diff --git a/mlir/include/mlir/Dialect/Linalg/Utils/Utils.h b/mlir/include/mlir/Dialect/Linalg/Utils/Utils.h
--- a/mlir/include/mlir/Dialect/Linalg/Utils/Utils.h
+++ b/mlir/include/mlir/Dialect/Linalg/Utils/Utils.h
@@ -41,12 +41,6 @@
 /// Check if a LinalgOp is an element-wise operation.
 bool isElementwise(LinalgOp op);
 
-/// Check if iterator type has "parallel" semantics.
-bool isParallelIterator(StringRef iteratorType);
-
-/// Check if iterator type  has "reduction" semantics.
-bool isReductionIterator(StringRef iteratorType);
-
 /// Helper function that creates a memref::DimOp or tensor::DimOp depending on
 /// the type of `source`.
 Value createOrFoldDimOp(OpBuilder &b, Location loc, Value source, int64_t dim);
diff --git a/mlir/include/mlir/Dialect/Tosa/Utils/CoversionUtils.h b/mlir/include/mlir/Dialect/Tosa/Utils/CoversionUtils.h
--- a/mlir/include/mlir/Dialect/Tosa/Utils/CoversionUtils.h
+++ b/mlir/include/mlir/Dialect/Tosa/Utils/CoversionUtils.h
@@ -21,9 +21,6 @@
 namespace mlir {
 namespace tosa {
 
-// Creates a SmallVector of Stringrefs for N parallel loops
-SmallVector<StringRef> getNParallelLoopsAttrs(unsigned nParallelLoops);
-
 // Takes a vector of values and condenses them to a vector with no gaps.
 SmallVector<Value> condenseValues(const SmallVector<Value> &values);
 
diff --git a/mlir/include/mlir/Dialect/Utils/StructuredOpsUtils.h b/mlir/include/mlir/Dialect/Utils/StructuredOpsUtils.h
--- a/mlir/include/mlir/Dialect/Utils/StructuredOpsUtils.h
+++ b/mlir/include/mlir/Dialect/Utils/StructuredOpsUtils.h
@@ -122,6 +122,24 @@
   }
 }
 
+namespace utils {
+
+/// Check if iterator type has "parallel" semantics.
+inline bool isParallelIterator(StringRef iteratorType) {
+  return iteratorType == getParallelIteratorTypeName();
+}
+
+/// Check if iterator type  has "reduction" semantics.
+inline bool isReductionIterator(StringRef iteratorType) {
+  return iteratorType == getReductionIteratorTypeName();
+}
+
+/// Returns an array of iterator types that contains `nParallelLoops` "parallel"
+/// attributes.
+SmallVector<StringRef> getNParallelIterators(unsigned nParallel);
+
+} // namespace utils
+
 /// Helper StructuredGenerator class to manipulate and rewrite ops with
 /// `StructuredOpInterface`. This is templated for now because VectorOps do not
 /// yet implement the StructuredOpInterface itself.
diff --git a/mlir/lib/Conversion/TosaToLinalg/TosaToLinalg.cpp b/mlir/lib/Conversion/TosaToLinalg/TosaToLinalg.cpp
--- a/mlir/lib/Conversion/TosaToLinalg/TosaToLinalg.cpp
+++ b/mlir/lib/Conversion/TosaToLinalg/TosaToLinalg.cpp
@@ -625,7 +625,7 @@
   bool didEncounterError = false;
   auto linalgOp = rewriter.create<linalg::GenericOp>(
       loc, opResultTypes, operands, emptyTensors, indexingMaps,
-      getNParallelLoopsAttrs(rank),
+      utils::getNParallelIterators(rank),
       [&](OpBuilder &nestedBuilder, Location nestedLoc, ValueRange blockArgs) {
         Value opResult = createLinalgBodyCalculationForElementwiseOp(
             operation, blockArgs.take_front(operation->getNumOperands()),
@@ -1119,7 +1119,7 @@
 
