Account and QOS limits under SLURM
Every group on HiPerGator (HPG) must have an investment with a corresponding hardware allocation to be able to do any work on HPG. Each allocation is associated with a scheduler account. Each account has two quality of service (QOS) levels - high-priority investment QOS and a low-priority burst QOS. The latter allows short-term borrowing of unused resources from other groups' accounts. In turn, each user in a group has a scheduler account association. In the end, it is this association which determines which QOSes are available to a particular user. Users with secondary Linux group membership will have associations with QOSes from their secondary groups.
In summary, each HPG user has scheduler associations with group account based QOSes that determine what resources are available to the users's jobs. These QOSes can be thought of as pools of computational (CPU cores), memory (RAM), maximum run time (time limit) resources with associated starting priority levels that can be consumed by jobs to run applications according to QOS levels, which we will review below.
Account and QOS
Using/Finding the resources from a secondary group
To view instructions on using SLURM resources from one of your secondary groups, or find what those associations are, view Checking and Using Secondary Resources
CPU cores and Memory (RAM) Resource Use
CPU cores and RAM are allocated to jobs independently as requested in job scripts. Considerations for selecting how many CPU cores and how much memory to request for a job must take into account the QOS limits based on the group investment, the limitations of the hardware (compute nodes), and the desire to be a good neighbor on a shared resource like HiPerGator to ensure that system resources are allocated efficiently, used fairly, and everyone has a chance to get their work done without causing negative impacts on work performed by other researchers.
HiPerGator consists of many interconnected servers (compute nodes). The hardware resources of each compute node, including CPU cores, memory, memory bandwidth, network bandwidth, and local storage are limited. If any single one of the above resources is fully consumed the remaining unused resources can become effectively wasted, which makes it progressively harder or even impossible to achieve the shared goals of Research Computing and the UF Researcher Community stated above. See the Available Node Features for details on the hardware on compute nodes. Nodes with similar hardware are generally separated into partitions. If the job requires larger nodes or particular hardware make sure to explicitly specify a partition. Example:
When a job is submitted, if no resource request is provided, the default limits of 1 CPU core, 600MB of memory, and a 10 minute time limit will be set on the job by the scheduler. Check the resource request if it's not clear why the job ended before the analysis was done. Premature exit can be due to the job exceeding the time limit or the application using more memory than the request.
Run testing jobs to find out what resource a particular analysis needs. To make sure that the analysis is performed successfully without wasting valuable resources you must specify both the number of CPU cores and the amount of memory needed for the analysis in the job script. See Sample SLURM Scripts for examples of specifying CPU core requests depending on the nature of the application running in a job. Use
--mem (total job memory on a node) or
--mem-per-cpu (per-core memory) options to request memory. Use
--time to set a time limit to an appropriate value within the QOS limit.
As jobs are submitted and the resources under a particular account are consumed the group may reach either the CPU or Memory group limit. The group has consumed all cores in a QOS if the scheduler shows
QOSGrpCpuLimit or memory if the scheduler shows
QOSGrpMemLimit in the reason a job is pending ('NODELIST(REASON)' column of the
squeue command output). Example:
JOBID PARTITION NAME USER ST TIME NODES NODELIST(REASON) 123456 bigmem test_job jdoe PD 0:00 1 (QOSGrpMemLimit)
Reaching a resource limit of a QOS does not interfere with job submission. However, the jobs with this reason will not run and will remain in the pending state until the QOS use falls below the limit.
If the resource request for submitted job is impossible to satisfy within either the QOS limits or HiPerGator compute node hardware for a particular partition the scheduler will refuse the job submission altogether and return the following error message,
sbatch: error: Batch job submission failed: Job violates accounting/QOS policy (job submit limit, user's size and/or time limits)
Time and Resource Limits
See SLURM Partition Limits for partition time limits.
For details on the limits placed on time and resources like GPUs on SLURM, view QOS Limits.
To view a summary of currently active jobs for a group, use the slurmInfo command from the ufrc module.
slurmInfo -pu -g groupname
Choosing QOS for a Job
For advice on choosing QOS, go to Choosing QOS for a Job.
Pending Job Reasons
To reiterate, the following Reasons can be seen in the
NODELIST(REASON) column of the
squeue command when the group reaches the resource limit for a QOS:
All CPU cores available for the listed account within the respective QOS are in use.
All memory available for the listed account within the respective QOS as described in the previous section is in use.
QOSGrpMemLimit, SLURM may not evaluate other jobs and they may simply be listed with the
Priorityreason code. See FAQ at the bottom of the page for a list of reasons.