COMPMID-3737: Remove OpenCL padding: CLWidthConcatenate2TensorsKernel

Remove padding from CLWidthConcatenate2TensorsKernel
Remove padding from CLWidthConcatenate4TensorsKernel

Change-Id: I2142618e87bf11f831fe3b9375c4a7efda8d3a21
Signed-off-by: Sheri Zhang <sheri.zhang@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4266
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>

3 files changed, 75 insertions, 148 deletions

diff --git a/src/core/CL/cl_kernels/concatenate.cl b/src/core/CL/cl_kernels/concatenate.cl
index 7c6c8d211a..19494b109f 100644
--- a/src/core/CL/cl_kernels/concatenate.cl
+++ b/src/core/CL/cl_kernels/concatenate.cl
@@ -53,7 +53,9 @@ inline VEC_QUANT requantize(VEC_QUANT input, float in_offset, float out_offset,
 #error "Element size not supported"
 #endif // ELEMENT_SIZE
 
-#if VEC_SIZE == 2
+#if VEC_SIZE == 1
+#define SEQ ((int)(0))
+#elif VEC_SIZE == 2
 #define SEQ ((int2)(0, 1))
 #elif VEC_SIZE == 4
 #define SEQ ((int4)(0, 1, 2, 3))
@@ -69,7 +71,7 @@ inline VEC_QUANT requantize(VEC_QUANT input, float in_offset, float out_offset,
  *
  * @note The data type has to be passed at compile time using -DDATA_TYPE. i.e. -DDATA_TYPE=float
  * @note Vector size has to be passed at compile time using -DVEC_SIZE. i.e. -DVEC_SIZE=16
- * @note The offset for the first spatial dimension has to be passed at compile time using -DWIDTH_OFFSET. i.e. -DWIDTH_OFFSET=128
+ * @note Leftover vector size has to be passed at compile time using -DVEC_SIZE_LEFTOVER. e.g. -DVEC_SIZE_LEFTOVER=3. It is defined as the remainder between the input's first dimension and VEC_SIZE
  * @note Tensor depth should be given as a preprocessor argument using -DDEPTH=size. e.g. -DDEPTH=16
  * @note First input tensor width should be given as a preprocessor argument using -DINPUT1_WIDTH=width. e.g. -DINPUT1_WIDTH=8
  *
@@ -103,34 +105,29 @@ inline VEC_QUANT requantize(VEC_QUANT input, float in_offset, float out_offset,
  * @param[in]  dst_stride_w                       Stride of the destination tensor in Z dimension (in bytes)
  * @param[in]  dst_step_w                         output_stride_z * number of elements along Z 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]  src1_pad_right                     Right paddings of the first input tensor in unit of elements
- * @param[in]  src1_pad_left                      Left paddings of the second input tensor in unit of elements
  */
 __kernel void concatenate_width_x2(
     TENSOR4D_DECLARATION(src1),
     TENSOR4D_DECLARATION(src2),
-    TENSOR4D_DECLARATION(dst),
-    uint src1_pad_right,
-    uint src2_pad_left)
+    TENSOR4D_DECLARATION(dst))
 {
-    Tensor4D dst = CONVERT_TO_TENSOR4D_STRUCT(dst, DEPTH);
-
     // Calculate input indices
-    const int x  = get_global_id(0) * (int)VEC_SIZE;
+    const int x  = max((int)(get_global_id(0) * VEC_SIZE - (VEC_SIZE - VEC_SIZE_LEFTOVER) % VEC_SIZE), 0);
     const int y  = get_global_id(1);
     const int z  = get_global_id(2) % (int)DEPTH;
     const int w  = get_global_id(2) / (int)DEPTH;
-    const int x1 = min(x, (int)INPUT1_WIDTH + (int)src1_pad_right - (int)VEC_SIZE);
-    const int x2 = max(x - (int)INPUT1_WIDTH, -(int)src2_pad_left);
+    const int x1 = min(x, (int)INPUT1_WIDTH - (int)VEC_SIZE);
+    const int x2 = max(x - (int)INPUT1_WIDTH, 0);
 
