All University of Arizona Principal Investigators (PIs; aka Faculty) that register for access to the UA High Performance Computing (HPC) receive allocation on the HPC machines. Currently all PIs receive:
When you obtain a new HPC account, you will be provided with the following storage:
File count limit:
Use this link for details on xdisk usage
/extra is something new with Ocelote. When you log in to Ocelote for the first time, an allocation of 200GB will be created for you. It takes an hour or two to show up, and then it is permanent. Remember that it is not backed up like /home. The number of files within the 200GB is limited to 120,000.
Job Time Limits
Each group is allocated a base of 36,000 hours of compute time. This allocation is refreshed monthly. This allocation can be subdivided by the PI using the portal at https://portal.hpc.arizona.edu/portal/
You can use this time on either the standard nodes which do not require special attributes in the scheduler script, or on the GPU nodes which do require special attributes. The queues are setup so that jobs that do not request GPU's will not run there.
ElGato has a different allocation method of time as it is funded through an NSF MRI grant with usage time provided for campus researchers outside of the grant recipients.
PBS Batch Queue Limits
The batch queues on the different systems have the following memory, time and core limits.
|debug||Used as a high priority to test code or jobs.|
|standard||Used to consume the monthly allocation of hours provided to each group|
|windfall||Used when standard is depleted but subject to preemption|
|high_priority||Used by 'buy-in' users for purchased nodes|
# of Compute Nodes
Max Wallclock Hrs / Job
|Total cores in use / group|
Largest job / memory
Max # of Running Jobs
|Max Queued Jobs|
|El Gato||standard||131||240||512 cores||512||1024GB||75||1000|
*** This limit is shared by all members of a group across all queues. So you can use the system 2016 core limit by one user on the standard queue or share it across multiple users or queues.