Note that conda’s official document mainly targets Python user. For parallel processing in Stata you must use stata-mp at the bottom of your. Refer to conda’s official document for more on virtual environment and package management. All Roar users- students, faculty, and staff- are invited to take a brief.
![use stata mp on hpc use stata mp on hpc](https://www.stata.com/includes/ir17/gui-mac17.png)
Next time, all you need to do is step (1) and (3) to start the virtual environment and using R. (If you have followed the “Note” in step 3, you can use conda deactivate instead.) (Type rstudio & will start RStudio and return you the terminal prompt.)Īfter you’re done with R, type source deactivate to return to the base environment. Start RStudio by typing rstudio in the terminal.
#Use stata mp on hpc install
If you are not able to find an R package with conda install -c r (packages built and maintained by Anaconda official channel) or conda install -c conda-forge (packages built and maintained by conda community), you can still try install.packages("packageName") in R console as discussed in Install R packages. Note the r- prefix to the usual R package name. See this official Anaconda document for all R packages maintained. The simplest way to use Stata on the HPC clusters is through the Open OnDemand web. Choose 'StataSE 17' after the desktop loads. The -c r option means installing package from the r channel. Running Stata via Your Web Browser Princeton Virtual Desktop. This is especially helpful when a package is partially developed using languages other than R (e.g. C++). The advantage of using conda is that it takes care of the package dependency for us.
![use stata mp on hpc use stata mp on hpc](https://wiki.uiowa.edu/download/attachments/109796340/stata2.png)
Note that we use conda for package management instead of R itself ( install.packages()). 2.2.2 Interactive mode (Python console).