     // Calculate inputs and output addresses
-    const __global uchar *in1_ptr = src1_ptr + (int)src1_offset_first_element_in_bytes + x1 * (int)src1_stride_x + y * (int)src1_stride_y + z * (int)src1_stride_z + w * (int)src1_stride_w;
-    const __global uchar *in2_ptr = src2_ptr + (int)src2_offset_first_element_in_bytes + x2 * (int)src2_stride_x + y * (int)src2_stride_y + z * (int)src2_stride_z + w * (int)src2_stride_w;
+    const __global uchar *dst_addr  = dst_ptr + (int)dst_offset_first_element_in_bytes + x * sizeof(DATA_TYPE) + y * (int)dst_stride_y + z * (int)dst_stride_z + w * (int)dst_stride_w;
+    const __global uchar *src1_addr = src1_ptr + (int)src1_offset_first_element_in_bytes + x1 * sizeof(DATA_TYPE) + y * (int)src1_stride_y + z * (int)src1_stride_z + w * (int)src1_stride_w;
+    const __global uchar *src2_addr = src2_ptr + (int)src2_offset_first_element_in_bytes + x2 * sizeof(DATA_TYPE) + y * (int)src2_stride_y + z * (int)src2_stride_z + w * (int)src2_stride_w;
 
     VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
-    src1_values = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)in1_ptr);
+    src1_values = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)src1_addr);
     VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
-    src2_values = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)in2_ptr);
+    src2_values = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)src2_addr);
 
 #if defined(OFFSET_IN1) && defined(OFFSET_IN2) && defined(OFFSET_OUT) && defined(SCALE_IN1) && defined(SCALE_IN2) && defined(SCALE_OUT)
     src1_values = requantize(src1_values, OFFSET_IN1, OFFSET_OUT, SCALE_IN1, SCALE_OUT);
@@ -138,10 +135,14 @@ __kernel void concatenate_width_x2(
 #endif /* defined(OFFSET_IN1) && defined(OFFSET_IN2) && defined(OFFSET_OUT) && defined(SCALE_IN1)  && defined(SCALE_IN2) && defined(SCALE_OUT) */
     const VEC_DATA_TYPE(int, VEC_SIZE) x_coords        = SEQ + (VEC_DATA_TYPE(int, VEC_SIZE))(x);
     const VEC_DATA_TYPE(COND_DATA_TYPE, VEC_SIZE) cond = CONVERT(x_coords < (VEC_DATA_TYPE(int, VEC_SIZE))(INPUT1_WIDTH), VEC_DATA_TYPE(COND_DATA_TYPE, VEC_SIZE));
-    const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) values    = select(src2_values, src1_values, cond);
 
-    VSTORE(VEC_SIZE)
-    (values, 0, (__global DATA_TYPE *)dst.ptr);
+    // Rotate src1/2_values, if values0 is a combination of src1_values and src2_values.
+    src1_values = (x < INPUT1_WIDTH && x1 == INPUT1_WIDTH - VEC_SIZE) ? ROTATE(src1_values, VEC_SIZE, INPUT1_ROTATE_N) : src1_values;
+    src2_values = (x < INPUT1_WIDTH && x1 == INPUT1_WIDTH - VEC_SIZE) ? ROTATE(src2_values, VEC_SIZE, INPUT1_ROTATE_N) : src2_values;
+
+    const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) values0 = select(src2_values, src1_values, cond);
+
+    STORE_VECTOR_SELECT(values, DATA_TYPE, dst_addr, VEC_SIZE, VEC_SIZE_LEFTOVER, VEC_SIZE_LEFTOVER != 0 && get_global_id(0) == 0)
 }
 
