Parallel IO Libraries for Managing HEP Experimental Data

Author:

Bashyal Amit,Jones Christopher,Knoepfel Kyle,Van Gemmeren Peter,Sehrish Saba,Byna Suren

Abstract

The computing and storage requirements of the energy and intensity frontiers will grow significantly during the Run 4 & 5 and the HL-LHC era. Similarly, in the intensity frontier, with larger trig ger readouts during supernovae explosions, the Deep Underground Neutrino Experiment (DUNE) will have unique computing challenges that could be addressed by the use of parallel and accelerated dataprocessing capabilities. Most of the requirements of the energy and intensity frontier experiments rely on increasing the role of high performance computing (HPC) in the HEP community. In this presentation, we will describe our ongoing efforts that are focused on using HPC resources for the next generation HEP experiments. The HEPCCE (High Energy Physics-Center for Computational Excellence) IOS (Input/Output and Storage) group has been developing approaches to map HEP data to the HDF5 , an IO library optimized for the HPC platforms to store the intermediate HEP data. The complex HEP data products are serialized using ROOT to allow for experiment independent general mapping approaches of the HEP data to the HDF5 format. The mapping approaches can be optimized for high performance parallel IO. Similarly, simpler data can be directly mapped into the HDF5, which can also be suitable for offloading into the GPUs directly. We will present our works on both complex and simple data model models.

Publisher

EDP Sciences

Reference9 articles.

1. Bashyal A., Van Gemmeren P., Sehrish S., Knoepfel K., Byna S., Kang Q. (HEP-CCE IOS Group), Data Storage for HEP Experiments in the Era of High-Performance Computing, in 2022 Snowmass Summer Study (2022), 2203.07885

2. Marshall Z., Catmore J., Calafiura A., Girolamo Paolo Di, A. Collaboration, Tech. rep. (2022), https://cds.cern.ch/record/2800627

3. Peckham O., CERN is betting big on Exa-Scale (2022), “https://www.hpcwire.com/2021/04/01/cern-is-betting-big-on-exascale/”

4. Calafuira P., Habib S., HEP computational requirements on behalf of HEP-CCE (2022)

5. The HDF Group, Hierarchical data format version 5 (2000-2010), “http://www. hdfgroup.org/HDF5”

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