• How do I know what number of nodes, cores, memory etc to ask for my jobs?

• How do I find out whether a cluster/partition supports these resources?

• How do I find out whether these resources are available on the cluster?

• How long will I have to wait in the queue before my job starts? How busy is the cluster?

• How do I monitor the progress of my job?

• My job finished before the wall time - what happens?

• How do I know what number of nodes, cores, memory etc to ask for my jobs?

  • Understand your software and application. 

    • Read the docs – look at the help for commands/options.

    • Can it run multiple threads - use multi cores (OpenMP) / nodes (MPI)?

    • Can it use a GPU? Nvidia cuda.

    • Are their suggestions on data and memory requirements?

• How do I find out whether a cluster/partition supports these resources?

• How do I find out whether these resources are available on the cluster?

  • Consult the wiki: Medicine Hardware Summary Table

• How long will I have to wait in the queue before my job starts? 

  • How busy is the cluster? 

  • Current Cluster utilization: Commands sinfo / arccjobs / pestat and OnDemand’s MedicineBow System Status page.

• How do I monitor the progress of my job?

  • Slurm commands: squeue

• My job finished before the wall time - what happens?

  • If your job has completely finished before the wall time you requested (e.g. it finished in two hours and you requested four hours) i.e. it’s status is no longer running, then Slurm will remove the job from the queue, release any requested resources back to the cluster, and allow other jobs to start running. Your job is not sitting idle on the cluster waiting for the wall time to run down.

• Not defining the account and time options.

• The account is the name of the project you are associated with. It is not your username.

• Requesting combinations of resources that can not be satisfied: Medicine Hardware Summary Table

  • For example, you can not request 40 cores on a compute node with a max of 32.

  • Requesting too much memory, or too many GPU devices with respect to a partition.

• My job is pending? Why? 

  • Because the resources are currently not available.

    • Be mindful of specialized nodes (such as our huge mem with 4T of RAM) we might only have a few of them.

  • Have you unnecessarily defined a specific partition (restricted yourself) that is busy? 

  • We only have a small number of GPUs.

  • This is a shared resource - sometimes you just have to be patient…

  • Check current cluster utilization.

  • What ever resources you are asking for are currently not available. Slurm will start you job when they become available.

  • We do empathize and under the frustration, but this is a shared resource, and sometimes we just have to be patient and wait in the queue.

• Preemption: Users of an investment get priority on their hardware.

  • We have the non-investor partition.

When we have schedule maintenance on the cluster, an announcement will go out and indicate the date/time that this is scheduled to start.

All jobs currently running on the cluster are allowed to finish, and we can aspect further jobs if Slurm can complete them before the maintenance starts.

Be conscious of: If an announcement goes out on a Monday that maintenance is to start on the following Friday, there is only a window of four days that any new job must complete within.

If you submit a job with a wall time of seven days, then this can not and will not be started since it can not complete before Friday.

You job will be accepted by Slurm, queued, have a status of pending, and automatically started once maintenance is completed and Slurm is restarted.

Remember: By default you must define the project (account) you’re using and a walltime.

If you need to explicitly request a partition, the name must be correct:

Use the sinfo command to get a list of know partitions, as well as detailing their current use:

Timeouts aren’t errors as such, just that the time you requested was not long enough to compete the computation.

The maximum allowed wall time is 7 days:

Do not request 7 days just because you can!

Wall time is considered when Slurm tries to allocate your job.

A job is more likely to be back filled (slotted onto the cluster) in busy times than pending jobs will longer wall times.

ARCC can provide users with wall times longer than 7 days.

Please contact use, but we require that you can demonstrate that you job can not be optimized, for example:

• Can it run faster by using more cores, or even multiple nodes?

• Can it utilize GPUs?

• Can the job actually be divided up into sections that can be run concurrently across multiple jobs?

ARCC can provide assistance with trying to understand if a job can be optimized.

This is caused because you’re trying to request a configuration that isn’t available, or requires more details: For example:

Segmentation faults are typically caused by an application trying to access memory outside what has been allocated to the job.

Basically, you job is out of memory of what it requested.

Resolved: Request more memory using either the mem or mem-per-cpu .

• As discussed in the Intro to HPC workshop, we have a Condominium Model where if your job is running an a compute node that is part of another project’s hardware investment, your job can be preempted.

• Your job will be stopped and automatically re-queued and when resources come available on the cluster, it will be restarted.

• Further details can be found on our Slurm and Preemption page and how to use the non-investor partition to prevent this from happening.

When I run pestat, it appears that my job is one of many on a particular compute node.

As discussed in the Intro to HPC workshop when talking about Compute Nodes this is perfectly acceptable and one of the tasks that Slurm manages.

Remember: All jobs are independent and do not affect anyone else.

General Use Case: You have a job running on the cluster, from which you’d like to submit further jobs.

General Answer: Yes.

If you have the scripting ability, then you can write code that creates a submission script, and then calls the sbatch command.

This submission will be treated as any other submission and be added to the queue, and depending on the current cluster utilization might be pending before it starts running.

This can also be performed from scripts that are already running as part of a job.

Is this a good idea? Again yes. There are existing applications that do exactly this, and with some extra Slurm understanding, you can have jobs that are dependent on other jobs i.e. job B won’t start until job A is completed, basically breaking a pipeline down into a sequence of jobs.

Note: There is a maximum number of jobs that Slurm can accommodate within the queue (currently set at 75K), do not try submitting more that this in one batch, and you will need to throttle their submission i.e. submit say 10 every second.

If you try submitting 1000s in a single call then you can affect Slurm. Be a good cluster citizen.

Possible Alternative: Use a Slurm Job Array which allows you to submit a single submission script that will be run by the size of the array (current max size is 10K). i.e. you request an array of size 100, Slurm will automatically submit 100 jobs with a copy of the original submission script - with a little scripting you can have each copy use different input values/data, but all perform the same defined workflow.

If you have a Linux session running in a terminal, in which you have an salloc interactive session running, and your terminal session closes, or is interrupted for any reason, your interactive session will be stopped.

From the command-line you can not go back into it, you will have to start a new interactive session.