diff options
Diffstat (limited to 'src/core/CL/cl_kernels/common/mat_mul_mmul.cl')
| -rw-r--r-- | src/core/CL/cl_kernels/common/mat_mul_mmul.cl | 271 |
1 files changed, 171 insertions, 100 deletions
diff --git a/src/core/CL/cl_kernels/common/mat_mul_mmul.cl b/src/core/CL/cl_kernels/common/mat_mul_mmul.cl index a53db27fb8..e549da86d4 100644 --- a/src/core/CL/cl_kernels/common/mat_mul_mmul.cl +++ b/src/core/CL/cl_kernels/common/mat_mul_mmul.cl @@ -24,6 +24,21 @@ #include "helpers.h" #include "tile_helpers.h" +#ifdef BIAS +// This function performs in-place bias addition for float and half datatypes when bias is enabled. +// Note The tile's dimensions used for the LHS and RHS matrices (M0, N0) must be passed at compile time using -DN0, -DM0 (e.g. -DN0=8, -DM0=4). +inline void perform_bias_addition(uchar *bias_ptr, uint bias_offset_first_element_in_bytes, TILE(DATA_TYPE, M0, N0, acc), uint x) +{ + TILE(DATA_TYPE, 1, N0, bias_tile); + + // below expands to use bias_ptr and bias_offset_first_element_in_bytes + T_LOAD(DATA_TYPE, 1, N0, BUFFER, bias, x, 0, 1, 0, bias_tile); + + // c = c + bias[broadcasted] + T_ELTWISE_BROADCAST_ADD_X(DATA_TYPE, M0, N0, acc, bias_tile, acc); +} +#endif // defined(BIAS) + #if defined(MAT_MUL_NATIVE_MMUL_NT_NT) /** This OpenCL kernel performs the batch matrix multiplication (BatchMatMul) using MMUL: LHS non-transposed, RHS non-transposed - buffer only * @@ -40,34 +55,44 @@ * - K0 = 1 * @note Values > 8 for M0 are not expected to be efficient * - * @param[in] lhs_ptr Pointer to the lhs matrix. Supported data types: F32/F16 - * @param[in] lhs_stride_y Stride of the lhs matrix in Y (2nd) dimension (in bytes) - * @param[in] lhs_stride_z Stride of the lhs tensor in Z (3rd) dimension (in bytes) - * @param[in] lhs_w The width of the lhs tensor - * @param[in] lhs_h The height of the lhs tensor - * @param[in] lhs_n Number of the matrices (buffers) in the batch - * @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the lhs matrix - * @param[in] rhs_ptr Pointer to the rhs matrix. Supported data types: same as @p lhs_ptr - * @param[in] rhs_stride_y Stride of the rhs matrix in Y (2nd) dimension (in bytes) - * @param[in] rhs_stride_z Stride of the rhs tensor in Z (3rd) dimension (in bytes) - * @param[in] rhs_w The width of the rhs tensor - * @param[in] rhs_h The height of the rhs tensor - * @param[in] rhs_n Number of the matrices (buffers) in the batch - * @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the rhs matrix - * @param[out] dst_ptr Pointer to the dst matrix. Supported data types: same as @p lhs_ptr - * @param[in] dst_stride_y Stride of the dst matrix in Y (2nd) dimension (in bytes) - * @param[in] dst_stride_z Stride of the dst tensor in Z (3rd) dimension (in bytes) - * @param[in] dst_w The width of the dst tensor - * @param[in] dst_h The height of the dst tensor - * @param[in] dst_n Number of the matrices (buffers) in the batch - * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the dst matrix - * @param[in] M Number of rows in LHS matrix - * @param[in] N Number of columns in RHS matrix - * @param[in] K Number of columns in LHS matrix and rows in RHS matrix, which is multiple of MMUL_K0. + * @param[in] lhs_ptr Pointer to the lhs matrix. Supported data types: F32/F16 + * @param[in] lhs_stride_y Stride of the lhs matrix in Y (2nd) dimension (in bytes) + * @param[in] lhs_stride_z Stride of the lhs tensor in Z (3rd) dimension (in bytes) + * @param[in] lhs_w The width of the lhs tensor + * @param[in] lhs_h The height of the lhs tensor + * @param[in] lhs_n Number of the matrices (buffers) in the batch + * @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the lhs matrix + * @param[in] rhs_ptr