-vector-to-scf -lower-affine -convert-linalg-to-loops | \
+
+// RUN: mlir-opt -canonicalize -convert-scf-to-std -convert-vector-to-llvm | \
+// RUN: mlir-cpu-runner -O3 -e main -entry-point-result=void \
+// Activate to dump assembly
+// R_UN:   -dump-object-file -object-filename=/tmp/a.o \
+// RUN:   -shared-libs=%mlir_integration_test_dir/libmlir_runner_utils%shlibext | \
+// Use tee to both print to stderr and FileCheck
+// RUN: tee -a /dev/stderr | FileCheck %s
+
+
+!elem_type_a = type i8
+!elem_type_b = type i8
+!elem_type_c = type i32
+!row_major_A = type memref<${M}x${K}x!elem_type_a>
+!row_major_B = type memref<${K}x${N}x!elem_type_b>
+!row_major_C = type memref<${M}x${N}x!elem_type_c>
+
+func @matmul(%a: !row_major_A, %b: !row_major_B, %c: !row_major_C)
+// TODO: activate manually for now.
+// attributes { passthrough = [["target-cpu", "skylake-avx512"], ["prefer-vector-width", "512"]]}
+{
+  linalg.matmul_i8_i8_i32 ins(%a, %b : !row_major_A, !row_major_B)
+    outs(%c: !row_major_C)
+  return
+}
+
+func @print_perf(%iters: index, %total_time: f64) {
+  %c2 = constant 2 : index
+  %cM = constant ${M} : index
+  %cN = constant ${N} : index
+  %cK = constant ${K} : index
+
+  %mn = muli %cM, %cN : index
+  %mnk = muli %mn, %cK : index
+
+  // 2*M*N*K.
+  %flops_per_iter = muli %c2, %mnk : index
+  %flops = muli %iters, %flops_per_iter : index
+  %flops_i64 = index_cast %flops : index to i64
+  %flops_f = sitofp %flops_i64 : i64 to f64
+  %flops_per_s = divf %flops_f, %total_time : f64
+  vector.print %flops_per_s : f64
+
+  return
+}
+
+func @main() {
+  %v0 = constant 0 : !elem_type_c
+  %v1 = constant 1 : !elem_type_a
+
+  %A = alloc() : !row_major_A
+  %B = alloc() : !row_major_B
+  %C = alloc() : !row_major_C
+
+  linalg.fill(%A, %v1) : !row_major_A, !elem_type_a
+  linalg.fill(%B, %v1) : !row_major_B, !elem_type_b
+  linalg.fill(%C, %v0) : !row_major_C, !elem_type_c
+
+  %c0 = constant 0: index
+  %c1 = constant 1: index
+  %iters = constant ${ITERS}: index
+
+  /// Run and dump performance for matmul.
+  /// Preheating run:
+  scf.for %arg0 = %c0 to %iters step %c1 {
+    linalg.fill(%C, %v0) : !row_major_C, !elem_type_c
+    call @matmul(%A, %B, %C) : (!row_major_A, !row_major_B, !row_major_C) -> ()
+  }
+  %t_start_matmul = call @rtclock() : () -> f64
+  scf.for %arg0 = %c0 to %iters step %c1 {
+    // linalg.matmul writes %C in place, need to reset it to zero every time.
+    // This is accounts for about 10-15% perf hit on small sizes.
+    // Once linalg on tensors is ready, fusing fill at teh register level will
+    // be easy.
+    linalg.fill(%C, %v0) : !row_major_C, !elem_type_c
+    call @matmul(%A, %B, %C) : (!row_major_A, !row_major_B, !row_major_C) -> ()
+  }
+  %t_end_matmul = call @rtclock() : () -> f64
+  %tmatmul = subf %t_end_matmul, %t_start_matmul: f64
+  call @print_perf(%iters, %tmatmul) : (index, f64) -> ()
+
+  %res = load %C[%c0, %c0]: !row_major_C
+  // CHECK: 64
+  vector.print %res: !elem_type_c
+
+  dealloc %A : !row_major_A
+  dealloc %B : !row_major_B
+  dealloc %C : !row_major_C
+
+  return
+}
+
+func private @rtclock() -> f64
+
+// TODO: init with random, run and check output.
+// func private @fill_random_f32(memref<*xf32>)

diff  --git a/mlir/lib/Dialect/Linalg/Transforms/CodegenStrategy.cpp b/mlir/lib/Dialect/Linalg/Transforms/CodegenStrategy.cpp
index 02058f886451..5c9d1df0c056 100644
--- a/mlir/lib/Dialect/Linalg/Transforms/CodegenStrategy.cpp
+++ b/mlir/lib/Dialect/Linalg/Transforms/CodegenStrategy.cpp
@@ -37,8 +37,10 @@ void mlir::linalg::CodegenStrategy::transform(FuncOp func) const {
   for (const std::unique_ptr<Transformation> &t : transformationSequence) {
     auto nextState = Identifier::get(std::to_string(++stepCount), context);
     auto marker = (currentState == zeroState)
-                      ? linalg::LinalgMarker({}, nextState)
-                      : linalg::LinalgMarker(currentState, nextState);
+                      ? linalg::LinalgTransformationFilter(
+                            t->filter, ArrayRef<Identifier>{}, nextState)
+                      : linalg::LinalgTransformationFilter(
+                            t->filter, currentState, nextState);
     stage1Patterns.emplace_back(t->buildRewritePatterns(context, marker));
     currentState = nextState;
   }
@@ -47,15 +49,17 @@ void mlir::linalg::CodegenStrategy::transform(FuncOp func) const {
       linalg::getLinalgTilingCanonicalizationPatterns(context);
   stage2Patterns.insert<AffineMinSCFCanonicalizationPattern>(context);
 
