Automatic Differentiation
 
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sum.hpp
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1#ifndef STAN_MATH_OPENCL_PRIM_SUM_HPP
2#define STAN_MATH_OPENCL_PRIM_SUM_HPP
3#ifdef STAN_OPENCL
4
9
10namespace stan {
11namespace math {
12
19template <typename T,
20 require_all_kernel_expressions_and_none_scalar_t<T>* = nullptr>
21value_type_t<T> sum(const T& m) {
22 if (is_matrix_cl<T>::value && m.size() < 1000) {
23 // for small matrices running another kernel is not worth it
24 return sum(from_matrix_cl(m));
25 }
26 matrix_cl<value_type_t<T>> res;
27 if (m.rows() <= 8) {
28 // without transpose we would use just a few threads in a work group
29 res = sum_2d(transpose(m));
30 } else {
31 res = sum_2d(m);
32 }
33 return sum(from_matrix_cl(res));
34}
35
36} // namespace math
37} // namespace stan
38
39#endif
40#endif
auto sum_2d(T &&a)
Two dimensional sum - reduction of a kernel generator expression.
auto transpose(Arg &&a)
Transposes a kernel generator expression.
auto from_matrix_cl(const T &src)
Copies the source matrix that is stored on the OpenCL device to the destination Eigen matrix.
Definition copy.hpp:61
fvar< T > sum(const std::vector< fvar< T > > &m)
Return the sum of the entries of the specified standard vector.
Definition sum.hpp:22
The lgamma implementation in stan-math is based on either the reentrant safe lgamma_r implementation ...
Definition fvar.hpp:9