 #if defined(INPUT2_WIDTH) && defined(INPUT3_WIDTH)
@@ -149,7 +150,7 @@ __kernel void concatenate_width_x2(
  *
  * @note The data type has to be passed at compile time using -DDATA_TYPE. i.e. -DDATA_TYPE=float
  * @note Vector size has to be passed at compile time using -DVEC_SIZE. i.e. -DVEC_SIZE=16
- * @note The offset for the first spatial dimension has to be passed at compile time using -DWIDTH_OFFSET. i.e. -DWIDTH_OFFSET=128
+ * @note Leftover vector size has to be passed at compile time using -DVEC_SIZE_LEFTOVER. e.g. -DVEC_SIZE_LEFTOVER=3. It is defined as the remainder between the input's first dimension and VEC_SIZE
  * @note Tensor depth should be given as a preprocessor argument using -DDEPTH=size. e.g. -DDEPTH=16
  * @note First input tensor width should be given as a preprocessor argument using -DINPUT1_WIDTH=width. e.g. -DINPUT1_WIDTH=8
  * @note Second input tensor width should be given as a preprocessor argument using -DINPUT2_WIDTH=width. e.g. -DINPUT2_WIDTH=8
@@ -205,53 +206,40 @@ __kernel void concatenate_width_x2(
  * @param[in]  dst_stride_w                       Stride of the destination tensor in Z dimension (in bytes)
  * @param[in]  dst_step_w                         output_stride_z * number of elements along Z 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]  src1_pad_right                     Right paddings of the first input tensor in unit of elements
- * @param[in]  src2_pad_left                      Left paddings of the second input tensor in unit of elements
- * @param[in]  src2_pad_right                     Right paddings of the second input tensor in unit of elements
- * @param[in]  src3_pad_left                      Left paddings of the third input tensor in unit of elements
- * @param[in]  src3_pad_right                     Right paddings of the third input tensor in unit of elements
- * @param[in]  src4_pad_left                      Left paddings of the fourth input tensor in unit of elements
  */
 __kernel void concatenate_width_x4(
     TENSOR4D_DECLARATION(src1),
     TENSOR4D_DECLARATION(src2),
     TENSOR4D_DECLARATION(src3),
     TENSOR4D_DECLARATION(src4),
-    TENSOR4D_DECLARATION(dst),
-    uint src1_pad_right,
-    uint src2_pad_left,
-    uint src2_pad_right,
-    uint src3_pad_left,
-    uint src3_pad_right,
-    uint src4_pad_left)
+    TENSOR4D_DECLARATION(dst))
 {
-    Tensor4D dst = CONVERT_TO_TENSOR4D_STRUCT(dst, DEPTH);
-
     // Calculate input indices
-    const int x = get_global_id(0) * (int)VEC_SIZE;
+    const int x = max((int)(get_global_id(0) * VEC_SIZE - (VEC_SIZE - VEC_SIZE_LEFTOVER) % VEC_SIZE), 0);
     const int y = get_global_id(1);
     const int z = get_global_id(2) % (int)DEPTH;
     const int w = get_global_id(2) / (int)DEPTH;
 
-    const int x1 = min(x, (int)INPUT1_WIDTH + (int)src1_pad_right - (int)VEC_SIZE);
-    const int x2 = min(max(x - (int)INPUT1_WIDTH, -(int)src2_pad_left), (int)INPUT2_WIDTH + (int)src2_pad_right - (int)VEC_SIZE);
-    const int x3 = min(max(x - (int)INPUT1_WIDTH - (int)INPUT2_WIDTH, -(int)src3_pad_left), (int)INPUT3_WIDTH + (int)src3_pad_right - (int)VEC_SIZE);
-    const int x4 = max(x - (int)INPUT1_WIDTH - (int)INPUT2_WIDTH - (int)INPUT3_WIDTH, -(int)src4_pad_left);
+    const int x1 = min(x, (int)INPUT1_WIDTH - (int)VEC_SIZE);
+    const int x2 = min(max(x - (int)INPUT1_WIDTH, 0), (int)INPUT2_WIDTH - (int)VEC_SIZE);
+    const int x3 = min(max(x - (int)INPUT1_WIDTH - (int)INPUT2_WIDTH, 0), (int)INPUT3_WIDTH - (int)VEC_SIZE);
+    const int x4 = max(x - (int)INPUT1_WIDTH - (int)INPUT2_WIDTH - (int)INPUT3_WIDTH, 0);
 
