Let’s get our hands dirty: a comprehensive evaluation of DAQDB, key-value store for petascale hot storage

Author:

Abed Abud Adam,Cicalese Danilo,Jereczek Grzegorz,Le Goff Fabrice,Lehmann Miotto Giovanna,Love Jeremy,Maciejewski Maciej,Mommsen Remigius K,Radtke Jakub,Schmiegel Jakub,Szychowska Malgorzata

Abstract

Data acquisition systems are a key component for successful data taking in any experiment. The DAQ is a complex distributed computing system and coordinates all operations, from the data selection stage of interesting events to storage elements. For the High Luminosity upgrade of the Large Hadron Collider, the experiments at CERN need to meet challenging requirements to record data with a much higher occupancy in the detectors. The DAQ system will receive and deliver data with a significantly increased trigger rate, one million events per second, and capacity, terabytes of data per second. An effective way to meet these requirements is to decouple real-time data acquisition from event selection. Data fragments can be temporarily stored in a large distributed key-value store. Fragments belonging to the same event can be then queried on demand, by the data selection processes. Implementing such a model relies on a proper combination of emerging technologies, such as persistent memory, NVMe SSDs, scalable networking, and data structures, as well as high performance, scalable software. In this paper, we present DAQDB (Data Acquisition Database) — an open source implementation of this design that was presented earlier, with an extensive evaluation of this approach, from the single node to the distributed performance. Furthermore, we complement our study with a description of the challenges faced and the lessons learned while integrating DAQDB with the existing software framework of the ATLAS experiment.

Publisher

EDP Sciences

Reference7 articles.

1. The design of a distributed key-value store for petascale hot storage in data acquisition systems

2. Data AcQuisition DataBase, https://github.com/daq-db/daqdb

3. Leis V., Kemper A., Neumann T., The adaptive radix tree: ARTful indexing for mainmemory databases, in ICDE’13 (IEEE, 2013), pp. 38–49, ISBN 978-1-4673-4910-9

4. Kalia A., Kaminsky M., Andersen D.G., preprint arXiv:1806.00680 (2018)

5. LCG Info: Releases, Packages & Platforms, http://lcginfo.cern.ch/

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3