diff --git a/src/core/CL/cl_kernels/dwc_native_quantized_nhwc.cl b/src/core/CL/cl_kernels/dwc_native_quantized_nhwc.cl
new file mode 100644
index 0000000..cd0f292
--- /dev/null
+++ b/src/core/CL/cl_kernels/dwc_native_quantized_nhwc.cl
@@ -0,0 +1,277 @@
+/*
+ * Copyright (c) 2021 Arm Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+
+#include "helpers.h"
+#include "tile_helpers.h"
+
+#define CALCULATE_WEIGHTS_OFFSET_CORRECTION(A_DATA_TYPE, B_DATA_TYPE) CALCULATE_WEIGHTS_OFFSET_CORRECTION_STR(A_DATA_TYPE, B_DATA_TYPE)
+#define CALCULATE_WEIGHTS_OFFSET_CORRECTION_STR(A_DATA_TYPE, B_DATA_TYPE) CALCULATE_WEIGHTS_OFFSET_CORRECTION_##A_DATA_TYPE##_##B_DATA_TYPE
+#define CALCULATE_WEIGHTS_OFFSET_CORRECTION_char_char (0)
+#define CALCULATE_WEIGHTS_OFFSET_CORRECTION_uchar_uchar (0)
+#define CALCULATE_WEIGHTS_OFFSET_CORRECTION_uchar_char (128)
+#define CALCULATE_WEIGHTS_OFFSET_CORRECTION_char_uchar (-128)
+
+#define T_LOAD_MULTIPLIERS_SHIFT_PER_TENSOR() \
+    ({})
+
+#define T_LOAD_MULTIPLIERS_SHIFT_PER_CHANNEL()                                                                           \
+    TILE(DST_MULTIPLIERS_DATA_TYPE, 1, N0, multipliers);                                                                 \
+    TILE(DST_SHIFTS_DATA_TYPE, 1, N0, shifts);                                                                           \
+    T_LOAD(DST_MULTIPLIERS_DATA_TYPE, 1, N0, BUFFER, dst_multipliers, cout *DEPTH_MULTIPLIER + d, 0, 0, 0, multipliers); \
+    T_LOAD(DST_SHIFTS_DATA_TYPE, 1, N0, BUFFER, dst_shifts, cout *DEPTH_MULTIPLIER + d, 0, 0, 0, shifts);
+
+#define T_LOAD_MULTIPLIERS_SHIFT(QUANTIZATION_TYPE) T_LOAD_MULTIPLIERS_SHIFT_STR(QUANTIZATION_TYPE)
+#define T_LOAD_MULTIPLIERS_SHIFT_STR(QUANTIZATION_TYPE) T_LOAD_MULTIPLIERS_SHIFT_##QUANTIZATION_TYPE()
+
+#if defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(DST_WIDTH) && defined(DST_HEIGHT) && defined(WEI_WIDTH) && defined(WEI_HEIGHT) && defined(N0) && defined(M0) && defined(DILATION_X) && defined(DILATION_Y) && defined(STRIDE_X) && defined(STRIDE_Y) && defined(PAD_LEFT) && defined(PAD_TOP)
+//! @cond Doxygen_Suppress
+/** OpenCL kernel to compute the depthwise convolution for quantized data types
+ *
+ * @note Data layout supported: NHWC
+ * @note Data type supported: QSYMM8/QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL
+ * @note The convolution padding (left and top) must be passed at compile time using -DPAD_LEFT and -DPAD_TOP (e.g. -DPAD_LEFT=2, -DPAD_TOP=2)
+ * @note The convolution strides must be passed at compile time using -DSTRIDE_X and -DSTRIDE_Y (e.g. -DSTRIDE_X=2, -DSTRIDE_Y=2)
+ * @note The convolution dilations must be passed at compile time using -DDILATION_X and -DDILATION_Y (e.g. -DDILATION_X=2, -DDILATION_Y=2)
+ * @note The spatial dimensions of the weights must be passed at compile time using -DWEI_WIDTH and -DWEI_HEIGHT (e.g. -DWEI_WIDTH=9, -DWEI_HEIGHT=9)
+ * @note The spatial dimensions of the source tensor must be passed at compile time using -DSRC_WIDTH and -DSRC_HEIGHT (e.g. -DSRC_WIDTH=96, -DSRC_HEIGHT=64)
+ * @note The spatial dimensions of the destination tensor must be passed at compile time using -DDST_WIDTH and -DDST_HEIGHT (e.g. -DDST_WIDTH=96, -DDST_HEIGHT=64)
+ * @note The channels of the source tensor must be passed at compile time using -DSRC_CHANNELS (e.g. -DSRC_CHANNELS=64)
+ * @note The channels of the destination tensor must be passed at compile time using -DDST_CHANNELS (e.g. -DDDST_CHANNELS=64)
+ * @note The tensor type ("BUFFER" or "IMAGE") of the source tensor must be passed at compile time using -DSRC_TENSOR_TYPE (e.g. -DSRC_TENSOR_TYPE=BUFFER)
+ * @note The tensor type ("BUFFER" or "IMAGE") of the weights tensor must be passed at compile time using -DWEI_TENSOR_TYPE (e.g. -DWEI_TENSOR_TYPE=BUFFER)