     // Calculate inputs and output addresses
-    const __global uchar *in1_ptr = src1_ptr + (int)src1_offset_first_element_in_bytes + x1 * (int)src1_stride_x + y * (int)src1_stride_y + z * (int)src1_stride_z + w * (int)src1_stride_w;
-    const __global uchar *in2_ptr = src2_ptr + (int)src2_offset_first_element_in_bytes + x2 * (int)src2_stride_x + y * (int)src2_stride_y + z * (int)src2_stride_z + w * (int)src2_stride_w;
-    const __global uchar *in3_ptr = src3_ptr + (int)src3_offset_first_element_in_bytes + x3 * (int)src3_stride_x + y * (int)src3_stride_y + z * (int)src3_stride_z + w * (int)src3_stride_w;
-    const __global uchar *in4_ptr = src4_ptr + (int)src4_offset_first_element_in_bytes + x4 * (int)src4_stride_x + y * (int)src4_stride_y + z * (int)src4_stride_z + w * (int)src4_stride_w;
+    const __global uchar *dst_addr  = dst_ptr + (int)dst_offset_first_element_in_bytes + x * sizeof(DATA_TYPE) + y * (int)dst_stride_y + z * (int)dst_stride_z + w * (int)dst_stride_w;
+    const __global uchar *src1_addr = src1_ptr + (int)src1_offset_first_element_in_bytes + x1 * sizeof(DATA_TYPE) + y * (int)src1_stride_y + z * (int)src1_stride_z + w * (int)src1_stride_w;
+    const __global uchar *src2_addr = src2_ptr + (int)src2_offset_first_element_in_bytes + x2 * sizeof(DATA_TYPE) + y * (int)src2_stride_y + z * (int)src2_stride_z + w * (int)src2_stride_w;
+    const __global uchar *src3_addr = src3_ptr + (int)src3_offset_first_element_in_bytes + x3 * sizeof(DATA_TYPE) + y * (int)src3_stride_y + z * (int)src3_stride_z + w * (int)src3_stride_w;
+    const __global uchar *src4_addr = src4_ptr + (int)src4_offset_first_element_in_bytes + x4 * sizeof(DATA_TYPE) + y * (int)src4_stride_y + z * (int)src4_stride_z + w * (int)src4_stride_w;
 
     VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
-    src1_values = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)in1_ptr);
+    src1_values = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)src1_addr);
     VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
-    src2_values = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)in2_ptr);
+    src2_values = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)src2_addr);
     VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
-    src3_values = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)in3_ptr);
+    src3_values = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)src3_addr);
     VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
-    src4_values = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)in4_ptr);
+    src4_values = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)src4_addr);
 
 #if defined(OFFSET_IN1) && defined(OFFSET_OUT) && defined(SCALE_IN1) && defined(SCALE_OUT) && defined(OFFSET_IN2) && defined(SCALE_IN2) && defined(OFFSET_IN3) && defined(SCALE_IN3) && defined(OFFSET_IN4) && defined(SCALE_IN4)
     src1_values = requantize(src1_values, OFFSET_IN1, OFFSET_OUT, SCALE_IN1, SCALE_OUT);
@@ -266,13 +254,22 @@ __kernel void concatenate_width_x4(
     const VEC_DATA_TYPE(COND_DATA_TYPE, VEC_SIZE) cond_in3 = CONVERT(x_coords < (VEC_DATA_TYPE(int, VEC_SIZE))(INPUT1_WIDTH + INPUT2_WIDTH), VEC_DATA_TYPE(COND_DATA_TYPE, VEC_SIZE));
     const VEC_DATA_TYPE(COND_DATA_TYPE, VEC_SIZE) cond_in4 = CONVERT(x_coords < (VEC_DATA_TYPE(int, VEC_SIZE))(INPUT1_WIDTH + INPUT2_WIDTH + INPUT3_WIDTH), VEC_DATA_TYPE(COND_DATA_TYPE, VEC_SIZE));
 