-  auto stage3Transforms = [](Operation *op) {
+  auto stage3Transforms = [&](Operation *op) {
     // Some of these may be too aggressive as a stage 3 that is applied on each
     // stage 1 application and may have to be split out to post staged patterns
     // application (in which case they could just be passes, TBD).
-    op->walk([&](LoopLikeOpInterface loopLike) {
-      LLVM_DEBUG(loopLike.print(llvm::dbgs() << "\nOriginal loop:\n"));
-      if (failed(moveLoopInvariantCode(loopLike)))
-        llvm_unreachable("unexpected LICM failure");
-    });
+    if (enableLICM) {
+      op->walk([&](LoopLikeOpInterface loopLike) {
+        LLVM_DEBUG(loopLike.print(llvm::dbgs() << "\nOriginal loop:\n"));
+        if (failed(moveLoopInvariantCode(loopLike)))
+          llvm_unreachable("unexpected LICM failure");
+      });
+    }
     promoteSingleIterationLoops(cast<FuncOp>(op));
     hoistViewAllocOps(cast<FuncOp>(op));
     hoistRedundantVectorTransfers(cast<FuncOp>(op));

diff  --git a/mlir/lib/Dialect/Linalg/Transforms/Generalization.cpp b/mlir/lib/Dialect/Linalg/Transforms/Generalization.cpp
index 454bbbe3578a..997fa692c2b1 100644
--- a/mlir/lib/Dialect/Linalg/Transforms/Generalization.cpp
+++ b/mlir/lib/Dialect/Linalg/Transforms/Generalization.cpp
@@ -63,7 +63,8 @@ namespace {
 // into auto-generated ones.
 template <typename ConcretePattern, typename RootOp>
 struct LinalgGeneralizationPattern : OpRewritePattern<RootOp> {
-  LinalgGeneralizationPattern(MLIRContext *context, linalg::LinalgMarker marker,
+  LinalgGeneralizationPattern(MLIRContext *context,
+                              linalg::LinalgTransformationFilter marker,
                               PatternBenefit benefit = 1)
       : OpRewritePattern<RootOp>(context, benefit), marker(std::move(marker)) {}
 
@@ -81,12 +82,13 @@ struct LinalgGeneralizationPattern : OpRewritePattern<RootOp> {
       return failure();
 
     rewriter.replaceOp(rootOp, genericOp.getResults());
-    marker.replaceLinalgMarker(rewriter, genericOp.getOperation());
+    marker.replaceLinalgTransformationFilter(rewriter,
+                                             genericOp.getOperation());
     return success();
   }
 
 private:
-  linalg::LinalgMarker marker;
+  linalg::LinalgTransformationFilter marker;
 };
 
 struct GeneralizeConvOp
@@ -100,7 +102,7 @@ struct GeneralizeConvOp
 /// linalg.generic.
 struct LinalgNamedOpGeneralizationPattern : RewritePattern {
   LinalgNamedOpGeneralizationPattern(MLIRContext *context,
-                                     linalg::LinalgMarker marker,
+                                     linalg::LinalgTransformationFilter marker,
                                      PatternBenefit benefit = 1)
       : RewritePattern(benefit, MatchAnyOpTypeTag()),
         marker(std::move(marker)) {}
@@ -123,12 +125,13 @@ struct LinalgNamedOpGeneralizationPattern : RewritePattern {
       return failure();
 
     rewriter.replaceOp(rootOp, genericOp.getResults());
-    marker.replaceLinalgMarker(rewriter, genericOp.getOperation());
+    marker.replaceLinalgTransformationFilter(rewriter,
+                                             genericOp.getOperation());
     return success();
   }
 
 private:
-  linalg::LinalgMarker marker;
+  linalg::LinalgTransformationFilter marker;
 };
 
 struct LinalgGeneralizationPass
@@ -165,13 +168,13 @@ linalg::GenericOp GeneralizeConvOp::createGenericOp(linalg::ConvOp convOp,
 
 void mlir::linalg::populateLinalgConvGeneralizationPatterns(
     MLIRContext *context, OwningRewritePatternList &patterns,
-    linalg::LinalgMarker marker) {
+    linalg::LinalgTransformationFilter marker) {
   patterns.insert<GeneralizeConvOp>(context, marker);
 }
 
 void mlir::linalg::populateLinalgNamedOpsGeneralizationPatterns(
     MLIRContext *context, OwningRewritePatternList &patterns,
-    linalg::LinalgMarker marker) {
+    linalg::LinalgTransformationFilter marker) {
   patterns.insert<LinalgNamedOpGeneralizationPattern>(context, marker);
 }
 

diff  --git a/mlir/lib/Dialect/Linalg/Transforms/Tiling.cpp b/mlir/lib/Dialect/Linalg/Transforms/Tiling.cpp
index d723dc47ac57..ce41560f7557 100644
--- a/mlir/lib/Dialect/Linalg/Transforms/Tiling.cpp
+++ b/mlir/lib/Dialect/Linalg/Transforms/Tiling.cpp
@@ -536,7 +536,9 @@ class RewritePatternList<OpTy, OpTypes...> {
   static void insert(OwningRewritePatternList &patterns,
                      const LinalgTilingOptions &options, MLIRContext *ctx) {
     patterns.insert<LinalgTilingPattern<OpTy>>(
-        ctx, options, LinalgMarker({}, Identifier::get("tiled", ctx)));
+        ctx, options,
+        LinalgTransformationFilter(ArrayRef<Identifier>{},
+                                   Identifier::get("tiled", ctx)));
     RewritePatternList<OpTypes...>::insert(patterns, options, ctx);
   }
 };

diff  --git a/mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp b/mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp
index b0cb51516e25..b4c94ae53937 100644
--- a/mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp
+++ b/mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp
@@ -46,14 +46,23 @@ using namespace mlir::linalg;
 const StringLiteral mlir::linalg::LinalgTransforms::kLinalgTransformMarker =
     "__internal_linalg_transform__";
 
