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SLURM

All jobs on the general purpose cluster request resources via SLURM. SLURM, is open source software that allocates resources to users for their computations, provides a framework for starting, executing and monitoring compute jobs, and arbitrates contention for resources by managing a queue of pending work. SLURM is widely used in the high performance computing (HPC) landscape and it is likely you will encounter it outside of our systems. For more information please see https://slurm.schedmd.com/ 

General Purpose Computing

All resources on the general purpose cluster are submitted using the SLURM scheduler. For more information, please read the Frequently asked Questions. Jobs can be submitted from the following headnodes:

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Or from the large memory machine:

Resource information

All users have access to the "batch" partition for general purpose computing.

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How can I request access to more nodes, or a longer time limit?

 On a case by case basis, ARCC will grant users temporary access to more than the default job limitations. Please contact rts@albany.edu if you would like to request access to more nodes, or a longer time limit.

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Can I restrict my job to a certain CPU architecture?

 Yes! Use the --constraint flag in #SBATCH. To few available architecture on individual nodes use scontrol show node

$ scontrol show node uagc19-06
NodeName=uagc19-06 Arch=x86_64 CoresPerSocket=10
   CPUAlloc=0 CPUErr=0 CPUTot=20 CPULoad=0.00
   AvailableFeatures=intel,skylake,sse4_2,avx,avx2,avx512
   ActiveFeatures=intel,skylake,sse4_2,avx,avx2,avx512
   Gres=(null)
   NodeAddr=uagc19-06.arcc.albany.edu NodeHostName=uagc19-06 Version=17.11
   OS=Linux 4.14.35-1844.0.7.el7uek.x86_64 #2 SMP Wed Dec 12 19:48:02 PST 2018
   RealMemory=94956 AllocMem=0 FreeMem=93582 Sockets=2 Boards=1
   State=IDLE ThreadsPerCore=1 TmpDisk=4086 Weight=256 Owner=N/A MCS_label=N/A
   Partitions=batch
   BootTime=2019-02-11T10:15:23 SlurmdStartTime=2019-02-11T10:15:48
   CfgTRES=cpu=20,mem=94956M,billing=20
   AllocTRES=
   CapWatts=n/a
   CurrentWatts=0 LowestJoules=0 ConsumedJoules=0
   ExtSensorsJoules=n/s ExtSensorsWatts=0 ExtSensorsTemp=n/s

How do I spawn on the infiniband nodes?

You need to add the directive --constraint=mpi_ib

srun --partition=batch --nodes=1 --constraint=mpi_ib --time=01:00:00 --cpus-per-task=4 --mem=400 --x11 --pty $SHELL -i 

OR

#SBATCH --constraint=mpi_ib

How can I allocate GPU resources?

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1. https://jupyterlab.arcc.albany.edu ; please see How-to: Using Jupyterhub for more information

2. If you need more resources, or longer than an eight hour time limit, you can run jupyter notebook interactively

   1. First, ssh into head.arcc.albany.edu and run; then enter a password at the prompt (note that you will not see your password, but it is being registered)

      Code Block
      language bash
      /network/rit/misc/software/jupyterhub/miniconda3/bin/jupyter notebook password

   2. Next, you can either run jupyter notebook interactively with srun, or you can submit the process via sbatch script located at /network/rit/misc/software/examples/slurm/spawn_jhub.sh (see below)

      1. Spawning jupyter notebook interactively using ARCC's anaconda (you may change the path to your own conda distribution) 

         
         

         1. Code Block
            language bash
            srun --partition=batch --nodes=1 --time=01:00:00 --cpus-per-task=4 --mem=400 --pty $SHELL -i unset XDG_RUNTIME_DIR /network/rit/misc/software/jupyterhub/miniconda3/bin/jupyter notebook --no-browser --ip=0.0.0.0

         2. You should see a jupyter output related to launching the server. Once it is complete, you should see output that looks like:

            Code Block
            language bash
            [I 08:31:49.694 NotebookApp] http://(uagc19-02.rit.albany.edu or 127.0.0.1):8889/ [I 08:31:49.694 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).

            Open up a web browser and navigate to the suggested location, in the example we would navigate to uagc19-02.rit.albany.edu:8889 , enter the configured password at the prompt, and that you are all set! 

            
      2. Spawning jupyter notebook via sbatch using ARCCs anaconda (you may change the path to your own conda distribution):

         1. ssh into head.arcc.albany.edu and copy the file below to your home directory and submit the script with sbatch.

            Code Block
            language bash
            # Copy the file cp /network/rit/misc/software/examples/slurm/spawn_jupyter.sh ~/spawn_jupyter.sh   # change the directory to the home directory cd ~/   # submit the script sbatch spawn_jupyter.sh

            Info
            Note that you will want to edit the script to request the amount of resources that you need

         2. This script will create an output file called juptyer.[jobid].log. Open up this file, replacing [jobid] with the allocation number you were given (you can get this by looking at squeue) and you will see output that looks like: 

            Code Block
            language bash firstline 1 linenumbers true
            USER [netid] was granted 1 cores and MB per node on uagc12-02. The job is current running with job #144168.\n [I 10:06:31.758 NotebookApp] JupyterLab extension loaded from /network/rit/misc/software/jupyterhub/miniconda3/lib/python3.6/site-packages/jupyterlab [I 10:06:31.758 NotebookApp] JupyterLab application directory is /network/rit/misc/software/jupyterhub/miniconda3/share/jupyter/lab [I 10:06:31.779 NotebookApp] Serving notebooks from local directory: /network/rit/home/[netid] [I 10:06:31.779 NotebookApp] The Jupyter Notebook is running at: [I 10:06:31.780 NotebookApp] http://(uagc12-02.arcc.albany.edu or 127.0.0.1):8888/ [I 10:06:31.780 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).

            
            
            

         3. Open up a web browser, and point to the location noted in the second to last line, in the above example, http://uagc12-02.arcc.albany.edu:8888, enter your password, and you are all set!