Remove OpenCL padding: CLL2NormalizeLayerKernel

Resolves: COMPMID-3909

Change-Id: I00a1705ed202002e2a6053702272181805fa6869
Signed-off-by: Manuel Bottini <manuel.bottini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5360
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

2 files changed, 147 insertions, 133 deletions

diff --git a/src/core/CL/cl_kernels/l2_normalize.cl b/src/core/CL/cl_kernels/l2_normalize.cl
index 14b37e3257..fbe3406239 100644
--- a/src/core/CL/cl_kernels/l2_normalize.cl
+++ b/src/core/CL/cl_kernels/l2_normalize.cl
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 Arm Limited.
+ * Copyright (c) 2016-2021 Arm Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -23,142 +23,167 @@
  */
 #include "helpers.h"
 
+#if defined(VEC_SIZE_X) && defined(VEC_SIZE_LEFTOVER_X)
 /** This kernel performs l2 normalization on x-axis
  *
  * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float
- * @note The data size must be passed at compile time using -DDATA_SIZE e.g. -DDATA_SIZE=32
+ * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE_X=size. e.g. -DVEC_SIZE_X=16
+ * @note The leftover size in the X dimension shoud be given as preprocessor argument using -DVEC_SIZE_LEFTOVER_X is; x_dimension % VEC_SIZE_X. e.g. -DVEC_SIZE_LEFTOVER_X=1
  *
- * @param[in]  src_ptr                           Pointer to the source tensor. Supported data types: F16/F32
- * @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 X processed per workitem(in bytes)
- * @param[in]  src_offset_first_element_in_bytes The offset of the first element in the source tensor
- * @param[in]  sum_ptr                           Pointer to the source tensor. Supported data types: F16/F32
- * @param[in]  sum_stride_x                      Stride of the source tensor in X dimension (in bytes)
- * @param[in]  sum_step_x                        sum_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in]  sum_stride_y                      Stride of the source tensor in Y dimension (in bytes)
- * @param[in]  sum_step_y                        sum_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in]  sum_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 types: 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_offset_first_element_in_bytes The offset of the first element in the destination tensor
- * @param[in]  epsilon                           Epsilon value
+ * @param[in]  input_ptr                            Pointer to the source tensor. Supported data types: F16/F32
+ * @param[in]  input_stride_x                       Stride of the source tensor in X dimension (in bytes)
+ * @param[in]  input_step_x                         input_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in]  input_stride_y                       Stride of the source tensor in Y dimension (in bytes)
+ * @param[in]  input_step_y                         input_stride_y * number of elements along X processed per workitem(in bytes)
+ * @param[in]  input_offset_first_element_in_bytes  The offset of the first element in the source tensor
+ * @param[in]  sum_ptr                              Pointer to the source tensor. Supported data types: F16/F32
+ * @param[in]  sum_stride_x                         Stride of the source tensor in X dimension (in bytes)
+ * @param[in]  sum_step_x                           sum_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in]  sum_stride_y                         Stride of the source tensor in Y dimension (in bytes)
+ * @param[in]  sum_step_y                           sum_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in]  sum_offset_first_element_in_bytes    The offset of the first element in the source tensor
+ * @param[out] output_ptr                           Pointer to the destination tensor. Supported data types: same as @p input_ptr
+ * @param[in]  output_stride_x                      Stride of the destination tensor in X dimension (in bytes)
+ * @param[in]  output_step_x                        output_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in]  output_stride_y                      Stride of the destination tensor in Y dimension (in bytes)
+ * @param[in]  output_step_y                        output_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in]  output_offset_first_element_in_bytes The offset of the first element in the destination tensor
+ * @param[in]  epsilon                              Epsilon value
  */
 __kernel void l2_normalize_x(
-    IMAGE_DECLARATION(src),
+    IMAGE_DECLARATION(input),
     IMAGE_DECLARATION(sum),
-    IMAGE_DECLARATION(dst),
+    IMAGE_DECLARATION(output),
     DATA_TYPE epsilon)
 {
-    Image src = CONVERT_TO_IMAGE_STRUCT(src);
-    Image sum = CONVERT_TO_IMAGE_STRUCT(sum);
-    Image dst = CONVERT_TO_IMAGE_STRUCT(dst);
+    // Offset computation
+    const uint x_offs = max((int)(get_global_id(0) * VEC_SIZE_X - (VEC_SIZE_X - VEC_SIZE_LEFTOVER_X) % VEC_SIZE_X), 0);
 
