Speaker
Description
The CBM First-Level Event Selector (FLES) serves as the central data processing and event selection system for the upcoming CBM experiment at FAIR. Designed as a scalable high-performance computing cluster, it facilitates online event reconstruction and selection of unfiltered physics data at rates surpassing 1 TByte/s. The FLES input data originates from approximately 5000 detector links, each delivering time-stamped messages in a free-streaming data acquisition mode. For efficient data handling, these detector data streams are time-partitioned into context-free packages called microslices, which are subsequently aggregated into larger processing intervals known as timeslices.
We present a new design for the FLES input processing chain that introduces subtimeslices as a new data structure enabling local aggregation of timeslice components on entry nodes. The main characteristic of the new design is a shift from data-driven to wall-time-driven operation with dynamic timeslice component building.
Exploiting the time information inherent in the data streams, the content of each timeslice component is dynamically determined by evaluating the timestamps of available microslices against the defined time boundaries of the timeslice component. Subtimeslices are assembled opportunistically based on wall time ensuring that subtimeslices are formed even when some contributions are delayed or missing. As an additional benefit, this approach enables automatic synchronization of channels into the data stream without complex extra logic, as channels automatically participate once new microslices become available.
These developments significantly improve resilience against detector malfunctions and overload conditions, reduce networking overhead and buffer fragmentation, and enable modular system startup. The redesigned system is currently operational in our development setup, with deployment to production planned for the upcoming beam time campaigns.
This work is supported by BMFTR (05P24RF3).