On Tue, 31 Dec 2019, maurizio marchi wrote:
Anyway I was wondering whether any other ways were available. My question concern how to speed up old R codes involving GIS procedures and mainly using rgdal, raster, biomod2, dismo, sp or other Spatial packages.
Maurizio, How many cores are in the CPU of your machine? AMD processors have two threads per core (e.g., the Ryzen7 in my desktop has 8 cores and 16 threads). Programs need to be compiled to use multiple threads and you need libraries such as mesa or opengl to take advantage of that. Also, how much memory is installed on that system? More is always better.
I was wondering if this could be used with R. In other words I would like to solve the issue from the beginning, opening an R session from terminal running on the GPU instead of on CPU(s).
Something else for you to consider is that there are two types of video cards: those designed for gamers and those designed for technical work. An explanation of the differences (focused on nVidia's products) is here: <https://www.quora.com/What-is-the-different-between-gaming-GPU-vs-professional-graphics-programming-GPU>. There are multiple facturs involved so it's not a simple solution. Of course, if you have a long spatial model running you can start it using screen and it will continue running even after you log out as long as the computer is running. Hope this helps, Rich _______________________________________________ R-sig-Geo mailing list R-sig-Geo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
