diff options
Diffstat (limited to 'src/core/CL/cl_kernels/softmax_layer.cl')
| -rw-r--r-- | src/core/CL/cl_kernels/softmax_layer.cl | 611 |
1 files changed, 0 insertions, 611 deletions
diff --git a/src/core/CL/cl_kernels/softmax_layer.cl b/src/core/CL/cl_kernels/softmax_layer.cl deleted file mode 100644 index 767cf4c4f7..0000000000 --- a/src/core/CL/cl_kernels/softmax_layer.cl +++ /dev/null @@ -1,611 +0,0 @@ -/* - * Copyright (c) 2017-2019 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" - -#define MAX_OP(x, y, type, size) max((x), (y)) -#define ADD_OP(x, y, type, size) ((x) + (y)) -#define SUB_OP(x, y, type, size) ((x) - (y)) -#define MUL_OP(x, y, type, size) ((x) * (y)) -#define DIV_OP(x, y, type, size) ((x) / (y)) -#define EXP_OP(x, type, size) exp((x)) - -#ifdef USE_F16 -#define MINVAL -HALF_MAX -#define SELECT_DATA_TYPE short -#else /* USE_F16 */ -#define MINVAL -FLT_MAX -#define SELECT_DATA_TYPE int -#endif /* USE_F16 */ - -/* Number of workitems in dimension 0. */ -#if !defined(GRID_SIZE) -#define GRID_SIZE 1 -#endif /* !defined(GRID_SIZE) */ - -/* Vector size, i.e. number of vector elements. */ -#if VECTOR_SIZE == 2 -__constant VEC_DATA_TYPE(DATA_TYPE, 2) type_min_ = (VEC_DATA_TYPE(DATA_TYPE, 2))(MINVAL); -__constant uint2 idx__ = (uint2)(0, 1); - -#elif VECTOR_SIZE == 4 -__constant VEC_DATA_TYPE(DATA_TYPE, 4) type_min_ = (VEC_DATA_TYPE(DATA_TYPE, 4))(MINVAL); -__constant uint4 idx__ = (uint4)(0, 1, 2, 3); - -#elif VECTOR_SIZE == 8 -__constant VEC_DATA_TYPE(DATA_TYPE, 8) type_min_ = (VEC_DATA_TYPE(DATA_TYPE, 8))(MINVAL); -__constant uint8 idx__ = (uint8)(0, 1, 2, 3, 4, 5, 6, 7); - -#else /* VECTOR_SIZE DEFAULT */ -#define VECTOR_SIZE 16 -#define LOG_VECTOR_SIZE 4 -__constant VEC_DATA_TYPE(DATA_TYPE, 16) type_min_ = (VEC_DATA_TYPE(DATA_TYPE, 16))(MINVAL); -__constant uint16 idx__ = (uint16)(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15); - -#endif /* VECTOR_SIZE END */ - -// TODO (COMPMID-661): Remove if the non-fused kernels are removed -__constant VEC_DATA_TYPE(DATA_TYPE, 16) type_min = (VEC_DATA_TYPE(DATA_TYPE, 16))(MINVAL); -__constant uint16 idx16 = (uint16)(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15); -__constant uint4 idx4 = (uint4)(0, 1, 2, 3); - -/** Divides all the values of the input tensor by the sum calculated from softmax_layer_shift_exp_sum kernel. - * - * @note Datatype must be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short - * - * @param[in] src_ptr Pointer to the source tensor slice. 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 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_offset_first_element_in_bytes The offset of the first element in the source tensor - * @param[in] sum_ptr Pointer to the sum values tensor slice. Supported data types: same as @p src_ptr - * @param[in] sum_stride_x Stride of the sum values 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 sum values 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 sum values 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 sum values tensor - * @param[out] dst_ptr Pointer to the destination tensor slice. 