Difference between revisions of "Teach"

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== Teaching Cluster ==
 
== Teaching Cluster ==
  
SciNet has assembled some older compute hardware into a small cluster provided primarily for teaching purposes. It is configured similarly to the production [[Niagara]] system, however uses repurposed hardware.  Questions about its use or problems should be sent to '''support@scinet.utoronto.ca'''.
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SciNet has assembled some older compute hardware into a small cluster provided primarily for teaching purposes. It is configured similarly to the production [[Niagara_Quickstart]] system, however uses repurposed hardware.  Questions about its use or problems should be sent to '''support@scinet.utoronto.ca'''.
  
  

Revision as of 14:26, 30 October 2018

Teach Cluster
Ibm idataplex dx360 m4.jpg
Installed (orig Feb 2013), Oct 2018
Operating System Linux (Centos 7.4)
Number of Nodes 42
Interconnect Infiniband (QDR)
Ram/Node 64 Gb
Cores/Node 16
Login/Devel Node teach01 (from teach.scinet)
Vendor Compilers icc/gcc
Queue Submission slurm

Teaching Cluster

SciNet has assembled some older compute hardware into a small cluster provided primarily for teaching purposes. It is configured similarly to the production Niagara_Quickstart system, however uses repurposed hardware. Questions about its use or problems should be sent to support@scinet.utoronto.ca.


Specifications

The cluster consists of 42 repurposed x86_64 nodes each with two octal core Intel Xeon (Sandybridge) E5-2650 2.0GHz CPUs with 64GB of RAM per node. The nodes are interconnected with 2.6:1 blocking QDR Infiniband for MPI communications and disk I/O to the SciNet Niagara filesystems. In total this cluster contains 672 x86_64 cores.

Login/Devel Node

Login via ssh with your scinet account to teach.scinet.utoronto.ca, which will bring directly to teach01 the gateway/devel node for this cluster. From teach01 you can compile, do short tests, and submit your jobs to the queue.

Software Modules

 
module avail

Submit a Job

Teach uses SLURM as its job scheduler. More-advanced details of how to interact with the scheduler can be found on the Slurm page.

You submit jobs from a login node by passing a script to the sbatch command:

teach01:~scratch$ sbatch jobscript.sh

This puts the job in the queue. It will run on the compute nodes in due course.

In most cases, you will want to submit from your $SCRATCH directory, so that the output of your compute job can be written out (as mentioned above, $HOME is read-only on the compute nodes).