1#ifndef STAN_MATH_OPENCL_KERNELS_INVERSE_LOWER_TRI_MULTIPLY_HPP
2#define STAN_MATH_OPENCL_KERNELS_INVERSE_LOWER_TRI_MULTIPLY_HPP
11namespace opencl_kernels {
13static constexpr const char* inv_lower_tri_multiply_kernel_code =
STRINGIFY(
47 __global
double* temp,
48 const int A_rows,
const int rows) {
49 int result_matrix_id = get_global_id(2);
50 int offset = result_matrix_id *
rows * 2;
51 const int thread_block_row = get_local_id(0);
52 const int thread_block_col = get_local_id(1);
53 const int global_thread_row
54 = THREAD_BLOCK_SIZE * get_group_id(0) + thread_block_row;
55 const int global_thread_col
56 = THREAD_BLOCK_SIZE * get_group_id(1) + thread_block_col;
58 __local
double C2_local[THREAD_BLOCK_SIZE][THREAD_BLOCK_SIZE];
59 __local
double A3_local[THREAD_BLOCK_SIZE][THREAD_BLOCK_SIZE];
61 double acc[WORK_PER_THREAD] = {0};
63 const int num_tiles = (
rows + THREAD_BLOCK_SIZE - 1) / THREAD_BLOCK_SIZE;
64 for (
int tile_ind = 0; tile_ind < num_tiles; tile_ind++) {
67 for (
int w = 0; w < WORK_PER_THREAD; w++) {
68 const int tiled_i = THREAD_BLOCK_SIZE * tile_ind + thread_block_row;
69 const int tiled_j = THREAD_BLOCK_SIZE * tile_ind + thread_block_col;
72 const int C2_global_col
73 = offset +
rows + tiled_j + w * THREAD_BLOCK_SIZE_COL;
74 const int C2_global_row = offset + global_thread_row +
rows;
75 const int A3_global_col
76 = offset + global_thread_col + w * THREAD_BLOCK_SIZE_COL;
77 const int A3_global_row = tiled_i +
rows + offset;
80 const int local_col = thread_block_col + w * THREAD_BLOCK_SIZE_COL;
81 const int local_row = thread_block_row;
83 if (C2_global_col <= C2_global_row && C2_global_col < A_rows
84 && C2_global_row < A_rows) {
85 C2_local[local_col][local_row]
86 = A[C2_global_col * A_rows + C2_global_row];
88 C2_local[local_col][local_row] = 0;
90 if (A3_global_col < A_rows && A3_global_row < A_rows) {
91 A3_local[local_col][local_row]
92 = A[A3_global_col * A_rows + A3_global_row];
94 A3_local[local_col][local_row] = 0.0;
98 barrier(CLK_LOCAL_MEM_FENCE);
99 for (
int block_ind = 0; block_ind < THREAD_BLOCK_SIZE; block_ind++) {
100 for (
int w = 0; w < WORK_PER_THREAD; w++) {
101 const int local_col = thread_block_col + w * THREAD_BLOCK_SIZE_COL;
102 const int local_row = thread_block_row;
103 acc[w] += C2_local[block_ind][local_row]
104 * A3_local[local_col][block_ind];
107 barrier(CLK_LOCAL_MEM_FENCE);
110 const int batch_offset = result_matrix_id *
rows *
rows;
113 const int temp_global_row = global_thread_row;
115 for (
int w = 0; w < WORK_PER_THREAD; w++) {
117 const int temp_global_col
118 = global_thread_col + w * THREAD_BLOCK_SIZE_COL;
119 temp[batch_offset + temp_global_col *
rows + temp_global_row] = acc[w];
130 "inv_lower_tri_multiply",
132 {{
"THREAD_BLOCK_SIZE", 32}, {
"WORK_PER_THREAD", 8}});
const kernel_cl< in_buffer, out_buffer, int, int > inv_lower_tri_multiply("inv_lower_tri_multiply", {thread_block_helpers, inv_lower_tri_multiply_kernel_code}, {{"THREAD_BLOCK_SIZE", 32}, {"WORK_PER_THREAD", 8}})
See the docs for add() .
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.