Info |
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The jup_sched utility has been deprecated. Please refer to Getting started with HAL OnDemand for instructions to use Jupyter Notebook with HAL OnDemand |
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You will not get GPUs this way and will also impact others' ability to use the system. Refer to the link above |
Table of Contents |
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Code Block |
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$ jup_sched -h
usage: jup_sched [-h] [-e EMAIL] [-t TIME] [--gpu] [-py2] [--password] [-d]
Jupyter Notebook Scheduler
optional arguments:
-h, --help show this help message and exit
-e EMAIL, --email EMAIL
specify an email address for the scheduler
communication
-t TIME, --time TIME specify the running time for the scheduler in the
format HH:MM:SS
--gpu use this option if you require a GPU to be scheduled
-py2, --python2 use a Python 2.x environment (Python 3.x is used by
default)
--password re-print the password and address for the jupyter
notebook WILL IGNORE ALL OTHER ARGUMENTS
-d, --debug keep the scheduler's transcript of the console output
(off by default) |
Examples
...
To get a simple Jupyter Notebook running on one CPU core on a compute node:
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$ jup_sched
[jupyter_scheduler INFO] no time on arguments, scheduling notebook for 1 HOUR
[jupyter_scheduler INFO] Waiting for scheduler...
====================================
Please direct your browser to:
http://hal.ncsa.illinois.edu:10087
Use the password to login:
a25f9815bc783d0e3c7d
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Run "jup_sched --password" to view this message again |
Open a browser on your local computer (not HAL), navigate to the provided address and use the provided password to log in. The job will terminate when the time limit is reached or if you exit via the web interface.
To get a Jupyter Notebook for two hours:
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jup_sched -t 02:00:00 |
To get a Jupyter Notebook with a GPU:
Code Block |
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jup_sched --gpu |
Restrictions
...
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