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DTSTAMP:20210402T160546Z
LOCATION:Track 11
DTSTART;TZID=America/New_York:20201113T155000
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UID:submissions.supercomputing.org_SC20_sess233_ws_ihpc102@linklings.com
SUMMARY:Accelerating Fusion Energy Experimental Workflows Using HPC Resour
 ces
DESCRIPTION:Workshop\n\nAccelerating Fusion Energy Experimental Workflows 
 Using HPC Resources\n\nKube, Churchill, Choi, Wang, Klasky...\n\nExperimen
 ts on magnetic fusion energy routinely generate high-velocity, large-volum
 e datasets. In experiments, which last about one minute with about 30 minu
 te cool-down phases in between them, numerous diagnostics sample high-temp
 erature fusion plasmas with ever increasing spatial and temporal resolutio
 n. Analyzing and presenting these measurements in near real-time to the sc
 ience team aids in the rapid assessment of just-concluded experiments. It 
 also allows to make more informed decisions on setting up follow-up experi
 ments, thereby accelerating scientific discovery. Facilitating this workfl
 ow on HPC facilities requires, besides raw computational power, consistent
 ly available high-network throughput, and the availability of a database t
 hat is accessible from inside the HPC facility as well as externally.<br /
 ><br />We are developing the DELTA framework that aims to tackle these cha
 llenges specific to fusion energy sciences. For one, the workflows are oft
 en non-static. Depending on the data source and situation, different analy
 ses need to be performed. DELTA is aimed to be highly configurable and fac
 ilitate a broad range of workflows. Parallelizing data analysis routines, 
 which are often run on workstations, to HPC settings also requires to make
  choices between data and task parallelism. Finally, DELTA aims to provide
  real-time analysis results. As such, it needs to span from the data sourc
 e to the visualization output. Implementing this software architecture on 
 modern HPC systems requires to coordinate the interaction of multiple soft
 ware components.<br /><br />In this paper we describe the implementation a
 nd performance of DELTA on Cori, a Cray XC-40 supercomputer operated by th
 e National Energy Research Scientific Compute Center (NERSC) in California
 . Leveraging the ADIOS2 I/O library, DELTA allows to routinely stream meas
 urement data from the KSTAR fusion facility in Korea to Cori with more tha
 n 500 MByte/sec. Distributing data analysis tasks among Cori compute nodes
  allows to perform routine correlation analysis over 100 times faster than
  on a traditional single-core workstations. The analyzed data is stored on
  a local no-SQL database instance. There it is consumed by a single-page w
 eb application, running on NERSC's spin container service, to provide real
 -time visualization to the science team. We further describe current effor
 ts to incorporate machine learning for data compression and select relevan
 t portions of the data stream to analyze.\n\nTag: Interactive HPC\n\nRegis
 tration Category: Workshop Reg Pass
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