Title: Emerging Computational Workflows for Experiments at Particle Accelerators

Speaker: Christine Sweeney

Modern upgraded particle accelerator facilities are providing increased data volumes and velocity along with potentially shorter data collection times.  Facility users are faced with many challenges in data analytics to support their experiments during beam time and in post-processing.   The good news is that new software tools, AI/ML techniques, and hardware resources are becoming available.  In this talk I will present three computational workflows: 1) real-time data analytics for dynamic diamond anvil cell and dynamic compression light source experiments, 2) an interfacility (light source to supercomputer) workflow for scalable single particle imaging, and 3) machine learning workflows for control and analysis of accelerator experiments.   I will also mention some promising DOE efforts to support computational workflows at DOE facilities.  Lastly, I will point to some future trends in computational workflows for accelerator applications.