The package offers a variety of functions that are frequently being used in genomic prediction
and genomewide association studies. The package is based onRcpp andRcppEigen, hence all routines
are implemented using the matrix algebra library Eigen.
The main emphasis of the package lies in parallel computing which is realized by C++ functions making
use of shared memory multi-threading implemented through OpenMP.
R is of single-threaded nature, hence almost the entire package is written
in C++. The package offers a variety of functions that lets you control and check
the number of threads that are being used by the functions of the package.
Internally every function uses the global variable cpgen.threads which is stored in
options()$cpgen.threads.
The value can be changed using the function set_num_threads(). When the package is loaded
in an R-session cpgen.threads will be set to the value returned by get_max_threads() which
is a wrapper for the OpenMP-header function omp_get_max_threads()
devtools::install_github("cheuerde/cpgen", ref = "master", build_vignettes=FALSE)