SC22 Proceedings

The International Conference for High Performance Computing, Networking, Storage, and Analysis

Workshops Archive

Testing the Data Framework for an AI Algorithm in Preparation for High Data Rate X-Ray Facilities

Workshop: The 4th Annual Workshop on Extreme-Scale Experiment-in-the-Loop Computing

Authors: Hongwei Chen (SLAC National Accelerator Laboratory), Sathya Chitturi (Stanford University), and Rajan Plumley (SLAC National Accelerator Laboratory)

Abstract: The advent of next-generation X-ray free electron lasers will be capable of delivering X-rays at a repetition rate approaching 1 MHz continuously. This will require the development of data systems to handle experiments at these type of facilities, especially for high throughput applications, such as femtosecond X-ray crystallography and X-ray photon fluctuation spectroscopy. Here, we demonstrate a framework which captures single shot X-ray data at the LCLS and implements a machine-learning algorithm to automatically extract the contrast parameter from the collected data. We measure the time required to return the results and assess the feasibility of using this framework at high data volume. We use this experiment to determine the feasibility of solutions for ‘live’ data analysis at the MHz repetition rate.

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