| Issue |
EPJ Web of Conf.
Volume 295, 2024
26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023)
|
|
|---|---|---|
| Article Number | 05014 | |
| Number of page(s) | 8 | |
| Section | Sustainable and Collaborative Software Engineering | |
| DOI | https://doi.org/10.1051/epjconf/202429505014 | |
| Published online | 06 May 2024 | |
https://doi.org/10.1051/epjconf/202429505014
Meld Exploring the Feasibility of a Framework-less Framework
Fermi National Accelerator Laboratory, P.O. Box 500, Batavia, Illinois, United States
* e-mail: knoepfel@fnal.gov
Published online: 6 May 2024
HEP data-processing frameworks are essential ingredients in getting from raw data to physics results. But they are often tricky to use well, and they present a significant learning barrier for the beginning HEP physicist. In addition, existing frameworks typically support rigid, collider-based data models, which do not map well to neutrino-physics experiments like DUNE. Neutrino physicists thus expend significant effort working around framework limitations instead of using a framework that directly supports their needs.
Presented here is Meld, a Fermilab R&D project, which intends to address these limitations. By leveraging modern C++ capabilities, state-of-the-art concurrency libraries, and a flexible data model, it is possible for beginning (and seasoned) HEP physicists to execute framework programs easily and efficiently, with minimal coupling to framework-specific constructs. Meld aims to directly support the frameworks needs of neutrino experiments like DUNE as well as the more common collider-based experiments.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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