inference-engine/thirdparty/clDNN/kernel_selector/core/cl_kernels/convolution_gpu_yxfb_yxio_b16_fp16.cl

   1 // Copyright (c) 2016-2017 Intel Corporation
   2 //
   3 // Licensed under the Apache License, Version 2.0 (the "License");
   4 // you may not use this file except in compliance with the License.
   5 // You may obtain a copy of the License at
   6 //
   7 //      http://www.apache.org/licenses/LICENSE-2.0
   8 //
   9 // Unless required by applicable law or agreed to in writing, software
  10 // distributed under the License is distributed on an "AS IS" BASIS,
  11 // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  12 // See the License for the specific language governing permissions and
  13 // limitations under the License.
  14
  15
  16 #include "include/include_all.cl"
  17 #include "include/sub_group.cl"
  18
  19 __attribute__((intel_reqd_sub_group_size(16)))
  20 __attribute__((reqd_work_group_size(16, 1, 1)))
  21 KERNEL(convolution_gpu_yxfb_yxio_b16)(
  22     const __global UNIT_TYPE* input,
  23     __global UNIT_TYPE* output,
  24     const __global UNIT_TYPE* filter,
  25 #if BIAS_TERM
  26     const __global UNIT_TYPE* bias,
  27 #endif
  28     uint split_idx)
  29 {
  30     // get_global_size(0) -> Number of work items needed to compute all features and all batches for single output spatial position
  31     //                       (single (x, y) point in output).
  32     // get_global_size(1) -> Output size in X-dimension.
  33     // get_global_size(2) -> Output size in Y-dimension.
  34     // get_global_id(0)   -> Id of work item computing single spatial point of output indicated by get_global_id(1), get_global_id(2).
  35     // get_group_id(1)   -> Current x-position in output.
  36     // get_group_id(2)   -> Current y-position in output.
  37     //
  38     // WORK_ITEMS_PER_SINGLE_BATCHES_ELEMENTS -> Number of work items needed to compute entire one batch for at least one feature and one spatial point.
  39     //                                           (this number in current implementation computes also OFM_PER_WORK_ITEM output features at the same time).
  40     // FILTER_ARRAY_NUM                       -> Number of filters groups (split size).
  41
  42     const uint out_x = get_group_id(1);
  43     const uint out_y = get_group_id(2);
  44
  45     const uint output_f_size = OUTPUT_PAD_BEFORE_FEATURE_NUM + OUTPUT_FEATURE_NUM + OUTPUT_PAD_AFTER_FEATURE_NUM;
  46     const uint output_x_size = OUTPUT_PAD_BEFORE_SIZE_X + OUTPUT_SIZE_X + OUTPUT_PAD_AFTER_SIZE_X;
  47     const uint linear_id_xy = OUTPUT_PAD_BEFORE_SIZE_X + out_x + output_x_size * (out_y + OUTPUT_PAD_BEFORE_SIZE_Y);
  48     uint global_id = (((uint)get_global_id(0) / WORK_ITEMS_PER_SINGLE_BATCHES_ELEMENTS) + (linear_id_xy * FILTER_ARRAY_NUM + split_idx) * (output_f_size / OFM_PER_WORK_ITEM)) * WORK_ITEMS_PER_SINGLE_BATCHES_ELEMENTS;
  49
  50     const uint sub_group_id = get_local_id(0);
  51
  52 #if defined(USE_BLOCK_READ_2) || defined(USE_BLOCK_READ_1)
  53     const uint chunk_size = sizeof(uint)/sizeof(UNIT_TYPE);
  54 #else
  55     const uint chunk_size = 1;
  56 #endif
  57
  58     const uint out_batch_id = chunk_size * sub_group_id + LOCAL_WORK_GROUP_SIZE * BATCHES_PER_WORK_ITEM * ((uint)get_group_id(0) % LOCAL_WORK_GROUPS_PER_SINGLE_BATCHES_ELEMENTS);
  59
  60     const uint out_id = (global_id / WORK_ITEMS_PER_SINGLE_BATCHES_ELEMENTS) * OFM_PER_WORK_ITEM * OUTPUT_FEATURE_PITCH + OUTPUT_PAD_BEFORE_FEATURE_NUM * OUTPUT_FEATURE_PITCH + OUTPUT_PAD_BEFORE_BATCH_NUM + out_batch_id;
  61
  62     const uint ofm_offset = ((global_id * OFM_PER_WORK_ITEM) / WORK_ITEMS_PER_SINGLE_BATCHES_ELEMENTS) % output_f_size;
  63
  64     // Each component of vector element contains computation for separate output feature.