+    // Rotate src1/2_values, if values0 is a combination of src1_values and src2_values.
+    src1_values = (x < INPUT1_WIDTH && x1 == INPUT1_WIDTH - VEC_SIZE) ? ROTATE(src1_values, VEC_SIZE, INPUT1_ROTATE_N) : src1_values;
+    src2_values = (x < INPUT1_WIDTH && x1 == INPUT1_WIDTH - VEC_SIZE) ? ROTATE(src2_values, VEC_SIZE, INPUT1_ROTATE_N) : src2_values;
+    // Rotate src2/3_values, if values0 is a combination of src2_values and src3_values.
+    src2_values = (x < INPUT1_WIDTH + INPUT2_WIDTH && x2 == INPUT2_WIDTH - VEC_SIZE) ? ROTATE(src2_values, VEC_SIZE, INPUT2_ROTATE_N) : src2_values;
+    src3_values = (x < INPUT1_WIDTH + INPUT2_WIDTH && x2 == INPUT2_WIDTH - VEC_SIZE) ? ROTATE(src3_values, VEC_SIZE, INPUT2_ROTATE_N) : src3_values;
+    // Rotate src3/4_values, if values0 is a combination of src3_values and src4_values.
+    src3_values = (x < INPUT1_WIDTH + INPUT2_WIDTH + INPUT3_WIDTH && x3 == INPUT3_WIDTH - VEC_SIZE) ? ROTATE(src3_values, VEC_SIZE, INPUT3_ROTATE_N) : src3_values;
+    src4_values = (x < INPUT1_WIDTH + INPUT2_WIDTH + INPUT3_WIDTH && x3 == INPUT3_WIDTH - VEC_SIZE) ? ROTATE(src4_values, VEC_SIZE, INPUT3_ROTATE_N) : src4_values;
+
     VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
-    values = select(src2_values, src1_values, cond_in2);
-    values = select(src3_values, values, cond_in3);
-    values = select(src4_values, values, cond_in4);
+    values0 = select(src2_values, src1_values, cond_in2);
+    values0 = select(src3_values, values0, cond_in3);
+    values0 = select(src4_values, values0, cond_in4);
 
-    VSTORE(VEC_SIZE)
-    (values, 0, (__global DATA_TYPE *)dst.ptr);
+    STORE_VECTOR_SELECT(values, DATA_TYPE, dst_addr, VEC_SIZE, VEC_SIZE_LEFTOVER, VEC_SIZE_LEFTOVER != 0 && get_global_id(0) == 0)
 }
 #endif /* defined(INPUT2_WIDTH) && defined(INPUT3_WIDTH) */
 #endif /* defined(INPUT1_WIDTH) */
diff --git a/src/core/CL/kernels/CLWidthConcatenate2TensorsKernel.cpp b/src/core/CL/kernels/CLWidthConcatenate2TensorsKernel.cpp
index 27c650894c..a7a3463f59 100644
--- a/src/core/CL/kernels/CLWidthConcatenate2TensorsKernel.cpp
+++ b/src/core/CL/kernels/CLWidthConcatenate2TensorsKernel.cpp
@@ -28,7 +28,6 @@
 #include "arm_compute/core/CL/ICLTensor.h"
 #include "arm_compute/core/Utils.h"
 #include "arm_compute/core/utils/misc/ShapeCalculator.h"
-#include "src/core/AccessWindowStatic.h"
 #include "src/core/CL/CLValidate.h"
 #include "src/core/helpers/WindowHelpers.h"
 #include "src/core/utils/helpers/tensor_info.h"
@@ -40,25 +39,6 @@ namespace arm_compute
 {
 namespace
 {
-constexpr unsigned int num_elems_processed_per_iteration = 8;
-
-std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output)
-{
-    // The window needs to be based on the output
-    Window             win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration));
-    AccessWindowStatic input1_access(input1, 0, 0, ceil_to_multiple(input1->dimension(0), num_elems_processed_per_iteration), input1->dimension(1));
-    const unsigned int input2_right_padding = ((output->dimension(0) / num_elems_processed_per_iteration) * num_elems_processed_per_iteration - input1->dimension(0) - input2->dimension(
-                                                   0)) % num_elems_processed_per_iteration;
-    AccessWindowStatic input2_access(input2, -(input1->dimension(0) % num_elems_processed_per_iteration),
-                                     0, input2->dimension(0) + input2_right_padding, input2->dimension(1));
-    AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration);
-    bool                   window_changed = update_window_and_padding(win, input1_access, input2_access, output_access);
-
-    Window win_collapsed = win.collapse(win, Window::DimZ);
-
-    Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
-    return std::make_pair(err, win_collapsed);
-}
 Status validate_arguments(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, output);
@@ -81,7 +61,6 @@ Status validate_arguments(const ITensorInfo *input1, const ITensorInfo *input2,
 Status CLWidthConcatenate2TensorsKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output)
 {
     ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input1, input2, output));
-    ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input1->clone().get(), input2->clone().get(), output->clone().get()).first);
     return Status{};
 }
 
