Difference between revisions of "HPC Getting Started"

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(Off-campus Access)
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There are three ways to connect to HPC from off campus:
 
There are three ways to connect to HPC from off campus:
  
# [http://remoteaccess.uconn.edu/vpn-overview/connect-via-vpn-client-2/ VPN]: The UConn VPN is the recommended way to access the Storrs HPC cluster from off campus. Windows and Mac users should follow the instructions on that page for installing the VPN client. Linux users can install [[SSH on GNU Linux|OpenConnect version 7]] or later and connect to the VPN with: <code>openconnect --juniper sslvpn.uconn.edu</code>
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# [http://remoteaccess.uconn.edu/vpn-overview/connect-via-vpn-client-2/ VPN]: The UConn VPN is the recommended way to access the Storrs HPC cluster from off campus. Windows and Mac users should follow the instructions on that page for installing the VPN client. Linux users should follow [http://remoteaccess.uconn.edu/vpn-overview/connect-via-vpn-client-on-linux/ these alternate instructions].
 
# [http://skybox.uconn.edu UConn Skybox]: Login to a virtual desktop and then access the cluster via PuTTY.
 
# [http://skybox.uconn.edu UConn Skybox]: Login to a virtual desktop and then access the cluster via PuTTY.
 
# [http://help.engr.uconn.edu/linux-remote-access/ Engineering SSH] If you have a School of Engineering account you can login to their SSH relay, <code>icarus.engr.uconn.edu</code>, then SSH to the cluster. This process is outlined as follows:
 
# [http://help.engr.uconn.edu/linux-remote-access/ Engineering SSH] If you have a School of Engineering account you can login to their SSH relay, <code>icarus.engr.uconn.edu</code>, then SSH to the cluster. This process is outlined as follows:

Revision as of 14:36, 29 March 2017


Connecting to the cluster

If you don't already have an account, please fill out the cluster application form.

To access the cluster resources and send commands, SSH is used. SSH stands for secure shell. It is the industry standard for remote access and command execution.

SSH access

On Mac and GNU/Linux, from the a terminal simply run:

ssh <Your Net ID>@login.storrs.hpc.uconn.edu

Windows users can login using PuTTY.

This gives you access to a login node, and you should see a terminal prompt like:

[<Your Net ID>@cn01 ~]$

Off-campus Access

SSH connections are limited to on-campus addresses from both the wired network and the "UCONN-SECURE" wireless network.

There are three ways to connect to HPC from off campus:

  1. VPN: The UConn VPN is the recommended way to access the Storrs HPC cluster from off campus. Windows and Mac users should follow the instructions on that page for installing the VPN client. Linux users should follow these alternate instructions.
  2. UConn Skybox: Login to a virtual desktop and then access the cluster via PuTTY.
  3. Engineering SSH If you have a School of Engineering account you can login to their SSH relay, icarus.engr.uconn.edu, then SSH to the cluster. This process is outlined as follows:
   [<Your User>@<Your Hostname>]$ ssh <Your Net ID>@icarus.engr.uconn.edu
   [<Your Net ID>@icarus.engr.uconn.edu]$ ssh <Your Net ID>@login.storrs.hpc.uconn.edu

Submitting Jobs

All job submission, management, and scheduling is done using the job scheduler software SLURM. To learn more about job submission and management, please read our SLURM Guide.

Always run jobs via SLURM. If you do not, your process may be throttled or terminated.

Please read our usage policy for more details.

Overview of cluster nodes

There are four classes of nodes available on the HPC cluster, each named after the Intel CPU architecture, listed in the table below.

Configuration of each type of CPU compute node
Name CPU name Nodes Cores per Node Cores Total RAM (GB) CPU Frequency (GHz) Host Names
Broadwell Xeon E5-2699 v4 4 44 176 256 2.20 cn325 - cn328
Haswell Xeon E5-2690 v3 175 24 4,200 128 2.60 cn137 - cn324
Ivy Bridge Xeon E5-2680 v2 32 20 640 128 2.80 cn105 - cn136
Sandy Bridge Xeon E5-2650 40 16 640 64 2.00 cn65 - cn104

GPUs are installed in two nodes. How to submit jobs to these nodes is described in the GPU Guide.

Configuration of each type of GPU compute node
GPU name Nodes Cards per Node Cores per Card Cores Total RAM on Card (MB) Host Names
NVIDIA Tesla K40m 2 2 2,880 11,520 12GB gpu01, gpu02

HPC applications

We have created helpful software guides to demonstrate how to effectively use popular scientific applications on the HPC cluster.

Troubleshooting

For any errors, please read FAQ first. For further assistance, visit the Help page for further resources and contact information for technical support.