To use these scripts on NCI infrastructure do the following:
module use /g/data/hh5/public/modules
module load nci-scripts
Show extended information for jobs in the queue
$ uqstat
Job_Name queue state ncpus walltime su mem_pct cpu_pct qtime
961571.gadi-pbs STDIN copyq-exec R 1 01:26:18 3.0 100.000191 85.940518 00:10:00
Calculates what it would cost, in SU, for a job submitted to the PBS system with the same configuration.
The information is all contained in the PBS queue information is provided by NCI
but it can be tedious to determine which configuration of queue and memory request should be used
to minimise job cost. qcost was created to make this process easier.
Usage:
./qcost -h
usage: qcost [-h] -q QUEUE -n NCPUS -m MEM [-t TIME]
Return what it would cost (in SUs) for a PBS job submitted on gadi with the same
configuration. No checking is done to ensure requests are within queue limits.
optional arguments:
-h, --help show this help message and exit
-q QUEUE, --queue QUEUE
PBS queue
-n NCPUS, --ncpus NCPUS
Number of cpus
-m MEM, --mem MEM Requested memory
-t TIME, --time TIME Job walltime (hours)
e.g. qcost -q normal -n 4 -m 60GB -t 3:00:00
Note that if no time is specified it defaults to 1 hour (1:00:00). Walltime can be specified as H:M or H:M:S. Memory must be specified in units of bytes (B), e.g. 160GB, 2000MB
Example and output:
$ qcost -q normal -n 4 -m 60GB -t 3:00:00
90 SU
Run a Jupyter notebook on Gadi, displaying it in a local web browser.
THIS MUST BE RUN FROM YOUR OWN COMPUTER
So the first step is to clone this repository to your local workstation. It works on mac/linux/windows (for windows using e.g. git bash or Windows Ssubsystem for Linux).
By default the script will spawn a job with a single CPU, 4GB of memory and a walltime of 1 hour.
Command line options can be used to alter the resources requested, the conda environment used to spawn the job and NCI username
Usage:
gadi_jupyter -h
Run a Jupyter notebook on Gadi's compute nodes, presenting the interface in a
browser on the local machine
You can set a default username in your local ~/.ssh/config, e.g.
Host gadi.nci.org.au
User abc123
Your default project is set in the file on Gadi ~/.config/gadi-login.conf
General Options:
-h: Print help
-l USER: NCI username
-L HOST: NCI login node (default 'gadi.nci.org.au')
-e ENVIRON: Conda environment
-d: Debug mode
Queue Options:
-q QUEUE: Queue name
-n NCPU: Use NCPU cpus
-m MEM: Memory allocation (default 4*NCPU GB)
-t TIME: Walltime limit (default 1 hour)
-J JOBFS: Jobfs allocation (default 100 GB)
-P PROJ: Submit job under project PROJ
-s STORAGE: PBS Storage flags (e.g. 'scratch/w35+gdata/v45')
If not specified, all available storage is requested
You will need to have ssh keys setup for logging into gadi. There is a guide on how to do this on the CMS Wiki.
Run a Jupyter notebook on NCI Virtual Desktop Infrastructure (VDI), displaying it in a local web browser (run from your own computer).
To run:
python nci_scripts/vdi_jupyter.py
This script requires the pexpect package. To make a conda environment with the required
packages:
conda env create -f nci_scripts/vdi_environment.yml
then activate the environment:
conda activate jupyter_vdi
and run the script as above.
Note for Windows Users:
The pexpect package for Windows doesn't have the required functionality for running this script, so running the script will return an error. If you have Windows 10, you can install the Windows Subsystem for Linux (WSL or WSL 2) allowing you to set up a Linux environment on your Windows machine in which it will run.
qsub but it requests all of the -l storage= options for projects you're a member of
Upload data to https://cloudstor.aarnet.edu.au
Information about what projects are on which NCI Gdata mount
Available projects on gdata1a:
$ gdata-info -m gdata1a
e14
ks32
p66
p73
rr3
The gdata system for project e14:
$ gdata-info -P e14
gdata1a