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 Z processed per workitem(in bytes) - * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor - */ -__kernel void softmax_layer_norm( - TENSOR3D_DECLARATION(src), - TENSOR3D_DECLARATION(sum), - TENSOR3D_DECLARATION(dst)) -{ - Image src = CONVERT_TENSOR3D_TO_IMAGE_STRUCT(src); - Image dst = CONVERT_TENSOR3D_TO_IMAGE_STRUCT(dst); - Image sum = CONVERT_TENSOR3D_TO_IMAGE_STRUCT_NO_STEP(sum); - - // Load max value of 1D logits vector (row) - DATA_TYPE sum_val = *((__global DATA_TYPE *)offset(&sum, 0, get_global_id(1))); - VEC_DATA_TYPE(DATA_TYPE, 16) - data = vload16(0, (__global DATA_TYPE *)offset(&src, 0, 0)); -#ifdef LOG_SOFTMAX - vstore16(SUB_OP(data, sum_val, DATA_TYPE, 16), 0, (__global DATA_TYPE *)offset(&dst, 0, 0)); -#else /* LOG_SOFTMAX */ - vstore16(DIV_OP(data, sum_val, DATA_TYPE, 16), 0, (__global DATA_TYPE *)offset(&dst, 0, 0)); -#endif /* LOG_SOFTMAX */ -} - -/** Identifies the maximum value across the 1st dimension and shifts the values of the input tensor by this maximum value, - * then gets the exponent of each element as sums all elements across each row. - * - * @note Datatype must be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short - * @note In case the input is not a multiple of VECTOR_SIZE (2,4,8,16) -DNON_MULTIPLE_OF_VECTOR_SIZE must be passed. - * @note Beta can be optionally passed at compile time using -DBETA (by default, it is 1.0). - * - * @param[in] src_ptr Pointer to the source tensor slice. 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 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_offset_first_element_in_bytes The offset of the first element in the source tensor - * @param[in] maxo_ptr Pointer to the max values tensor slice. Supported data types: same as @p src_ptr - * @param[in] maxo_stride_x Stride of the max values tensor in X dimension (in bytes) - * @param[in] maxo_step_x max_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] maxo_stride_y Stride of the max values tensor in Y dimension (in bytes) - * @param[in] maxo_step_y max_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] maxo_stride_z Stride of the max values tensor in Z dimension (in bytes) - * @param[in] maxo_step_z max_stride_z * number of elements along Z processed per workitem(in bytes) - * @param[in] maxo_offset_first_element_in_bytes The offset of the first element in the max values tensor - * @param[out] dst_ptr Pointer to the destination tensor slice. 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 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[out] sum_ptr Pointer to the sum values tensor slice. Supported data types: same as @p src_ptr - * @param[in] sum_stride_x Stride of the sum values 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 sum values tensor in Y dimension (in bytes) - * @param[in] sum_step_y sum_stride_z * number of elements along Z processed per workitem(in bytes) - * @param[in] sum_stride_z Stride of the sum values 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 sum values tensor - * @param[in] width Input image width - */ -__kernel void softmax_layer_max_shift_exp_sum_serial( - TENSOR3D_DECLARATION(src), - TENSOR3D_DECLARATION(maxo), - TENSOR3D_DECLARATION(dst), - TENSOR3D_DECLARATION(sum), - uint width) -{ - Image src = CONVERT_TENSOR3D_TO_IMAGE_STRUCT(src); - Image dst = CONVERT_TENSOR3D_TO_IMAGE_STRUCT(dst); - Image maxo = CONVERT_TENSOR3D_TO_IMAGE_STRUCT(maxo); - Image sum = CONVERT_TENSOR3D_TO_IMAGE_STRUCT(sum); - -#ifdef BETA - // Initialize beta - VEC_DATA_TYPE(DATA_TYPE, VECTOR_SIZE) - beta = (VEC_DATA_TYPE(DATA_TYPE, VECTOR_SIZE))BETA; -#endif /* BETA */ - - // Initialize local maximum - VEC_DATA_TYPE(DATA_TYPE, VECTOR_SIZE) - max_val_vec = (VEC_DATA_TYPE(DATA_TYPE, VECTOR_SIZE))type_min_; - - // Calculate max of row - const uint width_ = width >> LOG_VECTOR_SIZE; - for(uint i = 0; i < width_; i++) - { - VEC_DATA_TYPE(DATA_TYPE, VECTOR_SIZE) - data_max = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)offset(&src, i << LOG_VECTOR_SIZE, 0)); - max_val_vec = MAX_OP(data_max, max_val_vec, DATA_TYPE, VECTOR_SIZE); - } - -#ifdef NON_MULTIPLE_OF_VECTOR_SIZE - VEC_DATA_TYPE(DATA_TYPE, VECTOR_SIZE) - data_max = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)offset(&src, width_ << LOG_VECTOR_SIZE, 0)); - VEC_DATA_TYPE(SELECT_DATA_TYPE, VECTOR_SIZE) - widx = CONVERT((EXPAND((CL_VEC_DATA_TYPE(uint, VECTOR_SIZE)))(width_ << LOG_VECTOR_SIZE) + idx__) < width, VEC_DATA_TYPE(SELECT_DATA_TYPE, VECTOR_SIZE)); - max_val_vec = MAX_OP(max_val_vec, select(type_min_, data_max, widx), DATA_TYPE, VECTOR_SIZE); -#endif /* NON_MULTIPLE_OF_VECTOR_SIZE */ - - // Perform max reduction -#if VECTOR_SIZE == 16 - max_val_vec.s01234567 = MAX_OP(max_val_vec.s01234567, max_val_vec.s89ABCDEF, DATA_TYPE, 8); -#endif /* VECTOR SIZE 16 END */ -#if VECTOR_SIZE >= 8 - max_val_vec.s0123 = MAX_OP(max_val_vec.s0123, max_val_vec.s4567, DATA_TYPE, 4); -#endif /* VECTOR SIZE 8 END */ -#if VECTOR_SIZE >= 4 - max_val_vec.s01 = MAX_OP(max_val_vec.s01, max_val_vec.s23, DATA_TYPE, 2); -#endif /* VECTOR SIZE 4 END */ - max_val_vec.s0 = MAX_OP(max_val_vec.s0, max_val_vec.s1, DATA_TYPE, 1); - // Store result - *((__global DATA_TYPE *)maxo.ptr) = max_val_vec.s0; - - /* Second section */ - - // Load max value of 1D logits vector (row) - DATA_TYPE max_val = *((__global DATA_TYPE *)offset(&maxo, 0, 0)); - - // Set sum vector - VEC_DATA_TYPE(DATA_TYPE, VECTOR_SIZE) - sum1D = 0; - - // Shift values, exp and sum - for(uint i = 0; i < width_; i++) - { - VEC_DATA_TYPE(DATA_TYPE, VECTOR_SIZE) - data = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)offset(&src, i << LOG_VECTOR_SIZE, 0)); - data = SUB_OP(data, max_val, DATA_TYPE, VECTOR_SIZE); -#ifdef BETA - data = MUL_OP(data, beta, DATA_TYPE, VECTOR_SIZE); -#endif /* BETA */ -#ifdef LOG_SOFTMAX - VSTORE(VECTOR_SIZE) - (data, 0, (__global DATA_TYPE *)offset(&dst, i << LOG_VECTOR_SIZE, 0)); - data = EXP_OP(data, DATA_TYPE, VECTOR_SIZE); -#else /* LOG_SOFTMAX */ - data = EXP_OP(data, DATA_TYPE, VECTOR_SIZE); - VSTORE(VECTOR_SIZE) - (data, 0, (__global DATA_TYPE *)offset(&dst, i << LOG_VECTOR_SIZE, 