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Table of Contents

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Action

To schedule research computing work using SLURM, follow the instructions below.

Instructions

Table of Contents

minLevel	2

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:

head.arcc.albany.edu
headnode7.rit.albany.edu

Or from the large memory machine:

lmm.

...

its.albany.edu

Resource information

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

Info
The batch partition is comprised of 544 CPUs and 21 1040 CPU cores (2080 threads) and 31 compute nodes. Note that a job can only request 3 nodes and may only be active for 14 days. If you need an exception to this, please contact rts@albanyaskIT@albany.edu

Code Block

language	bash

$ sinfo -p batch -o "%n, %c, %m" | sort

PARTITION, HOSTNAMES, CPUS, MEMORY
batch*, rheauagc19-01, 2440, 64133
batch*, rhea95902
uagc19-02, 2440, 64133
batch*, rhea95902
uagc19-03, 2440, 64133
batch*, rhea95902
uagc19-04, 3240, 96411
batch*, rhea-0595902
uagc20-01, 3264, 96411
batch*, rhea-06, 32, 96411
batch*, rhea-07, 40, 128619
batch*, rhea-08, 40, 128619
batch*, rhea-09, 48, 257627
batch*, rhea-10, 48, 257566
batch*, uagc12-01, 12, 64166
batch*, uagc12-02, 12, 64166
batch*, uagc12-03, 12, 64166
batch*, uagc12-04, 12, 64166
batch*, uagc12-05, 32, 128703
batch*, uagc19-01, 20, 94956
batch*, uagc19-02, 20, 94956
batch*, uagc19-03, 20, 94956
batch*, uagc19-04, 20, 94956
batch*, uagc19-05, 20, 94956
batch*, uagc19-06, 20, 94956

Frequently asked questions

...

191716
uagc20-02, 64, 191716
uagc20-03, 64, 191716
uagc20-04, 64, 191716
uagc20-05, 64, 191716
uagc20-06, 64, 191716
uagc20-07, 64, 191716
uagc20-08, 64, 191716
uagc20-09, 64, 191716
uagc20-10, 64, 191716
uagc20-11, 64, 191716
uagc20-12, 64, 191716
uagc20-13, 64, 191716
uagc20-14, 64, 191716
uagc20-15, 64, 191716
uagc21-01, 80, 385236
uagc21-02, 80, 385236
uagc21-03, 80, 385236
uagc21-04, 80, 385236
uagc21-05, 80, 385236
uagc21-06, 80, 385236
uagc21-07, 80, 385236
uagc21-08, 80, 385236
uagc21-09, 80, 385234
uagc21-10, 80, 385234
uagc21-11, 80, 385234
uagc21-12, 80, 385234

Frequently asked questions

SLURM documentation can be found at the SLURM website (https://slurm.schedmd.com); but below are answers to frequently asked questions which demonstrate several useful SLURM commands.

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View the current status, or resources available, of batch nodes

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sinfo is commonly used to few the status of a give given cluster or node, or how many resources are available to schedule.

