Speaker
Description
As Serial Micro- CT moves toward routine, high-throughput imaging of large sample collections, the underlying DAQ software must support flexible orchestration, distributed processing, and seamless integration of online services. We present a decentralized software architecture that addresses these requirements through a stream-oriented design. In this framework, an “experiment” is conceptualized as foundational concept for a measurement, representing an ordered collection of “acquisitions”. An acquisition acts as an asynchronous named data source, while processing functionality is encapsulated in independent “addons” that can attach to and detach from remote streams as needed. These addons consume incoming streams, perform online analysis, and optionally emit new streams to downstream services using ZeroMQ . The architecture thereby separates acquisition from processing and allows online reconstruction, quality assurance, live view, and data-writing tasks to run as decoupled compute nodes serving remote procedure calls. Nodes can further exchange information using event-driven framework, enabling coordination across the decentralized system. In the context of Serial Micro-CT, this approach provides flexibility to scale data processing with experimental demands, while maintaining a clear separation of responsibilities. We also outline ongoing efforts to improve reconstruction throughput on GPUs as part of this distributed workflow. Together, these developments establish a software foundation for scalable and adaptable beamline operation.
