diff --git a/include/aidge/backend/cpu/operator/ScalingImpl_forward_kernels.hpp b/include/aidge/backend/cpu/operator/ScalingImpl_forward_kernels.hpp
index 5258c4c3e7376c3883b119503ee9e6765de844d5..df8e1a7e7b02a4ad032d6f09fae3ae2cd8a42eff 100644
--- a/include/aidge/backend/cpu/operator/ScalingImpl_forward_kernels.hpp
+++ b/include/aidge/backend/cpu/operator/ScalingImpl_forward_kernels.hpp
@@ -9,13 +9,12 @@
  *
  ********************************************************************************/
 
-#ifndef AIDGE_CPU_OPERATOR_SCALINGIMPL_FORWARD_KERNEL_H
-#define AIDGE_CPU_OPERATOR_SCALINGIMPL_FORWARD_KERNEL_H
+#ifndef AIDGE_CPU_OPERATOR_SCALINGIMPL_FORWARD_KERNEL_H_
+#define AIDGE_CPU_OPERATOR_SCALINGIMPL_FORWARD_KERNEL_H_
 
 #include <cmath>
-
+#include <cstddef>
 #include "aidge/utils/Registrar.hpp"
-
 #include "aidge/backend/cpu/operator/ScalingImpl.hpp"
 
 //TODO : improve propagate, n2d2 :
@@ -61,12 +60,13 @@ const O& clamp(const O& x, const O& min, const O& max)
 }
 
 template<class O>
-O saturate(O value, std::size_t quantizedNbBits, bool isOutputUnsigned) {
+O saturate(const O value, const std::size_t quantizedNbBits, const bool isOutputUnsigned) {
+    // TODO: no assertions in kernel
     assert(quantizedNbBits > 0);
 
-    const O min = isOutputUnsigned?0:
+    const O min = isOutputUnsigned ? 0 :
                                   -(1ll << (quantizedNbBits - 1ll));
-    const O max = isOutputUnsigned?(1ll << quantizedNbBits) - 1ll:
+    const O max = isOutputUnsigned ? (1ll << quantizedNbBits) - 1ll :
                                    (1ll << (quantizedNbBits - 1ll)) - 1ll;
 
     return clamp(value, min, max);
@@ -81,8 +81,8 @@ void ScalingImpl_cpu_forward_kernel(const Scaling_Op::Attrs& attrs,
     const I* input = static_cast<const I*>(input_);
     O* output = static_cast<O*>(output_);
     const I& scalingFactor = static_cast<const I&>(std::get<0>(attrs));
-    std::size_t quantizedNbBits = static_cast<std::size_t>(std::get<1>(attrs));
-    bool isOutputUnsigned = static_cast<bool>(std::get<2>(attrs));
+    const std::size_t quantizedNbBits = static_cast<std::size_t>(std::get<1>(attrs));
+    const bool isOutputUnsigned = static_cast<bool>(std::get<2>(attrs));
 
     for (std::size_t i = 0; i < inputLenght; ++i) {
         output[i] = input[i] * scalingFactor;
@@ -103,4 +103,4 @@ static Registrar<ScalingImplForward_cpu> registrarScalingImplForward_cpu_Float64
 }  // namespace
 }  // namespace Aidge
 
-#endif /* AIDGE_CPU_OPERATOR_SCALINGIMPL_FORWARD_KERNEL_H */
+#endif /* AIDGE_CPU_OPERATOR_SCALINGIMPL_FORWARD_KERNEL_H_ */
\ No newline at end of file
diff --git a/include/aidge/backend/cpu/operator/SliceImpl.hpp b/include/aidge/backend/cpu/operator/SliceImpl.hpp
index 56fdf8b60977527382e0ad916d0dfdabc5db2846..80e2f0fcef83a369561095f8e55a437f7acc9675 100644
--- a/include/aidge/backend/cpu/operator/SliceImpl.hpp
+++ b/include/aidge/backend/cpu/operator/SliceImpl.hpp
@@ -68,4 +68,4 @@ static Registrar<Slice_Op> registrarSliceImpl_cpu("cpu", Aidge::SliceImpl_cpu::c
 }  // namespace
 }  // namespace Aidge
 
