This article refers to the research computing cluster designed for high-performance computational research. If you are interested in high-speed networking support or storage related to research, please take a look at this article for more information.
What is the CRUG Cluster?
One of the goals of Carleton’s Computational Research Users Group is to create a shared, powerful, and expandable computation cluster that is usable by as many of our users as possible and funded by grants and faculty startup funds. Our users include faculty and students from all departments, and their needs are diverse.
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The system is designed to take advantage of the Slurm workload manager. We expect that the majority of the jobs will take advantage of multiple cores through some type of parallel processing. 95% of our needs seem to be embarrassingly parallel. Users “ssh” into command.dmz.carleton.edu and submit Slurm jobs through the linux command line. . If you want to use the system to handle R jobs, specific documentation can be found here. An example of using Slurm can found at https://wiki.carleton.edu/pages/viewpage.action?pageId=57837534. Some useful Slurm commands can be found at https://wiki.carleton.edu/display/carl/Useful+Slurm+commands.
To run a job on command:
Use an sftp or scp client to upload your code and data to command.dmz.carleton.edu (If you are are looking for a graphical interface for these commands, we recommend winscp for Windows users and cyberduck for Mac Users.)
If your code requires an executable (C, C++, java), then compile your code on command.dmz.carleton.edu.
Submit your code to the compute nodes using a command such as srun or sbatch (for examples, see https://wiki.carleton.edu/pages/viewpage.action?pageId=57837534 ).
Note: command and all of the compute nodes share the same network based file system.
Note: running commands on command.dmz.carleton.edu does eat up cpu time. please limit your cpu usage on this machine; run your code on the compute nodes via slurm!
If you want a CRUG account or are new to this, please contact our technical staff Mike Tie for help.
What if I have a job that only needs one core or if I want to run a graphical application?
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What if my program needs more cores, memory, disk space, or gpus than the cluster currently has?
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As of July 27, 2019, none of the compute nodes are equipped with GPUs. Please help us find funding.
What if I want to run a Windows application, some other version of linuxLinux, or Mac OSX?
We can spin/set up small virtual machines for unique version of linux Linux or for windows Windows apps; please contact one of our technical staff. Unfortunately, Mac OSX is not supported in a virtual environment?.
How do I get software installed?
Speak with our technical staff.
Other questions?
Speak with Mike Tie.