diff options
Diffstat (limited to 'src/core/CL/cl_kernels/reduction_operation.cl')
| -rw-r--r-- | src/core/CL/cl_kernels/reduction_operation.cl | 287 |
1 files changed, 118 insertions, 169 deletions
diff --git a/src/core/CL/cl_kernels/reduction_operation.cl b/src/core/CL/cl_kernels/reduction_operation.cl index b2e56928d0..912b6c91a9 100644 --- a/src/core/CL/cl_kernels/reduction_operation.cl +++ b/src/core/CL/cl_kernels/reduction_operation.cl @@ -1,5 +1,5 @@ /* - * Copyright (c) 2016-2020 Arm Limited. + * Copyright (c) 2016-2021 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -32,67 +32,18 @@ #define ISGREATER(x, y) (x > y) ? 1 : 0 #define ISLESS(x, y) (x < y) ? 1 : 0 #else // !defined(WIDTH) -#define ISGREATER(x, y) select((int16)0, (int16)-1, x > y) -#define ISLESS(x, y) select((int16)0, (int16)-1, x < y) +#define ISGREATER(x, y) select((VEC_DATA_TYPE(int, VEC_SIZE))0, (VEC_DATA_TYPE(int, VEC_SIZE)) - 1, x > y) +#define ISLESS(x, y) select((VEC_DATA_TYPE(int, VEC_SIZE))0, (VEC_DATA_TYPE(int, VEC_SIZE)) - 1, x < y) #endif // defined(WIDTH) #endif // defined(FLOAT_DATA_TYPE) -/** Calculate square sum of a vector - * - * @param[in] input Pointer to the first pixel. - * - * @return square sum of vector. - */ -inline DATA_TYPE square_sum(__global const DATA_TYPE *input) -{ - VEC_DATA_TYPE(DATA_TYPE, 16) - in = vload16(0, input); - - in *= in; - - in.s01234567 += in.s89ABCDEF; - in.s0123 += in.s4567; - in.s01 += in.s23; - - return (in.s0 + in.s1); -} - -/** Calculate sum of a vector - * - * @param[in] input Pointer to the first pixel. - * - * @return sum of vector. - */ -inline DATA_TYPE sum(__global const DATA_TYPE *input) -{ - VEC_DATA_TYPE(DATA_TYPE, 16) - in = vload16(0, input); - - in.s01234567 += in.s89ABCDEF; - in.s0123 += in.s4567; - in.s01 += in.s23; - - return (in.s0 + in.s1); -} - -/** Calculate product of a vector - * - * @param[in] input Pointer to the first pixel. - * - * @return product of vector. - */ -inline DATA_TYPE product(__global const DATA_TYPE *input) -{ - VEC_DATA_TYPE(DATA_TYPE, 16) - in = vload16(0, input); +#if defined(WIDTH) +#if defined(OPERATION) - in.s01234567 *= in.s89ABCDEF; - in.s0123 *= in.s4567; - in.s01 *= in.s23; +#define sum(in0, in1, size) (in0 + SUM_REDUCE(in1, size)) +#define square_sum(in0, in1, size) (in0 + SUM_REDUCE((in1 * in1), size)) +#define product(in0, in1, size) (in0 * PROD_REDUCE(in1, size)) - return (in.s0 * in.s1); -} -#if defined(OPERATION) /** This kernel performs parallel reduction given an operation on x-axis. * * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float @@ -101,65 +52,57 @@ inline DATA_TYPE product(__global const DATA_TYPE *input) * @note The product flag must be passed at compile time using -DPROD if we want to compute the product, otherwise sum will be used * @note The width size must be passed at compile time using -DWIDTH e.g. -DWIDTH=128 if we want to compute the mean value * - * @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 Y 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] partial_res_ptr The local buffer to hold partial result values. Supported data types: same as @p src_ptr - * @param[in] partial_res_stride_x Stride of the output tensor in X dimension (in bytes) - * @param[in] partial_res_step_x partial_res_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] partial_res_stride_y Stride of the output tensor in Y dimension (in bytes) - * @param[in] partial_res_step_y partial_res_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] partial_res_offset_first_element_in_bytes The offset of the first element in the source tensor - * @param[in] local_results Local buffer for storing the partial result + * @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 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] output_ptr Pointer to the destination tensor. Supported data types: same as @p input + * @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 */ __kernel void