Difference between revisions of "Frequently Asked Questions"

Revision as of 14:29, 7 April 2022

Under Construction

I Can't Access the Frontenac Cluster

If you are receiving an 'Operation Timed out' message and you are from outside of Canada, you will need to use a VPN. If you are from the Queen's University Community, you can make use of the Fortinet VPN client offered by Queens.

I've Forgotten My CAC Password

Users can reset their CAC password their self, see https://login.cac.queensu.ca/pwr . Make sure you use the same email address as you used when you first signed up.

My jobs haven't started yet

You can check your pending job by running the command squeue -u $USER. You queue time for your job depends on two major factors. First is the cluster load, you can check the current load,i.e., running and pending jobs here: https://admin.cac.queensu.ca:4444/cgi-bin/cacMeters/cacMeter.cgi

Secondly, your priority might have dropped due to the recent usage of the compute resources from your group. You can check your group's fairshare level using sshare command (e.g., sshare -l -A def-hpcg9999). Your job priority depends on the LevelFS and anything less than 1 implies that you are over-served in the recent past and job are given a lower priority by the scheduler. This is to ensure fairshare usage amongst our user. Please note that your groups fairshare level will automatically recover with time, provide that the recent usage is low.

Can I use Conda for installing python packages

We don't recommend installing python packages using conda on our clusters. We suggest you consider other options like a virtual environment or a Singularity container, for the most complicated cases. You can find information on creating virtual environment here https://docs.computecanada.ca/wiki/Python/en#Creating_and_using_a_virtual_environment. Compute Canada wheelhouse is available on our cluster, you can view currently available packages using command avail_wheels

[hpc4774@caclogin04 ~]$ avail_wheels torch
name    version    build          python    arch
------  ---------  -------------  --------  ------
torch   1.10.0     computecanada  cp39      avx2
torch   1.10.0     computecanada  cp38      avx2
torch   1.10.0     computecanada  cp37      avx2

R and Rstudio

My job doesn't seems run any faster on the cluster compared to my PC/Laptop