SeaWulf Queues

Audience: Faculty, Guests, Researchers, Staff and Students

This KB Article References: High Performance Computing
This Information is Intended for: Faculty, Guests, Researchers, Staff, Students
Last Updated: July 14, 2020

What does each queue provide?

The following table details resource limits on jobs submitted to each queue via Slurm:


Default run time

Max run time

Max # of nodes

Min # of nodes

Max # of simultaneous jobs per user

debug-28core 1 hour 1 hour 8 n/a n/a
extended-24core 8 hours 7 days 2 n/a 4
extended-28core 8 hours 7 days 2 n/a 6
extended-40core 8 hours 7 days 2 n/a 3
gpu 1 hour 8 hours 2 n/a 2
gpu-long 8 hours 48 hours 1 n/a 2
gpu-large 1 hour 8 hours 4 n/a 1
large-24core 4 hours 8 hours 60 24 1
large-28core 4 hours 8 hours 80 24 1
large-40core 4 hours 8 hours 50 16 1
long-24core 8 hours 48 hours 8 n/a 6
long-28core 8 hours 48 hours 8 n/a 6
long-40core 8 hours 48 hours 6 n/a 3
medium-24core 4 hours 12 hours 24 8 2
medium-28core 4 hours 12 hours 24 8 2
medium-40core 4 hours 12 hours 16 6 1
p100 1 hour 24 hours 1 n/a 1
short-24core 1 hour 4 hours 12 n/a 8
short-28core 1 hour 4 hours 12 n/a 8
short-40core 1 hour 4 hours 8 n/a 4


In addition to the limits in the table above, users cannot use more than 32 nodes at one time on the Slurm queues unless running jobs on the large-24core or large-40core queues.


How are the queues different?

The queues mostly differ in the maximum runtime and number of nodes that can be allocated to jobs run on them.  Some sets of queues offer different hardware.  More specifically:

  • The debug, short, long, extended, medium, and large queues share a set of identical nodes that have a max of 28 Haswell cores.
  • The short-24core, long-24core, medium-24core, and large-24core queues share a second set of identical nodes that have 24 Haswell cores.
  • The short-40core, long-40core, medium-40core, and large-40core queues share a second set of identical nodes that have 40 Skylake cores.
  • The gpu and gpu-long queues share a third set of identical nodes that are similar to those used by the short, long, etc. queues but with multiple GPUs each.

Which queue should I use?

  • Use the gpu or gpu-long queue ony if you need a GPU for your job.  Check your software's documentation if you're unsure.
  • Use the debug queue for brief interactive jobs.  This can be useful for testing or debugging your code.
  • Use the extended queues for jobs that you intend to run for longer periods of time, particularly if:
    • Adding more nodes (with or without GPUs) will not speed up your job.
    • You're monitoring an outside data source (e.g. social media feeds, web-scraping).  Remember to watch your disk usage.
  • Use the long queue if you're not sure.  Once you understand what your job's needs are, pick another one if it's more suitable.
  • Use other queues depending on your needs and the level of MPI support offered by your choice of software.

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