reduction_operation_x( - IMAGE_DECLARATION(src), - IMAGE_DECLARATION(partial_res), - __local DATA_TYPE *local_results) + IMAGE_DECLARATION(input), + IMAGE_DECLARATION(output)) { - Image src = CONVERT_TO_IMAGE_STRUCT(src); - Image partial_res = CONVERT_TO_IMAGE_STRUCT(partial_res); + int y = get_global_id(1); - unsigned int lsize = get_local_size(0); - unsigned int lid = get_local_id(0); + __global uchar *input_addr = input_ptr + input_offset_first_element_in_bytes + y * input_stride_y; + __global uchar *output_addr = output_ptr + output_offset_first_element_in_bytes + y * output_stride_y; - for(unsigned int y = 0; y < get_local_size(1); ++y) - { - local_results[lid] = OPERATION((__global DATA_TYPE *)offset(&src, 0, y)); - barrier(CLK_LOCAL_MEM_FENCE); - - // Perform parallel reduction - for(unsigned int i = lsize >> 1; i > 0; i >>= 1) - { - if(lid < i) - { #if defined(PROD) - local_results[lid] *= local_results[lid + i]; -#else // !defined(PROD) - local_results[lid] += local_results[lid + i]; + DATA_TYPE res = (DATA_TYPE)1; +#else // defined(PROD) + DATA_TYPE res = (DATA_TYPE)0; #endif // defined(PROD) - } - barrier(CLK_LOCAL_MEM_FENCE); - } - - if(lid == 0) - { -#if defined(MEAN) && defined(WIDTH) - if(y == get_local_size(1) - 1) - { - local_results[0] /= WIDTH; - } -#endif // defined(MEAN) && defined(WIDTH) - ((__global DATA_TYPE *)offset(&partial_res, get_group_id(0), y))[0] = local_results[0]; - } + + int x = 0; + + for(; x <= (WIDTH - VEC_SIZE); x += VEC_SIZE) + { + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + vals = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(input_addr + x * sizeof(DATA_TYPE))); + res = OPERATION(res, vals, VEC_SIZE); + } + +#if(WIDTH % VEC_SIZE) + _Pragma("unroll") for(; x < WIDTH; ++x) + { + DATA_TYPE val = *((__global DATA_TYPE *)(input_addr + x * sizeof(DATA_TYPE))); + res = OPERATION(res, val, 1); } +#endif // (WIDTH % VEC_SIZE) + +#if defined(MEAN) + res /= WIDTH; +#endif // defined(MEAN) + *((__global DATA_TYPE *)output_addr) = res; } #endif // defined(OPERATION) - -#if defined(WIDTH) /** This kernel performs reduction on x-axis. (Non parallel) * * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float @@ -167,23 +110,23 @@ __kernel void reduction_operation_x( * @note The product flag must be passed at compile time using -DPROD if we want to compute the product, otherwise sum will be used * @note In case of MIN and MAX the condition data type must be passed at compile time using -DCOND_DATA_TYPE e.g. -DCOND_DATA_TYPE=short * - * @param[in] src_ptr Pointer to the source tensor. Supported data types: S32/F16/F32 and QASYMM8/QASYMM8_SIGNED for operation MEAN - * @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_offset_first_element_in_bytes The offset of the first element in the source tensor - * @param[in] output_ptr The local buffer to hold sumed values. Supported data types: same as @p src_ptr + * @param[in] input_ptr Pointer to the source tensor. Supported data types: S32/F16/F32 and QASYMM8/QASYMM8_SIGNED for operation MEAN + * @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_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[in] output_ptr The local buffer to hold sumed values. Supported data types: same as @p input_ptr * @param[in] output_stride_x Stride of the output 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_offset_first_element_in_bytes The offset of the first element in the source tensor */ __kernel void reduction_operation_non_parallel_x( - VECTOR_DECLARATION(src), + VECTOR_DECLARATION(input), VECTOR_DECLARATION(output)) { - Vector src = CONVERT_TO_VECTOR_STRUCT(src); + Vector input = CONVERT_TO_VECTOR_STRUCT(input); Vector output = CONVERT_TO_VECTOR_STRUCT(output); - DATA_TYPE_PROMOTED res = CONVERT(*((__global DATA_TYPE *)vector_offset(&src, 0)), DATA_TYPE_PROMOTED); + DATA_TYPE_PROMOTED res = CONVERT(*((__global DATA_TYPE *)vector_offset(&input, 0)), DATA_TYPE_PROMOTED); // Convert input into F32 in order to perform quantized multiplication #if