Near real-Time analysis of big fusion data on HPC systems

Ralph Kube, R. Michael Churchill, Jong Choi, Ruonan Wang, Minjun Choi, Scott Klasky, C. S. Chang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

We are developing the Delta framework that aims to tackle big-data challenges specific to fusion energy sciences. Delta can be used to connect fusion experiments to remote supercomputers. Streaming measurements to distributed compute resources allows to automatically perform high-dimensional data analysis on a cadence that exceeds experimental schedules. Making data analysis results available before the next experiments allows scientists to make more informed decisions about configuration of upcoming experiments. Here we describe how Delta uses database and virtualization facilities, as well as high-performance computing, at the National Energy Research Compute Center to offer a vertically integrated near real-Time data analysis and visualization. We also report on ongoing efforts to port the data analysis part of Delta to graphical processing units, which show a reduction of the analysis wall-Time for a benchmark workflow by about 35% when compared to a serial implementation.

Original languageEnglish
Title of host publicationProceedings of UrgentHPC 2020
Subtitle of host publication2020 International Workshops on Urgent and Interactive HPC, Held in conjunction with SC 2020: The International Conference for High Performance Computing, Networking, Storage and Analysis
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages55-63
Number of pages9
ISBN (Electronic)9781665422741
DOIs
StatePublished - Nov 2020
Event2020 IEEE/ACM International Workshops on Urgent and Interactive HPC, UrgentHPC 2020 - Virtual, Atlanta, United States
Duration: Nov 13 2020 → …

Publication series

NameProceedings of UrgentHPC 2020: 2020 International Workshops on Urgent and Interactive HPC, Held in conjunction with SC 2020: The International Conference for High Performance Computing, Networking, Storage and Analysis

Conference

Conference2020 IEEE/ACM International Workshops on Urgent and Interactive HPC, UrgentHPC 2020
Country/TerritoryUnited States
CityVirtual, Atlanta
Period11/13/20 → …

Funding

ACKNOWLEDGEMENTS The authors are pleased to acknowledge that the work reported on in this paper was substantially performed using the Princeton Research Computing resources at Princeton University which is consortium of groups led by the Princeton Institute for Computational Science and Engineering (PICSciE) and Office of Information Technology’s Research Computing. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility operated under Contract No. DE-AC02-05CH11231.

FundersFunder number
U.S. Department of EnergyDE-AC02-05CH11231

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