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Experience and performance of persistent memory for the DUNE data acquisition system

Emerging high-performance storage technologies are opening up the possibility of designing new distributed data acquisition (DAQ) system architectures, in which the live acquisition of data and their processing are decoupled through a storage element. An example of these technologies is 3D XPoint, w...

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Detalles Bibliográficos
Autores principales: Abed Abud, Adam, Miotto, Giovanna Lehmann, Sipos, Roland
Lenguaje:eng
Publicado: 2020
Materias:
Acceso en línea:https://dx.doi.org/10.1109/TNS.2021.3084848
http://cds.cern.ch/record/2746226
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author Abed Abud, Adam
Miotto, Giovanna Lehmann
Sipos, Roland
author_facet Abed Abud, Adam
Miotto, Giovanna Lehmann
Sipos, Roland
author_sort Abed Abud, Adam
collection CERN
description Emerging high-performance storage technologies are opening up the possibility of designing new distributed data acquisition (DAQ) system architectures, in which the live acquisition of data and their processing are decoupled through a storage element. An example of these technologies is 3D XPoint, which promises to fill the gap between memory and traditional storage and offers unprecedented high throughput for nonvolatile data. In this article, we characterize the performance of persistent memory devices that use the 3D XPoint technology, in the context of the DAQ system for one large Particle Physics experiment, DUNE. This experiment must be capable of storing, upon a specific signal, incoming data for up to 100 s, with a throughput of 1.5 TB/s, for an aggregate size of 150 TB. The modular nature of the apparatus allows splitting the problem into 150 identical units operating in parallel, each at 10 GB/s. The target is to be able to dedicate a single CPU to each of those units for DAQ and storage.
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publishDate 2020
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spelling cern-27462262023-03-14T19:07:05Zdoi:10.1109/TNS.2021.3084848http://cds.cern.ch/record/2746226engAbed Abud, AdamMiotto, Giovanna LehmannSipos, RolandExperience and performance of persistent memory for the DUNE data acquisition systemphysics.ins-detDetectors and Experimental TechniquesEmerging high-performance storage technologies are opening up the possibility of designing new distributed data acquisition (DAQ) system architectures, in which the live acquisition of data and their processing are decoupled through a storage element. An example of these technologies is 3D XPoint, which promises to fill the gap between memory and traditional storage and offers unprecedented high throughput for nonvolatile data. In this article, we characterize the performance of persistent memory devices that use the 3D XPoint technology, in the context of the DAQ system for one large Particle Physics experiment, DUNE. This experiment must be capable of storing, upon a specific signal, incoming data for up to 100 s, with a throughput of 1.5 TB/s, for an aggregate size of 150 TB. The modular nature of the apparatus allows splitting the problem into 150 identical units operating in parallel, each at 10 GB/s. The target is to be able to dedicate a single CPU to each of those units for DAQ and storage.Emerging high-performance storage technologies are opening up the possibility of designing new distributed data acquisition system architectures, in which the live acquisition of data and their processing are decoupled through a storage element. An example of these technologies is 3DXPoint, which promises to fill the gap between memory and traditional storage and offers unprecedented high throughput for data persistency. In this paper, we characterize the performance of persistent memory devices, which use the 3DXPoint technology, in the context of the data acquisition system for one large Particle Physics experiment, DUNE. This experiment must be capable of storing, upon a specific signal, incoming data for up to 100 seconds, with a throughput of 1.5 TB/s, for an aggregate size of 150 TB. The modular nature of the apparatus allows splitting the problem into 150 identical units operating in parallel, each at 10 GB/s. The target is to be able to dedicate a single CPU to each of those units for data acquisition and storage.arXiv:2011.01341oai:cds.cern.ch:27462262020-10-30
spellingShingle physics.ins-det
Detectors and Experimental Techniques
Abed Abud, Adam
Miotto, Giovanna Lehmann
Sipos, Roland
Experience and performance of persistent memory for the DUNE data acquisition system
title Experience and performance of persistent memory for the DUNE data acquisition system
title_full Experience and performance of persistent memory for the DUNE data acquisition system
title_fullStr Experience and performance of persistent memory for the DUNE data acquisition system
title_full_unstemmed Experience and performance of persistent memory for the DUNE data acquisition system
title_short Experience and performance of persistent memory for the DUNE data acquisition system
title_sort experience and performance of persistent memory for the dune data acquisition system
topic physics.ins-det
Detectors and Experimental Techniques
url https://dx.doi.org/10.1109/TNS.2021.3084848
http://cds.cern.ch/record/2746226
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