COMPMID-477 - Optimized CLNormalizationLayer

CLPixelWiseMultiplication has been removed within the function

Change-Id: Ibe7edd7921d5cef6ff68fdeeca89771129a8eaea
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/84459
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>

1 files changed, 51 insertions, 69 deletions

diff --git a/src/core/CL/cl_kernels/normalization_layer.cl b/src/core/CL/cl_kernels/normalization_layer.cl
index e2a5c4079a..4e65560b95 100644
--- a/src/core/CL/cl_kernels/normalization_layer.cl
+++ b/src/core/CL/cl_kernels/normalization_layer.cl
@@ -54,43 +54,33 @@
  *
  * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short
  * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE=size, e.g. -DVEC_SIZE=16
+ * @note The radius should be given as a preprocessor argument using -DRADIUS=size. e.g. -DRADIUS=5
+ * @note The number of slices should be given as a preprocessor argument using -DNUM_SLICES=size. e.g. -DNUM_SLICES=192
  * @note In case of fixed-point operation -DFIXED_POINT_POSITION=fixed_point_position must be provided: e.g. -DFIXED_POINT_POSITION=3
  * @note Scaling coefficient (= alpha/norm_size), beta and kappa need to be passed at compile time using -DCOEFF, -DALPHA and -DKAPPA
  *
- * @param[in]  input_ptr                                   Pointer to the first source tensor. Supported data types: QS8/QS16/F16/F32
- * @param[in]  input_stride_x                              Stride of the first 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 first 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 first 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 first source tensor
- * @param[in]  squared_input_ptr                           Pointer to the second source tensor. Supported data types: same as @p input_ptr
- * @param[in]  squared_input_stride_x                      Stride of the second source tensor in X dimension (in bytes)
- * @param[in]  squared_input_step_x                        input_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in]  squared_input_stride_y                      Stride of the second source tensor in Y dimension (in bytes)
- * @param[in]  squared_input_step_y                        input_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in]  squared_input_stride_z                      Stride of the second source tensor in Z dimension (in bytes)
- * @param[in]  squared_input_step_z                        input_stride_z * number of elements along Z processed per workitem(in bytes)
- * @param[in]  squared_input_offset_first_element_in_bytes The offset of the second element in the second 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]  radius                                      Number of elements on the right or left side to normalize across
+ * @param[in]  input_ptr                            Pointer to the first source tensor. Supported data types: QS8/QS16/F16/F32
+ * @param[in]  input_stride_x                       Stride of the first 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 first 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 first 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 first 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
  */
 __kernel void normalization_layer_cross_map(TENSOR3D_DECLARATION(input),
-                                            TENSOR3D_DECLARATION(squared_input),
-                                            TENSOR3D_DECLARATION(output),
-                                            uint radius)
+                                            TENSOR3D_DECLARATION(output))
 {
-    Tensor3D in         = CONVERT_TO_TENSOR3D_STRUCT(input);
-    Tensor3D squared_in = CONVERT_TO_TENSOR3D_STRUCT(squared_input);
-    Tensor3D out        = CONVERT_TO_TENSOR3D_STRUCT(output);
+    Tensor3D in  = CONVERT_TO_TENSOR3D_STRUCT(input);
+    Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output);
 
     VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
     acc = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))0;
@@ -101,15 +91,16 @@ __kernel void normalization_layer_cross_map(TENSOR3D_DECLARATION(input),
     const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
     kappa_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(KAPPA);
 
-    const int num_of_slices = get_global_size(2);
     const int current_slice = get_global_id(2);
 
