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
@@ -856,6 +856,48 @@
   }
 };
 
+struct TileConverter : public OpConversionPattern<tosa::TileOp> {
+  using OpConversionPattern<tosa::TileOp>::OpConversionPattern;
+
+  LogicalResult
+  matchAndRewrite(tosa::TileOp op, ArrayRef<Value> args,
+                  ConversionPatternRewriter &rewriter) const override {
+    auto input = op.input1();
+    auto inputTy = input.getType().cast<ShapedType>();
+    auto inputShape = inputTy.getShape();
+    auto resultTy = op.getType().cast<ShapedType>();
+    auto resultShape = resultTy.getShape();
+    int64_t rank = inputTy.getRank();
+
+    if (!inputTy.hasStaticShape() || !resultTy.hasStaticShape())
+      return failure();
+
+    SmallVector<AffineExpr, 2> inputExprs;
+    inputExprs.reserve(rank);
+
+    for (int64_t i = 0; i < rank; i++)
+      inputExprs.push_back(rewriter.getAffineDimExpr(i) %
+                           rewriter.getAffineConstantExpr(inputShape[i]));
+
+    auto initTensor = rewriter.create<linalg::InitTensorOp>(
+        op.getLoc(), ArrayRef<Value>({}), resultShape,
+        resultTy.getElementType());
+
+    SmallVector<AffineMap, 2> affineMaps = {
+        AffineMap::get(resultTy.getRank(), /*symbolCount=*/0, inputExprs,
+                       rewriter.getContext()),
+        rewriter.getMultiDimIdentityMap(resultTy.getRank())};
+
+    rewriter.replaceOpWithNewOp<linalg::GenericOp>(
+        op, resultTy, op.input1(), ValueRange{initTensor}, affineMaps,
+        getNParallelLoopsAttrs(resultTy.getRank()),
+        [&](OpBuilder &nestedBuilder, Location nestedLoc, ValueRange args) {
+          nestedBuilder.create<linalg::YieldOp>(op.getLoc(), *args.begin());
+        });
+    return success();
+  }
+};
+
 } // namespace
 
 void mlir::tosa::populateTosaToLinalgOnTensorsConversionPatterns(
@@ -880,5 +922,6 @@
       IdentityNConverter<tosa::IdentityNOp>, ReduceConverter<tosa::ReduceMinOp>,
       ReduceConverter<tosa::ReduceMaxOp>, ReduceConverter<tosa::ReduceSumOp>,
       ReduceConverter<tosa::ReduceProdOp>, ConcatOpConversion,
-      ReshapeOpConverter, TransposeConverter, RescaleOpConverter>(context);
+      ReshapeOpConverter, TileConverter, TransposeConverter,
+      RescaleOpConverter>(context);
 }
diff --git a/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg.mlir b/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg.mlir
--- a/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg.mlir
+++ b/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg.mlir
@@ -524,3 +524,25 @@
   %0 = "tosa.rescale"(%arg0) {input_zp = 243 : i32, output_zp = 252 : i32, multiplier = [19689 : i32], shift = [15 : i32], scale32 = true, double_round = true, per_channel = false} : (tensor<1xi8>)  -> (tensor<1xi8>)
   return %0 : tensor<1xi8>
 }
+
+// -----
+
+// CHECK: #[[$MAP0:.*]] = affine_map<(d0, d1) -> (d0 mod 2, d1 mod 3)>
+// CHECK: #[[$MAP1:.*]] = affine_map<(d0, d1) -> (d0, d1)>
+
+// CHECK-LABEL: @tile
+func @tile(%arg0 : tensor<2x3xi8>) -> () {
+  // CHECK: [[INIT:%.+]] = linalg.init_tensor [4, 3]
+  // CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#map0, #map1], iterator_types = ["parallel", "parallel"]} ins(%arg0 : tensor<2x3xi8>) outs([[INIT]] : tensor<4x3xi8>)
+  %0 = "tosa.tile"(%arg0) {multiples = [2, 1]} : (tensor<2x3xi8>)  -> (tensor<4x3xi8>)
+
+  // CHECK: linalg.init_tensor
+  // CHECK: linalg.generic
+  %1 = "tosa.tile"(%arg0) {multiples = [1, 2]} : (tensor<2x3xi8>)  -> (tensor<2x6xi8>)
+
+  // CHECK: linalg.init_tensor
+  // CHECK: linalg.generic
+  %2 = "tosa.tile"(%arg0) {multiples = [5, 7]} : (tensor<2x3xi8>)  -> (tensor<10x21xi8>)
+
+  return
+}