-    VEC_DATA_TYPE(DATA_TYPE, 16)
-    in = vload16(0, (__global DATA_TYPE *)src.ptr);
-    VEC_DATA_TYPE(DATA_TYPE, 16)
-    normalize_value = (VEC_DATA_TYPE(DATA_TYPE, 16))rsqrt(fmax(((__global DATA_TYPE *)sum.ptr)[0], epsilon));
+    // Address computation
+    __global uchar *input_addr  = input_ptr + input_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE) + get_global_id(1) * input_stride_y;
+    __global uchar *sum_addr    = sum_ptr + sum_offset_first_element_in_bytes + get_global_id(1) * sum_stride_y;
+    __global uchar *output_addr = output_ptr + output_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE) + get_global_id(1) * output_stride_y;
 
-    vstore16(in * normalize_value, 0, (__global DATA_TYPE *)dst.ptr);
+    VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X)
+    in = VLOAD(VEC_SIZE_X)(0, (__global DATA_TYPE *)input_addr);
+
+    VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X)
+    normalize_value = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X))rsqrt(fmax(*((__global DATA_TYPE *)sum_addr), epsilon));
+
+    const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X)
+    data0 = in * normalize_value;
+
+    STORE_VECTOR_SELECT(data, DATA_TYPE, output_addr, VEC_SIZE_X, VEC_SIZE_LEFTOVER_X, VEC_SIZE_LEFTOVER_X != 0 && get_global_id(0) == 0);
 }
 
 /** This kernel performs l2 normalization on y-axis.
  *
  * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float
- * @note The data size must be passed at compile time using -DDATA_SIZE e.g. -DDATA_SIZE=32
+ * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE_X=size. e.g. -DVEC_SIZE_X=16
+ * @note The leftover size in the X dimension shoud be given as preprocessor argument using -DVEC_SIZE_LEFTOVER_X is; x_dimension % VEC_SIZE_X. e.g. -DVEC_SIZE_LEFTOVER_X=1
  *
- * @param[in]  src_ptr                           Pointer to the source tensor. Supported data types: F16/F32
- * @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 Y 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 X processed per workitem(in bytes)
- * @param[in]  src_offset_first_element_in_bytes The offset of the first element in the source tensor
- * @param[in]  sum_ptr                           Pointer to the source tensor. Supported data types: F16/F32
- * @param[in]  sum_stride_x                      Stride of the source tensor in X dimension (in bytes)
- * @param[in]  sum_step_x                        sum_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in]  sum_stride_y                      Stride of the source tensor in Y dimension (in bytes)
- * @param[in]  sum_step_y                        sum_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in]  sum_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 types: 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_offset_first_element_in_bytes The offset of the first element in the destination tensor
- * @param[in]  epsilon                           Epsilon value
+ * @param[in]  input_ptr                            Pointer to the source tensor. Supported data types: F16/F32
+ * @param[in]  input_stride_x                       Stride of the source tensor in X dimension (in bytes)
+ * @param[in]  input_step_x                         input_stride_x * number of elements along Y processed per workitem(in bytes)
+ * @param[in]  input_stride_y                       Stride of the source tensor in Y dimension (in bytes)
+ * @param[in]  input_step_y                         input_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in]  input_offset_first_element_in_bytes  The offset of the first element in the source tensor
+ * @param[in]  sum_ptr                              Pointer to the source tensor. Supported data types: F16/F32
+ * @param[in]  sum_stride_x                         Stride of the source tensor in X dimension (in bytes)
+ * @param[in]  sum_step_x                           sum_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in]  sum_stride_y                         Stride of the source tensor in Y dimension (in bytes)
+ * @param[in]  sum_step_y                           sum_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in]  sum_offset_first_element_in_bytes    The offset of the first element in the source tensor
+ * @param[out] output_ptr                           Pointer to the destination tensor. Supported data types: same as @p input_ptr
+ * @param[in]  output_stride_x                      Stride of the destination tensor in X dimension (in bytes)
+ * @param[in]  output_step_x                        output_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in]  output_stride_y                      Stride of the destination tensor in Y dimension (in bytes)
+ * @param[in]  output_step_y                        output_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in]  output_offset_first_element_in_bytes The offset of the first element in the destination tensor
+ * @param[in]  epsilon                              Epsilon value
  */
 __kernel void l2_normalize_y(
-    IMAGE_DECLARATION(src),
+    IMAGE_DECLARATION(input),
     IMAGE_DECLARATION(sum),
-    IMAGE_DECLARATION(dst),
+    IMAGE_DECLARATION(output),
     DATA_TYPE epsilon)
 {
-    Image src = CONVERT_TO_IMAGE_STRUCT(src);
-    Image sum = CONVERT_TO_IMAGE_STRUCT(sum);
-    Image dst = CONVERT_TO_IMAGE_STRUCT(dst);
+    // Offset computation
+    const uint x_offs = max((int)(get_global_id(0) * VEC_SIZE_X - (VEC_SIZE_X - VEC_SIZE_LEFTOVER_X) % VEC_SIZE_X), 0);
+
+    // Address computation
+    __global uchar *input_addr  = input_ptr + input_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE) + get_global_id(1) * input_stride_y;
+    __global uchar *sum_addr    = sum_ptr + sum_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE);
+    __global uchar *output_addr = output_ptr + output_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE) + get_global_id(1) * output_stride_y;
 