0)); -#endif /* LOG_SOFTMAX */ - sum1D = ADD_OP(sum1D, data, DATA_TYPE, VECTOR_SIZE); - } - -#ifdef NON_MULTIPLE_OF_VECTOR_SIZE - VEC_DATA_TYPE(DATA_TYPE, VECTOR_SIZE) - data = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)offset(&src, width_ << LOG_VECTOR_SIZE, 0)); - data = SUB_OP(data, max_val, DATA_TYPE, VECTOR_SIZE); -#ifdef BETA - data = MUL_OP(data, beta, DATA_TYPE, VECTOR_SIZE); -#endif /* BETA */ -#ifdef LOG_SOFTMAX - VSTORE(VECTOR_SIZE) - (data, 0, (__global DATA_TYPE *)offset(&dst, width_ << LOG_VECTOR_SIZE, 0)); - data = EXP_OP(data, DATA_TYPE, VECTOR_SIZE); - widx = CONVERT((EXPAND((CL_VEC_DATA_TYPE(uint, VECTOR_SIZE)))(width_ << LOG_VECTOR_SIZE) + idx__) < width, VEC_DATA_TYPE(SELECT_DATA_TYPE, VECTOR_SIZE)); - data = select(0, data, widx); -#else /* LOG_SOFTMAX */ - data = EXP_OP(data, DATA_TYPE, VECTOR_SIZE); - widx = CONVERT((EXPAND((CL_VEC_DATA_TYPE(uint, VECTOR_SIZE)))(width_ << LOG_VECTOR_SIZE) + idx__) < width, VEC_DATA_TYPE(SELECT_DATA_TYPE, VECTOR_SIZE)); - data = select(0, data, widx); - VSTORE(VECTOR_SIZE) - (data, 0, (__global DATA_TYPE *)offset(&dst, width_ << LOG_VECTOR_SIZE, 0)); -#endif /* LOG_SOFTMAX */ - sum1D = ADD_OP(sum1D, data, DATA_TYPE, VECTOR_SIZE); -#endif /* NON_MULTIPLE_OF_VECTOR_SIZE */ - - // Perform sum reduction -#if VECTOR_SIZE == 16 - sum1D.s01234567 = ADD_OP(sum1D.s01234567, sum1D.s89ABCDEF, DATA_TYPE, 8); -#endif /* VECTOR SIZE 16 END */ -#if VECTOR_SIZE >= 8 - sum1D.s0123 = ADD_OP(sum1D.s0123, sum1D.s4567, DATA_TYPE, 4); -#endif /* VECTOR SIZE 8 END */ -#if VECTOR_SIZE >= 4 - sum1D.s01 = ADD_OP(sum1D.s01, sum1D.s23, DATA_TYPE, 2); -#endif /* VECTOR SIZE 4 END */ - sum1D.s0 = ADD_OP(sum1D.s0, sum1D.s1, DATA_TYPE, 1); - - // Calculate and store result - *((__global DATA_TYPE *)sum.ptr) = sum1D.s0; -} - -/** Identifies the maximum value across the 1st dimension and shifts the values of the input tensor by this maximum value, - * then gets the exponent of each element as sums all elements across each row. - * - * @note Datatype must be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short - * @note In case the input is not a multiple of VECTOR_SIZE (2,4,8,16) -DNON_MULTIPLE_OF_VECTOR_SIZE must be passed. - * @note Beta can be optionally passed at compile time using -DBETA (by default, it is 1.0). - * - * @param[in] src_ptr Pointer to the source tensor slice. 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 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_offset_first_element_in_bytes The offset of the first element in the source tensor - * @param[in] maxo_ptr Pointer to the max values tensor slice. Supported data types: same as @p src_ptr - * @param[in] maxo_stride_x Stride of the max values tensor in X dimension (in bytes) - * @param[in] maxo_step_x max_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] maxo_stride_y Stride of the max values tensor in Y dimension (in bytes) - * @param[in] maxo_step_y max_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] maxo_stride_z Stride of the max values tensor in Z dimension (in bytes) - * @param[in] maxo_step_z max_stride_z * number of elements along Z processed per workitem(in bytes) - * @param[in] maxo_offset_first_element_in_bytes The offset of the first element in the max values tensor - * @param[out] dst_ptr Pointer to the destination tensor slice. 