@@ -90,13 +69,22 @@ void CLWidthConcatenate2TensorsKernel::configure(const CLCompileContext &compile
     ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input1, input2, output));
 
+    auto padding_info = get_padding_info({ input1, input2, output });
+
+    const unsigned int min_dimension                     = std::min(input1->dimension(0), input2->dimension(0));
+    const unsigned int num_elems_processed_per_iteration = adjust_vec_size(8, min_dimension);
+    const unsigned int vec_size_leftover                 = output->dimension(0) % num_elems_processed_per_iteration;
+
     // Add build options
     CLBuildOptions build_opts;
     build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input1->data_type()));
     build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration));
+    build_opts.add_option("-DVEC_SIZE_LEFTOVER=" + support::cpp11::to_string(vec_size_leftover));
     build_opts.add_option("-DDEPTH=" + support::cpp11::to_string(input1->dimension(2)));
     build_opts.add_option("-DINPUT1_WIDTH=" + support::cpp11::to_string(input1->dimension(0)));
+    build_opts.add_option("-DINPUT2_WIDTH=" + support::cpp11::to_string(input2->dimension(0)));
     build_opts.add_option("-DELEMENT_SIZE=" + support::cpp11::to_string(input1->element_size()));
+    build_opts.add_option("-DINPUT1_ROTATE_N=" + support::cpp11::to_string((input1->dimension(0) - vec_size_leftover) % num_elems_processed_per_iteration));
 
     // If input have different quantization info set quantization parameters needed for the re-quantization process
     const bool have_different_qinfo = helpers::tensor_info::tensors_have_different_quantization_info(output, input1, input2);
@@ -118,21 +106,12 @@ void CLWidthConcatenate2TensorsKernel::configure(const CLCompileContext &compile
     _kernel = create_kernel(compile_context, "concatenate_width_x2", build_opts.options());
 
     // Configure kernel window
-    auto win_config = validate_and_configure_window(input1, input2, output);
-    ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config));
-
-    ICLKernel::configure_internal(std::get<1>(win_config));
+    Window win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration));
+    ICLKernel::configure_internal(win.collapse(win, Window::DimZ));
 
     // Set output valid region
     output->set_valid_region(ValidRegion(Coordinates(), output->tensor_shape()));
-
-    // Pass paddings as arguments to the kernel
-    const unsigned int input1_width         = input1->dimension(0);
-    const unsigned int input1_right_padding = ceil_to_multiple(input1_width, num_elems_processed_per_iteration) - input1_width;
-    const unsigned int input2_left_padding  = input1_width % num_elems_processed_per_iteration;
-    unsigned int       idx0                 = 3 * num_arguments_per_4D_tensor();
-    _kernel.setArg<cl_uint>(idx0++, input1_right_padding);
-    _kernel.setArg<cl_uint>(idx0++, input2_left_padding);
+    ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
 
