diff --git a/mlir/lib/Dialect/SparseTensor/Transforms/CodegenUtils.h b/mlir/lib/Dialect/SparseTensor/Transforms/CodegenUtils.h
--- a/mlir/lib/Dialect/SparseTensor/Transforms/CodegenUtils.h
+++ b/mlir/lib/Dialect/SparseTensor/Transforms/CodegenUtils.h
@@ -362,8 +362,8 @@
       ArrayRef<size_t> dims, SmallVectorImpl<Value> &reduc, bool needsUniv,
       ArrayRef<size_t> extraTids = {}, ArrayRef<size_t> extraDims = {});
 
-  SmallVector<Value, 2> exitCurrentLoop(OpBuilder &builder, Location loc,
-                                        ArrayRef<Value> reduc = {});
+  void exitCurrentLoop(RewriterBase &rewriter, Location loc,
+                       SmallVectorImpl<Value> &reduc);
 
   /// Return the array of coordinate for all the loop generated till now.
   void getCoordinateArray(SmallVectorImpl<Value> &coords) const {
@@ -435,17 +435,32 @@
   }
 
   /// Exits a for loop, returns the reduction results, e.g.,
+  /// For for loops:
   /// %ret = for () {
   ///   ...
+  ///   %val = addi %args, %c
   ///   yield %val
   /// }
+  /// For parallel loops, the following generated code by users
+  /// %ret = parallel () init(%args) {
+  ///   ...
+  ///   %val = addi %args, %c
+  /// }
+  /// will be transformed into
+  /// %ret = parallel () init(%args) {
+  ///   ...
+  ///   scf.reduce(%c) bb0(%0, %1){
+  ///     %val = addi %0, %1
+  ///     scf.reduce.return %val
+  ///   }
+  /// }
   /// Return %ret to user, while %val is provided by users (`reduc`)
-  SmallVector<Value, 2> exitForLoop(OpBuilder &builder, Location loc,
-                                    ArrayRef<Value> reduc);
+  void exitForLoop(RewriterBase &rewriter, Location loc,
+                   SmallVectorImpl<Value> &reduc);
 
   /// Exits a while loop, returns the reduction results.
-  SmallVector<Value, 2> exitCoiterationLoop(OpBuilder &builder, Location loc,
-                                            ArrayRef<Value> reduc);
+  void exitCoiterationLoop(OpBuilder &builder, Location loc,
+                           SmallVectorImpl<Value> &reduc);
 
   struct LoopLevelInfo {
     LoopLevelInfo(ArrayRef<size_t> tids, ArrayRef<size_t> dims, Operation *loop,
diff --git a/mlir/lib/Dialect/SparseTensor/Transforms/CodegenUtils.cpp b/mlir/lib/Dialect/SparseTensor/Transforms/CodegenUtils.cpp
--- a/mlir/lib/Dialect/SparseTensor/Transforms/CodegenUtils.cpp
+++ b/mlir/lib/Dialect/SparseTensor/Transforms/CodegenUtils.cpp
@@ -166,9 +166,12 @@
     OpBuilder &builder, Location loc, size_t tid, size_t dim,
     SmallVectorImpl<Value> &reduc, bool isParallel, ArrayRef<size_t> extraTids,
     ArrayRef<size_t> extraDims) {
+
   assert(dimTypes[tid].size() > dim);
   // We can not re-enter the same level.
   assert(!coord[tid][dim]);
+  // TODO: support multiple return on parallel for?
+  assert(!isParallel || reduc.empty() <= 1);
 
