Compute Resources

Overview

El Gato

Implemented at the start of 2014 and it has been reprovisioned with CentOS 7 and new compilers and libraries. It also uses PBS as the scheduler consistent with Ocelote.  El Gato is a large GPU cluster, purchased by an NSF MRI grant by researchers in Astronomy and SISTA. Whilst the Nvidia K20 GPUs are five years old, they are still valuable for single-precision workload. There are 90 nodes with one or two GPU's.

Ocelote

Implemented in the middle of 2016.  It is designed to support all workloads on the standard nodes except:

1. Large memory workloads that do not run within the 192GB RAM of each node can also be handled with the large memory node.
2. GPU's are available as a buy-in option or windfall and are now available standard on Ocelote.

Puma

Will have a soft opening August 2020. Similarly to Ocelote it will have standard CPU nodes (with 96 cores and 521 GB of memory per node), GPU nodes (with Nvidia V100) and a high-memory node (3 TB). Local scratch storage increased to ~1,6 TB. The new cluster is going to run on CentOS 8 which will improve compatibility with the latest software.

Puma is currently different from ElGato and Ocelote in these ways:

• Puma uses SLURM for job scheduling
• Puma has many programs installed natively (e.g. Singularity). You won't have to module load Singularity any more!
• There's a new alias command: interactive. This automatically places you in a single-cpu interactive session for debugging, testing, and development. 
• Modules are no long available on the login nodes. To view and test modules, an interactive session is necessary (see above).

Free vs Buy-In

The HPC resources at UA are differentiated from many other universities in that there is central funding for a significant portion of the available resources. Each PI receives a standard monthly allocation of hours at no charge.  There is no charge to the allocation for windfall usage and that has proven to be very valuable for researchers with substantial compute requirements.  

Research groups can 'Buy-In' (add resources such as processors, memory, storage, etc.) to the base HPC systems as funding becomes available. Buy-In research groups will have highest priority on the resources they add to the system.  If the expansion resources are not fully utilized by the Buy-In group they will be made available to all users as windfall.

Details on allocations

Details on buy-in

Test Environment

HPC has a test / trial environment as well as the primary clusters detailed below.  This environment is intended to be used for projects that are six months or less in duration and cannot be run on the production systems. Reasons for not being able to be run on the production systems include requiring root access, and hardware or software requirements that cannot be met by one of the production systems. If you have a project in mind that we might be able to support, contact hpc-consult@list.arizona.edu