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diff --git a/runtimes/neurun/src/kernel/cpu/MaxPoolLayer.cc b/runtimes/neurun/src/kernel/cpu/MaxPoolLayer.cc
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+++ b/runtimes/neurun/src/kernel/cpu/MaxPoolLayer.cc
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+/*
+ * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "MaxPoolLayer.h"
+
+#include "tensorflow/contrib/lite/kernels/internal/optimized/optimized_ops.h"
+#include "kernel/cpu/OperationUtils.h"
+
+namespace neurun
+{
+namespace kernel
+{
+namespace cpu
+{
+
+#define MAXPOOLING_PARAMETERS                               \
+  uint32_t height = getSizeOfDimension(_inputShape, 1);     \
+  uint32_t width = getSizeOfDimension(_inputShape, 2);      \
+  uint32_t outHeight = getSizeOfDimension(_outputShape, 1); \
+  uint32_t outWidth = getSizeOfDimension(_outputShape, 2);  \
+                                                            \
+  uint32_t paddingHeight = (uint32_t)_paddingTop;           \
+  uint32_t paddingWidth = (uint32_t)_paddingLeft;
+
+MaxPoolLayer::MaxPoolLayer()
+    : _inputData(nullptr), _outputData(nullptr), _inputShape(), _outputShape(), _paddingLeft(0),
+      _paddingTop(0), _paddingRight(0), _paddingBottom(0), _strideWidth(0), _strideHeight(0),
+      _kernelWidth(0), _kernelHeight(0), _activation(ANEURALNETWORKS_FUSED_NONE),
+      _inputType(OperandType::SCALAR_FLOAT32)
+{
+  // DO NOTHING
+}
+
+bool MaxPoolLayer::maxPoolFloat32()
+{
+
+  MAXPOOLING_PARAMETERS
+  float output_activation_min, output_activation_max;
+  CalculateActivationRangeFloat(_activation, &output_activation_min, &output_activation_max);
+
+  ::tflite::optimized_ops::MaxPool(
+      reinterpret_cast<const float *>(_inputData), convertShapeToDims(_inputShape), _strideWidth,
+      _strideHeight, paddingWidth, paddingHeight, _kernelWidth, _kernelHeight,
+      output_activation_min, output_activation_max, reinterpret_cast<float *>(_outputData),
+      convertShapeToDims(_outputShape));
+  return true;
+}
+bool MaxPoolLayer::maxPoolQuant8()
+{
+
+  MAXPOOLING_PARAMETERS
+  int32_t output_activation_min = 0;
+  int32_t output_activation_max = 0;
+  CalculateActivationRangeUint8(_activation, _outputShape, &output_activation_min,
+                                &output_activation_max);
+
+  ::tflite::optimized_ops::MaxPool(_inputData, convertShapeToDims(_inputShape), _strideWidth,
+                                   _strideHeight, paddingWidth, paddingHeight, _kernelWidth,
+                                   _kernelHeight, output_activation_min, output_activation_max,
+                                   _outputData, convertShapeToDims(_outputShape));
+  return true;
+}
+
+void MaxPoolLayer::configure(uint8_t *inputData, const Shape inputShape, const uint32_t paddingLeft,
+                             const uint32_t paddingRight, const uint32_t paddingTop,
+                             const uint32_t paddingBottom, const uint32_t strideWidth,
+                             const uint32_t strideHeight, const uint32_t kernelWidth,
+                             const uint32_t kernelHeight, const FuseCode activation,
+                             uint8_t *outputData, const Shape outputShape)
+{
+  _inputData = inputData;
+
+  _inputShape = inputShape;
+  _inputType = inputShape.type;
+  _paddingLeft = paddingLeft;
+  _paddingRight = paddingRight;
+  _paddingTop = paddingTop;
+  _paddingBottom = paddingBottom;
+  _strideWidth = strideWidth;
+  _strideHeight = strideHeight;
+  _kernelWidth = kernelWidth;
+  _kernelHeight = kernelHeight;
+  _activation = activation;
+  _outputData = outputData;
+  _outputShape = outputShape;
+}
+
+void MaxPoolLayer::run()
+{
+  if (_inputType == OperandType::TENSOR_FLOAT32)
+  {
+    maxPoolFloat32();
+  }
+  else if (_inputType == OperandType::TENSOR_QUANT8_ASYMM)
+  {
+    throw std::runtime_error{"MaxPoolLayer : Not tested for TENSOR_QUANT8_ASYMM"};
+    // maxPoolQuant8();
+  }
+}
+
+#undef MAXPOOLING_PARAMETERS
+
+} // namespace cpu
+} // namespace kernel
+} // namespace neurun