Research on distributed data acquisition software for high frame rate area detectors

BackgroundThe high frame rate area detector is the core detector for the major imaging-based experimental stations at the Shanghai HIgh repetitioN rate xfel and Extreme light facility (SHINE), and its data throughput is expected to reach more than 20 GB·s-1. For the real-time receiving and processing of tens of GB·s-1 raw data, traditional single-machine systems are difficult to cope with.PurposeThis study aims to propose a multi-node distributed data acquisition and processing software architecture for high frame rate area detector at imaging-based experimental stations of SHINE.MethodsFirstly, the performance of different network libraries was investigated, and the synchronous transmission method combined with CPU thread binding was found to have the best single-thread data receiving performance. Then, a parallel event building method was introduced by simultaneously dispatching and combing different module data across multiple nodes based on Bunch ID. Furthermore, the data calibration and the bitshuffle/LZ4 compression algorithm were implemented and tested.ResultsTest results show that the highest single-thread data receiving rate is achieved at nearly 3 GB·s-1, a parallel event building data rate of approximately 23.5 GB·s-1 is achieved by using 4 server nodes, and the realized compression ratio is about 5.7.ConclusionsThe feasibility of the multi-node distributed parallel data acquisition method for high frame rate area detector is verified in this study, providing a foundation for the subsequent development of high-throughput data acquisition software for area detectors.

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-10-01
DOI
https://doi.org/10.11889/j.0253-3219.2024.hjs.47.100403
Primary Topic
Optical Systems and Laser Technology
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on distributed data acquisition software for high frame rate area detectors

SHILAP Revista de lepidopterología
Optical Systems and Laser Technology
article

Research on distributed data acquisition software for high frame rate area detectors

article en

Abstract

BackgroundThe high frame rate area detector is the core detector for the major imaging-based experimental stations at the Shanghai HIgh repetitioN rate xfel and Extreme light facility (SHINE), and its data throughput is expected to reach more than 20 GB·s-1. For the real-time receiving and processing of tens of GB·s-1 raw data, traditional single-machine systems are difficult to cope with.PurposeThis study aims to propose a multi-node distributed data acquisition and processing software architecture for high frame rate area detector at imaging-based experimental stations of SHINE.MethodsFirstly, the performance of different network libraries was investigated, and the synchronous transmission method combined with CPU thread binding was found to have the best single-thread data receiving performance. Then, a parallel event building method was introduced by simultaneously dispatching and combing different module data across multiple nodes based on Bunch ID. Furthermore, the data calibration and the bitshuffle/LZ4 compression algorithm were implemented and tested.ResultsTest results show that the highest single-thread data receiving rate is achieved at nearly 3 GB·s-1, a parallel event building data rate of approximately 23.5 GB·s-1 is achieved by using 4 server nodes, and the realized compression ratio is about 5.7.ConclusionsThe feasibility of the multi-node distributed parallel data acquisition method for high frame rate area detector is verified in this study, providing a foundation for the subsequent development of high-throughput data acquisition software for area detectors.

SHILAP Revista de lepidopterología
Industry, innovation and infrastructure
Openalex Percentile: Top 71%
Optical Systems and Laser Technology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.