     rewriter.replaceOpWithNewOp<linalg::GenericOp>(
         op, resultTy, op.getInput1(), ValueRange{emptyTensor}, affineMaps,
-        getNParallelLoopsAttrs(resultTy.getRank()),
+        utils::getNParallelIterators(resultTy.getRank()),
         [&](OpBuilder &nestedBuilder, Location nestedLoc, ValueRange args) {
           nestedBuilder.create<linalg::YieldOp>(loc, *args.begin());
         });
@@ -1230,7 +1230,7 @@
 
     auto linalgOp = rewriter.create<linalg::GenericOp>(
         loc, outputTy, genericInputs, ValueRange{emptyTensor}, indexingMaps,
-        getNParallelLoopsAttrs(rank),
+        utils::getNParallelIterators(rank),
         [&](OpBuilder &nestedBuilder, Location nestedLoc,
             ValueRange blockArgs) {
           Value value = blockArgs[0];
@@ -1452,7 +1452,7 @@
     Value resize = input;
     auto genericOp = rewriter.create<linalg::GenericOp>(
         loc, resultTy, ValueRange({}), ValueRange{emptyTensor}, affineMaps,
-        getNParallelLoopsAttrs(resultTy.getRank()));
+        utils::getNParallelIterators(resultTy.getRank()));
     resize = genericOp.getResult(0);
 
     OpBuilder::InsertionGuard regionGuard(rewriter);
@@ -1840,7 +1840,7 @@
 
     rewriter.replaceOpWithNewOp<linalg::GenericOp>(
         op, resultTy, ArrayRef<Value>({}), ValueRange{emptyTensor}, affineMaps,
-        getNParallelLoopsAttrs(resultTy.getRank()),
+        utils::getNParallelIterators(resultTy.getRank()),
         [&](OpBuilder &nestedBuilder, Location nestedLoc, ValueRange args) {
           llvm::SmallVector<Value> indices;
           for (unsigned int i = 0; i < inputTy.getRank(); i++) {
@@ -1921,7 +1921,7 @@
     auto genericOp = rewriter.create<linalg::GenericOp>(
         loc, RankedTensorType::get(genericShape, elementTy), input,
         ValueRange{emptyTensor}, affineMaps,
-        getNParallelLoopsAttrs(genericShape.size()),
+        utils::getNParallelIterators(genericShape.size()),
         [&](OpBuilder &nestedBuilder, Location nestedLoc, ValueRange args) {
           nestedBuilder.create<linalg::YieldOp>(op.getLoc(), *args.begin());
         });
@@ -2083,8 +2083,8 @@
 
     // We need to reduce along the arg-max axis, with parallel operations along
     // the rest.
-    SmallVector<StringRef, 4> iteratorTypes;
-    iteratorTypes.resize(inputTy.getRank(), getParallelIteratorTypeName());
+    SmallVector<StringRef, 4> iteratorTypes =
+        utils::getNParallelIterators(inputTy.getRank());
     iteratorTypes[axis] = getReductionIteratorTypeName();
 
     SmallVector<AffineExpr, 2> srcExprs;
@@ -2176,7 +2176,7 @@
     auto genericOp = rewriter.create<linalg::GenericOp>(
         loc, ArrayRef<Type>({resultTy}), ValueRange{indices},
         ValueRange{emptyTensor}, affineMaps,
-        getNParallelLoopsAttrs(resultTy.getRank()),
+        utils::getNParallelIterators(resultTy.getRank()),
         [&](OpBuilder &b, Location loc, ValueRange args) {
           auto indexValue = args[0];
           auto index0 = rewriter.create<linalg::IndexOp>(loc, 0);
@@ -2231,7 +2231,7 @@
 
     auto genericOp = rewriter.create<linalg::GenericOp>(
         loc, resultTy, ValueRange({input}), ValueRange{emptyTensor}, affineMaps,
-        getNParallelLoopsAttrs(resultTy.getRank()));
+        utils::getNParallelIterators(resultTy.getRank()));
     rewriter.replaceOp(op, genericOp.getResult(0));
 
