Public Documentation for US ATLAS Analysis Facilities¶
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US ATLAS hosts three shared Tier 3 computing spaces at BNL, SLAC, and UChicago, also known as Analysis Facilities (AF). These three facilities are available to all US ATLAS physicists and computer scientists. They are organized and managed to support US ATLAS users' need for computing resources including login, run interactive and batch jobs, access ATLAS data, store private data, etc.
View the facility usage dashboard
The AFs also support a wide variety of tools specific for analysis, including ATLAS/CERN software in CVMFS, Grid middleware, Rucio clients, Machine Learning packages, MPI, Jupyter Lab with PyROOT, XCache with auto data discovery, GPUs, etc. The three facilities are backed by staff to support software environments, unix systems and storage.
Need Help?
See our Getting Help page for support options and how to reach the ATLAS AF team.
Documentation Overview¶
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User Onboarding
Details the process of applying for user accounts at BNL, SLAC, and UChicago
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Quickstart Guides
Walkthroughs for accessing the Analysis Facilities
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Machine Learning Containers
Information and use of ML containers
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ATLAS Containers
Information and use of ATLAS containers
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Data Storing, Accessing, and Sharing
Explains the ways users can use their ATLAS data at AFs
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Jupyter at Analysis Facilities
Highlights the different aspects of Jupyter and how to use it at AFs
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Data Analysis Tutorials
Step-by-step tutorials on using AFs for analyses
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Containers
Detailed information on container-based data processing and how to use them at AFs
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Using VSCode
Detailed guide on using Visual Studio Code
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FAQ
Answers to frequently asked questions