A RoCE-based network framework for science workloads in HEPS data center

According to the estimated data rates, it is predicted that 800 TB raw experimental data will be produced per day from 14 beamlines at the first stage of the High-Energy Photon Source (HEPS) in China, and the data volume will be even greater with the completion of over 90 beamlines at the second stage in the future. Therefore, designing a high-performance, scalable network architecture plays a crucial role in the efficient output of scientific tasks. We designed a RoCE-based network framework for science workloads in HEPS data center, which provides high-performance network connectivity both between HPES Data Acquisition system(DAQ) and HEPS data center, and between the compute and storage system within the HEPS data center.

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Publication Details

Journal
EPJ Web of Conferences
Published
2025-01-01
DOI
https://doi.org/10.1051/epjconf/202533701175
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
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article

A RoCE-based network framework for science workloads in HEPS data center

Fazhi Qi, Cui Tao, Yanming Wang, Shan Zeng
EPJ Web of Conferences
Distributed and Parallel Computing Systems
article

A RoCE-based network framework for science workloads in HEPS data center

Fazhi Qi, Cui Tao, Yanming Wang, Shan Zeng
article en

Abstract

According to the estimated data rates, it is predicted that 800 TB raw experimental data will be produced per day from 14 beamlines at the first stage of the High-Energy Photon Source (HEPS) in China, and the data volume will be even greater with the completion of over 90 beamlines at the second stage in the future. Therefore, designing a high-performance, scalable network architecture plays a crucial role in the efficient output of scientific tasks. We designed a RoCE-based network framework for science workloads in HEPS data center, which provides high-performance network connectivity both between HPES Data Acquisition system(DAQ) and HEPS data center, and between the compute and storage system within the HEPS data center.

EPJ Web of ConferencesVol. 337
Institute of High Energy Physics (CN)
Openalex Percentile: Top 68%
Distributed and Parallel Computing Systems
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