     {
diff --git a/mlir/lib/Conversion/TosaToLinalg/TosaToLinalgNamed.cpp b/mlir/lib/Conversion/TosaToLinalg/TosaToLinalgNamed.cpp
--- a/mlir/lib/Conversion/TosaToLinalg/TosaToLinalgNamed.cpp
+++ b/mlir/lib/Conversion/TosaToLinalg/TosaToLinalgNamed.cpp
@@ -289,7 +289,8 @@
           rewriter
               .create<linalg::GenericOp>(
                   loc, resultTy, ValueRange({bias, conv}), biasEmptyTensor,
-                  indexingMaps, getNParallelLoopsAttrs(resultTy.getRank()),
+                  indexingMaps,
+                  utils::getNParallelIterators(resultTy.getRank()),
                   [&](OpBuilder &nestedBuilder, Location nestedLoc,
                       ValueRange args) {
                     Value added = nestedBuilder.create<arith::AddIOp>(
@@ -311,7 +312,7 @@
         rewriter
             .create<linalg::GenericOp>(
                 loc, resultTy, ValueRange({bias, conv}), biasEmptyTensor,
-                indexingMaps, getNParallelLoopsAttrs(resultTy.getRank()),
+                indexingMaps, utils::getNParallelIterators(resultTy.getRank()),
                 [&](OpBuilder &nestedBuilder, Location nestedLoc,
                     ValueRange args) {
                   Value added = nestedBuilder.create<arith::AddFOp>(
@@ -452,7 +453,7 @@
               .create<linalg::GenericOp>(
                   loc, resultTy, ValueRange({bias, convReshape}),
                   biasEmptyTensor, indexingMaps,
-                  getNParallelLoopsAttrs(resultRank),
+                  utils::getNParallelIterators(resultRank),
                   [&](OpBuilder &nestedBuilder, Location nestedLoc,
                       ValueRange args) {
                     Value added = nestedBuilder.create<arith::AddFOp>(
@@ -479,7 +480,7 @@
               .create<linalg::GenericOp>(
                   loc, resultTy, ValueRange({bias, convReshape}),
                   biasEmptyTensor, indexingMaps,
-                  getNParallelLoopsAttrs(resultRank),
+                  utils::getNParallelIterators(resultRank),
                   [&](OpBuilder &nestedBuilder, Location nestedLoc,
                       ValueRange args) {
                     Value added = nestedBuilder.create<arith::AddIOp>(
@@ -637,7 +638,8 @@
           rewriter
               .create<linalg::GenericOp>(
                   loc, outputTy, ValueRange({bias, matmul}), biasEmptyTensor,
-                  indexingMaps, getNParallelLoopsAttrs(outputTy.getRank()),
+                  indexingMaps,
+                  utils::getNParallelIterators(outputTy.getRank()),
                   [&](OpBuilder &nestedBuilder, Location nestedLoc,
                       ValueRange args) {
                     Value added = nestedBuilder.create<arith::AddFOp>(
@@ -665,7 +667,7 @@
         rewriter
             .create<linalg::GenericOp>(
                 loc, outputTy, ValueRange({bias, matmul}), biasEmptyTensor,
-                indexingMaps, getNParallelLoopsAttrs(outputTy.getRank()),
+                indexingMaps, utils::getNParallelIterators(outputTy.getRank()),
                 [&](OpBuilder &nestedBuilder, Location nestedLoc,
                     ValueRange args) {
                   Value added = nestedBuilder.create<arith::AddIOp>(
@@ -825,7 +827,7 @@
         loc, ArrayRef<Type>({resultTy}), ValueRange{poolingOp},
         ValueRange{genericEmptyTensor},
