2023/08/31 by Knoepfel, Kyle J.
#Computational Physics (physics.comp-ph) #D.1.1 #D.1.3 #Distributed #FOS: Computer and information sciences #FOS: Physical sciences #G.2.m #High Energy Physics - Experiment (hep-ex) #Parallel #and Cluster Computing (cs.DC)
paper · doi:10.48550/arxiv.2308.16710
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.