+ * @note The tensor type ("BUFFER" or "IMAGE") of the destination tensor must be passed at compile time using -DDST_TENSOR_TYPE (e.g. -DDST_TENSOR_TYPE=BUFFER)
+ * @note The data type of the source tensor must be passed at compile time using -DSRC_DATA_TYPE (e.g. -DSRC_DATA_TYPE=int8)
+ * @note The data type of the weights tensor must be passed at compile time using -DWEI_DATA_TYPE (e.g. -DWEI_DATA_TYPE=int8)
+ * @note The data type of the destination tensor must be passed at compile time using -DDST_DATA_TYPE (e.g. -DDST_DATA_TYPE=int8)
+ * @note The data type of the accumulators must be passed at compile time using -DACC_DATA_TYPE (e.g. -DACC_DATA_TYPE=int)
+ * @note The number of M0 rows (width) to process must be passed at compile time using -DM0 (e.g. -DM0=2)
+ * @note The number of N0 output channels to process must be passed at compile time using -DN0 (e.g. -DN0=2)
+ * @note The size of the partial store block in the first dimension must be passed at compile time using -DPARTIAL_N0 (e.g. -DPARTIAL_N0=1)
+ * @note The activation type must be passed at compile using -DACTIVATION_TYPE e.g. -DACTIVATION_TYPE=relu
+ * @note The A and B variables required by some activation functions must be passed at compile time using -DA_VAL= and -DB_VAL= respectively
+ * @note The quantization offset used for both the per-tensor and per-channel quantization must be passed at compile using -DDST_OFFSET (e.g., -DDST_OFFSET=3)
+ * @note The quantization shift for the per-tensor quantization must be passed at compile time using -DDST_SHIFT (e.g., -DDST_SHIFT=1)
+ * @note The quantization multiplier for the per-tensor quantization must be passed at compile using -DDST_MULTIPLIER (e.g., -DDST_MULTIPLER=121432)
+ * @note Only the following configurations of M0 and N0 are currently supported:
+ *  - M0 = 1, 2, 3, 4, 5, .... n (M0 != 1 with STRIDE_X == 1 && DILATION_X == 1 only)
+ *  - N0 = 2, 3, 4, 8, 16
+ * @note The number of rows to read from the src tensor must be passed at compile time using -DM0_A (e.g., -DM0_A=3). M0_A must be equal to WEI_WIDTH + (M0 - 1)
+ *
+ * @param[in]  src_ptr                                       Pointer to the source tensor. Supported data type: QSYMM8/QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL
+ * @param[in]  src_stride_x                                  Stride of the source tensor in X dimension (in bytes)
+ * @param[in]  src_step_x                                    src_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in]  src_stride_y                                  Stride of the source tensor in Y dimension (in bytes)
+ * @param[in]  src_step_y                                    src_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in]  src_stride_z                                  Stride of the source tensor in Z dimension (in bytes)
+ * @param[in]  src_step_z                                    src_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in]  src_stride_w                                  Stride of the source tensor in W dimension (in bytes)
+ * @param[in]  src_step_w                                    src_stride_w * number of elements along W processed per workitem(in bytes)
+ * @param[in]  src_offset_first_element_in_bytes             The offset of the first element in the source tensor
+ * @param[out] dst_ptr                                       Pointer to the destination tensor. Supported data type: same as @p src_ptr
+ * @param[in]  dst_stride_x                                  Stride of the destination tensor in X dimension (in bytes)
+ * @param[in]  dst_step_x                                    dst_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in]  dst_stride_y                                  Stride of the destination tensor in Y dimension (in bytes)
+ * @param[in]  dst_step_y                                    dst_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in]  dst_stride_z                                  Stride of the destination tensor in Z dimension (in bytes)