     // Set config_id for enabling LWS tuning
     _config_id = "concatenate_width_x2_";
diff --git a/src/core/CL/kernels/CLWidthConcatenate4TensorsKernel.cpp b/src/core/CL/kernels/CLWidthConcatenate4TensorsKernel.cpp
index 5ef2cc46ee..1c8fef2db3 100644
--- a/src/core/CL/kernels/CLWidthConcatenate4TensorsKernel.cpp
+++ b/src/core/CL/kernels/CLWidthConcatenate4TensorsKernel.cpp
@@ -28,7 +28,6 @@
 #include "arm_compute/core/CL/ICLTensor.h"
 #include "arm_compute/core/Helpers.h"
 #include "arm_compute/core/Utils.h"
-#include "src/core/AccessWindowStatic.h"
 #include "src/core/CL/CLValidate.h"
 #include "src/core/helpers/WindowHelpers.h"
 #include "src/core/utils/helpers/tensor_info.h"
@@ -40,41 +39,6 @@ namespace arm_compute
 {
 namespace
 {
-constexpr unsigned int num_elems_processed_per_iteration = 8;
-
-std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *input3, ITensorInfo *input4, ITensorInfo *output)
-{
-    const unsigned int input1_width = input1->dimension(0);
-    const unsigned int input2_width = input2->dimension(0);
-    const unsigned int input3_width = input3->dimension(0);
-    const unsigned int input4_width = input4->dimension(0);
-
-    // The window needs to be based on the output
-    Window             win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration));
-    AccessWindowStatic input1_access(input1, 0, 0, ceil_to_multiple(input1_width, num_elems_processed_per_iteration), input1->dimension(1));
-
-    const unsigned int input2_left_padding  = input1_width % num_elems_processed_per_iteration;
-    const unsigned int input2_right_padding = ((input1_width + input2_width) / num_elems_processed_per_iteration) * num_elems_processed_per_iteration - input1_width + num_elems_processed_per_iteration -
-                                              input2_width;
-    AccessWindowStatic input2_access(input2, -input2_left_padding, 0, input2_width + input2_right_padding, input2->dimension(1));
-
-    const unsigned int input3_left_padding  = (input1_width + input2_width) % num_elems_processed_per_iteration;
-    const unsigned int input3_right_padding = ((input1_width + input2_width + input3_width) / num_elems_processed_per_iteration) * num_elems_processed_per_iteration - input1_width - input2_width +
-                                              num_elems_processed_per_iteration - input3_width;
-    AccessWindowStatic input3_access(input3, -input3_left_padding, 0, input3_width + input3_right_padding, input3->dimension(1));
-
-    const unsigned int input4_left_padding  = (input1_width + input2_width + input3_width) % num_elems_processed_per_iteration;
-    const unsigned int input4_right_padding = (output->dimension(0) / num_elems_processed_per_iteration) * num_elems_processed_per_iteration + num_elems_processed_per_iteration - output->dimension(0);
-    AccessWindowStatic input4_access(input4, -input4_left_padding, 0, input4_width + input4_right_padding, input4->dimension(1));
-
-    AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration);
-    bool                   window_changed = update_window_and_padding(win, input1_access, input2_access, input3_access, input4_access, output_access);
-
-    Window win_collapsed = win.collapse(win, Window::DimZ);
-
-    Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
-    return std::make_pair(err, win_collapsed);
-}
 Status validate_arguments(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *input3, const ITensorInfo *input4, const ITensorInfo *output)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, input3, input4, output);
@@ -103,7 +67,6 @@ CLWidthConcatenate4TensorsKernel::CLWidthConcatenate4TensorsKernel()
 Status CLWidthConcatenate4TensorsKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *input3, const ITensorInfo *input4, const ITensorInfo *output)
 {
     ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input1, input2, input3, input4, output));
-    ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input1->clone().get(), input2->clone().get(), input3->clone().get(), input4->clone().get(), output->clone().get()).first);
     return Status{};
 }
 
@@ -115,15 +78,25 @@ void CLWidthConcatenate4TensorsKernel::configure(const CLCompileContext &compile
     ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, input3, input4, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input1, input2, input3, input4, output));
 
