Statcomp2 is a 64 bit Linux server equipped with 2 Intel Xeon X5647 processors running at 2.93GHz, 96Gb of memory, and approximately 2TB of hard drive space. It's purpose is to run statistical applications that work on large datasets and/or are compute intensive. It has a non-uniform memory architecture (NUMA).

statcomp2 ...
  • runs Ubuntu Linux as its operating system
  • is intended for jobs that are unsuitable for running on a local workstation due to large memory requirements or long run times
  • R is installed
  • There is no windowing software installed. All work is done via the command line.

Typical work flow

Note: The programs mentioned here (scp, WinSCP, ssh, putty) are just suggestions. There are many other tools available for transferring files and logging on to remote computers.

  • Develop and test your program on your local workstation. If your program process a large data set, do you testing with a small subset of the data.
  • When you program is ready, use scp (on Linux or Mac) or WinSCP (Windows) to copy your program and data to statcomp2
  • Use ssh (Linux and Mac) or Putty (Windows) to log on to statcomp2.
  • Run you program on statcomp2. If you expect the program to run a long time, run your job as a batch job. See the Frequently Asked Questions (FAQ) topic (in the "How do I run my R program as a batch job?" section) for details.

If you'd rather use a graphical user interface to transfer files to and from the statcomp2 server, have a look at

Account Setup

Please email to request an account on statcomp2.

Understanding CPU Utilization

With top, a user can determine which cpu is running a particular job by enabling the "j" column to be displayed. It's heading is "P" and will be displayed right next to the "COMMAND" column. To turn this on, follow these steps:

  • 1. start top
  • 2. type the key "f"
  • 3. type the key "j"
  • 4. hit the enter key

You should now see a column with heading "P". Each entry will have a 1 or 0 in it corresponding to cpu 1 or 0.

The SUMMARY area just above the table of processes lists the CPU utilization percentages.

  • type 1 to toggle between aggregate CPU and per CPU utilization.

Also, to save all the nifty changes you made to your top display:

  • type the key "W" to save this preference to $HOME/.toprc

View Screenshop of top

R Installed Packages and Personal Packages

When R looks for packages to load via the library() or require() function, it searches directory paths in the order they are specified in the shell environment variable R_LIBS. On the server the default paths are specified in the file /etc/R/Renviron, and the paths are /usr/local/lib/R/site-library, /usr/lib/R/site-library, and /usr/lib/R/library. Only root can add packages to these directories.

If you would like to use a package that's not installed on the server, and you feel it could be useful for others, please send an email request to and we will install it for you.

Othewise, you can install it yourself into a directory in your home area and set the R_LIBS environment variable to point to that directory. Some reasons for doing this:

  • Your package contains secret research that no-one else should see
  • You'd like to install a different version of an already installed package
  • The administrators are dragging their feet on your package install request (sorry, we can get busy).

Note that you don't have to add the additional paths specified in /etc/R/Renviron as R will do that for you.

To install a package into a directory in your home area

$ R CMD INSTALL -l ~/Rlib PackageName.tar.gz

Notice that the ~ (tilde) character expands to your home area path, which is in the environment variable HOME.

And set the R_LIBS environment variable... BEFORE running R

$ export R_LIBS=~/Rlib

You should place the above line in your .bashrc file so that the next time you log in, the variable will be set.
Topic revision: r9 - 05 Sep 2018, DalePlummer

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