Just announced: HPCWire Reveals Winners of the 22nd Annual Readers’ and Editors’ Choice Awards During SC25.
Additional Article: https://ncsa.illinois.edu/2025/11/19/ncsa-receives-honors-in-2025-hpcwire-readers-and-editors-choice-awards/
“Each year, HPCwire readers and our editorial team select the technologies, use cases, companies, and leaders that have contributed to the fantastic growth of the HPC market and community,” said Alex Woodie, Managing Editor of HPCwire. “These remarkable submissions come from around the globe and represent the best people, projects, collaborations, and technology in the supercomputing community.”
HPCwire has designated two categories of awards: (1) Readers’ Choice, where winners have been elected by HPCwire readers, and (2) Editors’ Choice, where winners have been selected by a panel of HPCwire editors and thought leaders in HPC. The process started with an open nomination process, with voting taking place throughout the month of September.
These awards, now in their 22nd year, are widely recognized as being among the most prestigious recognition given by the HPC community to its own each year, and are the only awards that open voting to a worldwide audience of end users.
Congratulations to NCSA and DeltAI for winning the Best Use of HPC in Energy Award!
Best Use of HPC in Energy
Editors’ Choice: Researchers at the National Center for Supercomputing Applications (NCSA) and the University of Illinois Urbana-Champaign developed a deep learning operator, based on a virtual sensing digital twin and trained on the NVIDIA GH200-powered DeltaAI HPC cluster, to monitor inaccessible nuclear reactor locations in real time. The work delivers predictions of critical and previously unmeasurable parameters 1,400× faster than traditional simulations, surpassing the limits of conventional sensors and AI methods.
More kudos to NCSA and Delta AI for winning the Best Use of HPC in Industry Award!
Best Use of HPC in Industry (Automotive, Aerospace, Manufacturing, Chemical, etc.)
Editors’ Choice: Researchers from the University of Illinois, the Massachusetts Institute of Technology (MIT), Sandia National Laboratories (SNL), and National Center for Supercomputing Applications (NCSA) have developed a novel generative AI model, trained on NCSA’s Delta system. The model enables inverse design of complex patterned polymers by rapidly generating multiple high-fidelity manufacturing solutions from desired pattern images, and advances AI-driven materials design through HPC.