+    auto               padding_info                      = get_padding_info({ input1, input2, input3, input4, output });
+    const unsigned int min_dimension                     = std::min(std::min(input1->dimension(0), input2->dimension(0)), std::min(input3->dimension(0), input4->dimension(0)));
+    const unsigned int num_elems_processed_per_iteration = adjust_vec_size(8, min_dimension);
+    const unsigned int vec_size_leftover                 = output->dimension(0) % num_elems_processed_per_iteration;
+
     // Add build options
     CLBuildOptions build_opts;
     build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input1->data_type()));
     build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration));
+    build_opts.add_option("-DVEC_SIZE_LEFTOVER=" + support::cpp11::to_string(vec_size_leftover));
     build_opts.add_option("-DDEPTH=" + support::cpp11::to_string(input1->dimension(2)));
     build_opts.add_option("-DINPUT1_WIDTH=" + support::cpp11::to_string(input1->dimension(0)));
     build_opts.add_option("-DINPUT2_WIDTH=" + support::cpp11::to_string(input2->dimension(0)));
     build_opts.add_option("-DINPUT3_WIDTH=" + support::cpp11::to_string(input3->dimension(0)));
+    build_opts.add_option("-DINPUT4_WIDTH=" + support::cpp11::to_string(input4->dimension(0)));
     build_opts.add_option("-DELEMENT_SIZE=" + support::cpp11::to_string(input1->element_size()));
+    build_opts.add_option("-DINPUT1_ROTATE_N=" + support::cpp11::to_string((input1->dimension(0) - vec_size_leftover) % num_elems_processed_per_iteration));
+    build_opts.add_option("-DINPUT2_ROTATE_N=" + support::cpp11::to_string((input1->dimension(0) + input2->dimension(0) - vec_size_leftover) % num_elems_processed_per_iteration));
+    build_opts.add_option("-DINPUT3_ROTATE_N=" + support::cpp11::to_string((input1->dimension(0) + input2->dimension(0) + input3->dimension(0) - vec_size_leftover) % num_elems_processed_per_iteration));
 
     // If input have different quantization info set quantization parameters needed for the re-quantization process
     const bool have_different_qinfo = helpers::tensor_info::tensors_have_different_quantization_info(output, input1, input2, input3, input4);
@@ -151,34 +124,12 @@ void CLWidthConcatenate4TensorsKernel::configure(const CLCompileContext &compile
     _kernel = create_kernel(compile_context, "concatenate_width_x4", build_opts.options());
 
     // Configure kernel window
-    auto win_config = validate_and_configure_window(input1, input2, input3, input4, output);
-    ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config));
-
-    ICLKernel::configure_internal(std::get<1>(win_config));
+    Window win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration));
+    ICLKernel::configure_internal(win.collapse(win, Window::DimZ));
 
     // Set output valid region
     output->set_valid_region(ValidRegion(Coordinates(), output->tensor_shape()));
-
-    // Pass paddings as arguments to the kernel
-    const unsigned int input1_width = input1->dimension(0);
-    const unsigned int input2_width = input2->dimension(0);
-    const unsigned int input3_width = input3->dimension(0);
-
-    const unsigned int input1_right_padding = ceil_to_multiple(input1_width, num_elems_processed_per_iteration) - input1_width;
-    const unsigned int input2_left_padding  = input1_width % num_elems_processed_per_iteration;
-    const unsigned int input2_right_padding = ((input1_width + input2_width) / num_elems_processed_per_iteration) * num_elems_processed_per_iteration - input1_width + num_elems_processed_per_iteration -
-                                              input2_width;
-    const unsigned int input3_left_padding  = (input1_width + input2_width) % num_elems_processed_per_iteration;
-    const unsigned int input3_right_padding = ((input1_width + input2_width + input3_width) / num_elems_processed_per_iteration) * num_elems_processed_per_iteration - input1_width - input2_width +
-                                              num_elems_processed_per_iteration - input3_width;
-    const unsigned int input4_left_padding  = (input1_width + input2_width + input3_width) % num_elems_processed_per_iteration;
-    unsigned int       idx0                 = 5 * num_arguments_per_4D_tensor();
-    _kernel.setArg<cl_uint>(idx0++, input1_right_padding);
-    _kernel.setArg<cl_uint>(idx0++, input2_left_padding);
-    _kernel.setArg<cl_uint>(idx0++, input2_right_padding);
-    _kernel.setArg<cl_uint>(idx0++, input3_left_padding);
-    _kernel.setArg<cl_uint>(idx0++, input3_right_padding);
-    _kernel.setArg<cl_uint>(idx0++, input4_left_padding);
+    ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
 
     // Set config_id for enabling LWS tuning
     _config_id = "concatenate_width_x4_";