-    VEC_DATA_TYPE(DATA_TYPE, 16)
-    in = vload16(0, (__global DATA_TYPE *)src.ptr);
-    VEC_DATA_TYPE(DATA_TYPE, 16)
-    sums = vload16(0, (__global DATA_TYPE *)sum.ptr);
+    VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X)
+    in = VLOAD(VEC_SIZE_X)(0, (__global DATA_TYPE *)input_addr);
+    VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X)
+    sums = VLOAD(VEC_SIZE_X)(0, (__global DATA_TYPE *)sum_addr);
 
-    VEC_DATA_TYPE(DATA_TYPE, 16)
-    normalize_value = (VEC_DATA_TYPE(DATA_TYPE, 16))rsqrt(fmax(sums, epsilon));
+    VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X)
+    normalize_value = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X))rsqrt(fmax(sums, epsilon));
 
-    vstore16(in * normalize_value, 0, (__global DATA_TYPE *)dst.ptr);
+    const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X)
+    data0 = in * normalize_value;
+
+    STORE_VECTOR_SELECT(data, DATA_TYPE, output_addr, VEC_SIZE_X, VEC_SIZE_LEFTOVER_X, VEC_SIZE_LEFTOVER_X != 0 && get_global_id(0) == 0);
 }
+
 /** This kernel performs l2 normalization on z-axis.
  *
  * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float
- * @note The data size must be passed at compile time using -DDATA_SIZE e.g. -DDATA_SIZE=32
+ * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE_X=size. e.g. -DVEC_SIZE_X=16
+ * @note The leftover size in the X dimension shoud be given as preprocessor argument using -DVEC_SIZE_LEFTOVER_X is; x_dimension % VEC_SIZE_X. e.g. -DVEC_SIZE_LEFTOVER_X=1
  *
- * @param[in]  src_ptr                           Pointer to the source tensor. Supported data types: F16/F32
- * @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 Y 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 X 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_offset_first_element_in_bytes The offset of the first element in the source tensor
- * @param[in]  sum_ptr                           Pointer to the source tensor. Supported data types: F16/F32
- * @param[in]  sum_stride_x                      Stride of the source tensor in X dimension (in bytes)
- * @param[in]  sum_step_x                        sum_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in]  sum_stride_y                      Stride of the source tensor in Y dimension (in bytes)
- * @param[in]  sum_step_y                        sum_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in]  sum_stride_z                      Stride of the source tensor in Z dimension (in bytes)
- * @param[in]  sum_step_z                        sum_stride_z * number of elements along Z processed per workitem(in bytes)
- * @param[in]  sum_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 types: 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 Y 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]  epsilon                           Epsilon value
+ * @param[in]  input_ptr                            Pointer to the source tensor. Supported data types: F16/F32
+ * @param[in]  input_stride_x                       Stride of the source tensor in X dimension (in bytes)
+ * @param[in]  input_step_x                         input_stride_x * number of elements along Y processed per workitem(in bytes)
+ * @param[in]  input_stride_y                       Stride of the source tensor in Y dimension (in bytes)
+ * @param[in]  input_step_y                         input_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in]  input_stride_z                       Stride of the source tensor in Z dimension (in bytes)
+ * @param[in]  input_step_z                         input_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in]  input_offset_first_element_in_bytes  The offset of the first element in the source tensor
+ * @param[in]  sum_ptr                              Pointer to the source tensor. Supported data types: F16/F32
+ * @param[in]  sum_stride_x                         Stride of the source tensor in X dimension (in bytes)