defined(PROD) && defined(OFFSET) && defined(SCALE) @@ -192,7 +135,7 @@ __kernel void reduction_operation_non_parallel_x( for(unsigned int x = 1; x < WIDTH; ++x) { - DATA_TYPE_PROMOTED in = CONVERT(*((__global DATA_TYPE *)vector_offset(&src, x)), DATA_TYPE_PROMOTED); + DATA_TYPE_PROMOTED in = CONVERT(*((__global DATA_TYPE *)vector_offset(&input, x)), DATA_TYPE_PROMOTED); #if defined(MIN) res = select(res, in, CONVERT(ISLESS(in, res), COND_DATA_TYPE)); #elif defined(MAX) @@ -233,13 +176,13 @@ __kernel void reduction_operation_non_parallel_x( * @note The input data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float * @note The height size must be passed at compile time using -DHEIGHT e.g. -DHEIGHT=128 * - * @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8/QASYMM8_SIGNED/S32/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_offset_first_element_in_bytes The offset of the first element in the source tensor - * @param[in] output_ptr The local buffer to hold sumed values. Supported data types: same as @p src_ptr + * @param[in] input_ptr Pointer to the source tensor. Supported data types: QASYMM8/QASYMM8_SIGNED/S32/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 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] output_ptr The local buffer to hold sumed values. Supported data types: same as @p input_ptr * @param[in] output_stride_x Stride of the output 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 output tensor in Y dimension (in bytes) @@ -247,18 +190,22 @@ __kernel void reduction_operation_non_parallel_x( * @param[in] output_offset_first_element_in_bytes The offset of the first element in the source tensor */ __kernel void reduction_operation_y( - IMAGE_DECLARATION(src), + IMAGE_DECLARATION(input), IMAGE_DECLARATION(output)) { - Image src = CONVERT_TO_IMAGE_STRUCT(src); - Image output = CONVERT_TO_IMAGE_STRUCT(output); + int x = max((int)(get_global_id(0) * VEC_SIZE - (VEC_SIZE - VEC_SIZE_LEFTOVER) % VEC_SIZE), 0); + int y = get_global_id(1); - VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16) - res = CONVERT(vload16(0, (__global DATA_TYPE *)offset(&src, 0, 0)), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16)); + __global uchar *input_addr = input_ptr + input_offset_first_element_in_bytes + x * sizeof(DATA_TYPE) + y * input_stride_y; + __global uchar *output_addr = output_ptr + output_offset_first_element_in_bytes + x * sizeof(DATA_TYPE) + y * output_stride_y; + + VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE) + res = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)input_addr), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE)); // Convert input into F32 in order to perform quantized multiplication #if defined(PROD) && defined(OFFSET) && defined(SCALE) - float16 res_f = DEQUANTIZE(res, OFFSET, SCALE, DATA_TYPE_PROMOTED, 16); + VEC_DATA_TYPE(float, VEC_SIZE) + res_f = DEQUANTIZE(res, OFFSET, SCALE, DATA_TYPE_PROMOTED, VEC_SIZE); #endif // defined(PROD) && defined(OFFSET) && defined(SCALE) #if defined(SUM_SQUARE) @@ -267,8 +214,8 @@ __kernel void reduction_operation_y( for(unsigned int y = 1; y < HEIGHT; ++y) { - VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16) - in = CONVERT(vload16(0, (__global DATA_TYPE *)offset(&src, 0, y)), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16)); + VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE) + in = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(input_addr + y * input_stride_y)), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE)); #if defined(MIN) res = select(res, in, ISLESS(in, res)); #elif defined(MAX) @@ -280,7 +227,7 @@ __kernel void reduction_operation_y( #if defined(PROD) #if defined(OFFSET) && defined(SCALE) - res_f *= DEQUANTIZE(in, OFFSET, SCALE, DATA_TYPE_PROMOTED, 16); + res_f *= DEQUANTIZE(in, OFFSET, SCALE, DATA_TYPE_PROMOTED, VEC_SIZE); #else // !