-#endif /* AIDGE_CPU_OPERATOR_LEAKYRELUIMPL_H_ */
+#endif /* AIDGE_CPU_OPERATOR_LEAKYRELUIMPL_H_ */
\ No newline at end of file
diff --git a/unit_tests/recipies/Test_HorizontalTiling.cpp b/unit_tests/recipies/Test_HorizontalTiling.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..b71a01d130a783caf5c643dfb0c3757b1c524e5e
--- /dev/null
+++ b/unit_tests/recipies/Test_HorizontalTiling.cpp
@@ -0,0 +1,208 @@
+/********************************************************************************
+ * Copyright (c) 2023 CEA-List
+ *
+ * This program and the accompanying materials are made available under the
+ * terms of the Eclipse Public License 2.0 which is available at
+ * http://www.eclipse.org/legal/epl-2.0.
+ *
+ * SPDX-License-Identifier: EPL-2.0
+ *
+ ********************************************************************************/
+
+#include <catch2/catch_test_macros.hpp>
+#include <set>
+
+#include "aidge/graph/GraphView.hpp"
+#include "aidge/graph/OpArgs.hpp"
+#include "aidge/operator/Conv.hpp"
+#include "aidge/operator/ReLU.hpp"
+#include "aidge/recipies/Recipies.hpp"
+#include "aidge/scheduler/Scheduler.hpp"
+#include "aidge/operator/Concat.hpp"
+
+
+namespace Aidge {
+
+TEST_CASE("[core/recipies] Tiling(transformation)", "[Tiling][Recipies]") {
+
+    SECTION("Transform a pre-generated GraphView") {
+
+        SECTION("Simple Node: Conv") {
+            std::shared_ptr<Node> myReLU = ReLU("myReLU");
+            std::shared_ptr<Node> myConv = Conv(3,4,{3,3}, "myconv");
+            std::shared_ptr<Tensor> myWeights = std::make_shared<Tensor>(Array4D<int,4,3,3,3> {
+                {
+                    {
+                        {{  0,   1,   2},
+                         {  3,   4,   5},
+                         {  6,   7,   8}},
+                        {{  9,  10,  11},
+                         { 12,  13,  14},
+                         { 15,  16,  17}},
+                        {{ 18,  19,  20},
+                         { 21,  22,  23},
+                         { 24,  25,  26}}
+                    },
+                    {
+                        {{ 27,  28,  29},
+                         { 30,  31,  32},
+                         { 33,  34,  35}},
+                        {{ 36,  37,  38},
+                         { 39,  40,  41},
+                         { 42,  43,  44}},
+                        {{ 45,  46,  47},
+                         { 48,  49,  50},
+                         { 51,  52,  53}}
+                    },
+                    {
+                        {{ 54,  55,  56},
+                         { 57,  58,  59},
+                         { 60,  61,  62}},
+                        {{ 63,  64,  65},
+                         { 66,  67,  68},
+                         { 69,  70,  71}},
+                        {{ 72,  73,  74},
+                         { 75,  76,  77},
+                         { 78,  79,  80}}
+                    },
+                    {
+                        {{ 81,  82,  83},
+                         { 84,  85,  86},
+                         { 87,  88,  89}},
+                        {{ 90,  91,  92},
+                         { 93,  94,  95},
+                         { 96,  97,  98}},
+                        {{ 99, 100, 101},
+                         {102, 103, 104},
+                         {105, 106, 107}}
+                    }
+                }
+            });
+            std::shared_ptr<Tensor> myBias = std::make_shared<Tensor>(Array1D<int,4> {{7,0,9,0}});
+            std::shared_ptr<Tensor> myInput = std::make_shared<Tensor>(Array4D<int,2,3,5,5> { //NCHW
+                {
+                    {
+                        {{  0,   1,   2,   3,   4},
+                        {  5,   6,   7,   8,   9},
+                        { 10,  11,  12,  13,  14},
+                        { 15,  16,  17,  18,  19},
+                        { 20,  21,  22,  23,  24}},
+
+                        {{ 25,  26,  27,  28,  29},
+                        { 30,  31,  32,  33,  34},
+                        { 35,  36,  37,  38,  39},
+                        { 40,  41,  42,  43,  44},
+                        { 45,  46,  47,  48,  49}},
+
+                        {{ 50,  51,  52,  53,  54},
+                        { 55,  56,  57,  58,  59},
+                        { 60,  61,  62,  63,  64},
+                        { 65,  66,  67,  68,  69},
