Computing

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Much of our programming (and almost all of Ryan’s) is done in Python, using the NumPy/SciPy/Matplotlib scientific programming stack. An easy way to install and maintain this stack is Enthought Canopy.

High performance computing

Our group owns 87,600 CPU-hours of monthly high priority time on the HTC cluster (queue htc_high), and 70,600 CPU-hours on Ocelote (queue new_high). These are in addition to the 60,000 CPU-hours in the standard queue. We also own 32 TB of cluster-attached storage, accessible under /rsgrps/rgutenk. To use this space, please create a subdirectory based on your NetID.

Extensive documentation is available for the HPC systems. In particular, the script builder is very helpful.

Network-attached storage

Our group has a 54 TB NAS box at mcb-gutennas.catnet.arizona.edu. Directories on this box can be mounted via Samba.