1#ifndef STAN_MATH_OPENCL_KERNELS_NEGATIVE_RECT_LOWER_TRI_MULTIPLY_HPP
2#define STAN_MATH_OPENCL_KERNELS_NEGATIVE_RECT_LOWER_TRI_MULTIPLY_HPP
11namespace opencl_kernels {
13static constexpr const char* neg_rect_lower_tri_multiply_kernel_code
44 __global
double* A,
const __global
double* temp,
const int A_rows,
46 int result_matrix_id = get_global_id(2);
47 int offset = result_matrix_id *
rows * 2;
48 const int thread_block_row = get_local_id(0);
49 const int thread_block_col = get_local_id(1);
50 const int i = THREAD_BLOCK_SIZE * get_group_id(0) + thread_block_row;
51 const int j = THREAD_BLOCK_SIZE * get_group_id(1) + thread_block_col;
53 __local
double temp_local[THREAD_BLOCK_SIZE][THREAD_BLOCK_SIZE];
54 __local
double C1_local[THREAD_BLOCK_SIZE][THREAD_BLOCK_SIZE];
56 double acc[WORK_PER_THREAD] = {0};
59 = (
rows + THREAD_BLOCK_SIZE - 1) / THREAD_BLOCK_SIZE;
60 for (
int tile_ind = 0; tile_ind < num_tiles; tile_ind++) {
63 for (
int w = 0; w < WORK_PER_THREAD; w++) {
65 = THREAD_BLOCK_SIZE * tile_ind + thread_block_row;
67 = THREAD_BLOCK_SIZE * tile_ind + thread_block_col;
68 const int temp_global_col = tiled_j + w * THREAD_BLOCK_SIZE_COL;
71 const int C1_global_col = offset + j + w * THREAD_BLOCK_SIZE_COL;
72 const int C1_global_row = tiled_i + offset;
76 = thread_block_col + w * THREAD_BLOCK_SIZE_COL;
77 const int local_row = thread_block_row;
78 if ((temp_global_col) <
rows && i <
rows) {
79 temp_local[local_col][local_row]
80 = temp[result_matrix_id *
rows *
rows
81 + temp_global_col *
rows + i];
83 temp_local[local_col][local_row] = 0.0;
86 if (C1_global_col <= C1_global_row && C1_global_col < A_rows
87 && C1_global_row < A_rows) {
88 C1_local[local_col][local_row]
89 = A[C1_global_col * A_rows + C1_global_row];
91 C1_local[local_col][local_row] = 0;
95 barrier(CLK_LOCAL_MEM_FENCE);
96 for (
int block_ind = 0; block_ind < THREAD_BLOCK_SIZE;
98 for (
int w = 0; w < WORK_PER_THREAD; w++) {
103 = thread_block_col + w * THREAD_BLOCK_SIZE_COL;
104 const int local_row = thread_block_row;
105 acc[w] += temp_local[block_ind][local_row]
106 * C1_local[local_col][block_ind];
109 barrier(CLK_LOCAL_MEM_FENCE);
113 const int A_global_row = i +
rows + offset;
114 const int A_global_col_offset = offset + j;
116 for (
int w = 0; w < WORK_PER_THREAD; w++) {
117 const int A_global_col
118 = A_global_col_offset + w * THREAD_BLOCK_SIZE_COL;
119 if (A_global_col < A_rows && (i +
rows + offset) < A_rows) {
120 A[A_global_col * A_rows + i +
rows + offset] = -acc[w];
134 "neg_rect_lower_tri_multiply",
136 {{
"THREAD_BLOCK_SIZE", 32}, {
"WORK_PER_THREAD", 8}});
const kernel_cl< in_out_buffer, in_buffer, int, int > neg_rect_lower_tri_multiply("neg_rect_lower_tri_multiply", {thread_block_helpers, neg_rect_lower_tri_multiply_kernel_code}, {{"THREAD_BLOCK_SIZE", 32}, {"WORK_PER_THREAD", 8}})
See the docs for neg_rect_lower_tri_multiply() .
int64_t rows(const T_x &x)
Returns the number of rows in the specified kernel generator expression.
static const std::string thread_block_helpers
Defines a helper macro for kernels with 2D local size.
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...
Creates functor for kernels.