https://wiki.umiacs.umd.edu/umiacs/api.php?action=feedcontributions&feedformat=atom&user=DyarnellUMIACS - User contributions [en]2026-06-01T16:29:44ZUser contributionsMediaWiki 1.43.7https://wiki.umiacs.umd.edu/umiacs/index.php?title=DataCenter&diff=13204DataCenter2026-04-08T18:41:32Z<p>Dyarnell: </p>
<hr />
<div>UMIACS maintains a set of Data Centers that hold computing infrastructures. All equipment within our Data Centers is managed by the UMIACS Technical Staff who will provision and provide a managed set of services or operating systems on all equipment.<br />
<br />
[[Media:UMIACS_Data_Center_Node_and_Infrastructure_Lifecycle_Support_Policy.pdf|UMIACS Data Center Node and<br />
Infrastructure Lifecycle Support Policy]]</div>Dyarnellhttps://wiki.umiacs.umd.edu/umiacs/index.php?title=DataCenter&diff=13203DataCenter2026-04-08T18:37:36Z<p>Dyarnell: </p>
<hr />
<div>UMIACS maintains a set of Data Centers that hold computing infrastructures.<br />
<br />
[[Media:UMIACS_Data_Center_Node_and_Infrastructure_Lifecycle_Support_Policy.pdf|UMIACS Data Center Node and<br />
Infrastructure Lifecycle Support Policy]]</div>Dyarnellhttps://wiki.umiacs.umd.edu/umiacs/index.php?title=DataCenter&diff=13202DataCenter2026-04-08T18:37:18Z<p>Dyarnell: </p>
<hr />
<div>UMIACS maintains a set of Data Centers that hold computing infrastructures.<br />
<br />
* [[Media:UMIACS_Data_Center_Node_and_Infrastructure_Lifecycle_Support_Policy.pdf|UMIACS Data Center Node and<br />
Infrastructure Lifecycle Support Policy]]</div>Dyarnellhttps://wiki.umiacs.umd.edu/umiacs/index.php?title=DataCenter&diff=13201DataCenter2026-04-08T18:37:10Z<p>Dyarnell: </p>
<hr />
<div>UMIACS maintains a set of Data Centers that hold computing infrastructures.<br />
<br />
[[Media:UMIACS_Data_Center_Node_and_Infrastructure_Lifecycle_Support_Policy.pdf|UMIACS Data Center Node and<br />
Infrastructure Lifecycle Support Policy]]</div>Dyarnellhttps://wiki.umiacs.umd.edu/umiacs/index.php?title=DataCenter&diff=13200DataCenter2026-04-08T18:36:46Z<p>Dyarnell: </p>
<hr />
<div>UMIACS maintains a set of Data Centers that hold computing infrastructures.<br />
<br />
[[Media:UMIACS_Data_Center_Node_and_Infrastructure_Lifecycle_Support_Policy.pdf]]</div>Dyarnellhttps://wiki.umiacs.umd.edu/umiacs/index.php?title=DataCenter&diff=13199DataCenter2026-04-08T18:36:17Z<p>Dyarnell: </p>
<hr />
<div>UMIACS maintains a set of Data Centers that hold computing infrastructures.<br />
<br />
[Uploads: UMIACS_Data_Center_Node_and_Infrastructure_Lifecycle_Support_Policy.pdf]</div>Dyarnellhttps://wiki.umiacs.umd.edu/umiacs/index.php?title=File:UMIACS_Data_Center_Node_and_Infrastructure_Lifecycle_Support_Policy.pdf&diff=13198File:UMIACS Data Center Node and Infrastructure Lifecycle Support Policy.pdf2026-04-08T18:35:45Z<p>Dyarnell: </p>
<hr />
<div></div>Dyarnellhttps://wiki.umiacs.umd.edu/umiacs/index.php?title=DataCenter&diff=13197DataCenter2026-04-08T18:35:34Z<p>Dyarnell: Created page with "UMIACS maintains a set of Data Centers that hold computing infrastructures."</p>
<hr />
<div>UMIACS maintains a set of Data Centers that hold computing infrastructures.</div>Dyarnellhttps://wiki.umiacs.umd.edu/umiacs/index.php?title=ClassAccounts&diff=12891ClassAccounts2025-10-28T15:19:16Z<p>Dyarnell: /* Overview */</p>
<hr />
<div>==Overview==<br />
UMIACS supports classes for all of UMIACS/CSD via class accounts that can access the [[Nexus]] cluster. Faculty may request that a class be supported by following the instructions [[ClassAccounts/Manage | here]].<br />
<br />
==Getting an account==<br />
Your TA or instructor will request an account for you. Once this is done, you will be notified by email that you have an account is ready to use.<br />
<br />
'''Any questions or issues with your account, storage, or cluster use must first be made through your TA or instructor.'''<br />
<br />
==Using your account==<br />
To access Nexus class resources in UMIACS you will need to be on the [https://itsupport.umd.edu/itsupport?id=kb_article_view&sysparm_article=KB0016076 '''UMD Global Protect VPN''']<br />
<br />
Once notified that your account has been installed, you can [[SSH]] to <code>nexusclass.umiacs.umd.edu</code> with your UMD directory ID and passphrase to log in to a submission node.<br />
<br />
If you store something in a local filesystem directory (/tmp, /scratch0) on one of the two submission nodes, you will need to connect to that same submission node to access it later. The actual submission nodes are:<br />
* <code>nexusclass00.umiacs.umd.edu</code><br />
* <code>nexusclass01.umiacs.umd.edu</code><br />
<br />
==Cleaning up your account before the end of the semester==<br />
Class accounts for a given semester are liable to be archived and deleted after that semester's completion as early as the following:<br />
* Winter semesters: February 1st of same year<br />
* Spring semesters: June 1st of same year<br />
* Summer semesters: September 1st of same year<br />
* Fall semesters: January 1st of next year<br />
<br />
It is your responsibility to ensure you have backed up anything you want to keep from your class account's personal or group storage (below sections) prior to the relevant date.<br />
<br />
==Personal Storage==<br />
Your home directory has a quota of 30GB and is located at:<br />
<pre><br />
/fs/classhomes/<username><br />
</pre><br />
<br />
You can request up to another 100GB of personal storage if you would like by '''having your TA or instructor [[HelpDesk | contact staff]]'''. This storage will be located at<br />
<pre><br />
/fs/class-projects/<semester><year>/<coursecode>/<username><br />
</pre><br />
<br />
where <code><semester></code> is either "spring", "summer", "fall", or "winter", <code><year></code> is the current year e.g., "2025", <coursecode> is the class' course code as listed in UMD's [https://app.testudo.umd.edu/soc/ Schedule of Classes] in all lowercase e.g., "cmsc999z", and <code><username></code> is the username.<br />
<br />
==Group Storage==<br />
You can also request group storage by '''having your TA or instructor [[HelpDesk | contact staff]]''' to specify the usernames of the accounts that should be in the group. Only other class accounts in the same class can be added to the group. The quota will be 100GB multiplied by the number of accounts in the group and will be located at<br />
<pre><br />
/fs/class-projects/<semester><year>/<coursecode>/<groupname><br />
</pre><br />
<br />
where <code><groupname></code> is composed of:<br />
* the abbreviated course code as used in the username e.g., "c999z"<br />
* the character "g"<br />
* the number of the group (starting at 0 for the first group for the class requested to us) prepended with 0s to make the total group name 8 characters long<br />
<br />
e.g., "c999zg00".<br />
<br />
==Cluster Usage==<br />
'''You may not run computational jobs on any submission node.''' You must [[SLURM/JobSubmission | schedule your jobs with the SLURM workload manager]]. You can also find out more with the public documentation for the [https://slurm.schedmd.com/quickstart.html SLURM Workload Manager].<br />
<br />
Class accounts only have access to the following submission parameters in SLURM:<br />
* <code>--partition</code> - <code>class</code><br />
* <code>--account</code> - <code>class</code><br />
* <code>--qos</code> - <code>default</code>, <code>medium</code>, and <code>high</code><br />
<br />
You must specify at least the partition parameter manually in any submission command you run. If you do not specify any QoS parameter, you will receive the QoS <code>default</code>.<br />