         ArrayRef<AffineMap>({affineMap, affineMap}),
-        getNParallelLoopsAttrs(resultTy.getRank()),
+        utils::getNParallelIterators(resultTy.getRank()),
         [&](OpBuilder &b, Location loc, ValueRange args) {
           auto zero = rewriter.create<arith::ConstantIndexOp>(loc, 0);
           auto one = rewriter.create<arith::ConstantIndexOp>(loc, 1);
diff --git a/mlir/lib/Dialect/Linalg/IR/LinalgInterfaces.cpp b/mlir/lib/Dialect/Linalg/IR/LinalgInterfaces.cpp
--- a/mlir/lib/Dialect/Linalg/IR/LinalgInterfaces.cpp
+++ b/mlir/lib/Dialect/Linalg/IR/LinalgInterfaces.cpp
@@ -321,7 +321,7 @@
     if (inputExprWalker.unConvolvedDims.count(outputDim) &&
         !filterDims.count(outputDim)) {
       // Batch dimension.
-      if (iteratorTypes[outputDim] != getParallelIteratorTypeName())
+      if (!utils::isParallelIterator(iteratorTypes[outputDim]))
         return MatchConvolutionResult::OutputDimsNotParallel;
       allLoopDims.insert(outputDim);
       continue;
@@ -329,7 +329,7 @@
     if (inputExprWalker.convolvedDims.count(outputDim) &&
         !filterDims.count(outputDim)) {
       // Output image Loop dimension.
-      if (iteratorTypes[outputDim] != getParallelIteratorTypeName())
+      if (!utils::isParallelIterator(iteratorTypes[outputDim]))
         return MatchConvolutionResult::OutputDimsNotParallel;
       allLoopDims.insert(outputDim);
       continue;
@@ -338,7 +338,7 @@
         !inputExprWalker.unConvolvedDims.count(outputDim) &&
         filterDims.count(outputDim)) {
       // Output channel dimension.
-      if (iteratorTypes[outputDim] != getParallelIteratorTypeName())
+      if (!utils::isParallelIterator(iteratorTypes[outputDim]))
         return MatchConvolutionResult::OutputDimsNotParallel;
       allLoopDims.insert(outputDim);
       continue;
@@ -346,7 +346,7 @@
     if (inputExprWalker.unConvolvedDims.count(outputDim) &&
         filterDims.count(outputDim)) {
       // Depth multiplier.
-      if (iteratorTypes[outputDim] != getParallelIteratorTypeName())
+      if (!utils::isParallelIterator(iteratorTypes[outputDim]))
         return MatchConvolutionResult::OutputDimsNotParallel;
       allLoopDims.insert(outputDim);
       continue;
@@ -364,7 +364,7 @@
     if (inputExprWalker.convolvedDims.count(filterDim) &&
         !outputDims.count(filterDim)) {
       // Filter loop dimension.
-      if (iteratorTypes[filterDim] != getReductionIteratorTypeName())
+      if (!utils::isReductionIterator(iteratorTypes[filterDim]))
         return MatchConvolutionResult::NonOutputDimNotReduction;
       if (allLoopDims.count(filterDim))
         return MatchConvolutionResult::NonConvolutionLoop;
@@ -374,7 +374,7 @@
     if (inputExprWalker.unConvolvedDims.count(filterDim) &&
         !outputDims.count(filterDim)) {
       // Input channel dimension.
-      if (iteratorTypes[filterDim] != getReductionIteratorTypeName())
+      if (!utils::isReductionIterator(iteratorTypes[filterDim]))
         return MatchConvolutionResult::NonOutputDimNotReduction;
       if (allLoopDims.count(filterDim))
         return MatchConvolutionResult::NonConvolutionLoop;
diff --git a/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp b/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
--- a/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
+++ b/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
@@ -1419,7 +1419,7 @@
 
