Statcomp2.vanderbilt.edu Information

Description

Statcomp2 is a 64 bit Linux server comprised of 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 are compute intensive. It also has a non uniform memory architecture (NUMA).

Account Setup

Please email biostat-it@list.vanderbilt.edu with your vunetid to gain access to statcomp.

Understanding CPU Utilization

There are currently 2 programs installed on statcomp2 that can give you an idea about cpu utilization: top which is command-line driven, and xosview which is graphical.

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

xosview is a graphical app that shows a crude representation of each cpu's utilization, among other things; it's not process specific. I don't think it's as useful as top, but I mention it nonetheless.

View Screenshot of xosview

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 biostat-it@list.vanderbilt.edu 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.