+                        { 70,  71,  72,  73,  74}}
+                    },
+                    {
+                        {{ 75,  76,  77,  78,  79},
+                        { 80,  81,  82,  83,  84},
+                        { 85,  86,  87,  88,  89},
+                        { 90,  91,  92,  93,  94},
+                        { 95,  96,  97,  98,  99}},
+
+                        {{100, 101, 102, 103, 104},
+                        {105, 106, 107, 108, 109},
+                        {110, 111, 112, 113, 114},
+                        {115, 116, 117, 118, 119},
+                        {120, 121, 122, 123, 124}},
+
+                        {{125, 126, 127, 128, 129},
+                        {130, 131, 132, 133, 134},
+                        {135, 136, 137, 138, 139},
+                        {140, 141, 142, 143, 144},
+                        {145, 146, 147, 148, 149}}
+                    }
+                }
+            });
+            std::shared_ptr<Tensor> myOutput = std::make_shared<Tensor>(Array4D<int,2,4,3,3> {
+                {
+                    {
+                        {{ 15226,  15577,  15928},
+                         { 16981,  17332,  17683},
+                         { 18736,  19087,  19438}},
+
+                        {{ 37818,  38898,  39978},
+                         { 43218,  44298,  45378},
+                         { 48618,  49698,  50778}},
+
+                        {{ 60426,  62235,  64044},
+                         { 69471,  71280,  73089},
+                         { 78516,  80325,  82134}},
+
+                        {{ 83016,  85554,  88092},
+                         { 95706,  98244, 100782},
+                         {108396, 110934, 113472}}
+                    },
+                    {
+                        {{ 41551,  41902,  42253},
+                         { 43306,  43657,  44008},
+                         { 45061,  45412,  45763}},
+
+                        {{118818, 119898, 120978},
+                         {124218, 125298, 126378},
+                         {129618, 130698, 131778}},
+
+                        {{196101, 197910, 199719},
+                         {205146, 206955, 208764},
+                         {214191, 216000, 217809}},
+
+                        {{273366, 275904, 278442},
+                         {286056, 288594, 291132},
+                         {298746, 301284, 303822}}
+                    }
+                }
+            });
+            myReLU->getOperator()->associateInput(0, myInput);
+            myReLU->addChild(myConv, 0, 0);
+            myConv->getOperator()->setInput(1, myWeights);
+            myConv->getOperator()->setInput(2, myBias);
+            std::dynamic_pointer_cast<Conv_Op<2>>(myConv->getOperator())->computeOutputDims();
+
+            std::shared_ptr<GraphView> g = std::make_shared<GraphView>();
+            g->add({myReLU, myConv});
+            g->compile("cpu", DataType::Int32);
+            std::set<std::shared_ptr<Node>> tiledConv = getConvHorizontalTiling(myConv, 2, 3);
+
+            SequentialScheduler s(g);
+            s.forward();
+            REQUIRE(*(std::dynamic_pointer_cast<Conv_Op<2>>(myConv->getOperator())->getOutput(0)) == *myOutput);
+
+            GraphView::replace({myConv, myConv->getParent(1), myConv->getParent(2)}, tiledConv);
+            g->compile("cpu", DataType::Int32);
+            s.resetScheduling();
+            s.forward();
+
+            REQUIRE(*(std::dynamic_pointer_cast<OperatorTensor>((*g->outputNodes().begin())->getOperator())->getOutput(0)) == *myOutput);
+        }
+    }
+}
+}
+        // std::shared_ptr<GraphView> g = Sequential({
+        //     Conv(3, 16, {3,3}, "conv1"),
+        //     ReLU("relu1"),
+        //     Conv(16, 32, {1,1}, "conv2"),
+        //     Conv(32, 16, {1,1}, "conv3"),
+        //     Conv(16, 10, {3,3}, "conv4"),
+        //     ReLU("relu2")
+        // });
+
+    //     for (auto& individualConv : g->match("Conv")) {
+    //         auto tiledConv = horizontalTiling(individualConv);
+    //         g->replace(individualConv, tiledConv);
+    //     }
+    // }
+
+    // SECTION("Create the GraphView with tiled layers") {
+    //     std::shared_ptr<GraphView> g;
+    //     g->addChild(horizontalTiling(Conv()))
+    // }
+
+// }
+// } // namespace Aidge
\ No newline at end of file