Code Block

language	bash
title	Viewing available resources

$-bash-4.2$  sinfo -p batch -o "%n, %a, %C, %e, %O" | sort
HOSTNAMES, AVAIL, CPUS(A/I/O/T), FREE_MEM, CPU_LOAD
rhea-0109, up, 10/230/096/2496, 47457N/A, 1.02N/A
rhea-0710, up, 80/320/096/4096, 106761N/A, 8.03
rhea-08N/A
uagc19-01, up, 82/3238/0/40, 11183393621, 80.0700
rheauagc19-1002, up, 812/4028/0/4840, 23847154240, 815.0190
rheauagc19-0903, up, 4814/026/0/4840, 24303367920, 4517.6912
rheauagc19-04, up, 3236/04/0/3240, 5084375889, 2016.2560
rheauagc20-0201, up, 0/2464/0/2464, 61907189368, 0.00
rheauagc20-0302, up, 0/2464/0/2464, 61530189359, 0.00
rheauagc20-0503, up, 0/3264/0/3264, 94105189367, 0.0200
rheauagc20-0604, up, 0/3264/0/3264, 93951189461, 0.00
uagc12uagc20-0105, up, 032/1232/0/1264, 6269198151, 032.0009
uagc12uagc20-0206, up, 032/1232/0/1264, 6267297446, 032.0010
uagc12uagc20-0307, up, 02/1262/0/1264, 62867188191, 0.0500
uagc12uagc20-0408, up, 032/1232/0/1264, 6286294065, 032.0011
uagc12uagc20-0509, up, 040/3224/0/3264, 127211180208, 048.0021
uagc19uagc20-0110, up, 64/0/20/0/2064, 934968985, 064.0335
uagc19uagc20-0211, up, 0/2064/0/2064, 93489189303, 0.00
uagc19uagc20-0312, up, 64/0/20/0/2064, 934829337, 064.0024
uagc19uagc20-0413, up, 024/2040/0/2064, 93570176151, 0.00
uagc19uagc20-0514, up, 0/2064/0/2064, 93579189364, 0.00
uagc19uagc20-0615, up, 0/2064/0/2064, 93583189343, 0.00

Info

Note that %a reports CPUS as allocated/idle/other/available. In this example, rhea-09 has all of it's cores allocated (48 out of 48), and is showing a CPU load of 45.68 (or that 45.68 cores

02
uagc21-01, up, 80/0/0/80, 278987, 1.47
uagc21-02, up, 20/60/0/80, 371334, 0.50
uagc21-03, up, 0/80/0/80, 381238, 0.00
uagc21-04, up, 0/80/0/80, 381046, 0.00
uagc21-05, up, 0/80/0/80, 290550, 0.00
uagc21-06, up, 80/0/0/80, 339206, 25.01
uagc21-07, up, 80/0/0/80, 247070, 4.17
uagc21-08, up, 80/0/0/80, 338115, 25.03
uagc21-09, up, 0/80/0/80, 380172, 0.75
uagc21-10, up, 0/80/0/80, 380682, 0.20
uagc21-11, up, 0/80/0/80, 381265, 0.00
uagc21-12, up, 0/80/0/80, 260703, 0.00

Info
Note that %a reports CPUS as allocated/idle/other/available. In this example, uagc20-10 has all of it's threads allocated (64 out of 64), and is showing a CPU load of 64.30 (or that 64.30 threads are active). Whereas, many of the other nodes have lower utilization. We can use this information to make smart decisions about how many resources we request.

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View jobs currently running, and waiting in queue

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squeue will show jobs currently waiting in the queue or running, for all partitions that you have access to.
...
Info
At the time this command was run, there were 7 jobs running or waiting in queue. JOBID 140574 is waiting in the queue due to inadequate available resources, while the other jobs have been running for a few days.
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View the resources requested for an active job

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scontrol show job [jobid] will generate a report with information about how a job was scheduled.

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Info

Here, the job requested 32 CPUs on one node, with 87.5GB of memory, at 2019-02-13T07:48:25, with a constraint of Features=avx2.

 NumNodes=1 NumCPUs=32 NumTasks=1 CPUs/Task=32 ReqB:S:C:T=0:0:*:*
   TRES=cpu=32,mem=87.50G,node=1

 Features=avx2

...

Maximum resources allowed

Code Block

language	bash

$ scontrol show partition batch
 
PartitionName=batch
   AllowGroups=ALL AllowAccounts=ALL AllowQos=ALL
   AllocNodes=ALL Default=YES QoS=N/A
   DefaultTime=NONE DisableRootJobs=NO ExclusiveUser=NO GraceTime=0 Hidden=NO
   MaxNodes=3 MaxTime=14-00:00:00 MinNodes=1 LLN=NO MaxCPUsPerNode=UNLIMITED
   Nodes=rhea-[01-10],uagc19-[01-06],uagc12-[01-05]
   PriorityJobFactor=1 PriorityTier=10 RootOnly=NO ReqResv=NO OverSubscribe=FORCE:1
   OverTimeLimit=NONE PreemptMode=OFF
   State=UP TotalCPUs=544 TotalNodes=21 SelectTypeParameters=NONE
   DefMemPerNode=UNLIMITED MaxMemPerNode=UNLIMITED