+ * @param[in]  dst_step_z                                    dst_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in]  dst_stride_w                                  Stride of the destination tensor in W dimension (in bytes)
+ * @param[in]  dst_step_w                                    dst_stride_w * number of elements along W processed per workitem(in bytes)
+ * @param[in]  dst_offset_first_element_in_bytes             The offset of the first element in the destination tensor
+ * @param[in]  wei_ptr                                       Pointer to the weights tensor. Supported data type: same as @p src_ptr
+ * @param[in]  wei_stride_x                                  Stride of the weights tensor in X dimension (in bytes)
+ * @param[in]  wei_step_x                                    wei_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in]  wei_stride_y                                  Stride of the weights tensor in Y dimension (in bytes)
+ * @param[in]  wei_step_y                                    wei_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in]  wei_stride_z                                  Stride of the weights tensor in Z dimension (in bytes)
+ * @param[in]  wei_step_z                                    wei_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in]  wei_stride_w                                  Stride of the weights tensor in W dimension (in bytes)
+ * @param[in]  wei_step_w                                    wei_stride_w * number of elements along W processed per workitem(in bytes)
+ * @param[in]  wei_offset_first_element_in_bytes             The offset of the first element in the weights tensor
+ * @param[in]  dst_multipliers_ptr                           Pointer to the destination multipliers tensor for the per-channel quantization. Supported data type: S32
+ * @param[in]  dst_multipliers_stride_x                      Stride of the destination multipliers tensor in X dimension (in bytes)
+ * @param[in]  dst_multipliers_step_x                        dst_multipliers_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in]  dst_multipliers_offset_first_element_in_bytes The offset of the first element in the destination multipliers tensor
+ * @param[in]  dst_shifts_ptr                                Pointer to the destination shifts tensor for the per-channel quantization. Supported data type: S32
+ * @param[in]  dst_shifts_stride_x                           Stride of the destination shifts tensor in X dimension (in bytes)
+ * @param[in]  dst_shifts_step_x                             dst_shifts_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in]  dst_shifts_offset_first_element_in_bytes      The offset of the first element in the destination shifts tensor
+ * @param[in]  bia_ptr                                       (Optional) Pointer to the bias tensor Supported data type: S32
+ * @param[in]  bia_stride_x                                  (Optional) Stride of the bias tensor in X dimension (in bytes)
+ * @param[in]  bia_step_x                                    (Optional) bia_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in]  bia_offset_first_element_in_bytes             (Optional) The offset of the first element in the bias tensor
+ */
+//! @endcond
+__kernel void dwc_native_quantized_nhwc(
+    TENSOR4D(src, SRC_TENSOR_TYPE),
+    TENSOR4D(dst, DST_TENSOR_TYPE),
+    TENSOR4D(wei, WEI_TENSOR_TYPE),
+    VECTOR_DECLARATION(dst_multipliers),
+    VECTOR_DECLARATION(dst_shifts)
+#if defined(HAS_BIAS)
+    ,
+    VECTOR_DECLARATION(bia)
+#endif // defined(HAS_BIAS)
+)
+{
+    // All the tensor dimensions are passed at compile time.
+    // In case of dynamic tensor support, the following dimensions should be passed as function argument.
