Research Computing on the Open Science Pool In-Person / Online
In this session you'll take an end-to-end research pipeline from a laptop-scale idea to a distributed job running on the Open Science Pool (OSPool). Working in Python, you'll pull data from a public API, stage it for compute, then submit a job to HTCondor on the OSPool access point. We'll walk through every piece of the stack together no assumed HTCondor experience.
By the end of this session participants will be able to:
- Write and submit an HTCondor submit file with the right resource requests, container image, and file-transfer directives
- Package a Python analysis for a shared container environment (installing dependencies into a portable directory instead of a venv)
- Interpret HTCondor job states (idle / running / held / completed) and read the .log, .out, .err triplet to diagnose failures
- Ship data up to OSPool, run the job, and pull the results back
- Understand OSPool policies around access-point use, background processes, and job duration categories
Please sign up in advance. We need your name a few days before the session so we can request an OSPool account for you and have it active by the workshop. Walk-ins can't be onboarded on the day. Seats are limited, so only register if you're committed to attending. If you sign up and don't show, someone on the waitlist misses out.
- Date:
- Wednesday, October 7, 2026 Show more dates
- Time:
- 2:00pm - 3:00pm
- Time Zone:
- Eastern Time - US & Canada (change)
- Campus:
- Remote
- Audience:
- Faculty Graduate Undergraduate
- Categories:
- Data Services Workshop