Speaker
Description
The increase in velocity, volume, and complexity of
the data generated by the upcoming LCLS-II upgrade presents a
considerable challenge for data acquisition, data processing, and
data management. These systems face formidable challenges due
to the extremely high data throughput, hundreds of GB/s to multi-
TB/s, generated by the detectors at the experimental facilities and
to the intensive computational demand for data processing and
scientific interpretation. The LCLS-II Data System offers a fast,
powerful, and flexible architecture that includes a feature
extraction layer designed to reduce the data volumes by at least
one order of magnitude while preserving the science content of the
data. Innovative architectures are required to implement this
reduction with a configurable approach that can adapt to the
multiple science areas served by LCLS. In order to increase the
likelihood of experiment success and improve the quality of
recorded data, a real-time analysis framework provides
visualization and graphically-configurable analysis of a selectable
subset of the data on the timescale of seconds. A fast feedback layer
offers dedicated processing resources to the running experiment
in order to provide experimenters feedback about the quality of
acquired data within minutes. We will present an overview of the
LCLS-II Data System architecture with an emphasis on the Data
Reduction Pipeline (DRP) and online monitoring framework.
| Minioral | Yes |
|---|---|
| IEEE Member | No |
| Are you a student? | No |