Info
batch has some important restrictions. A job can only request 3 nodes and will run for 14 days before being automatically terminated. If you need an exception to this rule, please contact rts@albany askIT@albany.edu

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Request access to more nodes, or a longer time limit

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

Schedule a non-interactive job

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There are many ways to schedule jobs via slurm. For non-interactive jobs, we recommend using sbatch with a shell script that runs your script. We will use #SBATCH commands to allocate the appropriate resources required for our script. Below is an example workflow of how to submit a python script via sbatch to batch.

First ssh into head.arcc.albany.edu. On windows, you can use an ssh client such as PuTTY, on mac, simply use the terminal. Replace [netid] below with your username and type in your password at the prompt. You will not see your password, but it is being typed.

Code Block

language	bash

$ ssh [netid]@head.arcc.albany.edu

Warning: Permanently added the ECDSA host key for IP address '169.226.65.82' to the list of known hosts.
[netid]@head.arcc.albany.edu's password:
 
Warning: No xauth data; using fake authentication data for X11 forwarding.
Last login: Wed Jan 30 13:49:20 2019 from lmm.ritits.albany.edu
================================================================================
 This University at Albany computer system is reserved for authorized use only.
              http://www.albany.edu/its/authorizeduse.htm
Headnodes:
 head.arcc.albany.edu
 headnode7.rit.albany.edu
 headnode.rit.albany.edu - LEGACY SUPPORT
General Purpose Computing:
 lmm.ritits.albany.edu - Large memory
x2go headnode:
 eagle.arcc.albany.edu
   Questions / Assistance - arcc@albanyaskIT@albany.edu
================================================================================

Next, change directories to /network/rit/misc/software/examples/slurm/
Code Block
language bash
$ cd /network/rit/misc/software/examples/slurm/

/network/rit/misc/software/examples/slurm/run.sh contains #SBATCH commands that will request the appropriate amount of resources for our python code, then execute the code.

Code Block

language	bash

$ more run.sh

#!/bin/bash
#SBATCH -p batch
#SBATCH --cpus-per-task=4
#SBATCH --mem-per-cpu=100
#SBATCH --mail-type=ALL
#SBATCH -o /network/rit/home/%u/example-slurm-%j.out

# Now, run the python script
/network/rit/misc/software/examples/slurm/simple_multiprocessing.py

Info

--cpus-per-task=4 tells SLURM how many cores we want to allocate on one node

--mem-per-cpu=100 tells SLURM how much memory to allocate per core (see also --mem)

In total, we are requesting 4 cores and 400MB of memory for this simple python code

To submit the job, we simply run sbatch run.sh. Keep note of the Job ID that is output to the terminal, it will be different that what is shown below.
Code Block
language bash
$ sbatch run.sh Submitted batch job 140584
Info
Note that you can use squeue to view the job status

The job will output a file to your home directory called ~/example-slurm-[jobid].out. We will view it using the "more" command. You should see output similar to below.

Code Block

language	bash

$ more ~/example-slurm-140584.out
USER [netid] was granted 4 cores and 100 MB per node on [hostname].
The job is current running with job # [jobid]
 Process D waiting 3 seconds
 Process D Finished.
 Process C waiting 1 seconds
 Process C Finished.
 Process E waiting 4 seconds
 Process E Finished.
 Process A waiting 5 seconds
 Process A Finished.
 Process B waiting 2 seconds
 Process B Finished.
 Process F waiting 5 seconds
 Process F Finished.

Congratulations, you just ran your first job on the cluster!

How do I schedule an interactive job?

To spawn a terminal session on a cluster node, with X11 forwarding, run:

Code Block

language	bash

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

...

waiting 5 seconds Process F Finished.
Congratulations, you just ran your first job on the cluster!