  65     half16 _data[BATCHES_PER_WORK_ITEM];
  66     for(uint i = 0; i < BATCHES_PER_WORK_ITEM; i++)
  67     {
  68         _data[i] = UNIT_VAL_ZERO;
  69     }
  70
  71     const int x = (int)out_x * STRIDE_SIZE_X - PADDING_SIZE_X;
  72     const int y = (int)out_y * STRIDE_SIZE_Y - PADDING_SIZE_Y;
  73
  74     for (uint i = 0; i < FILTER_SIZE_Y; i++)
  75     {
  76         const int input_offset_y = y + i * DILATION_SIZE_Y;
  77         const bool zero_y = input_offset_y >= INPUT0_SIZE_Y || input_offset_y < 0;
  78
  79         if(!zero_y)
  80         {
  81             for (uint j = 0; j < FILTER_SIZE_X; j++)
  82             {
  83                 const int input_offset_x = x + j * DILATION_SIZE_X;
  84                 const bool zero = input_offset_x >= INPUT0_SIZE_X || input_offset_x < 0;
  85
  86                 if(!zero)
  87                 {
  88                     uint input_idx = input_offset_x*INPUT0_X_PITCH + input_offset_y*INPUT0_Y_PITCH;
  89                     input_idx += INPUT0_OFFSET + split_idx * FILTER_IFM_NUM * INPUT0_FEATURE_PITCH;
  90                     input_idx += out_batch_id;
  91
  92                     //sub_group_id used as offset to make each workitem load different filter, and then shuffle it
  93                     // 2 * sub_group_id is used because we group 2 halfs as one uint element.
  94                     uint filter_idx = ofm_offset + 2*sub_group_id + i*FILTER_Y_PITCH + j*FILTER_X_PITCH;
  95
  96                     for (uint h = 0; h < FILTER_IFM_NUM; h++)
  97                     {
  98 #if defined(USE_BLOCK_READ_2)
  99                         half4 _input = as_half4(intel_sub_group_block_read2((const __global uint*)(input + input_idx)));
 100                         uint filter_val_pair = *(const __global uint*)(filter + filter_idx);
 101                         half16 filter_transp = TRANSPOSE_BLOCK_16_FP16(filter_val_pair);
 102                         _data[0] = fma(_input.s0, filter_transp, _data[0]);
 103                         _data[1] = fma(_input.s1, filter_transp, _data[1]);
 104                         _data[2] = fma(_input.s2, filter_transp, _data[2]);
 105                         _data[3] = fma(_input.s3, filter_transp, _data[3]);
 106                         input_idx += INPUT0_FEATURE_PITCH;
 107 #elif defined(USE_BLOCK_READ_1)
 108                         half2 _input = as_half2(intel_sub_group_block_read((const __global uint*)(input + input_idx)));
 109                         uint filter_val_pair = *(const __global uint*)(filter + filter_idx);
 110                         half16 filter_transp = TRANSPOSE_BLOCK_16_FP16(filter_val_pair);
 111                         _data[0] = fma(_input.s0, filter_transp, _data[0]);
 112                         _data[1] = fma(_input.s1, filter_transp, _data[1]);
 113                         input_idx += INPUT0_FEATURE_PITCH;
 114 #else
