5 ms·

I read about it before.[1] There is also a BLAS library made by Nvidia that makes use of CUDA. This post is about how to hook it up to GNU Octave but it also wo

by nequo 4y ago

I read about it before.[1] There is also a BLAS library made by Nvidia that makes use of CUDA. This post is about how to hook it up to GNU Octave but it also works with R: https://developer.nvidia.com/blog/drop-in-acceleration-gnu-octave/ https://developer.nvidia.com/blog/drop-in-acceleration-gnu-o... What sibling says about compiling R on your work computer so that it can make full use of your CPU can help too. I am curious if that closes the performance gap for you. [1] https://csantill.github.io/RPerformanceWBLAS/ https://csantill.github.io/RPerformanceWBLAS/

VeninVidiaVicii 4y ago
These tips speed up my Arch Linux R even more, but my Ubuntu setup is still just as slow, even with these optimizations. Somewhere along the journey I did see that Xeons have problems with R, but I can't seem to find where I saw that. Darn.
VeninVidiaVicii 4y ago
I’ll give it a shot when I make it back to campus. I’m snowed in at home, but I’ll let you know soon. Also, this really does look like the issue. Thanks for the insightful comments.