![]() ![]() If also make R to process faster since some packages are able to use all the cores of your computer after you compile them with OpenMP. OpenMP is a library for Open Multi-Processing, or in other words, be able to use all the cores of your processor when you are compiling C, C++, and Fortran. It’s usually a huge leap in performance when you begin to make complex mathematical operations. Basically, it optimizes your processor when you are doing mathematical operations, like when you are using R. OpenBLAS is a open implementation of the BLAS (Basic Linear Algebra Subprograms) API. The biggest advantage, besides of the regular advantages of installing something with HomeBrew, is you can create your own version of R, you can compile it, therefore you can compile it with steroids, so you can take advantage of the OpenBlas and OpenMP libraries. Nevertheless, you are going to be able to get support from Homebrew and of course, from the regular channels to get help for R, like the mail list. However, Homebrew setup isn’t officially supported by the R Core Team, so if you find problems with your R installation you aren’t going to get support from them. There are a lot of guides out there about how to have a R installation 100% Homebrew and some people, like me, like to have this kind of setup because it’s convenient and for the sake of lear a little bit more about how R works in more detail. I update the section about the Data Table Package accordingly.Īs you know I’m a big fan of Homebrew as a manager of part of the software of my Mac, since it make things easier. ![]() This is not exactly what the Data Table wiki recommends. ![]() ![]() Update Thursday, 22nd of March 2018: I have to add -fopenmp to both clang and clang++ variables in my makevars to be able to build data.table package correctly. Update Tuesday, 27th of March 2018: I just found out that seems you don’t just need to run sudo R CMD javareconf to configure Java an R, at least with the versions of Java 9.0.4 and R 3.4.4. Update Friday, 10th of May 2018: If you want to install R with all the capabilities you need to read this post too, and perhaps this one too. ![]()
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