<br />
You can view the resource limits for each QoS by running the command <code>show_qos</code>. The value in the MaxWall column is the maximum runtime you can run a single job for each QoS, and the values in the MaxTRES column are the maximum amount of CPU cores/GPUs/memory you can request for a single job using each QoS.<br />
<br />
Please note that you will be restricted to 32 total CPU cores, 4 total GPUs, and 256GB total RAM across all jobs you have running at once. This can be viewed with the command <code>show_partition_qos</code>.<br />
<br />
===Example===<br />
Here is a basic example to schedule a interactive job running bash with a single GPU in the partition <code>class</code>, with the account <code>class</code>, running with the QoS of <code>default</code> and the default CPU/memory allocation/time limit for the partition.<br />
<br />
<pre><br />
$ hostname<br />
nexusclass00.umiacs.umd.edu<br />
<br />
$ srun --partition=class --account=class --qos=default --gres=gpu:1 --pty bash<br />
srun: Job time limit was unset; set to partition default of 60 minutes<br />
srun: job 1333337 queued and waiting for resources<br />
srun: job 1333337 has been allocated resources<br />
<br />
$ hostname<br />
tron14.umiacs.umd.edu<br />
<br />
$ nvidia-smi -L<br />
GPU 0: NVIDIA RTX A4000 (UUID: GPU-55f2d3b7-9162-8b02-50de-476a012c626c)<br />
</pre><br />
<br />
===Available Nodes===<br />
You can list the available nodes and their current state with the <code>show_nodes -p class</code> command. This list of nodes is not completely static as nodes may be pulled out of service to troubleshoot GPUs or other components.<br />
<br />
<pre><br />
$ show_nodes -p class<br />
NODELIST CPUS MEMORY AVAIL_FEATURES GRES STATE<br />
tron06 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron07 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron08 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron09 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron10 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron11 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron12 16 126218 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron13 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron14 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron15 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron16 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron17 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron18 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron19 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron20 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron21 16 126218 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron22 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron23 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron24 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron25 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron26 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron27 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron28 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron29 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron30 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron31 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron32 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron33 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron34 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron35 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron36 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron37 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron38 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron39 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron40 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron41 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron42 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron43 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron44 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron46 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron47 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron48 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron49 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron50 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron51 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron52 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron53 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron54 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron55 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron56 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron57 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron58 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron59 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron60 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron61 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
</pre><br />
<br />
You can also find more granular information about an individual node with the <code>scontrol show node</code> command.<br />
<br />
<pre><br />
$ scontrol show node tron06<br />
NodeName=tron06 Arch=x86_64 CoresPerSocket=16<br />
CPUAlloc=0 CPUEfctv=16 CPUTot=16 CPULoad=0.08<br />
AvailableFeatures=rhel8,x86_64,Zen,EPYC-7302P,Ampere<br />
ActiveFeatures=rhel8,x86_64,Zen,EPYC-7302P,Ampere<br />
Gres=gpu:rtxa4000:4<br />
NodeAddr=tron06 NodeHostName=tron06 Version=23.02.6<br />
OS=Linux 4.18.0-513.11.1.el8_9.x86_64 #1 SMP Thu Dec 7 03:06:13 EST 2023<br />
RealMemory=126214 AllocMem=0 FreeMem=107174 Sockets=1 Boards=1<br />
State=IDLE ThreadsPerCore=1 TmpDisk=0 Weight=340 Owner=N/A MCS_label=N/A<br />
Partitions=class,scavenger,tron<br />
BootTime=2024-01-29T09:35:12 SlurmdStartTime=2024-02-05T15:14:20<br />
LastBusyTime=2024-02-16T15:59:38 ResumeAfterTime=None<br />
CfgTRES=cpu=16,mem=126214M,billing=638,gres/gpu=4,gres/gpu:rtxa4000=4<br />
AllocTRES=<br />
CapWatts=n/a<br />
CurrentWatts=0 AveWatts=0<br />
ExtSensorsJoules=n/s ExtSensorsWatts=0 ExtSensorsTemp=n/s<br />
</pre></div>Dyarnellhttps://wiki.umiacs.umd.edu/umiacs/index.php?title=ClassAccounts&diff=12890ClassAccounts2025-10-28T15:06:09Z<p>Dyarnell: /* Getting an account */</p>
<hr />
<div>==Overview==<br />
UMIACS supports classes for all of UMIACS/CSD via special class accounts that can access the [[Nexus]] cluster. Faculty may request that a class be supported by following the instructions [[ClassAccounts/Manage | here]].<br />
<br />
==Getting an account==<br />
Your TA or instructor will request an account for you. Once this is done, you will be notified by email that you have an account is ready to use.<br />
<br />
'''Any questions or issues with your account, storage, or cluster use must first be made through your TA or instructor.'''<br />
<br />
==Using your account==<br />
To access Nexus class resources in UMIACS you will need to be on the [https://itsupport.umd.edu/itsupport?id=kb_article_view&sysparm_article=KB0016076 '''UMD Global Protect VPN''']<br />
<br />
Once notified that your account has been installed, you can [[SSH]] to <code>nexusclass.umiacs.umd.edu</code> with your UMD directory ID and passphrase to log in to a submission node.<br />
<br />
If you store something in a local filesystem directory (/tmp, /scratch0) on one of the two submission nodes, you will need to connect to that same submission node to access it later. The actual submission nodes are:<br />
* <code>nexusclass00.umiacs.umd.edu</code><br />
