Yu, Se-young | Engineering Papers

DOE OSTI2025

ESnet Data and AI Workshop Report

In February 2025, the DOE user facility Energy Sciences Network (ESnet) held a three-day Data and AI Workshop in Berkeley, California. The objective of the workshop was to identify challenges within ESnet that could be addressed through data-driven methods, to help define ESnet’s data-analysis requirements, and to shape its AI strategy, guiding data-stewardship efforts and the direction of AI research and AIOps exploration for ESnet7, the next iteration of ESnet’s network. This report summarizes the multi-faceted discussions and findings and presents a set of recommendations for next steps.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

ROBIN (RuciO/BIgData Express/SENSE) A Next-Generation High-Performance Data Service Platform

Increasingly, scientific research discoverydepends on the analysis of extremely large amounts of data. Thisdata is gathered through very large scientific instruments, verylarge numbers of small devices, and mid-scale instruments.These devices generate exponentially increasing volumes of data.Such data is often obtained, analyzed, stored, visualized, andtransferred at and among sites world-wide by largecollaborations of science communities. Managing and movingextremely large volumes of data across today’s networks is aspecial multidimensional challenge. Also, existing datamanagement and movement services and tools often areinadequate to address all specific requirements. This paperdescribes the various components of this challenge and howthose issues can be addressed by ROBIN, a uniquecomprehensive set of integrated services designed specificallyfor managing and moving extremely large amounts of data overlong distances, e.g., thousands of miles around the globe. Thispaper also describes the results of initial experiments using thatset of integrated services.

Wu, Wenji↗