+ * @param[in]  sum_step_x                           sum_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in]  sum_stride_y                         Stride of the source tensor in Y dimension (in bytes)
+ * @param[in]  sum_step_y                           sum_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in]  sum_stride_z                         Stride of the source tensor in Z dimension (in bytes)
+ * @param[in]  sum_step_z                           sum_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in]  sum_offset_first_element_in_bytes    The offset of the first element in the source tensor
+ * @param[out] output_ptr                           Pointer to the destination tensor. Supported data types: same as @p input_ptr
+ * @param[in]  output_stride_x                      Stride of the destination tensor in X dimension (in bytes)
+ * @param[in]  output_step_x                        output_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in]  output_stride_y                      Stride of the destination tensor in Y dimension (in bytes)
+ * @param[in]  output_step_y                        output_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in]  output_stride_z                      Stride of the destination tensor in Z dimension (in bytes)
+ * @param[in]  output_step_z                        output_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in]  output_offset_first_element_in_bytes The offset of the first element in the destination tensor
+ * @param[in]  epsilon                              Epsilon value
  */
 __kernel void l2_normalize_z(
-    TENSOR3D_DECLARATION(src),
+    TENSOR3D_DECLARATION(input),
     TENSOR3D_DECLARATION(sum),
-    TENSOR3D_DECLARATION(dst),
+    TENSOR3D_DECLARATION(output),
     DATA_TYPE epsilon)
 {
-    Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src);
-    Tensor3D sum = CONVERT_TO_TENSOR3D_STRUCT(sum);
-    Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst);
+    // Offset computation
+    const uint x_offs = max((int)(get_global_id(0) * VEC_SIZE_X - (VEC_SIZE_X - VEC_SIZE_LEFTOVER_X) % VEC_SIZE_X), 0);
 
-    VEC_DATA_TYPE(DATA_TYPE, 16)
-    in = vload16(0, (__global DATA_TYPE *)src.ptr);
-    VEC_DATA_TYPE(DATA_TYPE, 16)
-    sums = vload16(0, (__global DATA_TYPE *)sum.ptr);
+    // Address computation
+    __global uchar *input_addr  = input_ptr + input_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE) + get_global_id(1) * input_stride_y + get_global_id(2) * input_stride_z;
+    __global uchar *sum_addr    = sum_ptr + sum_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE) + get_global_id(1) * sum_stride_y;
+    __global uchar *output_addr = output_ptr + output_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE) + get_global_id(1) * output_stride_y + get_global_id(2) * output_stride_z;
 
-    VEC_DATA_TYPE(DATA_TYPE, 16)
-    normalize_value = (VEC_DATA_TYPE(DATA_TYPE, 16))rsqrt(fmax(sums, epsilon));
+    VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X)
+    in = VLOAD(VEC_SIZE_X)(0, (__global DATA_TYPE *)input_addr);
+    VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X)
+    sums = VLOAD(VEC_SIZE_X)(0, (__global DATA_TYPE *)sum_addr);
 
-    vstore16(in * normalize_value, 0, (__global DATA_TYPE *)dst.ptr);
-}
\ No newline at end of file
+    VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X)
+    data0 = in * ((VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE_X))(rsqrt(fmax(sums, epsilon))));
+
+    STORE_VECTOR_SELECT(data, DATA_TYPE, output_addr, VEC_SIZE_X, VEC_SIZE_LEFTOVER_X, VEC_SIZE_LEFTOVER_X != 0 && get_global_id(0) == 0);
+}
+#endif // defined(VEC_SIZE_X) && defined(VEC_SIZE_LEFTOVER_X)
\ No newline at end of file
diff --git a/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp b/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp
index 213770591f..d9f293ba73 100644
--- a/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp
+++ b/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp
@@ -36,14 +36,14 @@
 