Pointer to the rhs matrix. Supported data types: same as @p lhs_ptr + * @param[in] rhs_stride_y Stride of the rhs matrix in Y (2nd) dimension (in bytes) + * @param[in] rhs_stride_z Stride of the rhs tensor in Z (3rd) dimension (in bytes) + * @param[in] rhs_w The width of the rhs tensor + * @param[in] rhs_h The height of the rhs tensor + * @param[in] rhs_n Number of the matrices (buffers) in the batch + * @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the rhs matrix + * @param[in] bias_ptr (Optional) Pointer to the bias tensor. Supported data type: same as @p lhs_ptr + * @param[in] bias_stride_y (Optional) Stride of the bias tensor in Y dimension (in bytes) + * @param[in] bias_stride_z (Optional) Stride of the bias tensor in Z dimension (in bytes) + * @param[in] bias_w (Optional) The size of the width dimension of the bias tensor + * @param[in] bias_h (Optional) The size of the height dimension of the bias tensor + * @param[in] bias_n (Optional) The size of the depth dimension of the bias tensor + * @param[in] bias_offset_first_element_in_bytes (Optional) The offset of the first element in the bias tensor + * @param[out] dst_ptr Pointer to the dst matrix. Supported data types: same as @p lhs_ptr + * @param[in] dst_stride_y Stride of the dst matrix in Y (2nd) dimension (in bytes) + * @param[in] dst_stride_z Stride of the dst tensor in Z (3rd) dimension (in bytes) + * @param[in] dst_w The width of the dst tensor + * @param[in] dst_h The height of the dst tensor + * @param[in] dst_n Number of the matrices (buffers) in the batch + * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the dst matrix + * @param[in] M Number of rows in LHS matrix + * @param[in] N Number of columns in RHS matrix + * @param[in] K Number of columns in LHS matrix and rows in RHS matrix, which is multiple of MMUL_K0. */ __kernel void mat_mul_native_mmul_nt_nt( TENSOR3D_T(lhs, BUFFER), TENSOR3D_T(rhs, BUFFER), +#ifdef BIAS + TENSOR3D_T(bias, BUFFER), +#endif // defined(BIAS) TENSOR3D_T(dst, BUFFER), const int M, const int N, @@ -90,7 +115,7 @@ __kernel void mat_mul_native_mmul_nt_nt( // x = [0, ((N / N0) / MMUL_N0) * MMUL_N0 * MMUL_M0) // x = [0, (N / N0) * MMUL_MO) const uint x0 = get_global_id(0); // [0, (N / N0) * MMUL_M0) - // The upper limit is a simplified version of (N / N0) / MMUL_N0) * MMUL_BLOCK_SIZE) + // The upper limit is a simplified version of (N / N0) / MMUL_N0) * MMUL_BLOCK_SIZE) const uint y0 = get_global_id(1); // [0, (M / M0) / MMUL_M0) const uint z = get_global_id(2); // Batch @@ -347,6 +372,10 @@ __kernel void mat_mul_native_mmul_nt_nt( #define c c_f32 #endif // defined(HALF_PRECISION) +#ifdef BIAS + perform_bias_addition(bias_ptr, bias_offset_first_element_in_bytes, c, dst_x); +#endif // defined(BIAS) + if(dst_x + N0 <= N || N0_LEFTOVER == 0) { LOOP_UNROLLING(int, m0, 0, 1, M0, @@ -391,34 +420,44 @@ __kernel void mat_mul_native_mmul_nt_nt( * - K0 = 1 * @note Values > 8 for M0 are not expected to be efficient * - * @param[in] lhs_ptr Pointer to the lhs matrix. Supported data types: F32/F16 - * @param[in] lhs_stride_y Stride of the lhs matrix in Y (2nd) dimension (in bytes) - * @param[in] lhs_stride_z Stride of the lhs tensor in Z (3rd) dimension (in bytes) - * @param[in] lhs_w The width of the lhs tensor - * @param[in] lhs_h The height of the lhs tensor - * @param[in] lhs_n Number of the matrices (buffers) in the batch - * @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the lhs matrix - * @param[in] rhs_ptr Pointer to the rhs matrix. Supported data types: same as @p lhs_ptr - * @param[in] rhs_stride_y Stride of the rhs matrix in Y (2nd) dimension (in bytes) - * @param[in] rhs_stride_z Stride of the