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-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/

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.

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.