| Issue |
EPJ Web of Conf.
Volume 295, 2024
26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023)
|
|
|---|---|---|
| Article Number | 04007 | |
| Number of page(s) | 8 | |
| Section | Distributed Computing | |
| DOI | https://doi.org/10.1051/epjconf/202429504007 | |
| Published online | 06 May 2024 | |
https://doi.org/10.1051/epjconf/202429504007
ATLAS Data Analysis using a Parallel Workflow on Distributed Cloud-based Services with GPUs
1 University of Massachusetts Amherst, Amherst, MA, USA
2 University of Texas at Arlington, Arlington, TX, USA
3 Brookhaven National Laboratory, Upton, NY, USA
* e-mail: jay.ajitbhai.sandesara@cern.ch
Published online: 6 May 2024
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.
© The Authors, published by EDP Sciences, 2024
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