Detector integration at HEPS: a systematic, efficient and high-performance approach

TL;DR

This paper presents a systematic approach for detector integration at HEPS, including software extensions and a new high-performance framework that overcomes existing limitations, enhancing efficiency and scalability.

Contribution

It introduces a comprehensive, high-performance detector integration framework based on QueueIOC and ZeroMQ, extending ADGenICam, and analyzing areaDetector's limitations for improved scalability.

Findings

Extended ADGenICam to support more detectors

Developed QueueIOC-based framework with ZeroMQ for data transport

Analyzed and addressed areaDetector's performance limitations

Abstract

At least 25 kinds of detector-like devices need to be integrated in Phase I of the High Energy Photon Source (HEPS), and the work needs to be carefully planned to maximise productivity with highly limited human resources. After a systematic analysis on the actual work involved in detector integration, a separation of concerns between collaborating groups of personnel is established to minimise the duplication of efforts. To facilitate software development for detector integration, the ADGenICam library, which abstracts repeated code in EPICS modules for cameras, is extended to support a much wider range of detectors. An increasingly considerable fraction of detectors, both inside and outside HEPS, offer performance that exceed capabilities of the areaDetector framework in EPICS. Given this background, areaDetector's limitations in performance and architecture are analysed, and a QueueIOC -based framework that overcomes these limitations is introduced. A simple, flexible ZeroMQ-based protocol is used for data transport in this framework, while RDMA transport and multi-node readout will be explored for higher data throughputs. By calling C/C++ libraries from within Python, the performance of the former and the expressiveness of the latter can coexist nicely; the expressiveness allows for much higher efficiency in the implementation and use of integration modules functionally comparable to their EPICS counterparts.