-mlir::linalg::LinalgMarker::LinalgMarker(ArrayRef<Identifier> matchDisjunction,
-                                         Optional<Identifier> replacement)
-    : matchDisjunction(matchDisjunction.begin(), matchDisjunction.end()),
+mlir::linalg::LinalgTransformationFilter::LinalgTransformationFilter(
+    ArrayRef<Identifier> matchDisjunction, Optional<Identifier> replacement)
+    : LinalgTransformationFilter([](Operation *) { return success(); },
+                                 matchDisjunction, replacement) {}
+
+mlir::linalg::LinalgTransformationFilter::LinalgTransformationFilter(
+    FilterFunction f, ArrayRef<Identifier> matchDisjunction,
+    Optional<Identifier> replacement)
+    : filter(f),
+      matchDisjunction(matchDisjunction.begin(), matchDisjunction.end()),
       replacement(replacement) {}
 
-LogicalResult
-mlir::linalg::LinalgMarker::checkAndNotify(PatternRewriter &rewriter,
-                                           Operation *op) const {
+LogicalResult mlir::linalg::LinalgTransformationFilter::checkAndNotify(
+    PatternRewriter &rewriter, Operation *op) const {
+  if (filter && failed(filter(op)))
+    return failure();
+
   auto attr = op->template getAttrOfType<StringAttr>(
       LinalgTransforms::kLinalgTransformMarker);
 
@@ -81,8 +90,9 @@ mlir::linalg::LinalgMarker::checkAndNotify(PatternRewriter &rewriter,
   });
 }
 
-void mlir::linalg::LinalgMarker::replaceLinalgMarker(PatternRewriter &rewriter,
-                                                     Operation *op) const {
+void mlir::linalg::LinalgTransformationFilter::
+    replaceLinalgTransformationFilter(PatternRewriter &rewriter,
+                                      Operation *op) const {
   if (replacement.hasValue())
     op->setAttr(LinalgTransforms::kLinalgTransformMarker,
                 rewriter.getStringAttr(replacement.getValue()));
@@ -219,12 +229,13 @@ static LogicalResult rewriteAsPaddedOp(PatternRewriter &rewriter,
 /// Linalg base tiling pattern.
 mlir::linalg::LinalgBaseTilingPattern::LinalgBaseTilingPattern(
     StringRef opName, MLIRContext *context, LinalgTilingOptions options,
-    LinalgMarker marker, PatternBenefit benefit)
+    LinalgTransformationFilter marker, PatternBenefit benefit)
     : RewritePattern(opName, {}, benefit, context), marker(marker),
       options(options) {}
 
 mlir::linalg::LinalgBaseTilingPattern::LinalgBaseTilingPattern(
-    LinalgTilingOptions options, LinalgMarker marker, PatternBenefit benefit)
+    LinalgTilingOptions options, LinalgTransformationFilter marker,
+    PatternBenefit benefit)
     : RewritePattern(benefit, MatchAnyOpTypeTag()), marker(marker),
       options(options) {}
 
@@ -250,9 +261,9 @@ LogicalResult mlir::linalg::LinalgBaseTilingPattern::matchAndRewriteBase(
     // Return relevant information to derived pattern.
     result = *res;
     // Replace marker on both tiledOp and tiledAndPaddedOp, if necessary.
-    marker.replaceLinalgMarker(rewriter, tiledOp);
+    marker.replaceLinalgTransformationFilter(rewriter, tiledOp);
     if (tiledOp != res->op)
-      marker.replaceLinalgMarker(rewriter, res->op);
+      marker.replaceLinalgTransformationFilter(rewriter, res->op);
   });
 
   // Consider padding on the fly only if the op has tensor semantics.
@@ -276,8 +287,8 @@ mlir::linalg::LinalgBaseTileAndFusePattern::LinalgBaseTileAndFusePattern(
     StringRef opName, MLIRContext *context,
     const LinalgDependenceGraph &dependenceGraph,
     LinalgTilingOptions tilingOptions, LinalgFusionOptions fusionOptions,
-    LinalgMarker marker, LinalgMarker fusedOpMarker,
-    LinalgMarker originalOpMarker, PatternBenefit benefit)
+    LinalgTransformationFilter marker, LinalgTransformationFilter fusedOpMarker,
+    LinalgTransformationFilter originalOpMarker, PatternBenefit benefit)
     : RewritePattern(opName, {}, benefit, context),
       dependenceGraph(dependenceGraph), tilingOptions(tilingOptions),
       fusionOptions(fusionOptions), marker(marker),
@@ -352,23 +363,26 @@ LogicalResult mlir::linalg::LinalgBaseTileAndFusePattern::matchAndRewrite(
     tiledAndFusedOps->op = unfusedTiledOp->op;
   }
 
-  marker.replaceLinalgMarker(rewriter, tiledAndFusedOps->op.getOperation());
+  marker.replaceLinalgTransformationFilter(rewriter,
+                                           tiledAndFusedOps->op.getOperation());
   for (auto fusedOp : tiledAndFusedOps->fusedProducers) {
-    fusedOpMarker.replaceLinalgMarker(rewriter, fusedOp.getOperation());
+    fusedOpMarker.replaceLinalgTransformationFilter(rewriter,
+                                                    fusedOp.getOperation());
   }
   for (auto origProducerOp : ArrayRef<LinalgOp>(fusionOps).drop_back()) {
-    originalOpMarker.replaceLinalgMarker(rewriter,
-                                         origProducerOp.getOperation());
+    originalOpMarker.replaceLinalgTransformationFilter(
+        rewriter, origProducerOp.getOperation());
   }
-  rewriter.updateRootInPlace(
-      op, [&]() { originalOpMarker.replaceLinalgMarker(rewriter, op); });
+  rewriter.updateRootInPlace(op, [&]() {
+    originalOpMarker.replaceLinalgTransformationFilter(rewriter, op);
+  });
   return success();
 }
 