 SmallVector<StringRef> MapOp::getIteratorTypesArray() {
   int64_t rank = getInit().getType().getRank();
-  return SmallVector<StringRef>(rank, getParallelIteratorTypeName());
+  return utils::getNParallelIterators(rank);
 }
 
 ArrayAttr MapOp::getIndexingMaps() {
@@ -1476,8 +1476,8 @@
 
 SmallVector<StringRef> ReduceOp::getIteratorTypesArray() {
   int64_t inputRank = getInputs()[0].getType().cast<ShapedType>().getRank();
-  SmallVector<StringRef> iteratorTypes(inputRank,
-                                       getParallelIteratorTypeName());
+  SmallVector<StringRef> iteratorTypes =
+      utils::getNParallelIterators(inputRank);
   for (int64_t reductionDim : getDimensions())
     iteratorTypes[reductionDim] = getReductionIteratorTypeName();
   return iteratorTypes;
@@ -1759,7 +1759,7 @@
 
 SmallVector<StringRef> TransposeOp::getIteratorTypesArray() {
   int64_t rank = getInit().getType().getRank();
-  return SmallVector<StringRef>(rank, getParallelIteratorTypeName());
+  return utils::getNParallelIterators(rank);
 }
 
 ArrayAttr TransposeOp::getIndexingMaps() {
diff --git a/mlir/lib/Dialect/Linalg/Transforms/ElementwiseOpFusion.cpp b/mlir/lib/Dialect/Linalg/Transforms/ElementwiseOpFusion.cpp
--- a/mlir/lib/Dialect/Linalg/Transforms/ElementwiseOpFusion.cpp
+++ b/mlir/lib/Dialect/Linalg/Transforms/ElementwiseOpFusion.cpp
@@ -470,10 +470,10 @@
                             .getValue()
                             .isProjectedPermutation();
                       }) &&
-         genericOp.getMatchingIndexingMap(fusableOpOperand).getNumResults() > 0 &&
-         llvm::all_of(genericOp.getIteratorTypesArray(), [](StringRef it) {
-           return it == getParallelIteratorTypeName();
-         });
+         genericOp.getMatchingIndexingMap(fusableOpOperand).getNumResults() >
+             0 &&
+         llvm::all_of(genericOp.getIteratorTypesArray(),
+                      utils::isParallelIterator);
 }
 
 namespace {
@@ -783,8 +783,8 @@
   }
 
   // The iterator types of the expanded op are all parallel.
-  SmallVector<StringRef> iteratorTypes(expansionInfo.getExpandedOpNumDims(),
-                                       getParallelIteratorTypeName());
+  SmallVector<StringRef> iteratorTypes =
+      utils::getNParallelIterators(expansionInfo.getExpandedOpNumDims());
 
   TypeRange resultTypes = ValueRange(outputs).getTypes();
   auto fusedOp =
@@ -1084,8 +1084,8 @@
 
