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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.


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.

Ocelote now has 46 nodes with Nvidia P100's that are available for "standard" and "windfall" queues. See details at GPU Nodes


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 7 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 

CPUXeon Westmere-EP X5650
Dual 6-core
Disk10TB (5 x 2TB)
NetworkGbE and QDR IB

Compute System Details


El Gato




IBM System X iDataPlex dx360 M4

Lenovo NeXtScale nx360 M5Penguin Altus XE2242

Year Purchased


2016 (2018 P100 nodes)2020

Node Count



Total System Memory (TB)

 26 TB

82.6 TB105 TB


Xeon Ivy Bridge E5-2650
Dual 8-core

Xeon Haswell E5-2695 Dual 14-core
Xeon Broadwell E5-2695 Dual 14-core

AMD EPYC 7642 Dual 48-core

Cores / Node



Total Cores



Processor Speed (GHz)



Memory / Node (GB)

 64 or 256

High memory node - 2TB

High memory node - 3 TB


137 Nvidia K20x 5 GB video mem

47 nodes with 2 K20x

43 nodes with 1 K20x

46 Nvidia P100 16 GB video mem
15 Nvidia K80 (buy-in only)

24 Nvidia V100 32 GB video mem
/tmp~840 GB spinning
/tmp is part of root filesystem
~840 GB spinning
/tmp is part of root filesystem
~1640 GB NVMe
/tmp is part of root filesystem

Max Performance




 Centos 7.6

 CentOS 6.10CentOS 7


FDR Inifinband

FDR Infiniband for node-node
10 Gb Ethernet node-storage

100 Gb/s Spine/Leaf
2x 25 Gb per compute node
Ethernet with RDMA via RoCEv2

* Ocelote includes a large memory node with 2TB of RAM available on 48 cores.  More details on the Large Memory Node

** Adjusted for the high memory node

Example Resource Requests

Note TypencpuspcmemMax memSample Request Statement

#PBS -l select=1:ncpus=16:mem=62gb:pcmem=4gb


#PBS -l select=1:ncpus=16:mem=250gb:ngpus=1:pcmem=16gb


#PBS select=1:ncpus=28:mem=168gb:pcmem=6gb


#PBS select=1:ncpus=28:mem=224gb:np100s=1:os7=True

High Memory4842gb2016gb

#PBS -l select=1:ncpus=48:mem=2016gb:pcmem=42gb

Standard945gb470gb 470gb

#SBATCH --nodes=1
#SBATCH --ntasks=94
#SBATCH --mem=470gb

GPU4945gb470gb 470gb

#SBATCH --nodes=1
#SBATCH --ntasks=94
#SBATCH --mem=470gb
#SBATCH --gres=gpu:1

High Memory9432gb3000gb

#SBATCH --nodes=1
#SBATCH --ntasks=94
#SBATCH --mem=3008gb

Two GPUs may be requested on ElGato with ngpus=2
There is a single node available on Ocelote with two GPUs. To request it, use np100s=2
Set os7=False for a CentOS 6 GPU node
Up to four GPUs may be requested on Puma with --gres=gpu=1, 2, 3, or 4