Integrating the PanDA Workload Management System with the Vera C. Rubin Observatory
- Brookhaven
- Fermilab
- Texas U., Arlington
- SLAC
- Illinois U., Urbana (main)
- Gemini Observ., La Serena
- Pittsburgh U.
The Vera C. Rubin Observatory will produce an unprecedented astronomical data set for studies of the deep and dynamic universe. Its Legacy Survey of Space and Time (LSST) will image the entire southern sky every three to four days and produce tens of petabytes of raw image data and associated calibration data over the course of the experiment’s run. More than 20 terabytes of data must be stored every night, and annual campaigns to reprocess the entire dataset since the beginning of the survey will be conducted over ten years. The Production and Distributed Analysis (PanDA) system was evaluated by the Rubin Observatory Data Management team and selected to serve the Observatory’s needs due to its demonstrated scalability and flexibility over the years, for its Directed Acyclic Graph (DAG) support, its support for multi-site processing, and its highly scalable complex workflows via the intelligent Data Delivery Service (iDDS). PanDA is also being evaluated for prompt processing where data must be processed within 60 seconds after image capture. This paper will briefly describe the Rubin Data Management system and its Data Facilities (DFs). Finally, it will describe in depth the work performed in order to integrate the PanDA system with the Rubin Observatory to be able to run the Rubin Science Pipelines using PanDA.
- Research Organization:
- SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States); Brookhaven National Laboratory (BNL), Upton, NY (United States); Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
- DOE Contract Number:
- AC02-07CH11359
- OSTI ID:
- 2468771
- Report Number(s):
- FERMILAB-CONF-24-0687-CSAID; oai:inspirehep.net:2785705
- Conference Information:
- Journal Name: EPJ Web Conf. Journal Volume: 295
- Country of Publication:
- United States
- Language:
- English
Design and development of the 3.2 gigapixel camera for the Large Synoptic Survey Telescope
|
conference | July 2010 |
The Vera C. Rubin Observatory Data Butler and pipeline execution system
|
conference | August 2022 |
LSST: From Science Drivers to Reference Design and Anticipated Data Products
|
journal | March 2019 |
ATLAS Data Carousel
|
journal | January 2020 |
Rucio: Scientific Data Management
|
journal | August 2019 |
Similar Records
Integrating the PanDA Workload Management System with the Vera C. Rubin Observatory
Preparation of the Multi-Site Data Processing at the Vera C. Rubin Observatory
PanDA: Production and Distributed Analysis System
Journal Article
·
Sun May 05 20:00:00 EDT 2024
· EPJ Web of Conferences (Online)
·
OSTI ID:2281342
Preparation of the Multi-Site Data Processing at the Vera C. Rubin Observatory
Conference
·
Wed Oct 01 00:00:00 EDT 2025
· EPJ Web Conf.
·
OSTI ID:3003660
PanDA: Production and Distributed Analysis System
Journal Article
·
Mon Jan 22 19:00:00 EST 2024
· Computing and Software for Big Science
·
OSTI ID:2283314