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Best practices for job submission: Difference between revisions
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Best practices for job submission (view source)
Revision as of 17:29, 2 September 2022
, 2 years agoAdded missing introductory sentence
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When submitting a job to one of the clusters, it's important to choose appropriate values for various parameters in order to ensure that your job doesn't waste resources or create problems for other users and yourself. This will ensure your job starts more quickly and that it is likely to finish correctly, producing the output you need to move your research forward. | When submitting a job to one of the clusters, it's important to choose appropriate values for various parameters in order to ensure that your job doesn't waste resources or create problems for other users and yourself. This will ensure your job starts more quickly and that it is likely to finish correctly, producing the output you need to move your research forward. | ||
For your first jobs on the cluster, it's understandably difficult to estimate how much time or memory may be needed for your job to carry out a particular simulation or analysis. This page should provide you useful tips. | |||
=Typical job submission problems= | =Typical job submission problems= | ||
* The more resources - time, memory, CPU cores, GPUs - that your job asks for, the more difficult it will be for the scheduler to find these resources and so the longer your job will wait in queue. | * The more resources - time, memory, CPU cores, GPUs - that your job asks for, the more difficult it will be for the scheduler to find these resources and so the longer your job will wait in queue. | ||
* But if not enough resources are requested, the job can be stopped if it goes beyond its time limit or its memory limit. | * But if not enough resources are requested, the job can be stopped if it goes beyond its time limit or its memory limit. | ||