     // Check that all folded iterator types are all parallel or all reductions.
     StringRef startIteratorType = iteratorTypes[foldedIterationSpaceDims[0]];
-    if (!isParallelIterator(startIteratorType) &&
-        !isReductionIterator(startIteratorType))
+    if (!utils::isParallelIterator(startIteratorType) &&
+        !utils::isReductionIterator(startIteratorType))
       continue;
     if (llvm::any_of(foldedIterationSpaceDims, [&](int64_t dim) {
           return iteratorTypes[dim] != startIteratorType;
@@ -1096,7 +1096,7 @@
     // the folded dimensions need to be "in-order". Strictly speaking this is
     // not necessary, for reductions that are associative and commutative,  but
     // using a more strict definition of reduction for now.
-    if (isReductionIterator(startIteratorType)) {
+    if (utils::isReductionIterator(startIteratorType)) {
       bool isContiguous = false;
       for (const auto &startDim : llvm::enumerate(reductionDims)) {
         // Move window in `reductionDims` to start of the folded iteration dims.
diff --git a/mlir/lib/Dialect/Linalg/Transforms/ElementwiseToLinalg.cpp b/mlir/lib/Dialect/Linalg/Transforms/ElementwiseToLinalg.cpp
--- a/mlir/lib/Dialect/Linalg/Transforms/ElementwiseToLinalg.cpp
+++ b/mlir/lib/Dialect/Linalg/Transforms/ElementwiseToLinalg.cpp
@@ -91,15 +91,13 @@
     SmallVector<AffineMap, 3> indexingMaps(
         op->getNumResults() + op->getNumOperands(),
         rewriter.getMultiDimIdentityMap(rank));
-    SmallVector<StringRef, 6> iteratorTypes(rank,
-                                            getParallelIteratorTypeName());
     auto outputs = getOrCreateOperandsMatchingResultTypes(rewriter, op);
     rewriter.replaceOpWithNewOp<linalg::GenericOp>(
         op, /*resultTensorTypes=*/op->getResultTypes(),
         /*inputs=*/op->getOperands(),
         /*outputs=*/outputs,
         /*indexingMaps=*/indexingMaps,
-        /*iteratorTypes=*/iteratorTypes,
+        /*iteratorTypes=*/utils::getNParallelIterators(rank),
         /*bodyBuilder=*/
         [&](OpBuilder &builder, Location loc, ValueRange regionArgs) {
           auto resultTypes = llvm::to_vector<6>(
diff --git a/mlir/lib/Dialect/Linalg/Transforms/Tiling.cpp b/mlir/lib/Dialect/Linalg/Transforms/Tiling.cpp
--- a/mlir/lib/Dialect/Linalg/Transforms/Tiling.cpp
+++ b/mlir/lib/Dialect/Linalg/Transforms/Tiling.cpp
@@ -472,7 +472,7 @@
     // Collect loop ranges of tiled loopss, loops that are parallel.
     SmallVector<Range> parallelLoopRanges;
     for (const auto &iteratorType : llvm::enumerate(iteratorTypes)) {
-      if (!isParallelIterator(iteratorType.value()))
+      if (!utils::isParallelIterator(iteratorType.value()))
         break;
       parallelLoopRanges.push_back(loopRanges[iteratorType.index()]);
     }
@@ -481,7 +481,7 @@
     unsigned procIdIdx = 0;
     // Update the distribution information for the loops.
     for (const auto &iteratorType : llvm::enumerate(iteratorTypes)) {
-      if (!isParallelIterator(iteratorType.value()))
+      if (!utils::isParallelIterator(iteratorType.value()))
         break;
       procInfo[iteratorType.index()] = returnedProcInfo[procIdIdx++];
     }
diff --git a/mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp b/mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp
--- a/mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp
+++ b/mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp
@@ -297,10 +297,6 @@
   return vectorizeCopy(rewriter, copyOp);
 }
 
-static SmallVector<StringRef> getNParallelLoopsAttrs(unsigned nParallelLoops) {
-  return SmallVector<StringRef>(nParallelLoops, getParallelIteratorTypeName());
-}
-
 /// Rewrite a tensor::PadOp into a sequence of EmptyOp, FillOp (to
 /// initialize with pad_val) and GenericOp (to copy contents).
 LogicalResult
@@ -356,7 +352,7 @@
 
   rewriter.replaceOpWithNewOp<linalg::GenericOp>(
       padOp, resultShapedType, padOp.getSource(), tmpTensor, transferMaps,
-      getNParallelLoopsAttrs(resultShapedType.getRank()),
+      utils::getNParallelIterators(resultShapedType.getRank()),
       [&](OpBuilder &nestedBuilder, Location nestedLoc, ValueRange args) {
         nestedBuilder.create<linalg::YieldOp>(nestedLoc, args[0]);
       });
diff --git a/mlir/lib/Dialect/Linalg/Transforms/Vectorization.cpp b/mlir/lib/Dialect/Linalg/Transforms/Vectorization.cpp
--- a/mlir/lib/Dialect/Linalg/Transforms/Vectorization.cpp
+++ b/mlir/lib/Dialect/Linalg/Transforms/Vectorization.cpp
@@ -190,8 +190,8 @@
 }
 
 static SmallVector<bool> getReductionMask(LinalgOp linalgOp) {
-  return llvm::to_vector(
-      llvm::map_range(linalgOp.getIteratorTypesArray(), isReductionIterator));
+  return llvm::to_vector(llvm::map_range(linalgOp.getIteratorTypesArray(),
+                                         utils::isReductionIterator));
 }
 