(defined(OFFSET) && defined(SCALE)) res *= in; #endif // defined(OFFSET) && defined(SCALE) @@ -302,11 +249,13 @@ __kernel void reduction_operation_y( // Re-quantize #if defined(PROD) && defined(OFFSET) && defined(SCALE) - res = QUANTIZE(res_f, OFFSET, SCALE, DATA_TYPE_PROMOTED, 16); + res = QUANTIZE(res_f, OFFSET, SCALE, DATA_TYPE_PROMOTED, VEC_SIZE); #endif // defined(PROD) && defined(OFFSET) && defined(SCALE) // Store result - vstore16(CONVERT_SAT(res, VEC_DATA_TYPE(DATA_TYPE, 16)), 0, (__global DATA_TYPE *)output.ptr); + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + res0 = CONVERT_SAT(res, VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)); + STORE_VECTOR_SELECT(res, DATA_TYPE, output_addr, VEC_SIZE, VEC_SIZE_LEFTOVER, VEC_SIZE_LEFTOVER != 0 && get_global_id(0) == 0); } #endif // defined(HEIGHT) @@ -337,34 +286,30 @@ __kernel void reduction_operation_z( TENSOR3D_DECLARATION(input), TENSOR3D_DECLARATION(output)) { - Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT(input); - Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT(output); + int x = max((int)(get_global_id(0) * VEC_SIZE - (VEC_SIZE - VEC_SIZE_LEFTOVER) % VEC_SIZE), 0); + int y = get_global_id(1); + int z = get_global_id(2); + + __global uchar *input_addr = input_ptr + input_offset_first_element_in_bytes + x * sizeof(DATA_TYPE) + y * input_stride_y + z * input_stride_z; + __global uchar *output_addr = output_ptr + output_offset_first_element_in_bytes + x * sizeof(DATA_TYPE) + y * output_stride_y + z * output_stride_z; - VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16) - res = CONVERT(vload16(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 0, 0)), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16)); + VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE) + res = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)input_addr), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE)); // Convert input into F32 in order to perform quantized multiplication #if defined(PROD) && defined(OFFSET) && defined(SCALE) - float16 res_f = DEQUANTIZE(res, OFFSET, SCALE, DATA_TYPE_PROMOTED, 16); + VEC_DATA_TYPE(float, VEC_SIZE) + res_f = DEQUANTIZE(res, OFFSET, SCALE, DATA_TYPE_PROMOTED, VEC_SIZE); #endif // defined(PROD) && defined(OFFSET) && defined(SCALE) -#if defined(COMPLEX) - VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16) - res1 = CONVERT(vload16(0, (__global DATA_TYPE *)tensor3D_offset(&input, 8, 0, 0)), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16)); -#endif // defined(COMPLEX) #if defined(SUM_SQUARE) res *= res; #endif // defined(SUM_SQUARE) for(unsigned int z = 1; z < DEPTH; ++z) { - VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16) - in = CONVERT(vload16(0, (__global DATA_TYPE *)tensor3D_offset(&input, 0, 0, z)), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16)); - -#if defined(COMPLEX) - VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16) - in1 = CONVERT(vload16(0, (__global DATA_TYPE *)tensor3D_offset(&input, 8, 0, z)), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16)); -#endif // defined(COMPLEX) + VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE) + in = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(input_addr + z * input_stride_z)), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE)); #if defined(MIN) res = select(res, in, ISLESS(in, res)); @@ -377,16 +322,13 @@ __kernel void reduction_operation_z( #if defined(PROD) #if defined(OFFSET) && defined(SCALE) - res_f *= DEQUANTIZE(in, OFFSET, SCALE, DATA_TYPE_PROMOTED, 16); + res_f *= DEQUANTIZE(in, OFFSET, SCALE, DATA_TYPE_PROMOTED, VEC_SIZE); #else // !