Speaker
Description
The Advanced Light Source Upgrade (ALS-U) is a major upgrade project for the existing light source at the Lawrence Berkeley National Laboratory. There is a growing interest in the community to employ ML/AI methods to use predictive analysis, optimization and error fault analysis. In order to enable those methods, a rich dataset must be available and integrated into the control system. This project aims at collecting, storing and providing methods to retrieve, initially, BPM data from the ALS-U Storage Ring, by using an additional, passive node connected to the Fast Orbit Feedback network. The data rate from just the BPMs alone would be on the order of 1Gbps (updating at a rate of 10kHz) with the requirement that the system must be able to store the data for 1 week, in a continuous manner, totaling dozens of TB of data. This paper describes a conceptual design and prototype details of the Fast Archiver. The authors are confident that the archiver can be easily extended to archiving other useful metrics of the ALS-U, like power supply setpoints and monitoring data.
Funding Agency
Work supported by the Director, Office of Science, Office of Basic Energy
Sciences, of the U.S. Department of Energy under Contract No. DEAC02-05CH11231.