 /// Build a vector.transfer_write of `value` into `outputOperand` at indices set
@@ -611,7 +611,7 @@
 // TODO: probably need some extra checks for reduction followed by consumer
 // ops that may not commute (e.g. linear reduction + non-linear instructions).
 static LogicalResult reductionPreconditions(LinalgOp op) {
-  if (llvm::none_of(op.getIteratorTypesArray(), isReductionIterator)) {
+  if (llvm::none_of(op.getIteratorTypesArray(), utils::isReductionIterator)) {
     LDBG("reduction precondition failed: no reduction iterator");
     return failure();
   }
diff --git a/mlir/lib/Dialect/Linalg/Utils/Utils.cpp b/mlir/lib/Dialect/Linalg/Utils/Utils.cpp
--- a/mlir/lib/Dialect/Linalg/Utils/Utils.cpp
+++ b/mlir/lib/Dialect/Linalg/Utils/Utils.cpp
@@ -186,14 +186,6 @@
   return hasOnlyScalarElementwiseOp(op->getRegion(0));
 }
 
-bool isParallelIterator(StringRef iteratorType) {
-  return iteratorType == getParallelIteratorTypeName();
-}
-
-bool isReductionIterator(StringRef iteratorType) {
-  return iteratorType == getReductionIteratorTypeName();
-}
-
 /// Helper function that creates a memref::DimOp or tensor::DimOp depending on
 /// the type of `source`.
 Value createOrFoldDimOp(OpBuilder &b, Location loc, Value source, int64_t dim) {
@@ -422,15 +414,11 @@
           b.getContext())),
       AffineMap::getMultiDimIdentityMap(transposeVector.size(),
                                         b.getContext())};
-  SmallVector<llvm::StringRef> iteratorTypes(transposeVector.size(),
-                                             getParallelIteratorTypeName());
 
   // Create a GenericOp to transpose `inputTensor` into `outputTensor`.
   auto transposeOp = b.create<GenericOp>(
-      loc, resultTensorType, inputTensor, outputTensor,
-      b.getAffineMapArrayAttr(indexingMaps), b.getStrArrayAttr(iteratorTypes),
-      /*doc=*/nullptr,
-      /*library_call=*/nullptr);
+      loc, resultTensorType, inputTensor, outputTensor, indexingMaps,
+      /*iteratorTypes=*/utils::getNParallelIterators(transposeVector.size()));
   Region &body = transposeOp.getRegion();
   body.push_back(new Block());
   body.front().addArguments({elementType, elementType}, {loc, loc});
@@ -452,14 +440,12 @@
 
   AffineMap id =
       AffineMap::getMultiDimIdentityMap(memrefTypeTo.getRank(), b.getContext());
-  SmallVector<StringRef> iteratorTypes(memrefTypeTo.getRank(),
-                                       getParallelIteratorTypeName());
   return b.create<linalg::GenericOp>(
       loc,
       /*inputs=*/from,
       /*outputs=*/to,
       /*indexingMaps=*/llvm::makeArrayRef({id, id}),
-      /*iteratorTypes=*/iteratorTypes,
+      /*iteratorTypes=*/utils::getNParallelIterators(memrefTypeTo.getRank()),
       [](OpBuilder &b, Location loc, ValueRange args) {
         b.create<linalg::YieldOp>(loc, args.front());
       });
@@ -582,7 +568,7 @@
 