   Value step = constantIndex(builder, loc, 1);
   auto dimType = dimTypes[tid][dim];
@@ -182,11 +185,38 @@
   Value lo = isSparseInput ? pidxs[tid][dim]      // current offset
                            : loopSeqStack.back(); // univeral tid
   Value hi = highs[tid][dim];
+  Operation *loop = nullptr;
+  Value iv;
+  if (isParallel) {
+    scf::ParallelOp parOp =
+        builder.create<scf::ParallelOp>(loc, lo, hi, step, reduc);
+    builder.setInsertionPointToStart(parOp.getBody());
+    assert(parOp.getNumReductions() == reduc.size());
+    iv = parOp.getInductionVars()[0];
+
+    // In-place update on the reduction variable vector.
+    // Note that the init vals is not the actual reduction variables but instead
+    // used as a `special handle` to (temporally) represent them. The
+    // expression on init vals will be moved into scf.reduce and replaced with
+    // the block arguments when exiting the loop (see exitForLoop). This is
+    // needed as we can not build the actual reduction block and get the actual
+    // reduction varaible before users fill parallel loop body.
+    for (int i = 0, e = reduc.size(); i < e; i++)
+      reduc[i] = parOp.getInitVals()[i];
+    loop = parOp;
+  } else {
+    scf::ForOp forOp = builder.create<scf::ForOp>(loc, lo, hi, step, reduc);
+    builder.setInsertionPointToStart(forOp.getBody());
+    iv = forOp.getInductionVar();
+
+    // In-place update on the reduction variable vector.
+    assert(forOp.getNumRegionIterArgs() == reduc.size());
+    for (int i = 0, e = reduc.size(); i < e; i++)
+      reduc[i] = forOp.getRegionIterArg(i);
+    loop = forOp;
+  }
+  assert(loop && iv);
 
-  scf::ForOp forOp = builder.create<scf::ForOp>(loc, lo, hi, step, reduc);
-  builder.setInsertionPointToStart(forOp.getBody());
-  Value iv = forOp.getInductionVar();
-  assert(iv);
   if (isSparseInput) {
     pidxs[tid][dim] = iv;
     // Generating a load on the indices array yields the coordinate.
@@ -203,16 +233,12 @@
 
   // NOTE: we can also prepares for next dim here in advance
   // Push the loop into stack
-  loopStack.emplace_back(ArrayRef<size_t>(tid), ArrayRef<size_t>(dim), forOp,
+  loopStack.emplace_back(ArrayRef<size_t>(tid), ArrayRef<size_t>(dim), loop,
                          coord[tid][dim]);
   // Emit extra locals.
   emitExtraLocalsForTensorsAtDenseDims(builder, loc, extraTids, extraDims);
 
-  // In-place update on the reduction variable vector.
-  assert(forOp.getNumRegionIterArgs() == reduc.size());
-  for (int i = 0, e = reduc.size(); i < e; i++)
-    reduc[i] = forOp.getRegionIterArg(i);
-  return forOp;
+  return loop;
 }
 
 Operation *SparseTensorLoopEmitter::enterCoiterationOverTensorsAtDims(
@@ -386,17 +412,68 @@
   }
 }
 
