ATLAS Data Analysis using a Parallel Workflow on Distributed Cloud-based Services with GPUs

Journal Article · 06 May 2024 · EPJ Web of Conferences (Online)

DOI: https://doi.org/10.1051/epjconf/202429504007 · OSTI ID:2429532

Sandesara, Jay ^[1]; Coelho Lopes de Sa, Rafael ^[1]; Martinez Outschoorn, Verena ^[1]; Barreiro Megino, Fernando ^[2]; Elmsheuser, Johannes ^[3]; Klimentov, Alexei ^[3]

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1. Univ. of Massachusetts, Amherst, MA (United States)
2. Univ. of Texas, Arlington, TX (United States)
3. Brookhaven National Laboratory (BNL), Upton, NY (United States)

A new type of parallel workflow is developed for the ATLAS experiment at the Large Hadron Collider, that makes use of distributed computing combined with a cloud-based infrastructure. This has been developed for a specific type of analysis using ATLAS data, one popularly referred to as Simulation-Based Inference (SBI). The JAX library is used for the parts of the workflow to compute gradients as well as accelerate program execution using just-in-time compilation, which becomes essential in a full SBI analysis and can also offer significant speed-ups in more traditional types of analysis.

• Research Organization: Brookhaven National Laboratory (BNL), Upton, NY (United States)
• Sponsoring Organization: USDOE Office of Science (SC), High Energy Physics (HEP)
• Grant/Contract Number: SC0012704
• OSTI ID: 2429532
• Report Number(s): BNL--225908-2024-JAAM
• Journal Information: EPJ Web of Conferences (Online), Journal Name: EPJ Web of Conferences (Online) Vol. 295; ISSN 2100-014X
• Publisher: EDP SciencesCopyright Statement
• Country of Publication: United States
• Language: English