* <code>nexusclass01.umiacs.umd.edu</code><br />
<br />
==Cleaning up your account before the end of the semester==<br />
Class accounts for a given semester are liable to be archived and deleted after that semester's completion as early as the following:<br />
* Winter semesters: February 1st of same year<br />
* Spring semesters: June 1st of same year<br />
* Summer semesters: September 1st of same year<br />
* Fall semesters: January 1st of next year<br />
<br />
It is your responsibility to ensure you have backed up anything you want to keep from your class account's personal or group storage (below sections) prior to the relevant date.<br />
<br />
==Personal Storage==<br />
Your home directory has a quota of 30GB and is located at:<br />
<pre><br />
/fs/classhomes/<username><br />
</pre><br />
<br />
You can request up to another 100GB of personal storage if you would like by '''having your TA or instructor [[HelpDesk | contact staff]]'''. This storage will be located at<br />
<pre><br />
/fs/class-projects/<semester><year>/<coursecode>/<username><br />
</pre><br />
<br />
where <code><semester></code> is either "spring", "summer", "fall", or "winter", <code><year></code> is the current year e.g., "2025", <coursecode> is the class' course code as listed in UMD's [https://app.testudo.umd.edu/soc/ Schedule of Classes] in all lowercase e.g., "cmsc999z", and <code><username></code> is the username.<br />
<br />
==Group Storage==<br />
You can also request group storage by '''having your TA or instructor [[HelpDesk | contact staff]]''' to specify the usernames of the accounts that should be in the group. Only other class accounts in the same class can be added to the group. The quota will be 100GB multiplied by the number of accounts in the group and will be located at<br />
<pre><br />
/fs/class-projects/<semester><year>/<coursecode>/<groupname><br />
</pre><br />
<br />
where <code><groupname></code> is composed of:<br />
* the abbreviated course code as used in the username e.g., "c999z"<br />
* the character "g"<br />
* the number of the group (starting at 0 for the first group for the class requested to us) prepended with 0s to make the total group name 8 characters long<br />
<br />
e.g., "c999zg00".<br />
<br />
==Cluster Usage==<br />
'''You may not run computational jobs on any submission node.''' You must [[SLURM/JobSubmission | schedule your jobs with the SLURM workload manager]]. You can also find out more with the public documentation for the [https://slurm.schedmd.com/quickstart.html SLURM Workload Manager].<br />
<br />
Class accounts only have access to the following submission parameters in SLURM:<br />
* <code>--partition</code> - <code>class</code><br />
* <code>--account</code> - <code>class</code><br />
* <code>--qos</code> - <code>default</code>, <code>medium</code>, and <code>high</code><br />
<br />
You must specify at least the partition parameter manually in any submission command you run. If you do not specify any QoS parameter, you will receive the QoS <code>default</code>.<br />
<br />
You can view the resource limits for each QoS by running the command <code>show_qos</code>. The value in the MaxWall column is the maximum runtime you can run a single job for each QoS, and the values in the MaxTRES column are the maximum amount of CPU cores/GPUs/memory you can request for a single job using each QoS.<br />
<br />
Please note that you will be restricted to 32 total CPU cores, 4 total GPUs, and 256GB total RAM across all jobs you have running at once. This can be viewed with the command <code>show_partition_qos</code>.<br />
<br />
===Example===<br />
Here is a basic example to schedule a interactive job running bash with a single GPU in the partition <code>class</code>, with the account <code>class</code>, running with the QoS of <code>default</code> and the default CPU/memory allocation/time limit for the partition.<br />
<br />
<pre><br />
$ hostname<br />
nexusclass00.umiacs.umd.edu<br />
<br />
$ srun --partition=class --account=class --qos=default --gres=gpu:1 --pty bash<br />
srun: Job time limit was unset; set to partition default of 60 minutes<br />
srun: job 1333337 queued and waiting for resources<br />
srun: job 1333337 has been allocated resources<br />
<br />
$ hostname<br />
tron14.umiacs.umd.edu<br />
<br />
$ nvidia-smi -L<br />
GPU 0: NVIDIA RTX A4000 (UUID: GPU-55f2d3b7-9162-8b02-50de-476a012c626c)<br />
</pre><br />
<br />
===Available Nodes===<br />
You can list the available nodes and their current state with the <code>show_nodes -p class</code> command. This list of nodes is not completely static as nodes may be pulled out of service to troubleshoot GPUs or other components.<br />
<br />
<pre><br />
$ show_nodes -p class<br />
NODELIST CPUS MEMORY AVAIL_FEATURES GRES STATE<br />
tron06 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron07 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron08 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron09 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron10 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron11 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron12 16 126218 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron13 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron14 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron15 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron16 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron17 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron18 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron19 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron20 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron21 16 126218 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron22 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron23 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron24 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron25 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron26 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron27 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron28 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron29 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron30 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron31 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron32 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron33 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron34 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron35 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron36 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron37 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron38 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron39 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron40 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron41 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron42 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron43 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron44 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron46 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron47 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron48 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron49 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron50 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron51 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron52 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron53 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron54 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron55 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron56 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron57 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron58 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron59 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron60 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron61 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