 /// Linalg base interchange pattern.
 mlir::linalg::LinalgBaseInterchangePattern::LinalgBaseInterchangePattern(
     StringRef opName, MLIRContext *context,
-    ArrayRef<unsigned> interchangeVector, LinalgMarker marker,
+    ArrayRef<unsigned> interchangeVector, LinalgTransformationFilter marker,
     PatternBenefit benefit)
     : RewritePattern(opName, {}, benefit, context), marker(marker),
       interchangeVector(interchangeVector.begin(), interchangeVector.end()) {}
@@ -388,14 +402,14 @@ LogicalResult mlir::linalg::LinalgBaseInterchangePattern::matchAndRewrite(
   rewriter.updateRootInPlace(op, [&]() {
     interchange(linalgOp, interchangeVector);
     // New marker if specified.
-    marker.replaceLinalgMarker(rewriter, op);
+    marker.replaceLinalgTransformationFilter(rewriter, op);
   });
   return success();
 }
 
 mlir::linalg::LinalgBasePromotionPattern::LinalgBasePromotionPattern(
     StringRef opName, MLIRContext *context, LinalgPromotionOptions options,
-    LinalgMarker marker, PatternBenefit benefit)
+    LinalgTransformationFilter marker, PatternBenefit benefit)
     : RewritePattern(opName, {}, benefit, context), marker(marker),
       options(options) {}
 
@@ -417,12 +431,12 @@ LogicalResult mlir::linalg::LinalgBasePromotionPattern::matchAndRewrite(
     return op->emitError("subview promotion failed");
   }
   rewriter.finalizeRootUpdate(op);
-  marker.replaceLinalgMarker(rewriter, op);
+  marker.replaceLinalgTransformationFilter(rewriter, op);
   return success();
 }
 
 mlir::linalg::LinalgBaseVectorizationPattern::LinalgBaseVectorizationPattern(
-    StringRef opName, MLIRContext *context, LinalgMarker marker,
+    StringRef opName, MLIRContext *context, LinalgTransformationFilter marker,
     PatternBenefit benefit)
     : RewritePattern(opName, {}, benefit, context), marker(marker) {}
 

diff  --git a/mlir/lib/Dialect/Linalg/Transforms/Vectorization.cpp b/mlir/lib/Dialect/Linalg/Transforms/Vectorization.cpp
index 76a5bb56a4b6..fa1aba8fd157 100644
--- a/mlir/lib/Dialect/Linalg/Transforms/Vectorization.cpp
+++ b/mlir/lib/Dialect/Linalg/Transforms/Vectorization.cpp
@@ -607,12 +607,13 @@ populateVectorizationPatterns(OwningRewritePatternList &tilingPatterns,
   constexpr static StringRef kPromotedMarker = "PROMOTED";
   tilingPatterns.insert<LinalgTilingPattern<ConvOp>>(
       context, LinalgTilingOptions().setTileSizes(tileSizes),
-      LinalgMarker({}, Identifier::get(kTiledMarker, context)));
+      LinalgTransformationFilter(ArrayRef<Identifier>{},
+                                 Identifier::get(kTiledMarker, context)));
 
   promotionPatterns.insert<LinalgPromotionPattern<ConvOp>>(
       context, LinalgPromotionOptions().setUseFullTileBuffersByDefault(true),
-      LinalgMarker(Identifier::get(kTiledMarker, context),
-                   Identifier::get(kPromotedMarker, context)));
+      LinalgTransformationFilter(Identifier::get(kTiledMarker, context),
+                                 Identifier::get(kPromotedMarker, context)));
 
   SmallVector<bool, 4> mask(N);
   int offset = tileSizes.size() - N;

diff  --git a/mlir/test/lib/Transforms/TestLinalgCodegenStrategy.cpp b/mlir/test/lib/Transforms/TestLinalgCodegenStrategy.cpp
index 8d80de793658..34ee46a91ac1 100644
--- a/mlir/test/lib/Transforms/TestLinalgCodegenStrategy.cpp
+++ b/mlir/test/lib/Transforms/TestLinalgCodegenStrategy.cpp
@@ -107,8 +107,12 @@ struct TestLinalgCodegenStrategy
 };
 } // end anonymous namespace
 
-template <typename LinalgNamedOp>
-void TestLinalgCodegenStrategy::applyStrategyToNamedLinalgOp() {
+/// Apply transformations specified as patterns.
+void TestLinalgCodegenStrategy::runOnFunction() {
+  linalg::LinalgTransformationFilter::FilterFunction filterOpName =
+      [&](Operation *op) -> LogicalResult {
+    return success(op->getName().getStringRef() == anchorOpName);
+  };
   LinalgTilingOptions tilingOptions;
   if (!tileSizes.empty())
     tilingOptions = tilingOptions.setTileSizes(tileSizes);
@@ -134,19 +138,20 @@ void TestLinalgCodegenStrategy::applyStrategyToNamedLinalgOp() {
           .Default(vector::VectorTransferSplit::None);
 
   CodegenStrategy strategy;
-  strategy.template tileIf<LinalgNamedOp>(!tileSizes.empty(), tilingOptions)
-      .template promoteIf<LinalgNamedOp>(
-          promote, LinalgPromotionOptions()
-                       .setAlignment(16)
-                       .setUseFullTileBuffersByDefault(promoteFullTile))
-      .template tileIf<LinalgNamedOp>(!registerTileSizes.empty(),
-                                      registerTilingOptions)
-      .template promoteIf<LinalgNamedOp>(
-          registerPromote,
+  strategy.tileIf<LinalgOp>(!tileSizes.empty(), anchorOpName, tilingOptions)
+      .promoteIf<LinalgOp>(promote, anchorOpName,
+                           LinalgPromotionOptions()
+                               .setAlignment(16)
+                               .setUseFullTileBuffersByDefault(promoteFullTile),
+                           filterOpName)
+      .tileIf<LinalgOp>(!registerTileSizes.empty(), anchorOpName,
+                        registerTilingOptions)
+      .promoteIf<LinalgOp>(
+          registerPromote, anchorOpName,
           LinalgPromotionOptions()
               .setAlignment(16)
               .setUseFullTileBuffersByDefault(registerPromoteFullTile))
-      .template vectorizeIf<LinalgNamedOp>(vectorize)
+      .vectorizeIf<LinalgOp>(vectorize, anchorOpName)
       .setVectorTransformsOptions(
           vector::VectorTransformsOptions()
               .setVectorTransformsOptions(vectorContractLowering)
@@ -156,20 +161,6 @@ void TestLinalgCodegenStrategy::applyStrategyToNamedLinalgOp() {
   strategy.transform(getFunction());
 }
 
