| Issue |
EPJ Web of Conf.
Volume 295, 2024
26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023)
|
|
|---|---|---|
| Article Number | 02025 | |
| Number of page(s) | 6 | |
| Section | Online Computing | |
| DOI | https://doi.org/10.1051/epjconf/202429502025 | |
| Published online | 06 May 2024 | |
https://doi.org/10.1051/epjconf/202429502025
Streaming Readout and Data-Stream Processing With ERSAP
JLAB, CST Division, 12000 Jefferson Avenue, Newport News, Virginia, 23606, USA
* Corresponding author: gurjyan@jlab.org
Published online: 6 May 2024
With the exponential growth in the volume and complexity of data generated at high-energy physics and nuclear physics research facilities, there is an imperative demand for innovative strategies to process this data in real or near-real-time. Given the surge in the requirement for high-performance computing, it becomes pivotal to reassess the adaptability of current data processing architectures in integrating new technologies and managing streaming data. This paper introduces the ERSAP framework, a modern solution that synergizes flow-based programming with the reactive actor model, paving the way for distributed, reactive, and high performance in data stream processing applications. Additionally, we unveil a novel algorithm focused on time-based clustering and event identification in data streams. The efficacy of this approach is further exemplified through the data-stream processing outcomes obtained from the recent beam tests of the EIC prototype calorimeter at DESY.
© The Authors, published by EDP Sciences, 2024
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