(defined(OFFSET) && defined(SCALE)) res *= in; #endif // defined(OFFSET) && defined(SCALE) -#else // !defined(PROD) +#else // !defined(PROD) res += in; -#if defined(COMPLEX) - res1 += in1; -#endif // defined(COMPLEX) #endif // defined(PROD) #endif // defined(MAX) || defined(MIN) } @@ -402,14 +344,14 @@ __kernel void reduction_operation_z( // Re-quantize #if defined(PROD) && defined(OFFSET) && defined(SCALE) - res = QUANTIZE(res_f, OFFSET, SCALE, DATA_TYPE_PROMOTED, 16); + res = QUANTIZE(res_f, OFFSET, SCALE, DATA_TYPE_PROMOTED, VEC_SIZE); #endif // defined(PROD) && defined(OFFSET) && defined(SCALE) // Store result - vstore16(CONVERT_SAT(res, VEC_DATA_TYPE(DATA_TYPE, 16)), 0, (__global DATA_TYPE *)output.ptr); -#if defined(COMPLEX) - vstore16(CONVERT(res1, VEC_DATA_TYPE(DATA_TYPE, 16)), 0, (__global DATA_TYPE *)tensor3D_offset(&output, 8, 0, 0)); -#endif // defined(COMPLEX) + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + res0 = CONVERT_SAT(res, VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)); + + STORE_VECTOR_SELECT(res, DATA_TYPE, output_addr, VEC_SIZE, VEC_SIZE_LEFTOVER, VEC_SIZE_LEFTOVER != 0 && get_global_id(0) == 0); } #endif /* defined(DEPTH) */ @@ -445,15 +387,20 @@ __kernel void reduction_operation_w( TENSOR4D_DECLARATION(input), TENSOR4D_DECLARATION(output)) { - Tensor4D input = CONVERT_TO_TENSOR4D_STRUCT(input, DEPTH); - Tensor4D output = CONVERT_TO_TENSOR4D_STRUCT(output, DEPTH); + int x = max((int)(get_global_id(0) * VEC_SIZE - (VEC_SIZE - VEC_SIZE_LEFTOVER) % VEC_SIZE), 0); + int y = get_global_id(1); + int z = get_global_id(2); + + __global uchar *input_addr = input_ptr + input_offset_first_element_in_bytes + x * sizeof(DATA_TYPE) + y * input_stride_y + (z % DEPTH) * input_stride_z + (z / DEPTH) * input_stride_w; + __global uchar *output_addr = output_ptr + output_offset_first_element_in_bytes + x * sizeof(DATA_TYPE) + y * output_stride_y + (z % DEPTH) * output_stride_z + (z / DEPTH) * output_stride_z; - VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16) - res = CONVERT(vload16(0, (__global DATA_TYPE *)tensor4D_offset(&input, 0, 0, 0, 0)), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16)); + VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE) + res = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)input_addr), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE)); // Convert input into F32 in order to perform quantized multiplication #if defined(PROD) && defined(OFFSET) && defined(SCALE) - float16 res_f = DEQUANTIZE(res, OFFSET, SCALE, DATA_TYPE_PROMOTED, 16); + VEC_DATA_TYPE(float, VEC_SIZE) + res_f = DEQUANTIZE(res, OFFSET, SCALE, DATA_TYPE_PROMOTED, VEC_SIZE); #endif // defined(PROD) && defined(OFFSET) && defined(SCALE) #if defined(SUM_SQUARE) @@ -462,8 +409,8 @@ __kernel void reduction_operation_w( for(unsigned int w = 1; w < BATCH; ++w) { - VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16) - in = CONVERT(vload16(0, (__global DATA_TYPE *)tensor4D_offset(&input, 0, 0, 0, w)), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 16)); + VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE) + in = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(input_addr + w * input_stride_w)), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, VEC_SIZE)); #if defined(MIN) res = select(res, in, ISLESS(in, res)); @@ -476,7 +423,7 @@ __kernel void reduction_operation_w( #if defined(PROD) #if defined(OFFSET) && defined(SCALE) - res_f *= DEQUANTIZE(in, OFFSET, SCALE, DATA_TYPE_PROMOTED, 16); + res_f *= DEQUANTIZE(in, OFFSET, SCALE, DATA_TYPE_PROMOTED, VEC_SIZE); #else // !(defined(OFFSET) && defined(SCALE)) res *= in; #endif // defined(OFFSET) && defined(SCALE) @@ -498,10 +445,12 @@ __kernel void reduction_operation_w( // Re-quantize #if defined(PROD) && defined(OFFSET) && defined(SCALE) - res = QUANTIZE(res_f, OFFSET, SCALE, DATA_TYPE_PROMOTED, 16); + res = QUANTIZE(res_f, OFFSET, SCALE, DATA_TYPE_PROMOTED, VEC_SIZE); #endif // defined(PROD) && defined(OFFSET) && defined(SCALE) // Store result - vstore16(CONVERT_SAT(res, VEC_DATA_TYPE(DATA_TYPE, 16)), 0, (__global DATA_TYPE *)output.ptr); + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + res0 = CONVERT_SAT(res, VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)); + STORE_VECTOR_SELECT(res, DATA_TYPE, output_addr, VEC_SIZE, VEC_SIZE_LEFTOVER, VEC_SIZE_LEFTOVER != 0 && get_global_id(0) == 0); } #endif /* defined(BATCH) && defined(DEPTH) */ |