Speaker
Description
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 days and produce tens of petabytes of raw image data and associated calibration data. More than 20 terabytes of data must be processed and stored every night for ten years.
The Production and Distributed Analysis (PanDA) system was evaluated by the Vera C. 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, it’s 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 and alerts issued within 60 seconds.
This presentation will briefly describe the Vera C. Rubin Data Management system and its use at both the Interim Data Facility (IDF) hosted on the Google Cloud Platform (GCP) and the United States Data Facility (USDF) hosted at the SLAC Shared Scientific Data Facility (S3DF). Finally, it will describe in depth the work performed in order to integrate the PanDA system with the Vera Rubin Observatory to be able to run the Rubin Science Pipelines using PanDA.
| Consider for long presentation | No |
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