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habrok:job_management:checking_jobs [2024/05/14 11:08] – [Interpreting jobinfo output] fokkehabrok:job_management:checking_jobs [2025/08/29 13:09] (current) – [Finding back your own jobs] bob
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 ==== Finding back your own jobs ==== ==== Finding back your own jobs ====
  
-In order to find back the jobs that you submitted the ''-u'' option for ''squeue'' can be used. After the ''-u'' the username has to be supplied. In this example we use ''$USER'' for this, which will be replaced by your username: +In order to find back the jobs that you submitted, you can use ''%%squeue --me%%''. If you want to find the jobs of a particular user, you can instead use ''%%squeue -u p123456%%''; this command will only show the jobs submitted by the user given after the ''-u''. 
-<code> +
-squeue -u $USER +
-</code> +
-This command will only show the jobs submitted by the user given after the ''-u''.  +
  
 ===== Using jobinfo ===== ===== Using jobinfo =====
  
 From the moment that a job is submitted, you can request relevant information about this job using the jobinfo command. If you forgot the job ID that you want to have the information for, then you are able to request all jobs that you have submitted with ''squeue'' (see above), [[habrok:advanced_job_management:getting_information_about_jobs_nodes_partitions|sacct or sstat]]. The jobinfo command basically combines relevant output of the ''squeue'', ''sacct'' and ''sstat'' commands. It is also possible to use these commands themselves, especially if you want to have more detailed information about your jobs, such as info about available node partitions, lists of all your submitted jobs, a list of jobs that are in the queue or information about a node (that your job is running on). From the moment that a job is submitted, you can request relevant information about this job using the jobinfo command. If you forgot the job ID that you want to have the information for, then you are able to request all jobs that you have submitted with ''squeue'' (see above), [[habrok:advanced_job_management:getting_information_about_jobs_nodes_partitions|sacct or sstat]]. The jobinfo command basically combines relevant output of the ''squeue'', ''sacct'' and ''sstat'' commands. It is also possible to use these commands themselves, especially if you want to have more detailed information about your jobs, such as info about available node partitions, lists of all your submitted jobs, a list of jobs that are in the queue or information about a node (that your job is running on).
 +
 +The code for the jobinfo command is available at: https://github.com/rug-cit-hpc/hb-jobinfo
  
 After you submitted a job, you can request the information by using the command: After you submitted a job, you can request the information by using the command:
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 ===== jobinfo GPU example ===== ===== jobinfo GPU example =====
  
 +Here is the output of a job that was using a GPU:
 +<code>
 +Job ID                         : 833913
 +Name                           : gpu_job
 +User                           : s_number
 +Partition                      : gpumedium
 +Nodes                          : a100gpu5
 +Number of Nodes                : 1
 +Cores                          : 16
 +Number of Tasks                : 1
 +State                          : COMPLETED  
 +Submit                         : 2024-05-11T18:44:22
 +Start                          : 2024-05-11T18:46:03
 +End                            : 2024-05-11T21:14:37
 +Reserved walltime              : 06:00:00
 +Used walltime                  : 02:28:34
 +Used CPU time                  : 23:20:49 (Efficiency: 58.93%)
 +% User (Computation)           : 86.69%
 +% System (I/O)                 : 13.31%
 +Total memory reserved          : 16G
 +Maximum memory used            : 4.29G
 +Requested GPUs                 : a100=1
 +Allocated GPUs                 : a100=1
 +Max GPU utilization            : 35%
 +Max GPU memory used            : 3.76G
 +</code>
  
 +For a GPU job information about the GPU memory usage, GPU utilization and requested GPU resources is shown. The GPU utilization is the maximum utilization that was measured over the job's lifetime. Unfortunately this number may therefore not be very relevant as their may have been long periods of much lower GPU utilization. 
 +As you can see CPU memory and GPU memory are reported separately as they are different types of memory. CPU memory is connected to the CPU and GPU memory is separate memory on the GPU board.