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SUMMARY:Fusing Experiments\, Data\, and Computing at DIII-D and ALCF
DTSTART:20260716T180000Z
DTEND:20260716T190000Z
DTSTAMP:20260715T182000Z
UID:indico-event-897@events.cels.anl.gov
CONTACT:ALCFevents@alcf.anl.gov
DESCRIPTION:Modern experimental user facilities increasingly rely on a tig
 ht integration between experimental operations\, high-performance computin
 g (HPC)\, and streamlined data access. This two-part presentation highligh
 ts how the DIII-D National Fusion Facility is pioneering this space throug
 h automated remote analysis and the Fusion Data Platform (FDP)\, serving a
 s a blueprint for the broader Integrated Research Infrastructure (IRI) ini
 tiatives.\nPart 1: Automatic On-Demand Remote Analyses for Fusion Experime
 nts Mark Kostuk\, General Atomics \nPart 1 will focus on the DIII-D "digit
 al twin\," demonstrating how automated\, on-demand workflows utilize the G
 lobus API (Flows and Compute) to trigger resource-intensive plasma modelin
 g codes at leadership compute facilities (LCFs) like NERSC and ALCF immedi
 ately following an experiment.\nPart 2: An AI-Ready Data Harness for Fusio
 n: The Fusion Data Platform Brian Sammuli\, General Atomics\nPart 2 intro
 duces the Fusion Data Platform (FDP)\, a software stack that delivers fusi
 on data to any machine in the world through one common interface. FDP offe
 rs reusable patterns for scientists to reach and combine data across devic
 es\, integrating leadership-class facilities and AI workflows.\nSpeakers\n
 Dr. Mark Kostuk obtained his PhD in physics from The University of Califor
 nia\, San Diego with a focus on nonlinear dynamics system identification\,
  control theory and chaotic data assimilation. Since then he has been appl
 ying these skills to fusion simulation\, modeling and data analysis at Gen
 eral Atomics and the DIII-D National Fusion Facility. While there\, Kostuk
  led a group of collaborators to be among the first to address the challen
 ge of on-demand\, remote execution of large\, high-fidelity simulations at
  a leadership compute facility in support of ongoing plasma experiments at
  DIII-D. He currently leads the DIII-D digital twin development effort\, a
 nd is presently focused on the problems of heterogenous model integration\
 , modularity\, and performance-at-variable-scales that lie at the core of 
 the digital twin challenge.\n \nBrian Sammuli is the Lead for Applied Mac
 hine Learning and the Deputy Director of the Advanced Computing Center wit
 hin the Energy Group at General Atomics. He leads the development of AI\, 
 machine learning\, and data technologies for fusion energy\, serving as Pr
 incipal Investigator for the DOE-funded Fusion Data Platform and leading m
 ultiple initiatives in plasma control\, scientific machine learning\, and 
 large-scale fusion data infrastructure. His work spans real-time plasma co
 ntrol\, digital twins\, distributed scientific data systems\, and AI-drive
 n fusion research\, including the development of software and infrastructu
 re used to accelerate fusion experimentation and enable next-generation fu
 sion energy systems.\n \n\nhttps://events.cels.anl.gov/event/897/
IMAGE;VALUE=URI:https://events.cels.anl.gov/event/897/logo-3784314133.png
LOCATION:Online
URL:https://events.cels.anl.gov/event/897/
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