-SmallVector<Value, 2>
-SparseTensorLoopEmitter::exitForLoop(OpBuilder &builder, Location loc,
-                                     ArrayRef<Value> reduc) {
+void SparseTensorLoopEmitter::exitForLoop(RewriterBase &rewriter, Location loc,
+                                          SmallVectorImpl<Value> &reduc) {
   LoopLevelInfo &loopInfo = loopStack.back();
   auto &dims = loopStack.back().dims;
   auto &tids = loopStack.back().tids;
-  auto forOp = llvm::cast<scf::ForOp>(loopInfo.loop);
-  if (!reduc.empty()) {
-    assert(reduc.size() == forOp.getNumResults());
-    builder.setInsertionPointToEnd(forOp.getBody());
-    builder.create<scf::YieldOp>(loc, reduc);
+  auto forOp = llvm::dyn_cast<scf::ForOp>(loopInfo.loop);
+  if (forOp) {
+    if (!reduc.empty()) {
+      assert(reduc.size() == forOp.getNumResults());
+      rewriter.setInsertionPointToEnd(forOp.getBody());
+      rewriter.create<scf::YieldOp>(loc, reduc);
+    }
+    // Exit the loop.
+    rewriter.setInsertionPointAfter(forOp);
+    // In-place update reduction variables.
+    for (unsigned i = 0, e = forOp.getResults().size(); i < e; i++)
+      reduc[i] = forOp.getResult(i);
+  } else {
+    auto parOp = llvm::cast<scf::ParallelOp>(loopInfo.loop);
+    if (!reduc.empty()) {
+      assert(reduc.size() == parOp.getInitVals().size() && reduc.size() == 1);
+      Operation *redExp = reduc.front().getDefiningOp();
+      // reduction expression should have no use.
+      assert(redExp->getUses().empty());
+      // this must be a binary operation.
+      // This is users' responsibilty to ensure the operation are commutative.
+      assert(redExp->getNumOperands() == 2 && redExp->getNumResults() == 1);
+
+      Value redVal = parOp.getInitVals().front();
+      Value curVal;
+      if (redExp->getOperand(0) == redVal)
+        curVal = redExp->getOperand(1);
+      else if (redExp->getOperand(1) == redVal)
+        curVal = redExp->getOperand(0);
+      // one of the operands must be the init value (which is also the
+      // previous reduction value).
+      assert(curVal);
+      // the reduction expression should be the only user of the reduction val
+      // inside the parallel for.
+      unsigned numUsers = 0;
+      for (Operation *op : redVal.getUsers()) {
+        if (op->getParentOp() == parOp)
+          numUsers++;
+      }
+      assert(numUsers == 1);
+      (void)numUsers; // to silence unused variable warning in release build
+      rewriter.setInsertionPointAfter(redExp);
+      auto redOp = rewriter.create<scf::ReduceOp>(loc, curVal);
+      redExp->remove(); // detach from previous parents
+      // Attach to the reduction op.
+      Block *redBlock = &redOp.getRegion().getBlocks().front();
+      redBlock->push_back(redExp);
+      // replaced arguments
+      rewriter.updateRootInPlace(
+          redExp, [&]() { redExp->setOperands(redBlock->getArguments()); });
+      rewriter.setInsertionPointToEnd(redBlock);
+      rewriter.create<scf::ReduceReturnOp>(loc, redExp->getResult(0));
+    }
+    rewriter.setInsertionPointAfter(parOp);
+    // In-place update reduction variables.
+    for (unsigned i = 0, e = parOp.getResults().size(); i < e; i++)
+      reduc[i] = parOp.getResult(i);
   }
 
   // Finished iterating a tensor, clean up
@@ -410,14 +487,10 @@
     if (!isDenseDim(dimTypes[tid][dim]))
       highs[tid][dim] = Value();
   }
-  // exit the loop
-  builder.setInsertionPointAfter(forOp);
-  return forOp.getResults();
 }
 
-SmallVector<Value, 2>
-SparseTensorLoopEmitter::exitCoiterationLoop(OpBuilder &builder, Location loc,
-                                             ArrayRef<Value> reduc) {
+void SparseTensorLoopEmitter::exitCoiterationLoop(
+    OpBuilder &builder, Location loc, SmallVectorImpl<Value> &reduc) {
   auto whileOp = llvm::cast<scf::WhileOp>(loopStack.back().loop);
   auto &dims = loopStack.back().dims;
   auto &tids = loopStack.back().tids;
@@ -451,10 +524,10 @@
   }
 
   // Reduction value from users.
-  SmallVector<Value, 2> ret;
-  for (auto red : reduc) {
-    operands.push_back(red);
-    ret.push_back(whileOp->getResult(o++));
+  for (unsigned i = 0, e = reduc.size(); i < e; i++) {
+    operands.push_back(reduc[i]);
+    // In place update reduction variable.
+    reduc[i] = whileOp->getResult(o++);
   }
 
   // An (optional) universal index.
@@ -469,26 +542,24 @@
   assert(o == operands.size());
   builder.create<scf::YieldOp>(loc, operands);
   builder.setInsertionPointAfter(whileOp);
-  return ret;
 }
 
-SmallVector<Value, 2>
-SparseTensorLoopEmitter::exitCurrentLoop(OpBuilder &builder, Location loc,
-                                         ArrayRef<Value> reduc) {
+void SparseTensorLoopEmitter::exitCurrentLoop(RewriterBase &rewriter,
+                                              Location loc,
+                                              SmallVectorImpl<Value> &reduc) {
   // Clean up the values, it would help use to discover potential bug at a
   // earlier stage (instead of silently using a wrong value).
   LoopLevelInfo &loopInfo = loopStack.back();
   assert(loopInfo.tids.size() == loopInfo.dims.size());
   SmallVector<Value, 2> red;
   if (llvm::isa<scf::WhileOp>(loopInfo.loop)) {
-    red = exitCoiterationLoop(builder, loc, reduc);
+    exitCoiterationLoop(rewriter, loc, reduc);
   } else {
-    red = exitForLoop(builder, loc, reduc);
+    exitForLoop(rewriter, loc, reduc);
   }
 
   assert(loopStack.size() == loopSeqStack.size());
   loopStack.pop_back();
-  return red;
 }
 