</pre><br />
<br />
You can also find more granular information about an individual node with the <code>scontrol show node</code> command.<br />
<br />
<pre><br />
$ scontrol show node tron06<br />
NodeName=tron06 Arch=x86_64 CoresPerSocket=16<br />
CPUAlloc=0 CPUEfctv=16 CPUTot=16 CPULoad=0.08<br />
AvailableFeatures=rhel8,x86_64,Zen,EPYC-7302P,Ampere<br />
ActiveFeatures=rhel8,x86_64,Zen,EPYC-7302P,Ampere<br />
Gres=gpu:rtxa4000:4<br />
NodeAddr=tron06 NodeHostName=tron06 Version=23.02.6<br />
OS=Linux 4.18.0-513.11.1.el8_9.x86_64 #1 SMP Thu Dec 7 03:06:13 EST 2023<br />
RealMemory=126214 AllocMem=0 FreeMem=107174 Sockets=1 Boards=1<br />
State=IDLE ThreadsPerCore=1 TmpDisk=0 Weight=340 Owner=N/A MCS_label=N/A<br />
Partitions=class,scavenger,tron<br />
BootTime=2024-01-29T09:35:12 SlurmdStartTime=2024-02-05T15:14:20<br />
LastBusyTime=2024-02-16T15:59:38 ResumeAfterTime=None<br />
CfgTRES=cpu=16,mem=126214M,billing=638,gres/gpu=4,gres/gpu:rtxa4000=4<br />
AllocTRES=<br />
CapWatts=n/a<br />
CurrentWatts=0 AveWatts=0<br />
ExtSensorsJoules=n/s ExtSensorsWatts=0 ExtSensorsTemp=n/s<br />
</pre></div>Dyarnellhttps://wiki.umiacs.umd.edu/umiacs/index.php?title=ClassAccounts&diff=12835ClassAccounts2025-10-02T14:13:46Z<p>Dyarnell: /* Using your account */</p>
<hr />
<div>==Overview==<br />
UMIACS supports classes for all of UMIACS/CSD via special class accounts that can access the [[Nexus]] cluster. Faculty may request that a class be supported by following the instructions [[ClassAccounts/Manage | here]].<br />
<br />
==Getting an account==<br />
Your TA or instructor will request an account for you. Once this is done, you will be notified by email that you have an account to redeem. If you have not received an email, please contact your TA or instructor. '''You must redeem the account within 7 days or else the redemption token will expire.''' If your redemption token does expire, please contact your TA or instructor to have it renewed.<br />
<br />
Once you do redeem your account, you will need to wait until you get a confirmation email that your account has been installed. This is typically done once a day on days that the University is open for business.<br />
<br />
'''Any questions or issues with your account, storage, or cluster use must first be made through your TA or instructor.'''<br />
<br />
==Using your account==<br />
To access Nexus class resources in UMIACS you will need to be on the [https://itsupport.umd.edu/itsupport?id=kb_article_view&sysparm_article=KB0016076 '''UMD Global Protect VPN''']<br />
<br />
Once notified that your account has been installed, you can [[SSH]] to <code>nexusclass.umiacs.umd.edu</code> with your UMD directory ID and passphrase to log in to a submission node.<br />
<br />
If you store something in a local filesystem directory (/tmp, /scratch0) on one of the two submission nodes, you will need to connect to that same submission node to access it later. The actual submission nodes are:<br />
* <code>nexusclass00.umiacs.umd.edu</code><br />
* <code>nexusclass01.umiacs.umd.edu</code><br />
<br />
==Cleaning up your account before the end of the semester==<br />
Class accounts for a given semester are liable to be archived and deleted after that semester's completion as early as the following:<br />
* Winter semesters: February 1st of same year<br />
* Spring semesters: June 1st of same year<br />
* Summer semesters: September 1st of same year<br />
* Fall semesters: January 1st of next year<br />
<br />
It is your responsibility to ensure you have backed up anything you want to keep from your class account's personal or group storage (below sections) prior to the relevant date.<br />
<br />
==Personal Storage==<br />
Your home directory has a quota of 30GB and is located at:<br />
<pre><br />
/fs/classhomes/<username><br />
</pre><br />
<br />
You can request up to another 100GB of personal storage if you would like by '''having your TA or instructor [[HelpDesk | contact staff]]'''. This storage will be located at<br />
<pre><br />
/fs/class-projects/<semester><year>/<coursecode>/<username><br />
</pre><br />
<br />
where <code><semester></code> is either "spring", "summer", "fall", or "winter", <code><year></code> is the current year e.g., "2025", <coursecode> is the class' course code as listed in UMD's [https://app.testudo.umd.edu/soc/ Schedule of Classes] in all lowercase e.g., "cmsc999z", and <code><username></code> is the username.<br />
<br />
==Group Storage==<br />
You can also request group storage by '''having your TA or instructor [[HelpDesk | contact staff]]''' to specify the usernames of the accounts that should be in the group. Only other class accounts in the same class can be added to the group. The quota will be 100GB multiplied by the number of accounts in the group and will be located at<br />
<pre><br />
/fs/class-projects/<semester><year>/<coursecode>/<groupname><br />
</pre><br />
<br />
where <code><groupname></code> is composed of:<br />
* the abbreviated course code as used in the username e.g., "c999z"<br />
* the character "g"<br />
* the number of the group (starting at 0 for the first group for the class requested to us) prepended with 0s to make the total group name 8 characters long<br />
<br />
e.g., "c999zg00".<br />
<br />
==Cluster Usage==<br />
'''You may not run computational jobs on any submission node.''' You must [[SLURM/JobSubmission | schedule your jobs with the SLURM workload manager]]. You can also find out more with the public documentation for the [https://slurm.schedmd.com/quickstart.html SLURM Workload Manager].<br />
<br />
Class accounts only have access to the following submission parameters in SLURM:<br />
* <code>--partition</code> - <code>class</code><br />
* <code>--account</code> - <code>class</code><br />
* <code>--qos</code> - <code>default</code>, <code>medium</code>, and <code>high</code><br />
<br />
You must specify at least the partition parameter manually in any submission command you run. If you do not specify any QoS parameter, you will receive the QoS <code>default</code>.<br />
<br />
You can view the resource limits for each QoS by running the command <code>show_qos</code>. The value in the MaxWall column is the maximum runtime you can run a single job for each QoS, and the values in the MaxTRES column are the maximum amount of CPU cores/GPUs/memory you can request for a single job using each QoS.<br />
<br />
Please note that you will be restricted to 32 total CPU cores, 4 total GPUs, and 256GB total RAM across all jobs you have running at once. This can be viewed with the command <code>show_partition_qos</code>.<br />
<br />
===Example===<br />
Here is a basic example to schedule a interactive job running bash with a single GPU in the partition <code>class</code>, with the account <code>class</code>, running with the QoS of <code>default</code> and the default CPU/memory allocation/time limit for the partition.<br />
<br />
<pre><br />
$ hostname<br />
nexusclass00.umiacs.umd.edu<br />
<br />
$ srun --partition=class --account=class --qos=default --gres=gpu:1 --pty bash<br />