 115                         uint filter_val_pair = *(const __global uint*)(filter + filter_idx);
 116                         half16 filter_transp = TRANSPOSE_BLOCK_16_FP16(filter_val_pair);
 117                         for(uint s = 0; s < BATCHES_PER_WORK_ITEM; s++)
 118                         {
 119                             _data[s] = fma(input[input_idx], filter_transp, _data[s]);
 120                             input_idx += LOCAL_WORK_GROUP_SIZE;
 121                         }
 122                         input_idx += INPUT0_FEATURE_PITCH - BATCHES_PER_WORK_ITEM * LOCAL_WORK_GROUP_SIZE;
 123 #endif
 124                         filter_idx += FILTER_IFM_PITCH;
 125                     }
 126                 }
 127             }
 128         }
 129     }
 130
 131 #if BIAS_TERM
 132     uint bias_val_pair = *(const __global uint*)(bias + (ofm_offset + 2 * sub_group_id));
 133     for(uint s = 0; s < BATCHES_PER_WORK_ITEM; s++)
 134     {
 135         ADD_BIAS_16_FP16(_data[s], bias_val_pair);
 136     }
 137 #endif
 138     for(uint s = 0; s < BATCHES_PER_WORK_ITEM; s++)
 139     {
 140         _data[s] = ACTIVATION(_data[s], NL_M, NL_N);
 141     }
 142
 143 #if defined(USE_BLOCK_READ_2) || defined(USE_BLOCK_READ_1)
 144     #if BATCHES_PER_WORK_ITEM == 4
 145         uint _out_id = OUTPUT_VIEW_OFFSET + out_id;
 146         for(uint i = 0; i < 16; i++)
 147         {
 148             *(__global uint*)(output + _out_id) = as_uint((half2)(_data[0][i], _data[1][i]));
 149             *(__global uint*)(output + _out_id + 32) = as_uint((half2)(_data[2][i], _data[3][i]));
 150             _out_id += OUTPUT_FEATURE_PITCH;
 151         }
 152     #else
 153     for(uint s = 0; s < BATCHES_PER_WORK_ITEM / 2; s++)
 154     {
 155         uint _out_id = OUTPUT_VIEW_OFFSET + out_id + chunk_size * s * LOCAL_WORK_GROUP_SIZE;
 156         *(__global uint*)(output + _out_id) = as_uint((half2)(_data[chunk_size * s].s0, _data[chunk_size * s + 1].s0)); _out_id += OUTPUT_FEATURE_PITCH;
 157         *(__global uint*)(output + _out_id) = as_uint((half2)(_data[chunk_size * s].s1, _data[chunk_size * s + 1].s1)); _out_id += OUTPUT_FEATURE_PITCH;
 158         *(__global uint*)(output + _out_id) = as_uint((half2)(_data[chunk_size * s].s2, _data[chunk_size * s + 1].s2)); _out_id += OUTPUT_FEATURE_PITCH;
 159         *(__global uint*)(output + _out_id) = as_uint((half2)(_data[chunk_size * s].s3, _data[chunk_size * s + 1].s3)); _out_id += OUTPUT_FEATURE_PITCH;
 160         *(__global uint*)(output + _out_id) = as_uint((half2)(_data[chunk_size * s].s4, _data[chunk_size * s + 1].s4)); _out_id += OUTPUT_FEATURE_PITCH;
 161         *(__global uint*)(output + _out_id) = as_uint((half2)(_data[chunk_size * s].s5, _data[chunk_size * s + 1].s5)); _out_id += OUTPUT_FEATURE_PITCH;
 162         *(__global uint*)(output + _out_id) = as_uint((half2)(_data[chunk_size * s].s6, _data[chunk_size * s + 1].s6)); _out_id += OUTPUT_FEATURE_PITCH;