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 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[out] sum_ptr Pointer to the sum values tensor slice. Supported data types: same as @p src_ptr - * @param[in] sum_stride_x Stride of the sum values 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 sum values tensor in Y dimension (in bytes) - * @param[in] sum_step_y sum_stride_z * number of elements along Z processed per workitem(in bytes) - * @param[in] sum_stride_z Stride of the sum values 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 sum values tensor - * @param[in] width Input image width - */ -__kernel void softmax_layer_max_shift_exp_sum_parallel( - TENSOR3D_DECLARATION(src), - TENSOR3D_DECLARATION(maxo), - TENSOR3D_DECLARATION(dst), - TENSOR3D_DECLARATION(sum), - uint width) -{ - Image src = CONVERT_TENSOR3D_TO_IMAGE_STRUCT(src); - Image dst = CONVERT_TENSOR3D_TO_IMAGE_STRUCT(dst); - Image maxo = CONVERT_TENSOR3D_TO_IMAGE_STRUCT(maxo); - Image sum = CONVERT_TENSOR3D_TO_IMAGE_STRUCT(sum); - - const uint lid = get_local_id(0); - -#ifdef BETA - // Initialize beta - VEC_DATA_TYPE(DATA_TYPE, 4) - beta = (VEC_DATA_TYPE(DATA_TYPE, 4))BETA; -#endif /* BETA */ - - // Define one temporary vector per work-item. - __local VEC_DATA_TYPE(DATA_TYPE, 4) tmp_local[GRID_SIZE]; - __local DATA_TYPE max_local; - - __constant VEC_DATA_TYPE(DATA_TYPE, 4) type_min4 = (VEC_DATA_TYPE(DATA_TYPE, 4))(MINVAL); - VEC_DATA_TYPE(DATA_TYPE, 4) - max_val_vec = (VEC_DATA_TYPE(DATA_TYPE, 4))type_min4; - // Number of elements per work-item. - const uint row = width / GRID_SIZE; - // Number of iterations per work-item. - const uint width_ = row >> 2; - // Calculate max of row - uint i = 0; - for(; i < width_; i++) - { - VEC_DATA_TYPE(DATA_TYPE, 4) - data_max = VLOAD(4)(0, (__global DATA_TYPE *)offset(&src, i * GRID_SIZE * 4, 0)); - max_val_vec = MAX_OP(data_max, max_val_vec, DATA_TYPE, 4); - } -#ifdef NON_MULTIPLE_OF_GRID_SIZE - // How many work-items needed to complete the computation. - //TODO: Optimize this calculation (avoid %). - int boundary_workitems = (width % (GRID_SIZE * 4)) / 4; - if(lid < boundary_workitems) - { - VEC_DATA_TYPE(DATA_TYPE, 4) - data_max = VLOAD(4)(0, (__global DATA_TYPE *)offset(&src, i * GRID_SIZE * 4, 0)); - max_val_vec = MAX_OP(data_max, max_val_vec, DATA_TYPE, 4); - } -#ifdef NON_MULTIPLE_OF_VECTOR_SIZE - if(boundary_workitems == 0) - { - boundary_workitems = GRID_SIZE; - i--; - } - if(lid == (boundary_workitems - 1)) - { - // Handle non multiple of 4 - VEC_DATA_TYPE(DATA_TYPE, 4) - data_max = VLOAD(4)(0, (__global DATA_TYPE *)offset(&src, (GRID_SIZE * i * 4) + 4, 0)); - VEC_DATA_TYPE(SELECT_DATA_TYPE, 4) - widx = CONVERT(((uint4)(GRID_SIZE * i * 4) + boundary_workitems * 4 + idx4) < width, VEC_DATA_TYPE(SELECT_DATA_TYPE, 4)); - max_val_vec = MAX_OP(max_val_vec, select(type_min_, data_max, widx), DATA_TYPE, 4); - } -#endif /* NON_MULTIPLE_OF_VECTOR_SIZE */ -#endif /* NON_MULTIPLE_OF_GRID_SIZE */ - tmp_local[lid] = max_val_vec; - - barrier(CLK_LOCAL_MEM_FENCE); - - if(GRID_SIZE >= 256) - { - if(lid < 128) - { - tmp_local[lid] = MAX_OP(tmp_local[lid + 128], tmp_local[lid], DATA_TYPE, 4); - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(GRID_SIZE >= 128) - { - if(lid < 64) - { - tmp_local[lid] = MAX_OP(tmp_local[lid + 64], tmp_local[lid], DATA_TYPE, 4); - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(GRID_SIZE >= 64) - { - if(lid < 32) - { - tmp_local[lid] = MAX_OP(tmp_local[lid + 32], tmp_local[lid], DATA_TYPE, 4); - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(GRID_SIZE >= 32) - { - if(lid < 16) - { - tmp_local[lid] = MAX_OP(tmp_local[lid + 16], tmp_local[lid], DATA_TYPE, 4); - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(GRID_SIZE >= 16) - { - if(lid < 8) - { - tmp_local[lid] = MAX_OP(tmp_local[lid + 8], tmp_local[lid], DATA_TYPE, 4); - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(GRID_SIZE >= 8) - { - if(lid < 4) - { - tmp_local[lid] = MAX_OP(tmp_local[lid + 4], tmp_local[lid], DATA_TYPE, 4); - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(GRID_SIZE >= 4) - { - if(lid < 2) - { - tmp_local[lid] = MAX_OP(tmp_local[lid + 2], tmp_local[lid], DATA_TYPE, 4); - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(lid == 0) - { - max_val_vec = MAX_OP(tmp_local[lid + 1], tmp_local[lid], DATA_TYPE, 4); - max_val_vec.s01 = MAX_OP(max_val_vec.s01, max_val_vec.s23, DATA_TYPE, 2); - max_val_vec.s0 = MAX_OP(max_val_vec.s0, max_val_vec.s1, DATA_TYPE, 1); - max_local = max_val_vec.s0; - } - barrier(CLK_LOCAL_MEM_FENCE); - - /* Second section */ - - // Set sum vector - VEC_DATA_TYPE(DATA_TYPE, 4) - sum1D = 0; - DATA_TYPE max_val = max_local; - - // Shift values, exp and sum - for(i = 0; i < width_; i++) - { - VEC_DATA_TYPE(DATA_TYPE, 4) - data = VLOAD(4)(0, (__global DATA_TYPE *)offset(&src, i * GRID_SIZE * 4, 0)); - data = SUB_OP(data, max_val, DATA_TYPE, 4); -#ifdef BETA - data = MUL_OP(data, beta, DATA_TYPE, 4); -#endif /* BETA */ -#ifdef LOG_SOFTMAX - VSTORE(4) - (data, 0, (__global DATA_TYPE *)offset(&dst, i * GRID_SIZE * 4, 0)); - data = EXP_OP(data, DATA_TYPE, 4); -#else /* LOG_SOFTMAX */ - data = EXP_OP(data, DATA_TYPE, 4); - VSTORE(4) - (data, 0, (__global DATA_TYPE *)offset(&dst, i * GRID_SIZE * 4, 0)); -#endif /* LOG_SOFTMAX */ - sum1D = ADD_OP(sum1D, data, DATA_TYPE, 4); - } -#ifdef NON_MULTIPLE_OF_GRID_SIZE - //TODO: Optimize the calculation (avoid %). - boundary_workitems = (width % (GRID_SIZE * 4)) / 4; - if(lid < boundary_workitems) - { - VEC_DATA_TYPE(DATA_TYPE, 4) - data = VLOAD(4)(0, (__global DATA_TYPE *)offset(&src, i * GRID_SIZE * 4, 0)); - data = SUB_OP(data, max_val, DATA_TYPE, 4); -#ifdef BETA - data = MUL_OP(data, beta, DATA_TYPE, 4); -#endif /* BETA */ -#ifdef LOG_SOFTMAX - VSTORE(4) - (data, 0, (__global DATA_TYPE *)offset(&dst, i * GRID_SIZE * 4, 0)); - data = EXP_OP(data, DATA_TYPE, 4); -#else /* LOG_SOFTMAX */ - data = EXP_OP(data, DATA_TYPE, 4); - VSTORE(4) - (data, 0, (__global DATA_TYPE *)offset(&dst, i * GRID_SIZE * 4, 0)); -#endif /* LOG_SOFTMAX */ - sum1D = ADD_OP(sum1D, data, DATA_TYPE, 4); - } -#ifdef NON_MULTIPLE_OF_VECTOR_SIZE - if(boundary_workitems == 0) - { - boundary_workitems = GRID_SIZE; - i--; - } - if(lid == (boundary_workitems - 1)) - { - // Handle non multiple of vector size ((GRID_SIZE * i * 4) + 4, 0); move 4 float positions ahead, *4 is due to the stride - VEC_DATA_TYPE(DATA_TYPE, 4) - data = VLOAD(4)(0, (__global DATA_TYPE *)offset(&src, (GRID_SIZE * i * 4) + 4, 0)); - data = SUB_OP(data, max_val, DATA_TYPE, 4); -#ifdef BETA - data = MUL_OP(data, beta, DATA_TYPE, 4); -#endif /* BETA */ -#ifdef LOG_SOFTMAX - VSTORE(4) - (data, 0, (__global DATA_TYPE *)offset(&dst, (GRID_SIZE * i * 4) + 4, 0)); - data = EXP_OP(data, DATA_TYPE, 4); - VEC_DATA_TYPE(SELECT_DATA_TYPE, 4) - widx = CONVERT(((uint4)(GRID_SIZE * i * 4) + boundary_workitems * 4 + idx4) < width, VEC_DATA_TYPE(SELECT_DATA_TYPE, 4)); - data = select(0, data, widx); -#else /* LOG_SOFTMAX */ - data = EXP_OP(data, DATA_TYPE, 4); - VEC_DATA_TYPE(SELECT_DATA_TYPE, 4) - widx = CONVERT(((uint4)(GRID_SIZE * i * 4) + boundary_workitems * 4 + idx4) < width, VEC_DATA_TYPE(SELECT_DATA_TYPE, 4)); - data = select(0, data, widx); - VSTORE(4) - (data, 0, (__global DATA_TYPE *)offset(&dst, (GRID_SIZE * i * 4) + 4, 0)); -#endif /* LOG_SOFTMAX */ - sum1D = ADD_OP(sum1D, data, DATA_TYPE, 4); - } -#endif /* NON_MULTIPLE_OF_VECTOR_SIZE */ -#endif /* NON_MULTIPLE_OF_GRID_SIZE */ - tmp_local[lid] = sum1D; - - barrier(CLK_LOCAL_MEM_FENCE); - - if(GRID_SIZE >= 256) - { - if(lid < 128) - { - tmp_local[lid] = ADD_OP(tmp_local[lid + 128], tmp_local[lid], DATA_TYPE, 4); - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(GRID_SIZE >= 128) - { - if(lid < 64) - { - tmp_local[lid] = ADD_OP(tmp_local[lid + 64], tmp_local[lid], DATA_TYPE, 4); - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(GRID_SIZE >= 64) - { - if(lid < 32) - { - tmp_local[lid] = ADD_OP(tmp_local[lid + 32], tmp_local[lid], DATA_TYPE, 4); - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(GRID_SIZE >= 32) - { - if(lid < 16) - { - tmp_local[lid] = ADD_OP(tmp_local[lid + 16], tmp_local[lid], DATA_TYPE, 4); - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(GRID_SIZE >= 16) - { - if(lid < 8) - { - tmp_local[lid] = ADD_OP(tmp_local[lid + 8], tmp_local[lid], DATA_TYPE, 4); - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(GRID_SIZE >= 8) - { - if(lid < 4) - { - tmp_local[lid] = ADD_OP(tmp_local[lid + 4], tmp_local[lid], DATA_TYPE, 4); - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(GRID_SIZE >= 4) - { - if(lid < 2) - { - tmp_local[lid] = ADD_OP(tmp_local[lid + 2], tmp_local[lid], DATA_TYPE, 4); - } - barrier(CLK_LOCAL_MEM_FENCE); - } - if(lid == 0) - { - sum1D = ADD_OP(tmp_local[lid + 1], tmp_local[lid], DATA_TYPE, 4); - // Perform max reduction - sum1D.s01 = ADD_OP(sum1D.s01, sum1D.s23, DATA_TYPE, 2); - sum1D.s0 = ADD_OP(sum1D.s0, sum1D.s1, DATA_TYPE, 1); - *((__global DATA_TYPE *)sum.ptr) = sum1D.s0; - } -} |