srun: Job time limit was unset; set to partition default of 60 minutes<br />
srun: job 1333337 queued and waiting for resources<br />
srun: job 1333337 has been allocated resources<br />
<br />
$ hostname<br />
tron14.umiacs.umd.edu<br />
<br />
$ nvidia-smi -L<br />
GPU 0: NVIDIA RTX A4000 (UUID: GPU-55f2d3b7-9162-8b02-50de-476a012c626c)<br />
</pre><br />
<br />
===Available Nodes===<br />
You can list the available nodes and their current state with the <code>show_nodes -p class</code> command. This list of nodes is not completely static as nodes may be pulled out of service to troubleshoot GPUs or other components.<br />
<br />
<pre><br />
$ show_nodes -p class<br />
NODELIST CPUS MEMORY AVAIL_FEATURES GRES STATE<br />
tron06 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron07 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron08 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron09 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron10 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron11 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron12 16 126218 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron13 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron14 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron15 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron16 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron17 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron18 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron19 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron20 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron21 16 126218 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron22 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron23 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron24 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron25 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron26 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron27 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron28 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron29 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron30 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron31 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron32 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron33 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron34 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron35 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron36 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron37 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron38 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron39 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron40 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron41 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron42 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron43 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron44 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron46 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron47 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron48 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron49 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron50 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron51 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron52 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron53 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron54 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron55 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron56 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron57 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron58 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron59 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron60 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron61 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
</pre><br />
<br />
You can also find more granular information about an individual node with the <code>scontrol show node</code> command.<br />
<br />
<pre><br />
$ scontrol show node tron06<br />
NodeName=tron06 Arch=x86_64 CoresPerSocket=16<br />
CPUAlloc=0 CPUEfctv=16 CPUTot=16 CPULoad=0.08<br />
AvailableFeatures=rhel8,x86_64,Zen,EPYC-7302P,Ampere<br />
ActiveFeatures=rhel8,x86_64,Zen,EPYC-7302P,Ampere<br />
Gres=gpu:rtxa4000:4<br />
NodeAddr=tron06 NodeHostName=tron06 Version=23.02.6<br />
OS=Linux 4.18.0-513.11.1.el8_9.x86_64 #1 SMP Thu Dec 7 03:06:13 EST 2023<br />
RealMemory=126214 AllocMem=0 FreeMem=107174 Sockets=1 Boards=1<br />
State=IDLE ThreadsPerCore=1 TmpDisk=0 Weight=340 Owner=N/A MCS_label=N/A<br />
Partitions=class,scavenger,tron<br />
BootTime=2024-01-29T09:35:12 SlurmdStartTime=2024-02-05T15:14:20<br />
LastBusyTime=2024-02-16T15:59:38 ResumeAfterTime=None<br />
CfgTRES=cpu=16,mem=126214M,billing=638,gres/gpu=4,gres/gpu:rtxa4000=4<br />
AllocTRES=<br />
CapWatts=n/a<br />
CurrentWatts=0 AveWatts=0<br />
ExtSensorsJoules=n/s ExtSensorsWatts=0 ExtSensorsTemp=n/s<br />
</pre></div>Dyarnellhttps://wiki.umiacs.umd.edu/umiacs/index.php?title=ClassAccounts&diff=12822ClassAccounts2025-09-22T20:56:33Z<p>Dyarnell: /* Personal Storage */</p>
<hr />
<div>==Overview==<br />
UMIACS supports classes for all of UMIACS/CSD via special class accounts that can access the [[Nexus]] cluster. Faculty may request that a class be supported by following the instructions [[ClassAccounts/Manage | here]].<br />
<br />
==Getting an account==<br />
Your TA or instructor will request an account for you. Once this is done, you will be notified by email that you have an account to redeem. If you have not received an email, please contact your TA or instructor. '''You must redeem the account within 7 days or else the redemption token will expire.''' If your redemption token does expire, please contact your TA or instructor to have it renewed.<br />
<br />
Once you do redeem your account, you will need to wait until you get a confirmation email that your account has been installed. This is typically done once a day on days that the University is open for business.<br />
<br />
'''Any questions or issues with your account, storage, or cluster use must first be made through your TA or instructor.'''<br />
<br />
==Using your account==<br />
To access Nexus class resources in UMIACS you will need to be on the UMD Global Protect VPN.<br />
<br />
Once notified that your account has been installed, you can [[SSH]] to <code>nexusclass.umiacs.umd.edu</code> with your assigned username and your UMD passphrase to log in to a submission node.<br />
<br />
If you store something in a local filesystem directory (/tmp, /scratch0) on one of the two submission nodes, you will need to connect to that same submission node to access it later. The actual submission nodes are:<br />
* <code>nexusclass00.umiacs.umd.edu</code><br />
* <code>nexusclass01.umiacs.umd.edu</code><br />
<br />
==Cleaning up your account before the end of the semester==<br />
Class accounts for a given semester are liable to be archived and deleted after that semester's completion as early as the following:<br />
* Winter semesters: February 1st of same year<br />
* Spring semesters: June 1st of same year<br />
* Summer semesters: September 1st of same year<br />
* Fall semesters: January 1st of next year<br />
<br />
It is your responsibility to ensure you have backed up anything you want to keep from your class account's personal or group storage (below sections) prior to the relevant date.<br />
<br />
==Personal Storage==<br />