Schedule an interactive job

To spawn a terminal session on a cluster node run:

Code Block

language	bash

srun --partition=batch --nodes=1 --time=01:00:00 --cpus-per-task=42 --mem=400 --pty $SHELL -i

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View the resources used by a completed job

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sacct is useful to view accounting information on completed jobs. Read the documentation for all output fields.
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Info
This job ran on rhea-09, and it's max memory size was ~52 GB. That that I requested 60000MB, so I could refine this job to request slightly less memory. It ran for 14:50:14 and used about 350 CPU hours.
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Restrict a job to a certain CPU architecture

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

Code Block

language	bash

$ 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

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Spawn on the infiniband nodes

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You need to add the directive --constraint=mpi_ib

Code Block

language	bash

srun --partition=batch --nodes=12 --constraint=mpi_ib --time=01:00:00 --cpus-per-task=4 --mem=400 --x11 --pty $SHELL -i

OR

Code Block

language	bash

#SBATCH --constraint=mpi_ib

...

_ib

Allocate GPU resources

You can request access to the GPUs on --partition=ceashpc by adding the following flag:

--gres=gpu:1 # For half of the K80

--gres=gpu:2 # For the full K80

To request access to the A40s on the batch cluster for your research lab, please email askIT@albany.edu.

Once your group is added you can request access to the GPUs on --partition=batch or --partition=ceashpc gpu by adding the following flag:

--gres=gpu:1 # 1 # For half one of the K80A40s

--gres=gpu:2 # For the full K80

...

two of the A40s

etc.

Run jupyter notebook on the cluster

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There are two ways to spawn jupyter notebooks on the server:

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

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

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

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)

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

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

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!

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

ssh into head.arccits.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

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).

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!

Include Page

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Versions Compared

Old Version 41

New Version Current

Key

Action

Instructions

SLURM

General Purpose Computing

Resource information

Frequently asked questions

Frequently asked questions

View the current status, or resources available, of batch nodes

View jobs currently running, and waiting in queue

View the resources requested for an active job

Maximum resources allowed

Request access to more nodes, or a longer time limit

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

Schedule a non-interactive job

How do I schedule an interactive job?

Schedule an interactive job

View the resources used by a completed job

Restrict a job to a certain CPU architecture

Spawn on the infiniband nodes

You need to add the directive --constraint=mpi_ib
Code Block
language bash
srun --partition=batch --nodes=12 --constraint=mpi_ib --time=01:00:00 --cpus-per-task=4 --mem=400 --x11 --pty $SHELL -i
OR
Code Block
language bash
#SBATCH --constraint=mpi_ib
...
_ib

Allocate GPU resources

Run jupyter notebook on the cluster

Page Comparison

Versions Compared

Old Version 41

New Version Current

Key

<span class="diff-html-changed" data-a11y-before="Start of changed content" data-a11y-after="End of changed content" id="changed-diff-0">[data-colorid=</span>

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<span class="diff-html-added" data-a11y-before="Start of added content" data-a11y-after="End of added content" id="added-diff-13">#a3b1b9}</span>Action

Instructions

SLURM

General Purpose Computing

Resource information

Frequently asked questions

Frequently asked questions

View the current status, or resources available, of batch nodes

View jobs currently running, and waiting in queue

View the resources requested for an active job

Maximum resources allowed

Request access to more nodes, or a longer time limit

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

Schedule a non-interactive job

How do I schedule an interactive job?

Schedule an interactive job

View the resources used by a completed job

Restrict a job to a certain CPU architecture

Spawn on the infiniband nodes

You need to add the directive --constraint=mpi_ib Code Blocklanguagebashsrun --partition=batch --nodes=12 --constraint=mpi_ib --time=01:00:00 --cpus-per-task=4 --mem=400 --x11 --pty $SHELL -i OR Code Blocklanguagebash#SBATCH --constraint=mpi_ib..._ib

Allocate GPU resources

Run jupyter notebook on the cluster

Action

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

You need to add the directive --constraint=mpi_ib
Code Block
language bash
srun --partition=batch --nodes=12 --constraint=mpi_ib --time=01:00:00 --cpus-per-task=4 --mem=400 --x11 --pty $SHELL -i
OR
Code Block
language bash
#SBATCH --constraint=mpi_ib
...
_ib