+#define _IWEI_WIDTH WEI_WIDTH
+#define _IWEI_HEIGHT WEI_HEIGHT
+#define _ISRC_WIDTH SRC_WIDTH
+#define _ISRC_HEIGHT SRC_HEIGHT
+#define _IDST_WIDTH DST_WIDTH
+#define _IDST_HEIGHT DST_HEIGHT
+#define _IDST_CHANNELS DST_CHANNELS
+#define _IM0_A M0_A        // _IWEI_WIDTH + (M0 - 1) Rows tile A (If M0 != 1, the tiles overlap of 1 element on the X dimension)
+#define _IN0_A N0          // Cols tile A
+#define _IM0_B _IWEI_WIDTH // Rows tile B
+#define _IN0_B N0          // Cols tile B
+#define _IBOUNDARY_CHECK (!((WEI_WIDTH == 1 && WEI_HEIGHT == 1 && PAD_LEFT == 0 && PAD_TOP == 0 && M0 == 1)))
+
+    const int cout = GET_SPATIAL_IDX(0, N0, PARTIAL_N0); // OFM
+    const int xo   = GET_SPATIAL_IDX(1, M0, 0);          // WIDTH
+#if defined(BATCHED_EXECUTION)
+    const int yo   = GET_SPATIAL_IDX(2, 1, 0) % _IDST_HEIGHT; // HEIGHT
+    const int bout = GET_SPATIAL_IDX(2, 1, 0) / _IDST_HEIGHT; // BATCH SIZE IDX
+#else                                                         // defined(BATCHED_EXECUTION)
+    const int yo   = GET_SPATIAL_IDX(2, 1, 0); // HEIGHT
+    const int bout = 0;                        // BATCH SIZE IDX
+#endif                                                        // defined(BATCHED_EXECUTION)
+
+    int xi = xo * STRIDE_X;
+    int yi = yo * STRIDE_Y;
+    xi -= PAD_LEFT;
+    yi -= PAD_TOP;
+
+    int d = 0;
+#if DEPTH_MULTIPLIER != 1
+    for(; d < DEPTH_MULTIPLIER; d++)
+#endif // DEPTH_MULTIPLIER != 1
+    {
+        TILE(ACC_DATA_TYPE, M0, N0, c);
+
+        // Reset accumulators
+        LOOP_UNROLLING(int, i, 0, 1, M0,
+        {
+            c[i].v = 0;
+        })
+
+        LOOP_UNROLLING(int, yk, 0, 1, _IWEI_HEIGHT,
+        {
+            TILE(SRC_DATA_TYPE, _IM0_A, _IN0_A, a);
+
+            LOOP_UNROLLING(int, i, 0, 1, _IM0_A,
+            {
+                a[i].v = ZERO_VALUE;
+            })
+
+            // Load tile from the src tensor (TILE A)
+            T_LOAD_NHWC_WITH_DILATION(SRC_DATA_TYPE, 1, _IM0_A, _IN0_A, SRC_TENSOR_TYPE, src, bout, yi + yk * DILATION_Y, xi, cout, _ISRC_WIDTH, _ISRC_HEIGHT, DILATION_X, 1, _IBOUNDARY_CHECK, a);
+
+            TILE(WEI_DATA_TYPE, _IM0_B, _IN0_B, b);
+
+            // Load tile from the weights tensor (TILE B)
+            T_LOAD(WEI_DATA_TYPE, _IM0_B, _IN0_B, WEI_TENSOR_TYPE, wei, cout * DEPTH_MULTIPLIER + d, yk * _IM0_B, 1, wei_stride_y, b);
+
+            // Optimized path for STRIDE_X == 1
+            // If M0 != 1, we can skip the common loads between the two applied kernels on the X (WIDTH) dimension
+            LOOP_UNROLLING(int, m0, 0, 1, M0,
+            {
+                LOOP_UNROLLING(int, n0, 0, 1, N0,
+                {
+#if _IWEI_WIDTH <= 16
+#define DOT_DATA_TYPE SRC_DATA_TYPE
+#define WEI_OFFSET_CORRECTION (CALCULATE_WEIGHTS_OFFSET_CORRECTION(SRC_DATA_TYPE, WEI_DATA_TYPE))
+
+                    // Optimized path for the dot instruction
+                    TILE(DOT_DATA_TYPE, 1, _IWEI_WIDTH, x0);
+                    TILE(DOT_DATA_TYPE, 1, _IWEI_WIDTH, y0);
+                    ACC_DATA_TYPE offset_a = 0;
+                    ACC_DATA_TYPE offset_b = 0;
+
+                    LOOP_UNROLLING(int, xk, 0, 1, _IWEI_WIDTH,
+                    {
+                        x0[0].s[xk] = a[xk + m0].s[n0];