rhs tensor in Z (3rd) dimension (in bytes) - * @param[in] rhs_w The width of the rhs tensor - * @param[in] rhs_h The height of the rhs tensor - * @param[in] rhs_n Number of the matrices (buffers) in the batch - * @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the rhs matrix - * @param[out] dst_ptr Pointer to the dst matrix. Supported data types: same as @p lhs_ptr - * @param[in] dst_stride_y Stride of the dst matrix in Y (2nd) dimension (in bytes) - * @param[in] dst_stride_z Stride of the dst tensor in Z (3rd) dimension (in bytes) - * @param[in] dst_w The width of the dst tensor - * @param[in] dst_h The height of the dst tensor - * @param[in] dst_n Number of the matrices (buffers) in the batch - * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the dst matrix - * @param[in] M Number of rows in DST matrix - * @param[in] N Number of columns in DST matrix - * @param[in] K Number of rows in LHS and RHS matrices, which is multiple of MMUL_K0. + * @param[in] lhs_ptr Pointer to the lhs matrix. Supported data types: F32/F16 + * @param[in] lhs_stride_y Stride of the lhs matrix in Y (2nd) dimension (in bytes) + * @param[in] lhs_stride_z Stride of the lhs tensor in Z (3rd) dimension (in bytes) + * @param[in] lhs_w The width of the lhs tensor + * @param[in] lhs_h The height of the lhs tensor + * @param[in] lhs_n Number of the matrices (buffers) in the batch + * @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the lhs matrix + * @param[in] rhs_ptr Pointer to the rhs matrix. Supported data types: same as @p lhs_ptr + * @param[in] rhs_stride_y Stride of the rhs matrix in Y (2nd) dimension (in bytes) + * @param[in] rhs_stride_z Stride of the rhs tensor in Z (3rd) dimension (in bytes) + * @param[in] rhs_w The width of the rhs tensor + * @param[in] rhs_h The height of the rhs tensor + * @param[in] rhs_n Number of the matrices (buffers) in the batch + * @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the rhs matrix + * @param[in] bias_ptr (Optional) Pointer to the bias tensor. Supported data type: same as @p lhs_ptr + * @param[in] bias_stride_y (Optional) Stride of the bias tensor in Y dimension (in bytes) + * @param[in] bias_stride_z (Optional) Stride of the bias tensor in Z dimension (in bytes) + * @param[in] bias_w (Optional) The size of the width dimension of the bias tensor + * @param[in] bias_h (Optional) The size of the height dimension of the bias tensor + * @param[in] bias_n (Optional) The size of the depth dimension of the bias tensor + * @param[in] bias_offset_first_element_in_bytes (Optional) The offset of the first element in the bias tensor + * @param[out] dst_ptr Pointer to the dst matrix. Supported data types: same as @p lhs_ptr + * @param[in] dst_stride_y Stride of the dst matrix in Y (2nd) dimension (in bytes) + * @param[in] dst_stride_z Stride of the dst tensor in Z (3rd) dimension (in bytes) + * @param[in] dst_w The width of the dst tensor + * @param[in] dst_h The height of the dst tensor + * @param[in] dst_n Number of the matrices (buffers) in the batch + * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the dst matrix + * @param[in] M Number of rows in DST matrix + * @param[in] N Number of columns in DST matrix + * @param[in] K Number of rows in LHS and RHS matrices, which is multiple of MMUL_K0. */ __kernel void mat_mul_native_mmul_t_nt( TENSOR3D_T(lhs, BUFFER), TENSOR3D_T(rhs, BUFFER), +#ifdef BIAS + TENSOR3D_T(bias, BUFFER), +#endif // defined(BIAS) TENSOR3D_T(dst, BUFFER), const int M, const int N, @@ -428,7 +467,7 @@ __kernel void mat_mul_native_mmul_t_nt( // For explanations on how this kernel works, please refer to NT/NT kernel. This kernel makes little modifications to it. const