Speaker
Description
Recent advancements in high-repetition-rate x-ray sources and experimental complexity at large-scale facilities, such as FLASH (Free electron LASer in Hamburg), have placed increasing demands on data acquisition and analysis systems. While HPSS (High Performance Storage Systems) and HPC (High Performance Computing) clusters provide efficient resources for processing the vast data generated, many users face steep learning curves in accessing and analyzing this data efficiently. We introduce fab (Flash Analysis for Beamtimes), a Python-based library designed to streamline data loading and analysis at FLASH. fab automates the data retrieval and synchronization processes, handles interactions with the cluster workload manager, and provides an accessible platform for users with varying levels of data science experience. By simplifying the handling of device-specific formats and HPC configurations, fab enables researchers to focus on experiment-specific analyses without needing extensive technical expertise.