-/// Apply transformations specified as patterns.
-void TestLinalgCodegenStrategy::runOnFunction() {
-  if (anchorOpName == MatmulOp::getOperationName())
-    applyStrategyToNamedLinalgOp<MatmulOp>();
-  else if (anchorOpName == MatmulColumnMajorOp::getOperationName())
-    applyStrategyToNamedLinalgOp<MatmulColumnMajorOp>();
-  else if (anchorOpName == CopyOp::getOperationName())
-    applyStrategyToNamedLinalgOp<CopyOp>();
-  else if (anchorOpName == FillOp::getOperationName())
-    applyStrategyToNamedLinalgOp<FillOp>();
-  else
-    llvm_unreachable("Unsupported anchor op");
-}
-
 namespace mlir {
 namespace test {
 void registerTestLinalgCodegenStrategy() {

diff  --git a/mlir/test/lib/Transforms/TestLinalgFusionTransforms.cpp b/mlir/test/lib/Transforms/TestLinalgFusionTransforms.cpp
index 4ed00e4fbefc..f2c9067d5cc2 100644
--- a/mlir/test/lib/Transforms/TestLinalgFusionTransforms.cpp
+++ b/mlir/test/lib/Transforms/TestLinalgFusionTransforms.cpp
@@ -45,12 +45,15 @@ static void fillFusionPatterns(MLIRContext *context,
           .setTileSizes({32, 64, 16})
           .setLoopType(LinalgTilingLoopType::ParallelLoops),
       LinalgFusionOptions().setIndicesToFuse({2}),
-      LinalgMarker(Identifier::get("basic_fusion", context),
-                   Identifier::get("after_basic_fusion", context)),
-      LinalgMarker(ArrayRef<Identifier>(),
-                   Identifier::get("after_basic_fusion_producer", context)),
-      LinalgMarker(ArrayRef<Identifier>(),
-                   Identifier::get("after_basic_fusion_original", context)));
+      LinalgTransformationFilter(
+          Identifier::get("basic_fusion", context),
+          Identifier::get("after_basic_fusion", context)),
+      LinalgTransformationFilter(
+          ArrayRef<Identifier>(),
+          Identifier::get("after_basic_fusion_producer", context)),
+      LinalgTransformationFilter(
+          ArrayRef<Identifier>(),
+          Identifier::get("after_basic_fusion_original", context)));
 
   patterns.insert<LinalgTileAndFusePattern<MatmulOp>>(
       context, dependenceGraph,
@@ -58,12 +61,14 @@ static void fillFusionPatterns(MLIRContext *context,
           .setTileSizes({32, 64, 16})
           .setLoopType(LinalgTilingLoopType::ParallelLoops),
       LinalgFusionOptions().setIndicesToFuse({0}),
-      LinalgMarker(Identifier::get("lhs_fusion", context),
-                   Identifier::get("after_lhs_fusion", context)),
-      LinalgMarker(ArrayRef<Identifier>(),
-                   Identifier::get("after_lhs_fusion_producer", context)),
-      LinalgMarker(ArrayRef<Identifier>(),
-                   Identifier::get("after_lhs_fusion_original", context)));
+      LinalgTransformationFilter(Identifier::get("lhs_fusion", context),
+                                 Identifier::get("after_lhs_fusion", context)),
+      LinalgTransformationFilter(
+          ArrayRef<Identifier>(),
+          Identifier::get("after_lhs_fusion_producer", context)),
+      LinalgTransformationFilter(
+          ArrayRef<Identifier>(),
+          Identifier::get("after_lhs_fusion_original", context)));
 
   patterns.insert<LinalgTileAndFusePattern<MatmulOp>>(
       context, dependenceGraph,
@@ -71,12 +76,14 @@ static void fillFusionPatterns(MLIRContext *context,
           .setTileSizes({32, 64, 16})
           .setLoopType(LinalgTilingLoopType::ParallelLoops),
       LinalgFusionOptions().setIndicesToFuse({1}),
-      LinalgMarker(Identifier::get("rhs_fusion", context),
-                   Identifier::get("after_rhs_fusion", context)),
-      LinalgMarker(ArrayRef<Identifier>(),
-                   Identifier::get("after_rhs_fusion_producer", context)),
-      LinalgMarker(ArrayRef<Identifier>(),
-                   Identifier::get("after_rhs_fusion_original", context)));
+      LinalgTransformationFilter(Identifier::get("rhs_fusion", context),
+                                 Identifier::get("after_rhs_fusion", context)),
+      LinalgTransformationFilter(
+          ArrayRef<Identifier>(),
+          Identifier::get("after_rhs_fusion_producer", context)),
+      LinalgTransformationFilter(
+          ArrayRef<Identifier>(),
+          Identifier::get("after_rhs_fusion_original", context)));
 
   patterns.insert<LinalgTileAndFusePattern<MatmulOp>>(
       context, dependenceGraph,
@@ -84,12 +91,13 @@ static void fillFusionPatterns(MLIRContext *context,
           .setTileSizes({32, 64, 16})
           .setLoopType(LinalgTilingLoopType::ParallelLoops),
       LinalgFusionOptions().setIndicesToFuse({0, 2}),
-      LinalgMarker(Identifier::get("two_operand_fusion", context),
-                   Identifier::get("after_two_operand_fusion", context)),
-      LinalgMarker(
+      LinalgTransformationFilter(
+          Identifier::get("two_operand_fusion", context),
+          Identifier::get("after_two_operand_fusion", context)),
+      LinalgTransformationFilter(
           ArrayRef<Identifier>(),
           Identifier::get("after_two_operand_fusion_producer", context)),
-      LinalgMarker(
+      LinalgTransformationFilter(
           ArrayRef<Identifier>(),
           Identifier::get("after_two_operand_fusion_original", context)));
 
