Oscar
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  • Connecting to Oscar
    • SSH (Terminal)
      • SSH Key Login (Passwordless SSH)
        • Mac/Linux/Windows(PowerShell)
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        • Mac/Linux
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      • Arbiter2
    • Open OnDemand
      • Using File Explorer on OOD
      • Web-based Terminal App
      • Interactive Apps on OOD
      • Using Python or Conda environments in the Jupyter App
      • Using RStudio
      • Desktop App (VNC)
    • SMB (Local Mount)
    • Remote IDE (VS Code)
      • From Non-compliant Networks (2-FA)
      • Setup virtual environment and debugger
  • Managing files
    • Oscar's Filesystem
    • Transferring Files to and from Oscar
    • Transferring Files between Oscar and Campus File Storage (Replicated and Non-Replicated)
    • Resolving quota issues
      • Understanding Disk Quotas
    • Inspecting Disk Usage (Ncdu)
    • Restoring Deleted Files
    • Best Practices for I/O
    • Version Control
  • Submitting jobs
    • Running Jobs
    • Slurm Partitions
    • Interactive Jobs
    • Batch Jobs
    • Managing Jobs
    • Job Arrays
    • MPI Jobs
    • Condo/Priority Jobs
    • Dependent Jobs
    • Associations & Quality of Service (QOS)
  • GPU Computing
    • GPUs on Oscar
      • Grace Hopper GH200 GPUs
      • H100 NVL Tensor Core GPUs
      • Ampere Architecture GPUs
    • Submitting GPU Jobs
    • Intro to CUDA
    • Compiling CUDA
    • Installing Frameworks (PyTorch, TensorFlow, Jax)
      • Installing JAX
      • Installing TensorFlow
    • Mixing MPI and CUDA
  • Large Memory Computing
    • Large Memory Nodes on Oscar
  • Software
    • Software on Oscar
    • Using Modules
    • Migration of MPI Apps to Slurm 22.05.7
    • Python on Oscar
    • Python in batch jobs
    • Installing Python Packages
    • Installing R Packages
    • Using CCMake
    • Intro to Parallel Programming
    • Anaconda
    • Conda and Mamba
    • DMTCP
    • Screen
    • VASP
    • Gaussian
    • IDL
    • MPI4PY
  • Jupyter Notebooks/Labs
    • Jupyter Notebooks on Oscar
    • Jupyter Labs on Oscar
    • Tunneling into Jupyter with Windows
  • Debugging
    • Arm Forge
      • Configuring Remote Launch
      • Setting Job Submission Settings
  • MATLAB
    • Matlab GUI
    • Matlab Batch Jobs
    • Improving Performance and Memory Management
    • Parallel Matlab
  • Visualization 🕶
    • ParaView Remote Rendering
  • Singularity Containers
    • Intro to Apptainer
    • Building Images
    • Running Images
    • Accessing Oscar Filesystem
      • Example Container (TensorFlow)
    • Singularity Tips and Tricks
  • Installing Software Packages Locally
    • Installing your own version of Quantum Espresso
    • Installing your own version of Qmcpack
  • dbGaP
    • dbGaP Architecture
    • dbGaP Data Transfers
    • dbGaP Job Submission
  • RHEL9 Migration
    • RHEL-9 Migration
    • LMOD - New Module System
    • Module Changes
    • Testing Jupyter Notebooks on RHEL9 mini-cluster
  • Large Language Models
    • Ollama
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On this page
  • Listing running and queued jobs
  • Viewing estimated time until completion for pending jobs
  • Canceling jobs
  • View details about completed jobs
  • sacct
  • myjobinfo
  • jobstats

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  1. Submitting jobs

Managing Jobs

Listing running and queued jobs

The squeue command will list all jobs scheduled in the cluster. We have also written wrappers for squeue on Oscar that you may find more convenient:

myq                   List only your own jobs.
allq                  List all jobs, but organized by partition, and a summary of the nodes in use in the
                      partition.
allq <partition>      List all jobs in a single partition.
myjobinfo            Get the time and memory used for your jobs.

Viewing estimated time until completion for pending jobs

squeue -u <your-username> -t PENDING --start

This command will list all of your pending jobs and the estimated time until completion.

Canceling jobs

scancel <jobid>

View details about completed jobs

sacct

The sacct command will list all of your running, queued and completed jobs since midnight of the previous day. To pick an earlier start date, specify it with the -S option:

sacct -S 2012-01-01

To find out more information about a specific job, such as its exit status or the amount of runtime or memory it used, specify the -l ("long" format) and -j options with the job ID:

sacct -lj <jobid>

(example)

myjobinfo

The myjobinfo command uses the sacct command to display "Elapsed Time", "Requested Memory" and "Maximum Memory used on any one Node" for your jobs. This can be used to optimize the requested time and memory to have the job started as early as possible. Make sure you request a conservative amount based on how much was used.

myjobinfo

Info about jobs for user 'mdave' submitted since 2017-05-19T00:00:00
Use option '-S' for a different date or option '-j' for a specific Job ID.

JobID    JobName                  Submit      State        Elapsed     ReqMem     MaxRSS
1861     ior 2017-05-19T08:31:01  COMPLETED   00:00:09     2800Mc      1744K
1862     ior 2017-05-19T08:31:11  COMPLETED   00:00:54     2800Mc     22908K
1911     ior 2017-05-19T15:02:01  COMPLETED   00:00:06     2800Mc      1748K
1912     ior 2017-05-19T15:02:07  COMPLETED   00:00:21     2800Mc      1744K

ReqMem shows the requested memory: A c at the end of number represents Memory Per CPU, a n represents Memory Per Node. MaxRSS is the maximum memory used on any one node. Note that memory specified to sbatch using --mem is Per Node.

jobstats

The 'jobstats' utility is now available for analyzing recently completed jobs, comparing the resources used to those requested in the job script, including CPU, GPU, and memory. If email notifications are enabled, 'jobstats' sends an email with the results and includes a prompt to contact support for help with resource requests.

Run this command in a bash shell on Oscar. No additional module needs to be loaded.

jobstats <jobid>

To send this output to your email after the job is completed, make sure that these lines are in your job submit script

#SBATCH --mail-type=END
#SBATCH --mail-user=<email>
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Last updated 11 months ago

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