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Short answer: In general, data cannot be stored on the Storrs HPC if it contains any of the following:

  • personal identifiable information (e.g., SSN, Passport Number, Drivers License Number, D.OB.)

  • credit card and/or banking information (e.g., account numbers)

  • university records for individual students (e.g., grades)

  • personal health information / HIPAA-protected data (with few exceptions)

  • data for which the data owner has specified data protection requirements that are not compatible with the Storrs HPC environment

  • data protected by UConn’s Export Control Policy (e.g., DoD-related, requires a security clearance)

Long Answer: The Storrs HPC cluster cannot be used to generate or store data that is considered Sensitive University Data or covered by the university's Export Control Policy; for more info, see UConn’s Data Classification Policy. The documents linked in the previous sentence provide more detail about each of those classifications.

Data which may have been been classified as confidential or sensitive may be eligible for storage on Storrs HPC if the data has been de-identified sufficiently that the data classification no longer applies. Any de/re-identification key (if one was used) cannot be transmitted or stored with the data within the HPC environment.

All data that is stored on the cluster is subject to these restrictions, and data that is not in compliance may be removed. If you have read the above documents and you’re still not sure how your data would be classified, please send an email to security@uconn.edu.

Using the HPC

How do I

...

get priority access to HPC resources?

Expand

Short answer: First, you need to connect to UConn’s VPN. Then, you should be able to access the HPC.

Long Answer: The HPC Cluster only allows the connection of SSH from the campus-wide computers, for example:

  • computers in the UConn libraries

  • computers in campus offices/labs

  • computers connected to UCONN-SECURE WiFi, etc.).

In order to connect to the HPC when you are off campus, you will first need to connect to the UConn Virtual Private Network (VPN). After connecting to the VPN, you will be able to log in to the HPC as you normally do.

For instructions on how to install, set up, and connect your personal device(s) to UConn’s VPN, please go to this webpage.

How do I check what node I am on?

Expand

The node you are on will normally be shown next to your netID when you log in to the Storrs HPC. For instance, if Jonathan the Husky’s netID was jtk10001, his terminal might look like this.

Code Block
[jth10001@login6 ~]$

This would tell us that Jonathan is on the node called “login6.” Another way to check what node you are on is to use the hostname command. See below.

Code Block
[jth10001@login6 ~]$ hostname
login6

What programs am I allowed to run on the login nodes?

Faculty can purchase priority access for 5 years if they pay the upfront cost for the nodes.

Long answer: High-priority access is available under a “condo model,” where faculty are able to purchase semi-dedicated nodes which get made available to all users when there are unused compute cycles. Under the condo model, faculty researchers fund the capital equipment costs of individual compute nodes, while the university funds the operating costs of running these nodes for five years. Faculty who purchase compute nodes receive access to equivalent resources at a higher priority than other researchers. The faculty can designate others to receive access at the same priority level, such as their graduate students, postdoctoral researchers, etc. With priority access, computational jobs are moved higher in the queuing system, and in most cases begin execution within twelve hours, depending upon other FairShare factors. A priority user can utilize their resources indefinitely. All access to resources is managed through the cluster’s job scheduler. When a priority user is not using their assigned resources, the nodes are made available to all UConn researchers for general use.

Expand

Programs that are running on a login node (login.storrs.hpc.uconn.edu) without using the job scheduler are subject to certain restrictions. Programs that run on the login nodes for longer than 1 hour, use greater than 5% of CPU power, and/or use greater than 5% of RAM listed below may be throttled or terminated without notice.

Below is a list of programs that are allowed to run on the login node without restrictions:

  • awk

  • basemount

  • bash

  • bzip

  • chgrp

  • chmod

  • cmake

  • comsollauncher

  • cp

  • du

  • emacs

  • find

  • fort

  • gcc

  • gfortran

  • grep

  • gunzip

  • gzip

  • icc

  • ifort

  • jservergo

  • less

  • ls

  • make

  • more

  • mv

  • nano

  • ncftp

...

Using the HPC

How do I log in to the Storrs HPC when I am off campus?

Expand

Short answer: First, you need to connect to UConn’s VPN. Then, you should be able to access the HPC.

Long Answer: The HPC Cluster only allows the connection of SSH from the campus-wide computers, for example:

  • computers in the UConn libraries

  • computers in campus offices/labs

  • computers connected to UCONN-SECURE WiFi, etc.).

In order to connect to the HPC when you are off campus, you will first need to connect to the UConn Virtual Private Network (VPN). After connecting to the VPN, you will be able to log in to the HPC as you normally do.

For instructions on how to install, set up, and connect your personal device(s) to UConn’s VPN, please go to this webpage.

How do I check what node I am on?

Expand

The node you are on will normally be shown next to your netID when you log in to the Storrs HPC. For instance, if Jonathan the Husky’s netID was jtk10001, his terminal might look like this.

Code Block
[jth10001@login6 ~]$

This would tell us that Jonathan is on the node called “login6.” Another way to check what node you are on is to use the hostname command. See below.

Code Block
[jth10001@login6 ~]$ hostname
login6

What programs am I allowed to run on the login nodes?

Expand

Programs that are running on a login node (login.storrs.hpc.uconn.edu) without using the job scheduler are subject to certain restrictions. Programs that run on the login nodes for longer than 1 hour, use greater than 5% of CPU power, and/or use greater than 5% of RAM listed below may be throttled or terminated without notice.

Below is a list of programs that are allowed to run on the login node without restrictions:

  • awk

  • basemount

  • bash

  • bzip

  • chgrp

  • chmod

  • cmake

  • comsollauncher

  • cp

  • du

  • emacs

  • find

  • fort

  • gcc

  • gfortran

  • grep

  • gunzip

  • gzip

  • icc

  • ifort

  • jservergo

  • less

  • ls

  • make

  • more

  • mv

  • nano

  • ncftp

  • nvcc

  • perl

  • rm

  • rsync

  • ruby

  • setfacl

  • sftp

  • smbclient

  • ssh

  • tail

  • tar

  • ukbfetch

  • vim

  • wget

How do I get priority access to HPC resources?

Expand

Short answer: Faculty can purchase priority access for 5 years if they pay the upfront cost for the nodes.

Long answer: High-priority access is available under a “condo model,” where faculty are able to purchase semi-dedicated nodes which get made available to all users when there are unused compute cycles. Under the condo model, faculty researchers fund the capital equipment costs of individual compute nodes, while the university funds the operating costs of running these nodes for five years. Faculty who purchase compute nodes receive access to equivalent resources at a higher priority than other researchers. The faculty can designate others to receive access at the same priority level, such as their graduate students, postdoctoral researchers, etc. With priority access, computational jobs are moved higher in the queuing system, and in most cases begin execution within twelve hours, depending upon other FairShare factors. A priority user can utilize their resources indefinitely. All access to resources is managed through the cluster’s job scheduler. When a priority user is not using their assigned resources, the nodes are made available to all UConn researchers for general use.

How do I access old data after I leave the university?

...