Call for Papers: HPC-ODA 2026 Workshop at SC26

Apr 20, 2026·
Michael Ott
Michael Ott
Ayse Coskun
Ayse Coskun
Jeff Hanson
Jeff Hanson
Melissa Romanus
Melissa Romanus
Woong Shin
Woong Shin
Tim Osborne
Tim Osborne
· 2 min read

The 1st International Workshop on HPC Operational Data Analytics (HPC-ODA 2026) is now accepting paper and lightning talk submissions. The workshop will be held in conjunction with SC26 in Chicago, IL.

Submission Types

Full papers (8 two-column IEEE pages) and short papers (4 two-column IEEE pages) are invited on any aspect of operational data analytics in HPC. Topics of interest include ODA infrastructure, data collection pipelines, visualization and analytics, machine learning applications, data standardization and governance, energy and sustainability, digital twins, and HPC use cases and best practices.

Lightning talks (5-minute presentations, 1-2 page extended abstract) provide an opportunity to share emerging work, operational experiences, and tools that may not be ready for a full paper submission. Lightning talk abstracts will not appear in the proceedings but will be documented in the workshop report.

All submissions are peer-reviewed. Full and short papers will be published in the SC26 workshop proceedings in the IEEE Xplore Digital Library.

Important Dates

  • July 31, 2026, Full / Short Paper Submission Deadline
  • September 4, 2026, Author Notification
  • September 18, 2026, Camera-Ready Deadline
  • September 18, 2026, Lightning Talk Submission Deadline
  • September 25, 2026, Lightning Talk Notification

All deadlines are 11:59 PM AoE (Anywhere on Earth).

How to Submit

Submissions should use the IEEE conference template and will be handled via the SC Linklings submission system (link to be posted when open).

Full details are available on the workshop page. We look forward to receiving your contributions.

Workshop SC26 CFP
Michael Ott
Authors
Michael Ott
Senior Research Engineer
Michael Ott is a senior research engineer in the Future Computing group at Leibniz Supercomputing Centre (LRZ)
Ayse Coskun
Authors
Ayse Coskun
Professor, Electrical and Computer Engineering
Ayse Coskun is a Professor in the Department of Electrical and Computer Engineering at Boston University, where she also serves as Associate Dean for Research and Faculty Development and Director of the Center for Information and Systems Engineering. Her research focuses on energy-efficient computing and high-performance systems, spanning cloud computing, computer architecture, and embedded systems. She is a recipient of the NSF CAREER Award and IBM Faculty Award, and serves as Deputy Editor-in-Chief of IEEE Transactions on Computer Aided Design.
Jeff Hanson
Authors
Jeff Hanson
Monitoring Team Manager, HPC Cluster Products
Jeff Hanson manages the monitoring team for HPE HPC cluster products (CSM and HPCM). His background includes 25 years in various HPC roles, from engineering to research to support. He holds an MS in mathematics from Purdue University.
Melissa Romanus
Authors
Melissa Romanus
Data Management Engineer
Melissa Romanus is a data management engineer at the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory, where she is part of the Operations Technology Group. Her work focuses on the ingestion, collection, analysis, and visualization of real-time streaming operational and systems data in HPC data centers. Her research interests span operational data analytics, the architecture of large-scale data lakes, and automating scientific workloads on HPC systems.
Woong Shin
Authors
Woong Shin
Research Scientist
Woong Shin, Ph.D. is a Research Scientist at Oak Ridge National Laboratory (ORNL), specializing in high-performance computing (HPC), AI/ML applications, and energy-efficient supercomputing.
Tim Osborne
Authors
Tim Osborne
Senior Data Platform Engineer
Tim Osborne is a Senior Data Platform Engineer in the Analytics and Monitoring team at Oak Ridge National Laboratory, responsible for the streaming and monitoring infrastructure and operating Frontier’s IT Database. Before joining ORNL in 2021, he worked in the oil and gas industry, optimizing seismic processing algorithms and enabling machine learning and data analytics on an HPC cluster.

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