Your home directory has a quota of 30GB and is located at:<br />
<pre><br />
/fs/classhomes/<username><br />
</pre><br />
<br />
You can request up to another 100GB of personal storage if you would like by '''having your TA or instructor [[HelpDesk | contact staff]]'''. This storage will be located at<br />
<pre><br />
/fs/class-projects/<semester><year>/<coursecode>/<username><br />
</pre><br />
<br />
where <code><semester></code> is either "spring", "summer", "fall", or "winter", <code><year></code> is the current year e.g., "2025", <coursecode> is the class' course code as listed in UMD's [https://app.testudo.umd.edu/soc/ Schedule of Classes] in all lowercase e.g., "cmsc999z", and <code><username></code> is the username.<br />
<br />
==Group Storage==<br />
You can also request group storage by '''having your TA or instructor [[HelpDesk | contact staff]]''' to specify the usernames of the accounts that should be in the group. Only other class accounts in the same class can be added to the group. The quota will be 100GB multiplied by the number of accounts in the group and will be located at<br />
<pre><br />
/fs/class-projects/<semester><year>/<coursecode>/<groupname><br />
</pre><br />
<br />
where <code><groupname></code> is composed of:<br />
* the abbreviated course code as used in the username e.g., "c999z"<br />
* the character "g"<br />
* the number of the group (starting at 0 for the first group for the class requested to us) prepended with 0s to make the total group name 8 characters long<br />
<br />
e.g., "c999zg00".<br />
<br />
==Cluster Usage==<br />
'''You may not run computational jobs on any submission node.''' You must [[SLURM/JobSubmission | schedule your jobs with the SLURM workload manager]]. You can also find out more with the public documentation for the [https://slurm.schedmd.com/quickstart.html SLURM Workload Manager].<br />
<br />
Class accounts only have access to the following submission parameters in SLURM:<br />
* <code>--partition</code> - <code>class</code><br />
* <code>--account</code> - <code>class</code><br />
* <code>--qos</code> - <code>default</code>, <code>medium</code>, and <code>high</code><br />
<br />
You must specify at least the partition parameter manually in any submission command you run. If you do not specify any QoS parameter, you will receive the QoS <code>default</code>.<br />
<br />
You can view the resource limits for each QoS by running the command <code>show_qos</code>. The value in the MaxWall column is the maximum runtime you can run a single job for each QoS, and the values in the MaxTRES column are the maximum amount of CPU cores/GPUs/memory you can request for a single job using each QoS.<br />
<br />
Please note that you will be restricted to 32 total CPU cores, 4 total GPUs, and 256GB total RAM across all jobs you have running at once. This can be viewed with the command <code>show_partition_qos</code>.<br />
<br />
===Example===<br />
Here is a basic example to schedule a interactive job running bash with a single GPU in the partition <code>class</code>, with the account <code>class</code>, running with the QoS of <code>default</code> and the default CPU/memory allocation/time limit for the partition.<br />
<br />
<pre><br />
$ hostname<br />
nexusclass00.umiacs.umd.edu<br />
<br />
$ srun --partition=class --account=class --qos=default --gres=gpu:1 --pty bash<br />
srun: Job time limit was unset; set to partition default of 60 minutes<br />
srun: job 1333337 queued and waiting for resources<br />
srun: job 1333337 has been allocated resources<br />
<br />
$ hostname<br />
tron14.umiacs.umd.edu<br />
<br />
$ nvidia-smi -L<br />
GPU 0: NVIDIA RTX A4000 (UUID: GPU-55f2d3b7-9162-8b02-50de-476a012c626c)<br />
</pre><br />
<br />
===Available Nodes===<br />
You can list the available nodes and their current state with the <code>show_nodes -p class</code> command. This list of nodes is not completely static as nodes may be pulled out of service to troubleshoot GPUs or other components.<br />
<br />
<pre><br />
$ show_nodes -p class<br />
NODELIST CPUS MEMORY AVAIL_FEATURES GRES STATE<br />
tron06 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron07 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron08 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron09 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron10 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron11 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron12 16 126218 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron13 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron14 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron15 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron16 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron17 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron18 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron19 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron20 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron21 16 126218 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron22 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron23 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron24 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron25 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron26 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron27 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron28 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron29 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron30 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron31 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron32 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron33 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron34 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron35 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron36 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron37 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron38 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron39 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron40 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron41 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron42 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron43 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron44 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron46 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron47 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron48 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron49 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron50 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron51 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron52 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron53 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron54 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron55 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron56 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron57 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron58 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron59 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron60 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron61 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
</pre><br />
<br />
You can also find more granular information about an individual node with the <code>scontrol show node</code> command.<br />
<br />
<pre><br />
$ scontrol show node tron06<br />