 //===----------------------------------------------------------------------===//
diff --git a/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorRewriting.cpp b/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorRewriting.cpp
--- a/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorRewriting.cpp
+++ b/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorRewriting.cpp
@@ -500,7 +500,7 @@
     rewriter.eraseOp(srcBlock->getTerminator());
 
     for (int64_t i = 0; i < rank; i++) {
-      loopEmitter.exitCurrentLoop(rewriter, loc);
+      loopEmitter.exitCurrentLoop(rewriter, loc, reduc);
       loopEmitter.exitCurrentLoopSeq();
     }
 
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
@@ -473,6 +473,25 @@
 // Sparse compiler synthesis methods (statements and expressions).
 //===----------------------------------------------------------------------===//
 
+/// Generates stmts that updates reduction varaibles.
+static void
+genReducUpdateStmt(CodeGen &codegen, Merger &merger,
+                   function_ref<void(SmallVectorImpl<Value> &reduc)> callback) {
+  SmallVector<Value, 4> reduc;
+  if (codegen.redVal)
+    reduc.push_back(codegen.redVal);
+  if (codegen.expValues)
+    reduc.push_back(codegen.expCount);
+
+  callback(reduc);
+
+  // Callback should do in-place update on reduction value vector.
+  if (codegen.redVal)
+    updateReduc(merger, codegen, reduc.front());
+  if (codegen.expValues)
+    codegen.expCount = reduc.back();
+}
+
 /// Local bufferization of all dense and sparse data structures.
 static void genBuffers(Merger &merger, CodeGen &codegen, OpBuilder &builder,
                        linalg::GenericOp op) {
@@ -1005,8 +1024,7 @@
 /// Returns parallelization strategy. Any implicit loop in the Linalg
 /// operation that is marked "parallel" is a candidate. Whether it is actually
 /// converted to a parallel operation depends on the requested strategy.
-static bool isParallelFor(CodeGen &codegen, bool isOuter, bool isReduction,
-                          bool isSparse) {
+static bool isParallelFor(CodeGen &codegen, bool isOuter, bool isSparse) {
   // Reject parallelization of sparse output.
   if (codegen.sparseOut)
     return false;
@@ -1015,13 +1033,14 @@
   case SparseParallelizationStrategy::kNone:
     return false;
   case SparseParallelizationStrategy::kDenseOuterLoop:
-    return isOuter && !isSparse && !isReduction;
+    // We do not support parallel reduction on tensor expansion.
+    return isOuter && !isSparse && !codegen.expCount;
   case SparseParallelizationStrategy::kAnyStorageOuterLoop:
-    return isOuter && !isReduction;
+    return isOuter && !codegen.expCount;
   case SparseParallelizationStrategy::kDenseAnyLoop:
-    return !isSparse && !isReduction;
+    return !isSparse && !codegen.expCount;
   case SparseParallelizationStrategy::kAnyStorageAnyLoop:
-    return !isReduction;
+    return !codegen.expCount;
   }
   llvm_unreachable("unexpected parallelization strategy");
 }
@@ -1034,28 +1053,16 @@
                          ArrayRef<size_t> extraDims) {
   Location loc = op.getLoc();
   auto iteratorTypes = op.getIteratorTypesArray();
-  bool isReduction = linalg::isReductionIterator(iteratorTypes[idx]);
   bool isSparse = merger.isDimLevelType(tid, idx, DimLvlType::kCompressed) ||
                   merger.isDimLevelType(tid, idx, DimLvlType::kSingleton);
-  bool isParallel = isParallelFor(codegen, isOuter, isReduction, isSparse);
-  assert(!isParallel);
-
-  // Emit a sequential or vector loop.
-  SmallVector<Value, 4> operands;
-  if (codegen.redVal)
-    operands.push_back(codegen.redVal);
-  if (codegen.expValues)
-    operands.push_back(codegen.expCount);
-
-  Operation *loop = codegen.loopEmitter.enterLoopOverTensorAtDim(
-      builder, loc, tid, dim, operands, false, extraTids, extraDims);
-
-  // The operands should be updated by loop emitter already.
-  if (codegen.redVal)
-    updateReduc(merger, codegen, operands.front());
-  if (codegen.expValues)
-    codegen.expCount = operands.back();
-
+  bool isParallel = isParallelFor(codegen, isOuter, isSparse);
+
+  Operation *loop = nullptr;
+  genReducUpdateStmt(codegen, merger, [&](SmallVectorImpl<Value> &reduc) {
+    loop = codegen.loopEmitter.enterLoopOverTensorAtDim(
+        builder, loc, tid, dim, reduc, isParallel, extraTids, extraDims);
+  });
+  assert(loop);
   return loop;
 }
 