 163         *(__global uint*)(output + _out_id) = as_uint((half2)(_data[chunk_size * s].s7, _data[chunk_size * s + 1].s7)); _out_id += OUTPUT_FEATURE_PITCH;
 164         *(__global uint*)(output + _out_id) = as_uint((half2)(_data[chunk_size * s].s8, _data[chunk_size * s + 1].s8)); _out_id += OUTPUT_FEATURE_PITCH;
 165         *(__global uint*)(output + _out_id) = as_uint((half2)(_data[chunk_size * s].s9, _data[chunk_size * s + 1].s9)); _out_id += OUTPUT_FEATURE_PITCH;
 166         *(__global uint*)(output + _out_id) = as_uint((half2)(_data[chunk_size * s].sa, _data[chunk_size * s + 1].sa)); _out_id += OUTPUT_FEATURE_PITCH;
 167         *(__global uint*)(output + _out_id) = as_uint((half2)(_data[chunk_size * s].sb, _data[chunk_size * s + 1].sb)); _out_id += OUTPUT_FEATURE_PITCH;
 168         *(__global uint*)(output + _out_id) = as_uint((half2)(_data[chunk_size * s].sc, _data[chunk_size * s + 1].sc)); _out_id += OUTPUT_FEATURE_PITCH;
 169         *(__global uint*)(output + _out_id) = as_uint((half2)(_data[chunk_size * s].sd, _data[chunk_size * s + 1].sd)); _out_id += OUTPUT_FEATURE_PITCH;
 170         *(__global uint*)(output + _out_id) = as_uint((half2)(_data[chunk_size * s].se, _data[chunk_size * s + 1].se)); _out_id += OUTPUT_FEATURE_PITCH;
 171         *(__global uint*)(output + _out_id) = as_uint((half2)(_data[chunk_size * s].sf, _data[chunk_size * s + 1].sf)); _out_id += OUTPUT_FEATURE_PITCH;
 172     }
 173     #endif
 174 #else
 175     for(uint s = 0; s < BATCHES_PER_WORK_ITEM; s++)
 176     {
 177         uint _out_id = OUTPUT_VIEW_OFFSET + out_id + s * LOCAL_WORK_GROUP_SIZE;
 178         output[_out_id] = _data[s].s0; _out_id += OUTPUT_FEATURE_PITCH;
 179         output[_out_id] = _data[s].s1; _out_id += OUTPUT_FEATURE_PITCH;
 180         output[_out_id] = _data[s].s2; _out_id += OUTPUT_FEATURE_PITCH;
 181         output[_out_id] = _data[s].s3; _out_id += OUTPUT_FEATURE_PITCH;
 182         output[_out_id] = _data[s].s4; _out_id += OUTPUT_FEATURE_PITCH;
 183         output[_out_id] = _data[s].s5; _out_id += OUTPUT_FEATURE_PITCH;
 184         output[_out_id] = _data[s].s6; _out_id += OUTPUT_FEATURE_PITCH;
 185         output[_out_id] = _data[s].s7; _out_id += OUTPUT_FEATURE_PITCH;
 186         output[_out_id] = _data[s].s8; _out_id += OUTPUT_FEATURE_PITCH;
 187         output[_out_id] = _data[s].s9; _out_id += OUTPUT_FEATURE_PITCH;
 188         output[_out_id] = _data[s].sa; _out_id += OUTPUT_FEATURE_PITCH;
 189         output[_out_id] = _data[s].sb; _out_id += OUTPUT_FEATURE_PITCH;
 190         output[_out_id] = _data[s].sc; _out_id += OUTPUT_FEATURE_PITCH;
 191         output[_out_id] = _data[s].sd; _out_id += OUTPUT_FEATURE_PITCH;
 192         output[_out_id] = _data[s].se; _out_id += OUTPUT_FEATURE_PITCH;
 193         output[_out_id] = _data[s].sf; _out_id += OUTPUT_FEATURE_PITCH;
 194     }
 195 #endif
 196 }