uint x0 = get_global_id(0); // [0, (N / N0) * MMUL_M0) - // The upper limit is a simplified version of (N / N0) / MMUL_N0) * MMUL_BLOCK_SIZE) + // The upper limit is a simplified version of (N / N0) / MMUL_N0) * MMUL_BLOCK_SIZE) const uint y0 = get_global_id(1); // [0, (M / M0) / MMUL_M0) const uint z = get_global_id(2); // Batch @@ -511,6 +550,10 @@ __kernel void mat_mul_native_mmul_t_nt( #define c c_f32 #endif // defined(HALF_PRECISION) +#ifdef BIAS + perform_bias_addition(bias_ptr, bias_offset_first_element_in_bytes, c, dst_x); +#endif // defined(BIAS) + if(dst_x + N0 <= N || N0_LEFTOVER == 0) { LOOP_UNROLLING(int, m0, 0, 1, M0, @@ -554,34 +597,44 @@ __kernel void mat_mul_native_mmul_t_nt( * - K0 = 1 * @note Values > 8 for M0 are not expected to be efficient * - * @param[in] lhs_ptr Pointer to the lhs matrix. Supported data types: F32/F16 - * @param[in] lhs_stride_y Stride of the lhs matrix in Y (2nd) dimension (in bytes) - * @param[in] lhs_stride_z Stride of the lhs tensor in Z (3rd) dimension (in bytes) - * @param[in] lhs_w The width of the lhs tensor - * @param[in] lhs_h The height of the lhs tensor - * @param[in] lhs_n Number of the matrices (buffers) in the batch - * @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the lhs matrix - * @param[in] rhs_ptr Pointer to the rhs matrix. Supported data types: same as @p lhs_ptr - * @param[in] rhs_stride_y Stride of the rhs matrix in Y (2nd) dimension (in bytes) - * @param[in] rhs_stride_z Stride of the rhs tensor in Z (3rd) dimension (in bytes) - * @param[in] rhs_w The width of the rhs tensor - * @param[in] rhs_h The height of the rhs tensor - * @param[in] rhs_n Number of the matrices (buffers) in the batch - * @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the rhs matrix - * @param[out] dst_ptr Pointer to the dst matrix. Supported data types: same as @p lhs_ptr - * @param[in] dst_stride_y Stride of the dst matrix in Y (2nd) dimension (in bytes) - * @param[in] dst_stride_z Stride of the dst tensor in Z (3rd) dimension (in bytes) - * @param[in] dst_w The width of the dst tensor - * @param[in] dst_h The height of the dst tensor - * @param[in] dst_n Number of the matrices (buffers) in the batch - * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the dst matrix - * @param[in] M Number of rows in LHS matrix - * @param[in] N Number of columns in RHS matrix - * @param[in] K Number of columns in LHS matrix and columns in RHS matrix, which is multiple of MMUL_K0. + * @param[in] lhs_ptr Pointer to the lhs matrix. Supported data types: F32/F16 + * @param[in] lhs_stride_y Stride of the lhs matrix in Y (2nd) dimension (in bytes) + * @param[in] lhs_stride_z Stride of the lhs tensor in Z (3rd) dimension (in bytes) + * @param[in] lhs_w The width of the lhs tensor + * @param[in] lhs_h The height of the lhs tensor + * @param[in] lhs_n Number of the matrices (buffers) in the batch + * @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the lhs matrix + * @param[in] rhs_ptr Pointer to the rhs matrix. Supported data types: same as @p lhs_ptr + * @param[in] rhs_stride_y Stride of the rhs matrix in Y (2nd) dimension (in bytes) + * @param[in] rhs_stride_z Stride of the rhs tensor in Z (3rd) dimension (in bytes) + * @param[in] rhs_w The width of the rhs tensor + * @param[in] rhs_h The height of the rhs tensor + * @param[in] rhs_n Number of the matrices (buffers) in the batch + * @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the rhs matrix + * @param[in] bias_ptr (Optional) Pointer to the bias tensor. Supported data type: same as @p lhs_ptr + * @param[in] bias_stride_y (Optional) Stride of the bias tensor in Y dimension (in bytes) + * @param[in] bias_stride_z (Optional) Stride of the bias tensor in Z dimension (in bytes) + * @param[in] bias_w (Optional) The size of the width dimension of the bias tensor + * @param[in] bias_h (Optional) The size of the height dimension of the bias tensor + * @param[in] bias_n (Optional) The size of the depth dimension of the bias tensor + * @param[in] bias_offset_first_element_in_bytes (Optional) The offset of the first element in the bias tensor + * @param[out] dst_ptr Pointer to the dst matrix. Supported data types: same as @p lhs_ptr + * @param[in] dst_stride_y Stride of the dst matrix in Y (2nd) dimension (in bytes) + * @param[in] dst_stride_z Stride of the dst tensor in Z (3rd) dimension (in bytes) + * @param[in] dst_w The width of the dst tensor + * @param[in] dst_h The height of the dst tensor + * @param[in] dst_n Number of the matrices (buffers) in the batch + * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the dst matrix + * @param[in] M Number of rows in LHS matrix + * @param[in] N Number of columns in RHS matrix + * @param[in] K Number of columns in LHS matrix and columns in RHS matrix, which is multiple of MMUL_K0. */ __kernel void mat_mul_native_mmul_nt_t( TENSOR3D_T(lhs, BUFFER), TENSOR3D_T(rhs, BUFFER), +#ifdef BIAS + TENSOR3D_T(bias, BUFFER), +#endif // defined(BIAS) TENSOR3D_T(dst, BUFFER), const int M, const int N, @@ -591,7 +644,7 @@ __kernel void mat_mul_native_mmul_nt_t( // For explanations on how this kernel works, please refer to NT/NT kernel. This kernel makes little modifications to it. const uint x0 = get_global_id(0); // [0, (N / N0) * MMUL_M0) - // The upper limit is a simplified version of (N / N0) / MMUL_N0) * MMUL_BLOCK_SIZE) + // The upper limit is a simplified version of (N / N0) / MMUL_N0) * MMUL_BLOCK_SIZE) const uint y0 = get_global_id(1); // [0, (M / M0) / MMUL_M0) const uint z = get_global_id(2); // Batch @@ -679,6 +732,10 @@ __kernel void mat_mul_native_mmul_nt_t( #define c c_f32 #endif // defined(HALF_PRECISION) +#ifdef BIAS + perform_bias_addition(bias_ptr, bias_offset_first_element_in_bytes, c, dst_x); +#endif // defined(BIAS) + if(dst_x + N0 <= N || N0_LEFTOVER == 0) { LOOP_UNROLLING(int, m0, 0, 1, M0, @@ -722,34 +779,44 @@ __kernel void mat_mul_native_mmul_nt_t( * - K0 = 1 * @note Values > 8 for M0 are not expected to be efficient * - * @param[in] lhs_ptr Pointer to the lhs matrix. Supported data types: F32/F16 - * @param[in] lhs_stride_y Stride of the lhs matrix in Y (2nd) dimension (in bytes) - * @param[in] lhs_stride_z Stride of the lhs tensor in Z (3rd) dimension (in bytes) - * @param[in] lhs_w The width of the lhs tensor - * @param[in] lhs_h The height of the lhs tensor - * @param[in] lhs_n Number of the matrices (buffers) in the batch - * @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the lhs matrix - * @param[in] rhs_ptr Pointer to the rhs matrix. Supported data types: same as @p lhs_ptr - * @param[in] rhs_stride_y Stride of the rhs matrix in Y (2nd) dimension (in bytes) - * @param[in] rhs_stride_z Stride of the rhs tensor in Z (3rd) dimension (in bytes) - * @param[in] rhs_w The width of the rhs tensor - * @param[in] rhs_h The height of the rhs tensor - * @param[in] rhs_n Number of the matrices (buffers) in the batch - * @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the rhs matrix - * @param[out] dst_ptr Pointer to the dst matrix. Supported data types: same as @p lhs_ptr - * @param[in] dst_stride_y Stride of the dst matrix in Y (2nd) dimension (in bytes) - * @param[in] dst_stride_z Stride of the dst tensor in Z (3rd) dimension (in bytes) - * @param[in] dst_w The width of the dst tensor - * @param[in] dst_h The height of the dst tensor - * @param[in] dst_n Number of