End-to-end data acquisition pipeline for the Cherenkov Telescope Array
E. Lyard, R. Walter (for the CTA Consortium)

TL;DR
This paper presents a comprehensive data acquisition pipeline designed for the Cherenkov Telescope Array, capable of handling high data rates, heterogeneous data formats, and providing real-time processing and analysis interfaces.
Contribution
It introduces a novel end-to-end data acquisition pipeline tailored for CTA, including data formatting, camera-specific algorithms, compression, and a Python interface for analysis.
Findings
Successfully handled raw data streams up to 43 Gbps per telescope
Implemented data formatting to a common structure for heterogeneous data
Achieved real-time data processing with current performance metrics
Abstract
The Cherenkov Telescope Array (CTA) will operate several types of telescopes and cameras. The individual camera trigger rates will vary much - from 0.6 to 15 kHz - while the content of the raw data will be heterogeneous. Raw data streams of up to 43 Gbps per telescope must be handled efficiently, from the camera front-ends down to the on-site repository and real-time analysis. In addition, the system must transcode all raw data to a common, pre-calibrated format. We will present the pipeline that we propose to implement this data acquisition pipeline. It will format the raw data to a common structure, provide facilities to run camera-specific algorithms and compress and write data to the on-site repository. We will also present the Python interface that allows the analysis pipeline to access the data. Eventually, the two strategies foreseen to interface the camera servers will be…
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