NodeName=tron06 Arch=x86_64 CoresPerSocket=16<br />
CPUAlloc=0 CPUEfctv=16 CPUTot=16 CPULoad=0.08<br />
AvailableFeatures=rhel8,x86_64,Zen,EPYC-7302P,Ampere<br />
ActiveFeatures=rhel8,x86_64,Zen,EPYC-7302P,Ampere<br />
Gres=gpu:rtxa4000:4<br />
NodeAddr=tron06 NodeHostName=tron06 Version=23.02.6<br />
OS=Linux 4.18.0-513.11.1.el8_9.x86_64 #1 SMP Thu Dec 7 03:06:13 EST 2023<br />
RealMemory=126214 AllocMem=0 FreeMem=107174 Sockets=1 Boards=1<br />
State=IDLE ThreadsPerCore=1 TmpDisk=0 Weight=340 Owner=N/A MCS_label=N/A<br />
Partitions=class,scavenger,tron<br />
BootTime=2024-01-29T09:35:12 SlurmdStartTime=2024-02-05T15:14:20<br />
LastBusyTime=2024-02-16T15:59:38 ResumeAfterTime=None<br />
CfgTRES=cpu=16,mem=126214M,billing=638,gres/gpu=4,gres/gpu:rtxa4000=4<br />
AllocTRES=<br />
CapWatts=n/a<br />
CurrentWatts=0 AveWatts=0<br />
ExtSensorsJoules=n/s ExtSensorsWatts=0 ExtSensorsTemp=n/s<br />
</pre></div>Dyarnellhttps://wiki.umiacs.umd.edu/umiacs/index.php?title=ClassAccounts&diff=12821ClassAccounts2025-09-22T20:55:03Z<p>Dyarnell: </p>
<hr />
<div>==Overview==<br />
UMIACS supports classes for all of UMIACS/CSD via special class accounts that can access the [[Nexus]] cluster. Faculty may request that a class be supported by following the instructions [[ClassAccounts/Manage | here]].<br />
<br />
==Getting an account==<br />
Your TA or instructor will request an account for you. Once this is done, you will be notified by email that you have an account to redeem. If you have not received an email, please contact your TA or instructor. '''You must redeem the account within 7 days or else the redemption token will expire.''' If your redemption token does expire, please contact your TA or instructor to have it renewed.<br />
<br />
Once you do redeem your account, you will need to wait until you get a confirmation email that your account has been installed. This is typically done once a day on days that the University is open for business.<br />
<br />
'''Any questions or issues with your account, storage, or cluster use must first be made through your TA or instructor.'''<br />
<br />
==Using your account==<br />
To access Nexus class resources in UMIACS you will need to be on the UMD Global Protect VPN.<br />
<br />
Once notified that your account has been installed, you can [[SSH]] to <code>nexusclass.umiacs.umd.edu</code> with your assigned username and your UMD passphrase to log in to a submission node.<br />
<br />
If you store something in a local filesystem directory (/tmp, /scratch0) on one of the two submission nodes, you will need to connect to that same submission node to access it later. The actual submission nodes are:<br />
* <code>nexusclass00.umiacs.umd.edu</code><br />
* <code>nexusclass01.umiacs.umd.edu</code><br />
<br />
==Cleaning up your account before the end of the semester==<br />
Class accounts for a given semester are liable to be archived and deleted after that semester's completion as early as the following:<br />
* Winter semesters: February 1st of same year<br />
* Spring semesters: June 1st of same year<br />
* Summer semesters: September 1st of same year<br />
* Fall semesters: January 1st of next year<br />
<br />
It is your responsibility to ensure you have backed up anything you want to keep from your class account's personal or group storage (below sections) prior to the relevant date.<br />
<br />
==Personal Storage==<br />
Your home directory has a quota of 30GB and is located at:<br />
<pre><br />
/fs/classhomes/<semester><year>/<coursecode>/<username><br />
</pre><br />
<br />
where <code><semester></code> is either "spring", "summer", "fall", or "winter", <code><year></code> is the current year e.g., "2021", <coursecode> is the class' course code as listed in UMD's [https://app.testudo.umd.edu/soc/ Schedule of Classes] in all lowercase e.g., "cmsc999z", and <code><username></code> is the username mentioned in the email you received to redeem the account e.g., "c999z000".<br />
<br />
You can request up to another 100GB of personal storage if you would like by '''having your TA or instructor [[HelpDesk | contact staff]]'''. This storage will be located at<br />
<pre><br />
/fs/class-projects/<semester><year>/<coursecode>/<username><br />
</pre><br />
<br />
==Group Storage==<br />
You can also request group storage by '''having your TA or instructor [[HelpDesk | contact staff]]''' to specify the usernames of the accounts that should be in the group. Only other class accounts in the same class can be added to the group. The quota will be 100GB multiplied by the number of accounts in the group and will be located at<br />
<pre><br />
/fs/class-projects/<semester><year>/<coursecode>/<groupname><br />
</pre><br />
<br />
where <code><groupname></code> is composed of:<br />
* the abbreviated course code as used in the username e.g., "c999z"<br />
* the character "g"<br />
* the number of the group (starting at 0 for the first group for the class requested to us) prepended with 0s to make the total group name 8 characters long<br />
<br />
e.g., "c999zg00".<br />
<br />
==Cluster Usage==<br />
'''You may not run computational jobs on any submission node.''' You must [[SLURM/JobSubmission | schedule your jobs with the SLURM workload manager]]. You can also find out more with the public documentation for the [https://slurm.schedmd.com/quickstart.html SLURM Workload Manager].<br />
<br />
Class accounts only have access to the following submission parameters in SLURM:<br />
* <code>--partition</code> - <code>class</code><br />
* <code>--account</code> - <code>class</code><br />
* <code>--qos</code> - <code>default</code>, <code>medium</code>, and <code>high</code><br />
<br />
You must specify at least the partition parameter manually in any submission command you run. If you do not specify any QoS parameter, you will receive the QoS <code>default</code>.<br />
<br />
You can view the resource limits for each QoS by running the command <code>show_qos</code>. The value in the MaxWall column is the maximum runtime you can run a single job for each QoS, and the values in the MaxTRES column are the maximum amount of CPU cores/GPUs/memory you can request for a single job using each QoS.<br />
<br />
Please note that you will be restricted to 32 total CPU cores, 4 total GPUs, and 256GB total RAM across all jobs you have running at once. This can be viewed with the command <code>show_partition_qos</code>.<br />
<br />
===Example===<br />
Here is a basic example to schedule a interactive job running bash with a single GPU in the partition <code>class</code>, with the account <code>class</code>, running with the QoS of <code>default</code> and the default CPU/memory allocation/time limit for the partition.<br />
<br />
<pre><br />
$ hostname<br />
nexusclass00.umiacs.umd.edu<br />
<br />
$ srun --partition=class --account=class --qos=default --gres=gpu:1 --pty bash<br />
srun: Job time limit was unset; set to partition default of 60 minutes<br />
srun: job 1333337 queued and waiting for resources<br />
srun: job 1333337 has been allocated resources<br />
<br />
$ hostname<br />
tron14.umiacs.umd.edu<br />
<br />
$ nvidia-smi -L<br />
GPU 0: NVIDIA RTX A4000 (UUID: GPU-55f2d3b7-9162-8b02-50de-476a012c626c)<br />
</pre><br />
<br />
===Available Nodes===<br />
You can list the available nodes and their current state with the <code>show_nodes -p class</code> command. This list of nodes is not completely static as nodes may be pulled out of service to troubleshoot GPUs or other components.<br />
<br />
<pre><br />
$ show_nodes -p class<br />
