The LBNL Superfacility Project Report
Deborah Bard, Cory Snavely, Lisa Gerhardt, Jason Lee, Becci Totzke,, Katie Antypas, William Arndt, Johannes Blaschke, Suren Byna, Ravi Cheema,, Shreyas Cholia, Mark Day, Bjoern Enders, Aditi Gaur, Annette Greiner, Taylor, Groves, Mariam Kiran, Quincey Koziol, Tom Lehman

TL;DR
The LBNL Superfacility project developed an integrated ecosystem of tools, infrastructure, and policies to enable large-scale, automated data analysis for experimental science across multiple national facilities.
Contribution
It introduced a comprehensive model for a connected scientific ecosystem supporting automation, real-time computing, and cross-disciplinary collaboration in high-performance environments.
Findings
Automated large-scale data analysis pipelines demonstrated
Production-level services established for remote facilities
Lessons provided for future large-scale scientific collaborations
Abstract
The Superfacility model is designed to leverage HPC for experimental science. It is more than simply a model of connected experiment, network, and HPC facilities; it encompasses the full ecosystem of infrastructure, software, tools, and expertise needed to make connected facilities easy to use. The three-year Lawrence Berkeley National Laboratory (LBNL) Superfacility project was initiated in 2019 to coordinate work being performed at LBNL to support this model, and to provide a coherent and comprehensive set of science requirements to drive existing and new work. A key component of the project was the in-depth engagements with eight science teams that represent challenging use cases across the DOE Office of Science. By the close of the project, we met our project goal by enabling our science application engagements to demonstrate automated pipelines that analyze data from remote…
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Taxonomy
TopicsScientific Computing and Data Management · Advanced Data Storage Technologies · Cloud Computing and Resource Management