@@ -98,11 +106,13 @@ static void fillFusionPatterns(MLIRContext *context,
       LinalgTilingOptions().setTileSizes({32, 64}).setLoopType(
           LinalgTilingLoopType::ParallelLoops),
       LinalgFusionOptions().setIndicesToFuse({0, 1}),
-      LinalgMarker(Identifier::get("transpose_fusion", context),
-                   Identifier::get("after_transpose_fusion", context)),
-      LinalgMarker(ArrayRef<Identifier>(),
-                   Identifier::get("after_transpose_fusion_producer", context)),
-      LinalgMarker(
+      LinalgTransformationFilter(
+          Identifier::get("transpose_fusion", context),
+          Identifier::get("after_transpose_fusion", context)),
+      LinalgTransformationFilter(
+          ArrayRef<Identifier>(),
+          Identifier::get("after_transpose_fusion_producer", context)),
+      LinalgTransformationFilter(
           ArrayRef<Identifier>(),
           Identifier::get("after_transpose_fusion_original", context)));
 }

diff  --git a/mlir/test/lib/Transforms/TestLinalgTransforms.cpp b/mlir/test/lib/Transforms/TestLinalgTransforms.cpp
index a322b627756e..db05d60ad8c7 100644
--- a/mlir/test/lib/Transforms/TestLinalgTransforms.cpp
+++ b/mlir/test/lib/Transforms/TestLinalgTransforms.cpp
@@ -98,29 +98,35 @@ static void applyPatterns(FuncOp funcOp) {
   //===--------------------------------------------------------------------===//
   patterns.insert<LinalgTilingPattern<MatmulOp>>(
       ctx, LinalgTilingOptions().setTileSizes({2000, 3000, 4000}),
-      LinalgMarker(Identifier::get("MEM", ctx), Identifier::get("L3", ctx)));
+      LinalgTransformationFilter(Identifier::get("MEM", ctx),
+                                 Identifier::get("L3", ctx)));
   patterns.insert<LinalgTilingPattern<MatmulOp>>(
       ctx, LinalgTilingOptions().setTileSizes({200, 300, 400}),
-      LinalgMarker(Identifier::get("L3", ctx), Identifier::get("L2", ctx)));
+      LinalgTransformationFilter(Identifier::get("L3", ctx),
+                                 Identifier::get("L2", ctx)));
   patterns.insert<LinalgTilingPattern<MatmulOp>>(
       ctx, LinalgTilingOptions().setTileSizes({20, 30, 40}),
-      LinalgMarker(Identifier::get("L2", ctx), Identifier::get("L1", ctx)));
+      LinalgTransformationFilter(Identifier::get("L2", ctx),
+                                 Identifier::get("L1", ctx)));
   patterns.insert<LinalgTilingPattern<MatmulOp>>(
       ctx, LinalgTilingOptions().setTileSizes({2, 3, 4}),
-      LinalgMarker(Identifier::get("L1", ctx), Identifier::get("REG", ctx)));
+      LinalgTransformationFilter(Identifier::get("L1", ctx),
+                                 Identifier::get("REG", ctx)));
 
   patterns.insert<LinalgTilingPattern<MatvecOp>>(
       ctx,
       LinalgTilingOptions().setTileSizes({5, 6}).setLoopType(
           LinalgTilingLoopType::ParallelLoops),
-      LinalgMarker({}, Identifier::get("L1", ctx)));
+      LinalgTransformationFilter(ArrayRef<Identifier>{},
+                                 Identifier::get("L1", ctx)));
 
   patterns.insert<LinalgTilingPattern<DotOp>>(
       ctx, LinalgTilingOptions().setTileSizes(8000),
-      LinalgMarker(ArrayRef<Identifier>{Identifier::get("MEM", ctx),
-                                        Identifier::get("L3", ctx),
-                                        Identifier::get("L2", ctx)},
-                   Identifier::get("REG", ctx)));
+      LinalgTransformationFilter(
+          ArrayRef<Identifier>{Identifier::get("MEM", ctx),
+                               Identifier::get("L3", ctx),
+                               Identifier::get("L2", ctx)},
+          Identifier::get("REG", ctx)));
 
   //===--------------------------------------------------------------------===//
   // Linalg tiling and permutation patterns.
@@ -130,24 +136,24 @@ static void applyPatterns(FuncOp funcOp) {
       LinalgTilingOptions()
           .setTileSizes({2000, 3000, 4000})
           .setInterchange({1, 2, 0}),
-      LinalgMarker(Identifier::get("__with_perm__", ctx),
-                   Identifier::get("L2__with_perm__", ctx)));
+      LinalgTransformationFilter(Identifier::get("__with_perm__", ctx),
+                                 Identifier::get("L2__with_perm__", ctx)));
   patterns.insert<LinalgTilingPattern<MatmulOp>>(
       ctx,
       LinalgTilingOptions()
           .setTileSizes({200, 300, 400})
           .setInterchange({1, 0, 2}),
-      LinalgMarker(Identifier::get("L2__with_perm__", ctx),
-                   Identifier::get("L1__with_perm__", ctx)));
+      LinalgTransformationFilter(Identifier::get("L2__with_perm__", ctx),
+                                 Identifier::get("L1__with_perm__", ctx)));
   patterns.insert<LinalgTilingPattern<MatmulOp>>(
       ctx, LinalgTilingOptions().setTileSizes({20, 30, 40}),
-      LinalgMarker(Identifier::get("L1__with_perm__", ctx),
-                   Identifier::get("REG__with_perm__", ctx)));
+      LinalgTransformationFilter(Identifier::get("L1__with_perm__", ctx),
+                                 Identifier::get("REG__with_perm__", ctx)));
 
   patterns.insert<LinalgTilingPattern<MatvecOp>>(
       ctx, LinalgTilingOptions().setTileSizes({5, 6}).setInterchange({1, 0}),
-      LinalgMarker(Identifier::get("__with_perm__", ctx),
-                   Identifier::get("L1__with_perm__", ctx)));
+      LinalgTransformationFilter(Identifier::get("__with_perm__", ctx),
+                                 Identifier::get("L1__with_perm__", ctx)));
 
   patterns.insert<LinalgTilingPattern<MatmulOp>>(
       ctx,
@@ -155,8 +161,9 @@ static void applyPatterns(FuncOp funcOp) {
           .setTileSizes({16, 8, 4})
           .setInterchange({1, 2, 0})
           .setLoopType(LinalgTilingLoopType::ParallelLoops),
-      LinalgMarker(Identifier::get("par__with_perm__", ctx),
-                   Identifier::get("after_par__with_perm__", ctx)));
+      LinalgTransformationFilter(
+          Identifier::get("par__with_perm__", ctx),
+          Identifier::get("after_par__with_perm__", ctx)));
 
