Speaker
Description
Modern detectors typically consist of multiple modules to achieve large areas and generate increasingly high data rates. Synchronization across these modules, together with efficient real-time data handling, is therefore essential for enabling responsive and data-driven experiments.
ASAP::O, a high-performance streaming framework designed for low-latency data transport and scalable processing, has been developed and deployed at DESY. It decouples data acquisition from analysis via a producer–consumer architecture, enabling parallel data streaming, online processing, and distributed access. Because of its built-in synchronization mechanisms, ASAP::O provides unified and consistent access to data originating from multi-module detector systems, as well as from multiple detectors.
At DESY, ASAP::O is used for live detector data streaming to analysis nodes, integration with automated processing pipelines, and implementation of feedback-driven experimental workflows. These capabilities enable near real-time monitoring and support adaptive experiment control under high-throughput conditions.
Our results demonstrate that ASAP::O provides a robust and scalable backbone for next-generation data acquisition, enabling efficient workflows and supporting the transition toward autonomous beamline operation in preparation for the PETRA IV upgrade.