-    const int left_slice  = max(current_slice - (int)radius, (int)0);
-    const int right_slice = min(current_slice + (int)radius, (int)(num_of_slices - 1));
+    const int left_slice  = max(current_slice - (int)RADIUS, (int)0);
+    const int right_slice = min(current_slice + (int)RADIUS, (int)(NUM_SLICES - 1));
 
     for(int i = left_slice; i <= right_slice; i++)
     {
-        acc = ADD_OP(acc, LOAD_OP(0, (__global DATA_TYPE *)tensor3D_offset(&squared_in, 0, 0, i - current_slice)));
+        VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+        values = LOAD_OP(0, (__global DATA_TYPE *)tensor3D_offset(&in, 0, 0, i - current_slice));
+        acc    = ADD_OP(acc, MUL_OP(values, values));
     }
 
     acc = ADD_OP(MUL_OP(acc, coeff_v), kappa_v);
@@ -125,43 +116,32 @@ __kernel void normalization_layer_cross_map(TENSOR3D_DECLARATION(input),
  *
  * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short
  * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE=size, e.g. -DVEC_SIZE=16
+ * @note The radius should be given as a preprocessor argument using -DRADIUS=size. e.g. -DRADIUS=5
  * @note In case of fixed-point operation -DFIXED_POINT_POSITION=fixed_point_position must be provided: e.g. -DFIXED_POINT_POSITION=3
  * @note Scaling coefficient (= alpha/norm_size), beta and kappa need to be passed at compile time using -DCOEFF, -DALPHA and -DKAPPA
  *
- * @param[in]  input_ptr                                   Pointer to the first source tensor. Supported data types: QS8/F16/F32
- * @param[in]  input_stride_x                              Stride of the first 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 first 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 first 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 first source tensor
- * @param[in]  squared_input_ptr                           Pointer to the second source tensor. Supported data types: same as @p input_ptr
- * @param[in]  squared_input_stride_x                      Stride of the second source tensor in X dimension (in bytes)
- * @param[in]  squared_input_step_x                        input_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in]  squared_input_stride_y                      Stride of the second source tensor in Y dimension (in bytes)
- * @param[in]  squared_input_step_y                        input_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in]  squared_input_stride_z                      Stride of the second source tensor in Z dimension (in bytes)
- * @param[in]  squared_input_step_z                        input_stride_z * number of elements along Z processed per workitem(in bytes)
- * @param[in]  squared_input_offset_first_element_in_bytes The offset of the second element in the second 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 first 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 first source 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]  radius                                      Number of elements on the right or left side to normalize across
+ * @param[in]  input_ptr                            Pointer to the first source tensor. Supported data types: QS8/F16/F32
+ * @param[in]  input_stride_x                       Stride of the first 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 first 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 first 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 first 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 first 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 first source 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
  */
 __kernel void normalization_layer_in_map_1D(TENSOR3D_DECLARATION(input),
-                                            TENSOR3D_DECLARATION(squared_input),
-                                            TENSOR3D_DECLARATION(output),
-                                            uint radius)
+                                            TENSOR3D_DECLARATION(output))
 {
-    Tensor3D in         = CONVERT_TO_TENSOR3D_STRUCT(input);
-    Tensor3D squared_in = CONVERT_TO_TENSOR3D_STRUCT(squared_input);
-    Tensor3D out        = CONVERT_TO_TENSOR3D_STRUCT(output);
+    Tensor3D in  = CONVERT_TO_TENSOR3D_STRUCT(input);
+    Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output);
 
     VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
     acc = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))0;
@@ -174,12 +154,14 @@ __kernel void normalization_layer_in_map_1D(TENSOR3D_DECLARATION(input),
 
     const int current_pos = get_global_id(0) << 2;
 
-    const int left_pos  = max(current_pos - (int)radius, -3);
-    const int right_pos = min(current_pos + (int)radius, (int)((get_global_size(0) << 2) + 3 - 1));
+    const int left_pos  = max(current_pos - (int)RADIUS, -3);
+    const int right_pos = min(current_pos + (int)RADIUS, (int)((get_global_size(0) << 2) + 3 - 1));
 
     for(int i = left_pos; i <= right_pos; i += 1)
     {
-        acc = ADD_OP(acc, LOAD_OP(0, (__global DATA_TYPE *)tensor3D_offset(&squared_in, i - current_pos, 0, 0)));
+        VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+        values = LOAD_OP(0, (__global DATA_TYPE *)tensor3D_offset(&in, i - current_pos, 0, 0));
+        acc    = ADD_OP(acc, MUL_OP(values, values));
     }
 
     acc = ADD_OP(MUL_OP(acc, coeff_v), kappa_v);