   //===--------------------------------------------------------------------===//
   // Linalg to loops patterns.
@@ -164,7 +171,7 @@ static void applyPatterns(FuncOp funcOp) {
   patterns.insert<LinalgLoweringPattern<DotOp>>(
       ctx,
       /*loweringType=*/LinalgLoweringType::Loops,
-      LinalgMarker(Identifier::get("REG", ctx)));
+      LinalgTransformationFilter(Identifier::get("REG", ctx)));
 
   //===--------------------------------------------------------------------===//
   // Linalg distribution patterns.
@@ -178,7 +185,8 @@ static void applyPatterns(FuncOp funcOp) {
                   LinalgVectorizationPattern<FillOp>,
                   LinalgVectorizationPattern<CopyOp>,
                   LinalgVectorizationPattern<GenericOp>>(
-      ctx, LinalgMarker(Identifier::get("VECTORIZE", ctx)));
+      ctx, LinalgVectorizationOptions(),
+      LinalgTransformationFilter(Identifier::get("VECTORIZE", ctx)));
 
   //===--------------------------------------------------------------------===//
   // Linalg generic permutation patterns.
@@ -186,34 +194,38 @@ static void applyPatterns(FuncOp funcOp) {
   patterns.insert<LinalgInterchangePattern<GenericOp>>(
       ctx,
       /*interchangeVector=*/ArrayRef<unsigned>{1, 2, 0},
-      LinalgMarker({}, Identifier::get("PERMUTED", ctx)));
+      LinalgTransformationFilter(ArrayRef<Identifier>{},
+                                 Identifier::get("PERMUTED", ctx)));
   patterns.insert<LinalgInterchangePattern<IndexedGenericOp>>(
       ctx,
       /*interchangeVector=*/ArrayRef<unsigned>{1, 2, 0},
-      LinalgMarker({}, Identifier::get("PERMUTED", ctx)));
+      LinalgTransformationFilter(ArrayRef<Identifier>{},
+                                 Identifier::get("PERMUTED", ctx)));
 
   //===--------------------------------------------------------------------===//
   // Linalg subview operands promotion.
   //===--------------------------------------------------------------------===//
   patterns.insert<LinalgPromotionPattern<MatmulOp>>(
       ctx, LinalgPromotionOptions().setUseFullTileBuffersByDefault(true),
-      LinalgMarker(Identifier::get("_promote_views_", ctx),
-                   Identifier::get("_views_promoted_", ctx)));
+      LinalgTransformationFilter(Identifier::get("_promote_views_", ctx),
+                                 Identifier::get("_views_promoted_", ctx)));
   patterns.insert<LinalgPromotionPattern<MatmulOp>>(
       ctx,
       LinalgPromotionOptions()
           .setOperandsToPromote({0})
           .setUseFullTileBuffersByDefault(true),
-      LinalgMarker(Identifier::get("_promote_first_view_", ctx),
-                   Identifier::get("_first_view_promoted_", ctx)));
+      LinalgTransformationFilter(
+          Identifier::get("_promote_first_view_", ctx),
+          Identifier::get("_first_view_promoted_", ctx)));
   patterns.insert<LinalgPromotionPattern<FillOp>>(
       ctx,
       LinalgPromotionOptions()
           .setOperandsToPromote({0})
           .setUseFullTileBuffers({true})
           .setAlignment(32),
-      LinalgMarker(Identifier::get("_promote_views_aligned_", ctx),
-                   Identifier::get("_views_aligned_promoted_", ctx)));
+      LinalgTransformationFilter(
+          Identifier::get("_promote_views_aligned_", ctx),
+          Identifier::get("_views_aligned_promoted_", ctx)));
 
   applyPatternsAndFoldGreedily(funcOp, std::move(patterns));
 
@@ -230,18 +242,19 @@ static void fillL1TilingAndMatmulToVectorPatterns(
   patternsVector.emplace_back(std::make_unique<LinalgTilingPattern<MatmulOp>>(
       ctx,
       LinalgTilingOptions().setTileSizes({8, 12, 16}).setInterchange({1, 0, 2}),
-      LinalgMarker(Identifier::get(startMarker, ctx),
-                   Identifier::get("L1", ctx))));
+      LinalgTransformationFilter(Identifier::get(startMarker, ctx),
+                                 Identifier::get("L1", ctx))));
 
   patternsVector.emplace_back(
       std::make_unique<LinalgPromotionPattern<MatmulOp>>(
           ctx, LinalgPromotionOptions().setUseFullTileBuffersByDefault(true),
-          LinalgMarker(Identifier::get("L1", ctx),
-                       Identifier::get("VEC", ctx))));
+          LinalgTransformationFilter(Identifier::get("L1", ctx),
+                                     Identifier::get("VEC", ctx))));
 
