Student Cluster
This topic gives you a quick overview of the steps involved to run a job on the D-INFK student cluster.
Login in
If your course uses
Jupyter then go to
https://student-jupyter.inf.ethz.ch and log in there. More information can be found
here.
For running jobs directly and compiling software you can log in to
student-cluster.inf.ethz.ch
or
student-cluster2.inf.ethz.ch
via secure shell (
ssh).
When you log in you will be informed about the remaining GPU time per course and how much free space you have in your home directory. Keep an eye on these numbers that you do not run out of time or space before a deadline.
Running Jobs
Please read on
here.
GPUs
Currently there are only
NVidia GTX 1080 Ti cards in the cluster:
- 3584 CUDA cores
- 11 GB RAM
- Compute capability: 6.1
Limits
You have the following general limitations on resources that you can use.
Home Directory
You have 20 GB of space in your home directory, independent of how many courses you have.
Scratch Space
Your individual scratch space under
/work/scratch/{your user name} has a hard space limit of 100GB. Data in there has a retention period that depends on the amount of data:
The cleaning job that deletes data according to age starts
23:00 every day.
You are not allowed to keep data alive by automatically updating time stamps of files.
Work Space
Some courses provide additional work space for you or your team under
/work/courses or
/work/users in which case your TAs will inform you.
Jobs
Resources available for jobs have the following default limits:
| |
GPU jobs |
CPU jobs |
| Number of running jobs |
1 |
1 |
| GPUs per job |
1 |
- |
| CPU cores per job |
2 |
1, with time sharing |
| RAM per job |
24 GB |
4 to 8 GB, course specific |
Space in /tmp |
40 GB |
4 GB |
| Queued jobs |
2 |
- |
The amount of hours that you have as well as maximum runtime per job depends on the courses that you take. Each course comes with its own allowance which is displayed when you log in to a login node as well as in the spawner page of
JupyterHub.
For courses with special needs some of these limits may be different in which case your TAs will inform you..
Login Nodes
On the login nodes you also have the following restrictions:
Expiration of Access
Access to the cluster will be disabled in the morning of the last Monday of the semester holidays. All data in your home directory will also be deleted. Please
copy all data that you still need away before this happens.