@@ -1066,23 +1073,14 @@
                            ArrayRef<size_t> extraTids,
                            ArrayRef<size_t> extraDims) {
 
-  SmallVector<Value, 4> operands;
-  // Construct the while-loop with a parameter for each index.
-
-  if (codegen.redVal)
-    operands.push_back(codegen.redVal);
-  if (codegen.expValues)
-    operands.push_back(codegen.expCount);
-
-  Operation *loop = codegen.loopEmitter.enterCoiterationOverTensorsAtDims(
-      builder, op.getLoc(), condTids, condDims, operands, needsUniv, extraTids,
-      extraDims);
-
-  if (codegen.redVal)
-    updateReduc(merger, codegen, operands.front());
-  if (codegen.expValues)
-    codegen.expCount = operands.back();
-
+  Operation *loop = nullptr;
+  genReducUpdateStmt(codegen, merger, [&](SmallVectorImpl<Value> &reduc) {
+    // Construct the while-loop with a parameter for each index.
+    loop = codegen.loopEmitter.enterCoiterationOverTensorsAtDims(
+        builder, op.getLoc(), condTids, condDims, reduc, needsUniv, extraTids,
+        extraDims);
+  });
+  assert(loop);
   return loop;
 }
 
@@ -1300,33 +1298,20 @@
 }
 
 /// Ends a single loop in current sequence. Returns new values for needsUniv.
-static bool endLoop(Merger &merger, CodeGen &codegen, OpBuilder &builder,
+static bool endLoop(Merger &merger, CodeGen &codegen, RewriterBase &rewriter,
                     linalg::GenericOp op, Operation *loop, unsigned idx,
                     unsigned li, bool needsUniv) {
-  codegen.curVecLength = 1;
-
   // End a while-loop.
   if (auto whileOp = dyn_cast<scf::WhileOp>(loop)) {
-    finalizeWhileOp(merger, codegen, builder, op, idx, needsUniv,
+    finalizeWhileOp(merger, codegen, rewriter, op, idx, needsUniv,
                     merger.lat(li).bits, whileOp);
   } else {
     needsUniv = false;
   }
 
-  SmallVector<Value, 2> reduc;
-  if (codegen.redVal)
-    reduc.push_back(codegen.redVal);
-  if (codegen.expValues)
-    reduc.push_back(codegen.expCount);
-
-  auto loopRet =
-      codegen.loopEmitter.exitCurrentLoop(builder, op.getLoc(), reduc);
-  assert(reduc.size() == loopRet.size());
-
-  if (codegen.redVal)
-    updateReduc(merger, codegen, loopRet.front());
-  if (codegen.expValues)
-    codegen.expCount = loopRet.back();
+  genReducUpdateStmt(codegen, merger, [&](SmallVectorImpl<Value> &reduc) {
+    codegen.loopEmitter.exitCurrentLoop(rewriter, op.getLoc(), reduc);
+  });
 
