<aside> 📢 [2022.09.08] All clusters are deployed!! Thank you for waiting us.
</aside>
<aside> 📢 [2025.09.01] Important announcements & update!! Check below 2025-2 Update
</aside>
Equivalent question: “Why should we learn boilerplates about requesting GPUs while all we want to do is just running a single .py file?”
Of course, it is much easier to use when we assign each GPU to each user for a whole semester. But we should keep in mind that
Besides, last semester, when we didn't do any time-multiplexed management, averaged GPU utilization was under 1%!! Therefore, it's natural to reach the consensus that we should do some fine management to use limited resources as efficiently as possible. “The greatest happiness of the greatest number.”
PPTs have some crucial information. Please login with KHU-MS account if you want to see. The account will end with ‘@office.khu.ac.kr’
SSH access will be available after completing the tutorial.
# inside the KHU network
ssh YOURNAME@CLUSTERDOMAIN
# ex) ssh hyogun@ariel.khu.ac.kr
# outside of the network (for foreigners and commuters)
ssh YOURNAME@CLUSTERDOMAIN -p 30080
# ex) ssh hyogun@ariel.khu.ac.kr -p 30080