   patternsVector.emplace_back(
       std::make_unique<LinalgVectorizationPattern<MatmulOp>>(
-          ctx, LinalgMarker(Identifier::get("VEC", ctx))));
+          ctx, LinalgVectorizationOptions(),
+          LinalgTransformationFilter(Identifier::get("VEC", ctx))));
   patternsVector.back()
       .insert<LinalgVectorizationPattern<FillOp>,
               LinalgVectorizationPattern<CopyOp>>(ctx);
@@ -289,8 +302,8 @@ static void fillPromotionCallBackPatterns(MLIRContext *ctx,
                                           OwningRewritePatternList &patterns) {
   patterns.insert<LinalgTilingPattern<MatmulOp>>(
       ctx, LinalgTilingOptions().setTileSizes({16, 16, 16}),
-      LinalgMarker(Identifier::get("START", ctx),
-                   Identifier::get("PROMOTE", ctx)));
+      LinalgTransformationFilter(Identifier::get("START", ctx),
+                                 Identifier::get("PROMOTE", ctx)));
   patterns.insert<LinalgPromotionPattern<MatmulOp>>(
       ctx,
       LinalgPromotionOptions()
@@ -306,7 +319,7 @@ static void fillPromotionCallBackPatterns(MLIRContext *ctx,
                 copyCallBackFn(b, src, dst, true);
                 return success();
               }),
-      LinalgMarker(Identifier::get("PROMOTE", ctx)));
+      LinalgTransformationFilter(Identifier::get("PROMOTE", ctx)));
 }
 
 template <typename IdOp, typename NProcsOp>
@@ -335,8 +348,9 @@ static void fillTileAndDistributePatterns(MLIRContext *context,
             .setTileSizes({8, 8, 4})
             .setLoopType(LinalgTilingLoopType::ParallelLoops)
             .setDistributionOptions(cyclicNprocsEqNiters),
-        LinalgMarker(Identifier::get("distribute1", context),
-                     Identifier::get("after_distribute1", context)));
+        LinalgTransformationFilter(
+            Identifier::get("distribute1", context),
+            Identifier::get("after_distribute1", context)));
   }
 
   {
@@ -351,8 +365,9 @@ static void fillTileAndDistributePatterns(MLIRContext *context,
             .setTileSizes({8, 8, 4})
             .setLoopType(LinalgTilingLoopType::ParallelLoops)
             .setDistributionOptions(cyclicNprocsGeNiters),
-        LinalgMarker(Identifier::get("distribute2", context),
-                     Identifier::get("after_distribute2", context)));
+        LinalgTransformationFilter(
+            Identifier::get("distribute2", context),
+            Identifier::get("after_distribute2", context)));
   }
 
   {
@@ -367,8 +382,9 @@ static void fillTileAndDistributePatterns(MLIRContext *context,
             .setTileSizes({8, 8, 4})
             .setLoopType(LinalgTilingLoopType::ParallelLoops)
             .setDistributionOptions(cyclicNprocsDefault),
-        LinalgMarker(Identifier::get("distribute3", context),
-                     Identifier::get("after_distribute3", context)));
+        LinalgTransformationFilter(
+            Identifier::get("distribute3", context),
+            Identifier::get("after_distribute3", context)));
   }
 
   {
@@ -383,8 +399,9 @@ static void fillTileAndDistributePatterns(MLIRContext *context,
             .setTileSizes({8, 8, 4})
             .setLoopType(LinalgTilingLoopType::ParallelLoops)
             .setDistributionOptions(cyclicNprocsMixed1),
-        LinalgMarker(Identifier::get("distribute4", context),
-                     Identifier::get("after_distribute4", context)));
+        LinalgTransformationFilter(
+            Identifier::get("distribute4", context),
+            Identifier::get("after_distribute4", context)));
   }
 
   {
@@ -399,8 +416,9 @@ static void fillTileAndDistributePatterns(MLIRContext *context,
             .setTileSizes({8, 8, 4})
             .setLoopType(LinalgTilingLoopType::ParallelLoops)
             .setDistributionOptions(cyclicNprocsMixed2),
-        LinalgMarker(Identifier::get("distribute5", context),
-                     Identifier::get("after_distribute5", context)));
+        LinalgTransformationFilter(
+            Identifier::get("distribute5", context),
+            Identifier::get("after_distribute5", context)));
   }
 
   {
@@ -416,8 +434,9 @@ static void fillTileAndDistributePatterns(MLIRContext *context,
             .setTileSizes({8, 8, 4})
             .setLoopType(LinalgTilingLoopType::ParallelLoops)
             .setDistributionOptions(cyclicNprocsMixed3),
-        LinalgMarker(Identifier::get("distribute6", context),
-                     Identifier::get("after_distribute6", context)));
+        LinalgTransformationFilter(
+            Identifier::get("distribute6", context),
+            Identifier::get("after_distribute6", context)));
   }
 
   {
@@ -432,8 +451,9 @@ static void fillTileAndDistributePatterns(MLIRContext *context,
             .setTileSizes({8, 8, 4})
             .setLoopType(LinalgTilingLoopType::Loops)
             .setDistributionOptions(cyclicNprocsEqNiters),
-        LinalgMarker(Identifier::get("tensors_distribute1", context),
-                     Identifier::get("tensors_after_distribute1", context)));
+        LinalgTransformationFilter(
+            Identifier::get("tensors_distribute1", context),
+            Identifier::get("tensors_after_distribute1", context)));
   }
 }
 
@@ -452,8 +472,8 @@ applyMatmulToVectorPatterns(FuncOp funcOp,
         LinalgTilingOptions()
             .setTileSizes({768, 264, 768})
             .setInterchange({1, 2, 0}),
-        LinalgMarker(Identifier::get("START", ctx),
-                     Identifier::get("L2", ctx))));
+        LinalgTransformationFilter(Identifier::get("START", ctx),
+                                   Identifier::get("L2", ctx))));
     fillL1TilingAndMatmulToVectorPatterns(funcOp, Identifier::get("L2", ctx),
                                           stage1Patterns);
   }
@@ -511,7 +531,8 @@ static void applyTileAndPadPattern(FuncOp funcOp) {
           .setPaddingValueComputationFunction(getNeutralOfLinalgOp);
   tilingPattern.insert<linalg::LinalgTilingPattern<linalg::MatmulOp>>(
       context, linalgTilingOptions,
-      linalg::LinalgMarker(Identifier::get("tile-and-pad", context)));
+      linalg::LinalgTransformationFilter(
+          Identifier::get("tile-and-pad", context)));
   applyPatternsAndFoldGreedily(funcOp, std::move(tilingPattern));
 }
 


        


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