+                        y0[0].s[xk] = b[xk].s[n0] + (int)WEI_OFFSET_CORRECTION;
+                    })
+                    DOT_PRODUCT_INTEGER8(DOT_DATA_TYPE, DOT_DATA_TYPE, ACC_DATA_TYPE, _IWEI_WIDTH, x0[0].v, y0[0].v, c[m0].s[n0]);
+                    REDUCE_INTEGER8(DOT_DATA_TYPE, DOT_DATA_TYPE, ACC_DATA_TYPE, _IWEI_WIDTH, x0[0].v, offset_a);
+                    REDUCE_INTEGER8(DOT_DATA_TYPE, DOT_DATA_TYPE, ACC_DATA_TYPE, _IWEI_WIDTH, y0[0].v, offset_b);
+                    c[m0].s[n0] += offset_a * (ACC_DATA_TYPE)(WEI_OFFSET - (ACC_DATA_TYPE)WEI_OFFSET_CORRECTION) + offset_b * (ACC_DATA_TYPE)SRC_OFFSET;
+#else  // _IWEI_WIDTH <= 16
+                    LOOP_UNROLLING(int, xk, 0, 1, _IWEI_WIDTH,
+                    {
+                        c[m0].s[n0] += ((ACC_DATA_TYPE)a[xk + m0].s[n0] + (ACC_DATA_TYPE)(SRC_OFFSET)) * ((ACC_DATA_TYPE)b[xk].s[n0] + (ACC_DATA_TYPE)(WEI_OFFSET));
+                    })
+#endif // _IWEI_WIDTH <= 16
+                })
+            })
+        })
+
+#if _IWEI_WIDTH <= 16
+        T_ADD_CONSTANT(ACC_DATA_TYPE, M0, N0, c, (_IWEI_WIDTH * _IWEI_HEIGHT * SRC_OFFSET * (ACC_DATA_TYPE)(WEI_OFFSET - (ACC_DATA_TYPE)WEI_OFFSET_CORRECTION)), c);
+#endif // _IWEI_WIDTH <= 16
+
+#if defined(HAS_BIAS)
+        TILE(BIA_DATA_TYPE, 1, N0, bias0);
+
+        // Load bias
+        T_LOAD(BIA_DATA_TYPE, 1, N0, BUFFER, bia, cout * DEPTH_MULTIPLIER + d, 0, 0, 0, bias0);
+
+        // c = c + bias[broadcasted]
+        T_ADD_BROADCAST_X(ACC_DATA_TYPE, M0, N0, c, bias0, c);
+#endif // HAS_BIAS
+
+        T_LOAD_MULTIPLIERS_SHIFT(QUANTIZATION_TYPE);
+
+        // Quantize the tile
+        TILE(DST_DATA_TYPE, M0, N0, cq);
+        T_QUANTIZE8(ACC_DATA_TYPE, DST_DATA_TYPE, QUANTIZATION_TYPE, M0, N0, DST_OFFSET, DST_SHIFT, DST_MULTIPLIER, c, multipliers, shifts, cq);
+
+        // Perform activation
+        T_ACTIVATION_QUANTIZED(DST_DATA_TYPE, M0, N0, ACTIVATION_TYPE, DST_OFFSET, A_VAL, B_VAL, cq, cq);
+
+        bool x_cond = PARTIAL_N0 != 0 && get_global_id(0) == 0;
+
+        if(x_cond)
+        {
+            LOOP_UNROLLING(int, m0, 0, 1, M0,
+            {
+                int xi_out = min(xo + M0 - 1 - m0, (int)(_IDST_WIDTH) - 1);
+                VSTORE_PARTIAL(N0, PARTIAL_N0)
+                (cq[M0 - 1 - m0].v, 0, (__global DST_DATA_TYPE *)(dst_ptr + dst_offset_first_element_in_bytes + ((cout * DEPTH_MULTIPLIER) + d) * sizeof(DST_DATA_TYPE) + xi_out * dst_stride_y + yo * dst_stride_z + bout * dst_stride_w));
+            })
+        }
+        else
+        {
+            LOOP_UNROLLING(int, m0, 0, 1, M0,
+            {
+                int xi_out = min(xo + M0 - 1 - m0, (int)(_IDST_WIDTH) - 1);
+                VSTORE(N0)
+                (cq[M0 - 1 - m0].v, 0, (__global DST_DATA_TYPE *)(dst_ptr + dst_offset_first_element_in_bytes + ((cout * DEPTH_MULTIPLIER) + d) * sizeof(DST_DATA_TYPE) + xi_out * dst_stride_y + yo * dst_stride_z + bout * dst_stride_w));
+            })
+        }
+    }
+}
+#endif // defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(DST_WIDTH) && defined(DST_HEIGHT) && defined(WEI_WIDTH) && defined(WEI_HEIGHT) && defined(N0) && defined(M0) && defined(DILATION_X) && defined(DILATION_Y) && defined(STRIDE_X) && defined(STRIDE_Y) && defined(PAD_LEFT) && defined(PAD_TOP)
\ No newline at end of file