NODELIST CPUS MEMORY AVAIL_FEATURES GRES STATE<br />
tron06 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron07 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron08 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron09 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron10 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron11 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron12 16 126218 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron13 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron14 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron15 16 126214 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron16 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron17 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron18 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron19 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron20 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron21 16 126218 rhel8,x86_64,Zen,EPYC-7302P,Ampere gpu:rtxa4000:4 idle<br />
tron22 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron23 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron24 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron25 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron26 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron27 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron28 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron29 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron30 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron31 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron32 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron33 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron34 16 126217 rhel8,x86_64,Zen,EPYC-7313P,Ampere gpu:rtxa4000:4 idle<br />
tron35 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron36 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron37 16 126214 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron38 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron39 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron40 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron41 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron42 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron43 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron44 16 126218 rhel8,x86_64,Zen,EPYC-7302,Ampere gpu:rtxa4000:4 idle<br />
tron46 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron47 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron48 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron49 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron50 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron51 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron52 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron53 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron54 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron55 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron56 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron57 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron58 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron59 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron60 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
tron61 48 255232 rhel8,x86_64,Zen,EPYC-7352,Ampere gpu:rtxa5000:8 idle<br />
</pre><br />
<br />
You can also find more granular information about an individual node with the <code>scontrol show node</code> command.<br />
<br />
<pre><br />
$ scontrol show node tron06<br />
NodeName=tron06 Arch=x86_64 CoresPerSocket=16<br />
CPUAlloc=0 CPUEfctv=16 CPUTot=16 CPULoad=0.08<br />
AvailableFeatures=rhel8,x86_64,Zen,EPYC-7302P,Ampere<br />
ActiveFeatures=rhel8,x86_64,Zen,EPYC-7302P,Ampere<br />
Gres=gpu:rtxa4000:4<br />
NodeAddr=tron06 NodeHostName=tron06 Version=23.02.6<br />
OS=Linux 4.18.0-513.11.1.el8_9.x86_64 #1 SMP Thu Dec 7 03:06:13 EST 2023<br />
RealMemory=126214 AllocMem=0 FreeMem=107174 Sockets=1 Boards=1<br />
State=IDLE ThreadsPerCore=1 TmpDisk=0 Weight=340 Owner=N/A MCS_label=N/A<br />
Partitions=class,scavenger,tron<br />
BootTime=2024-01-29T09:35:12 SlurmdStartTime=2024-02-05T15:14:20<br />
LastBusyTime=2024-02-16T15:59:38 ResumeAfterTime=None<br />
CfgTRES=cpu=16,mem=126214M,billing=638,gres/gpu=4,gres/gpu:rtxa4000=4<br />
AllocTRES=<br />
CapWatts=n/a<br />
CurrentWatts=0 AveWatts=0<br />
ExtSensorsJoules=n/s ExtSensorsWatts=0 ExtSensorsTemp=n/s<br />
</pre></div>Dyarnellhttps://wiki.umiacs.umd.edu/umiacs/index.php?title=SSHFileTransferProtocol&diff=12709SSHFileTransferProtocol2025-06-25T17:59:53Z<p>Dyarnell: </p>
<hr />
<div>SSH File Transfer Protocol ([http://en.wikipedia.org/wiki/SSH_file_transfer_protocol SFTP]) is a network protocol used to securely transfer and manage files on remote systems. SFTP is layered on top of the [[SSH]] protocol, and is preferred over [[FTP]] as a method of remote file transfer.<br />
<br />
'''Warning:''' running interactive programs in your shell initialization files, such as starting another shell, causes SFTP to fail. See [[Shell]] on how to correctly change the shell you are using.<br />
<br />
==Connecting to an SFTP Server==<br />
Under [[RHEL | Red Hat Enterprise Linux (RHEL)]], [[Ubuntu]], and macOS, the following command from a terminal will connect a client computer to a remote host.<br />
<br />
<pre>sftp bkirz@$HOSTNAME.umiacs.umd.edu </pre><br />
Replace $HOSTNAME with the name of the host you are trying to connect.<br />
<br />
For Windows hosts please refer to [[WinSCP]] which is a SFTP compatible file transfer program. It is per-installed on UMIACS supported Windows hosts.<br />
<br />
==Further Information==<br />
More information about SFTP can be found at [http://www.openssh.org/ http://www.openssh.org/].</div>Dyarnellhttps://wiki.umiacs.umd.edu/umiacs/index.php?title=Accounts/UMD&diff=12692Accounts/UMD2025-06-20T13:57:15Z<p>Dyarnell: </p>
<hr />
<div>Before [[Accounts#Request_a_UMIACS_account | requesting a UMIACS account]], any new prospective UMIACS account holder needs to have a UMD directory ID. This is to allow them to [https://itsupport.umd.edu/itsupport?id=kb_article_view&sysparm_article=KB0016076 connect to UMD's GlobalProtect VPN] to be delegated access to our networked resources after their account install is completed. <br />
<br />
Existing UMD students, faculty, and staff should already have directory IDs. For external collaborators, at other institutions or otherwise, faculty members will need to request affiliate appointments for them. An overview of the different types of affiliate appointments can be found [https://itsupport.umd.edu/itsupport?id=kb_article_view&sysparm_article=KB0012328#mcetoc_1hjletjg132 here]. To actually request an appointment, fill out [https://wiki.umiacs.umd.edu/umiacs/images/6/6d/Affiliate_Data_Collection_Form_Blank2.pdf this form] and send it to [mailto:umiacs-payroll@umiacs.umd.edu umiacs-payroll@umiacs.umd.edu].<br />
<br />
If the person the appointment is being requested for already has a UMIACS account, please be sure to request their directory ID be the same as their UMIACS username, if the ID is available.<br />
<br />
Once the person gets their appointment and thus their directory ID, they can fill out the UMIACS account request form (if new) or [[HelpDesk | contact technical staff]] to get access to their existing UMIACS account again (if existing). If filling out the new UMIACS account request form, please let the person know they should use their directory ID as the requested UMIACS username.</div>Dyarnell