 #include "support/StringSupport.h"
 
+#include "utils/TypePrinter.h"
+
 namespace arm_compute
 {
 namespace
 {
 constexpr int max_input_tensor_dim = 3;
 
-constexpr unsigned int num_elems_processed_per_iteration = 16;
-
 Status validate_arguments(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, int axis, float epsilon)
 {
     ARM_COMPUTE_UNUSED(epsilon);
@@ -71,23 +71,6 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *sum, cons
 
     return Status{};
 }
-
-std::tuple<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output)
-{
-    Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration));
-
-    // Output tensor auto initialization if not yet initialized
-    auto_init_if_empty(*output, input->tensor_shape(), 1, input->data_type());
-
-    AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration);
-    AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration);
-
-    bool window_changed = update_window_and_padding(win, input_access, output_access);
-
-    Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
-
-    return std::make_tuple(err, win);
-}
 } // namespace
 
 CLL2NormalizeLayerKernel::CLL2NormalizeLayerKernel()
@@ -104,6 +87,7 @@ void CLL2NormalizeLayerKernel::configure(const CLCompileContext &compile_context
 {
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, sum, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), sum->info(), output->info(), axis, epsilon));
+    auto padding_info = get_padding_info({ input, sum, output });
 
     _input       = input;
     _sum         = sum;
@@ -111,10 +95,14 @@ void CLL2NormalizeLayerKernel::configure(const CLCompileContext &compile_context
     _actual_axis = wrap_around(axis, max_input_tensor_dim);
     _epsilon     = epsilon;
 
+    const unsigned int vec_size_x           = adjust_vec_size(max_cl_vector_width / input->info()->element_size(), input->info()->dimension(0));
+    const int          vec_size_x_leftovers = input->info()->dimension(0) % vec_size_x;
+
     // Set build options
-    std::set<std::string> build_opts;
-    build_opts.emplace(("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())));
-    build_opts.emplace(("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration)));
+    CLBuildOptions build_opts;
+    build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
+    build_opts.add_option("-DVEC_SIZE_X=" + support::cpp11::to_string(vec_size_x));
+    build_opts.add_option("-DVEC_SIZE_LEFTOVER_X=" + support::cpp11::to_string(vec_size_x_leftovers));
 
     // Create kernel
     std::string  kernel_name;
@@ -122,21 +110,21 @@ void CLL2NormalizeLayerKernel::configure(const CLCompileContext &compile_context
     switch(_actual_axis)
     {
         case 0:
-            kernel_name = "x";
+            kernel_name = "l2_normalize_x";
             idx         = num_arguments_per_2D_tensor() * 3;
             break;
         case 1:
-            kernel_name = "y";
+            kernel_name = "l2_normalize_y";
             idx         = num_arguments_per_2D_tensor() * 3;
             break;
         case 2:
-            kernel_name = "z";
+            kernel_name = "l2_normalize_z";
             idx         = num_arguments_per_3D_tensor() * 3;
             break;
         default:
             ARM_COMPUTE_ERROR("Axis not supported");
     }
-    _kernel = create_kernel(compile_context, "l2_normalize_" + kernel_name, build_opts);
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
 
     // Set epsilon argument
     if(input->info()->data_type() == DataType::F32)
@@ -149,17 +137,18 @@ void CLL2NormalizeLayerKernel::configure(const CLCompileContext &compile_context
     }
 
     // Configure kernel window
-    auto win_config = validate_and_configure_window(_input->info(), _output->info());
-    ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config));
+    Window win = calculate_max_window(*input->info(), Steps(vec_size_x));
 
-    ICLKernel::configure_internal(std::get<1>(win_config));
+    // Output tensor auto initialization if not yet initialized
+    auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, input->info()->data_type());
+
+    ICLKernel::configure_internal(win);
+    ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
 }
 
 Status CLL2NormalizeLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, int axis, float epsilon)
 {
     ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, sum, output, axis, epsilon));
-    ARM_COMPUTE_RETURN_ON_ERROR(std::get<0>(validate_and_configure_window(input->clone().get(), output->clone().get())));
-
     return Status{};
 }