the matrices (buffers) in the batch - * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the dst matrix - * @param[in] M Number of rows in LHS matrix - * @param[in] N Number of columns in RHS matrix - * @param[in] K Number of rows in LHS matrix and columns in RHS matrix, which is multiple of MMUL_K0. + * @param[in] lhs_ptr Pointer to the lhs matrix. Supported data types: F32/F16 + * @param[in] lhs_stride_y Stride of the lhs matrix in Y (2nd) dimension (in bytes) + * @param[in] lhs_stride_z Stride of the lhs tensor in Z (3rd) dimension (in bytes) + * @param[in] lhs_w The width of the lhs tensor + * @param[in] lhs_h The height of the lhs tensor + * @param[in] lhs_n Number of the matrices (buffers) in the batch + * @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the lhs matrix + * @param[in] rhs_ptr Pointer to the rhs matrix. Supported data types: same as @p lhs_ptr + * @param[in] rhs_stride_y Stride of the rhs matrix in Y (2nd) dimension (in bytes) + * @param[in] rhs_stride_z Stride of the rhs tensor in Z (3rd) dimension (in bytes) + * @param[in] rhs_w The width of the rhs tensor + * @param[in] rhs_h The height of the rhs tensor + * @param[in] rhs_n Number of the matrices (buffers) in the batch + * @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the rhs matrix + * @param[in] bias_ptr (Optional) Pointer to the bias tensor. Supported data type: same as @p lhs_ptr + * @param[in] bias_stride_y (Optional) Stride of the bias tensor in Y dimension (in bytes) + * @param[in] bias_stride_z (Optional) Stride of the bias tensor in Z dimension (in bytes) + * @param[in] bias_w (Optional) The size of the width dimension of the bias tensor + * @param[in] bias_h (Optional) The size of the height dimension of the bias tensor + * @param[in] bias_n (Optional) The size of the depth dimension of the bias tensor + * @param[in] bias_offset_first_element_in_bytes (Optional) The offset of the first element in the bias tensor + * @param[out] dst_ptr Pointer to the dst matrix. Supported data types: same as @p lhs_ptr + * @param[in] dst_stride_y Stride of the dst matrix in Y (2nd) dimension (in bytes) + * @param[in] dst_stride_z Stride of the dst tensor in Z (3rd) dimension (in bytes) + * @param[in] dst_w The width of the dst tensor + * @param[in] dst_h The height of the dst tensor + * @param[in] dst_n Number of the matrices (buffers) in the batch + * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the dst matrix + * @param[in] M Number of rows in LHS matrix + * @param[in] N Number of columns in RHS matrix + * @param[in] K Number of rows in LHS matrix and columns in RHS matrix, which is multiple of MMUL_K0. */ __kernel void mat_mul_native_mmul_t_t( TENSOR3D_T(lhs, BUFFER), TENSOR3D_T(rhs, BUFFER), +#ifdef BIAS + TENSOR3D_T(bias, BUFFER), +#endif // defined(BIAS) TENSOR3D_T(dst, BUFFER), const int M, const int N, @@ -759,7 +826,7 @@ __kernel void mat_mul_native_mmul_t_t( // For explanations on how this kernel works, please refer to NT/NT kernel. This kernel makes little modifications to it. const uint x0 = get_global_id(0); // [0, (N / N0) * MMUL_M0) - // The upper limit is a simplified version of (N / N0) / MMUL_N0) * MMUL_BLOCK_SIZE) + // The upper limit is a simplified version of (N / N0) / MMUL_N0) * MMUL_BLOCK_SIZE) const uint y0 = get_global_id(1); // [0, (M / M0) / MMUL_M0) const uint z = get_global_id(2); // Batch @@ -847,6 +914,10 @@ __kernel void mat_mul_native_mmul_t_t( #define c c_f32 #endif // defined(HALF_PRECISION) +#ifdef BIAS + perform_bias_addition(bias_ptr, bias_offset_first_element_in_bytes, c, dst_x); +#endif // defined(BIAS) + if(dst_x + N0 <= N || N0_LEFTOVER == 0) { LOOP_UNROLLING(int, m0, 0, 1, M0, |