   return needsUniv;
 }
diff --git a/mlir/test/Dialect/SparseTensor/sparse_parallel.mlir b/mlir/test/Dialect/SparseTensor/sparse_parallel.mlir
--- a/mlir/test/Dialect/SparseTensor/sparse_parallel.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_parallel.mlir
@@ -1,14 +1,14 @@
 // RUN: mlir-opt %s -sparsification="parallelization-strategy=none" | \
 // RUN:   FileCheck %s --check-prefix=CHECK-PAR0
 // FIXME: we do not support vectorization/parallel loops in loop emitter right now
-// R_U_N: mlir-opt %s -sparsification="parallelization-strategy=dense-outer-loop" | \
-// R_U_N:   FileCheck %s --check-prefix=CHECK-PAR1
-// R_U_N: mlir-opt %s -sparsification="parallelization-strategy=any-storage-outer-loop" | \
-// R_U_N:   FileCheck %s --check-prefix=CHECK-PAR2
-// R_U_N: mlir-opt %s -sparsification="parallelization-strategy=dense-any-loop" | \
-// R_U_N:   FileCheck %s --check-prefix=CHECK-PAR3
-// R_U_N: mlir-opt %s -sparsification="parallelization-strategy=any-storage-any-loop" | \
-// R_U_N:   FileCheck %s --check-prefix=CHECK-PAR4
+// RUN: mlir-opt %s -sparsification="parallelization-strategy=dense-outer-loop" | \
+// RUN:   FileCheck %s --check-prefix=CHECK-PAR1
+// RUN: mlir-opt %s -sparsification="parallelization-strategy=any-storage-outer-loop" | \
+// RUN:   FileCheck %s --check-prefix=CHECK-PAR2
+// RUN: mlir-opt %s -sparsification="parallelization-strategy=dense-any-loop" | \
+// RUN:   FileCheck %s --check-prefix=CHECK-PAR3
+// RUN: mlir-opt %s -sparsification="parallelization-strategy=any-storage-any-loop" | \
+// RUN:   FileCheck %s --check-prefix=CHECK-PAR4
 
 #DenseMatrix = #sparse_tensor.encoding<{
   dimLevelType = [ "dense", "dense" ]
@@ -151,7 +151,8 @@
 //
 // CHECK-PAR4-LABEL: func @matvec
 // CHECK-PAR4:         scf.parallel
-// CHECK-PAR4:           scf.for
+// CHECK-PAR4:           scf.parallel
+// CHECK-PAR4:             scf.reduce
 // CHECK-PAR4:         return
 //
 func.func @matvec(%arga: tensor<16x32xf32, #CSR>,
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_matvec.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_matvec.mlir
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_matvec.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_matvec.mlir
@@ -5,6 +5,14 @@
 // RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 //
+// Do the same run, but now with parallization
+// RUN: mlir-opt %s \
+// RUN:   --sparse-compiler="parallelization-strategy=any-storage-any-loop" | \
+// RUN: TENSOR0="%mlir_src_dir/test/Integration/data/wide.mtx" \
+// RUN: mlir-cpu-runner \
+// RUN:  -e entry -entry-point-result=void  \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN: FileCheck %s
 // Do the same run, but now with SIMDization as well. This should not change the outcome.
 // FIXME: support vector in sparse loop emitter.
 // R_U_N: mlir-opt %s \
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_spmm.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_spmm.mlir
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_spmm.mlir
+++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_spmm.mlir
@@ -6,13 +6,13 @@
 // RUN: FileCheck %s
 //
 // Do the same run, but now with SIMDization as well. This should not change the outcome.
-// FIXME: we do not support vectorization/parallel loops in loop emitter right now
-// R_U_N: mlir-opt %s --sparse-compiler="vectorization-strategy=any-storage-inner-loop vl=2" | \
-// R_U_N: TENSOR0="%mlir_src_dir/test/Integration/data/wide.mtx" \
-// R_U_N: mlir-cpu-runner \
-// R_U_N:  -e entry -entry-point-result=void  \
-// R_U_N:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
-// R_U_N: FileCheck %s
+//
+// RUN: mlir-opt %s --sparse-compiler="vectorization-strategy=any-storage-inner-loop vl=2" | \
+// RUN: TENSOR0="%mlir_src_dir/test/Integration/data/wide.mtx" \
+// RUN: mlir-cpu-runner \
+// RUN:  -e entry -entry-point-result=void  \
+// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN: FileCheck %s
 
 !Filename = !llvm.ptr<i8>