Issue |
EPJ Web Conf.
Volume 251, 2021
25th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2021)
|
|
---|---|---|
Article Number | 04013 | |
Number of page(s) | 8 | |
Section | Online Computing | |
DOI | https://doi.org/10.1051/epjconf/202125104013 | |
Published online | 23 August 2021 |
https://doi.org/10.1051/epjconf/202125104013
Evaluation of a high-performance storage buffer with 3D XPoint devices for the DUNE data acquisition system
1 Brookhaven National Laboratory, Upton, NY, USA
2 European Laboratory for Particle Physics (CERN), Geneva 23, CH-1211, Switzerland
3 Fermi National Accelerator Laboratory, Batavia, IL, USA
4 University of Liverpool, The Oliver Lodge, Oxford St, Liverpool L69 7ZE, United Kingdom
5 University of Oxford, Oxford OX1 3RH, United Kingdom
6 Rutherford Appleton Laboratory, Didcot, United Kingdom
* e-mail: adam.abed.abud@cern.ch
Published online: 23 August 2021
The DUNE detector is a neutrino physics experiment that is expected to take data starting from 2028. The data acquisition (DAQ) system of the experiment is designed to sustain several TB/s of incoming data which will be temporarily buffered while being processed by a software based data selection system. In DUNE, some rare physics processes (e.g. Supernovae Burst events) require storing the full complement of data produced over 1-2 minute window. These are recognised by the data selection system which fires a specific trigger decision. Upon reception of this decision data are moved from the temporary buffers to local, high performance, persistent storage devices. In this paper we characterize the performance of novel 3DXPoint SSD devices under different workloads suitable for high-performance storage applications. We then illustrate how such devices may be applied to the DUNE use-case: to store, upon a specific signal, 100 seconds of incoming data at 1.5 TB/s distributed among 150 identical units each operating at approximately 10GB/s.
© The Authors, published by EDP Sciences, 2021
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.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.