Is there any way to switch between OpenBLAS and ATLAS libraries from a running R session? I am using Ubuntu 12.04.
Thank you
The R documentation states that in order to use another BLAS library, this needs to be specified configure time. This means that R needs to be rebuilt from source if you want to switch libraries. So, it is not possible to switch between BLAS libraries in a running R session.
no need to rebuild R, but yes do it when R is not running. See here.
Related
I am new to cloud computing and GCP. I am trying to create a notebook instance running R with a GPU. I got a basic instance with 1 core and 0 GPUs to start and I was able to execute some code which was cool. When I try to create an instance with a GPU I keep getting all sorts of errors about something called live migration, or that there are no resources available, etc. Can someone tell me how to start an R notebook instance with a GPU? It can't be this difficult.
The CRAN (The Comprehensive R Archive Network) doesn't support GPU. However, you can follow this link might help you to install a Notebook instance running R with a GPU. You need a machine with Nvidia GPU drivers installed then install R and Jupyter Lab. After that compile those R packages which require it for use with GPU's.
I'm running Keras in R and using Tensorflow-GPU backend. Is it possible to force Keras to run on CPU without re-installing the backend?
Let me give you 2 answers.
Answer #1 (normal answer)
No, unfortunately not. For keras CPU and GPU are 2 different versions, from which you select at install time.
It seems you remember that you selected GPU at install time. I guess you're hoping that you were only setting a minor option, not selecting a version of the program. Unfortunately, you were selecting the version of keras to install.
Answer #2 (ok, maybe you can "trick" keras)
It seems you can use environment variable values to trick keras into thinking that your CPU is your GPU.
This seems like it may have unexpected results, but it seemed to work for these Python users.
I wouldn't worry about the fact that they are using Python. They are just using their language to set environment variables. So you can do the same in R
or directly within your OS.
i've been getting up to speed using R of late, and am wondering what the most efficient way is to clone an RStudio environment, especially the package installations, from one machine to another. i'd like to be able to switch from my desktop machine to my laptop, but i am adding packages very frequently to the desktop as i work and would like a simple way to make sure the same packages get installed on the laptop.
any help much appreciated
ps. not everything i'm installing is from CRAN...some are packages taken from github
If you have more than a couple of machine to maintain with the same R configuration, I think you should consider setting up your own local R repository.
And I will just redirect you to another SO question here:
Creating a local R package repository
You can also find the most useful information in the R manual.
Once this is done, you just have to update the local R repository and the packages will be updated on all machines, Windows or Unix
You can just copy and paste the folders in the R libraries between machines. As long as it is the same operating system on both machines there should not be any problem. If you want it to be automatically synchronised then place the R libraries into something like dropbox so that adding or updating a package will automatically appear on either machine with the next sync.
I have an R script which I want to deploy so that it's idiot-proof, one click runs it etc. Unfortunately I don't have the means to pay for a server, and the environment in which it needs to run does not allow the installation of new software, only portable style apps can be run. (School computers) My script also relies on several non-base packages.
Is there any way to deploy R and my script in an easy to run way so it can be used off a usb stick?
You can install R on a USB drive and use it on any computer running the same OS. If you're using Windows, see question 2.6 of the R for Windows FAQ.
If you made the USB stick a bootable disk environment (say linux) with R installed on it, you could boot off it and do it that way.
I am trying to connect R to a Hadoop cluster using R. The cluster has HDFS, Map Reduce, Hive, Pig and Sqoop installed on it.
R will be running on in the Windows environment. I know that rhdfs, rhadoop and rmr exist for Linuix, but I can't find anything on Windows.
Does anyone know of a library to use?
Thank you
Revolution Analytrics is trying to make a name for themselves in this space. They have a couple of nice packages (some of which are open-source and/or free for non-commercial use) which allow you to interact with Hadoop from R in a Windows environment fluidly.