   // If there are no outer parallel loops, generate one sequential loop and
   // recurse.
-  if (!isParallelIterator(iteratorTypes.front())) {
+  if (!utils::isParallelIterator(iteratorTypes.front())) {
     LoopNest singleLoop = buildLoopNest(
         b, loc, lbs.take_front(), ubs.take_front(), steps.take_front(),
         [&](OpBuilder &b, Location loc, ValueRange ivs) {
@@ -600,7 +586,8 @@
   unsigned numProcessed = 0;
   DistributionMethod distributionMethod = DistributionMethod::None;
   if (procInfo.empty()) {
-    numProcessed = nLoops - iteratorTypes.drop_while(isParallelIterator).size();
+    numProcessed =
+        nLoops - iteratorTypes.drop_while(utils::isParallelIterator).size();
   } else {
     distributionMethod = procInfo.front().distributionMethod;
     numProcessed =
diff --git a/mlir/lib/Dialect/SparseTensor/Transforms/Sparsification.cpp b/mlir/lib/Dialect/SparseTensor/Transforms/Sparsification.cpp
--- a/mlir/lib/Dialect/SparseTensor/Transforms/Sparsification.cpp
+++ b/mlir/lib/Dialect/SparseTensor/Transforms/Sparsification.cpp
@@ -186,7 +186,7 @@
   std::vector<unsigned> parIt; // parallel iterator with 0 degree
   for (unsigned i = 0; i < n; i++) {
     if (inDegree[i] == 0) {
-      if (linalg::isReductionIterator(iteratorTypes[i]))
+      if (utils::isReductionIterator(iteratorTypes[i]))
         redIt.push_back(i);
       else
         parIt.push_back(i);
@@ -202,7 +202,7 @@
     // Update in-degree, and push 0-degree node into worklist.
     for (unsigned dst = 0; dst < n; dst++)
       if (adjM[src][dst] && --inDegree[dst] == 0) {
-        if (linalg::isReductionIterator(iteratorTypes[dst]))
+        if (utils::isReductionIterator(iteratorTypes[dst]))
           redIt.push_back(dst);
         else
           parIt.push_back(dst);
@@ -348,7 +348,7 @@
   if (isMaterializing(lhs->get())) {
     unsigned nest = 0;
     for (unsigned i = 0; i < numLoops; i++) {
-      if (linalg::isReductionIterator(iteratorTypes[topSort[i]]))
+      if (utils::isReductionIterator(iteratorTypes[topSort[i]]))
         break; // terminate at first reduction
       nest++;
     }
@@ -898,7 +898,7 @@
                          ArrayRef<size_t> extraDims) {
   Location loc = op.getLoc();
   auto iteratorTypes = op.getIteratorTypesArray();
-  bool isReduction = linalg::isReductionIterator(iteratorTypes[idx]);
+  bool isReduction = utils::isReductionIterator(iteratorTypes[idx]);
   bool isSparse = isCompressedDLT(merger.getDimLevelType(tid, idx)) ||
                   isSingletonDLT(merger.getDimLevelType(tid, idx));
   bool isParallel = isParallelFor(codegen, isOuter, isReduction, isSparse);
diff --git a/mlir/lib/Dialect/Tosa/Utils/ConversionUtils.cpp b/mlir/lib/Dialect/Tosa/Utils/ConversionUtils.cpp
--- a/mlir/lib/Dialect/Tosa/Utils/ConversionUtils.cpp
+++ b/mlir/lib/Dialect/Tosa/Utils/ConversionUtils.cpp
@@ -15,11 +15,6 @@
 using namespace mlir;
 using namespace mlir::tosa;
 
-SmallVector<StringRef>
-mlir::tosa::getNParallelLoopsAttrs(unsigned nParallelLoops) {
-  return SmallVector<StringRef>(nParallelLoops, getParallelIteratorTypeName());
-}
-
 SmallVector<Value>
 mlir::tosa::condenseValues(const SmallVector<Value> &values) {
   SmallVector<Value> condensedValues;
diff --git a/mlir/lib/Dialect/Utils/StructuredOpsUtils.cpp b/mlir/lib/Dialect/Utils/StructuredOpsUtils.cpp
--- a/mlir/lib/Dialect/Utils/StructuredOpsUtils.cpp
+++ b/mlir/lib/Dialect/Utils/StructuredOpsUtils.cpp
@@ -92,3 +92,7 @@
   auto maps = ArrayAttr::get(context, {mapA, mapB, mapC});
   return indexingMaps == maps;
 }
+
+SmallVector<StringRef> mlir::utils::getNParallelIterators(unsigned nParallel) {
+  return SmallVector<StringRef>(nParallel, getParallelIteratorTypeName());
+}