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The research project will use the Institute for Computational and Data Sciences’ ROAR supercomputer. IMAGE: PENN STATE

Boosting research with supercomputing

Posted on October 17, 2025

Editor’s Note: The original version of this article first appeared on Penn State News.

UNIVERSITY PARK, Pa. — Researchers in any discipline can tackle large-scale scientific questions and simulations that a personal computer can’t using Penn State’s Roar supercomputer, housed within the Institute for Computational and Data Sciences (ICDS).

High-performance computing (HPC) typically is a large, powerful supercomputer or a cluster of computers working together, or a combination of the two, to store and process large datasets needed for research. Roar has been used to train machine learning models, perform complex analyses, run simulations and build algorithms needed to predict future climate events and identify molecular mechanisms underpinning disease.

According to ICDS co-hires Ed O’Brien, professor of chemistry in the Eberly College of Science, and Romit Maulik, assistant professor in the College of Information Sciences and Technology, HPC resources have been used to accelerate their research, lessening the time to science and discovery.

“My research tries to make sense of what is going on inside living cells, and to be able to do that, we need HPC resources to model what is happening using rule from chemistry and physics,” O’Brien said. “By using HPC, we can gain new insights into potential disease mechanisms, which could open future opportunities for therapeutic development. We could also gain a better understanding of novel aspects of cellular behavior, which could potentially lead to bioengineering opportunities.”

O’Brien’s team recently published a study using Roar that found a potential mechanism explaining why some proteins misfold, potentially leading to disease.

“All of my work requires training AI models or running simulations of complex dynamical systems that are not possible on a single workstation,” Maulik said. “My research uses graphics processing units (GPUs), which are used to speed up tasks and calculations and rendering of graphics and video, for training deep neural networks — AI models designed to mimic how the human brain operates — with applications for various computational physics problems.”

His research focuses on weather forecasting and climate modeling on Earth and beyond, to study the space around merging black holes and how to mitigate disruptions and damage for safe and efficient operation of nuclear fusion reactors.

Using Roar can help research teams similar to Maulik’s build better forecasting models, which could potentially help with improving the prediction of extreme events earlier and increase accurate forecasts, he said.

O’Brien’s team also uses GPUs, in combination with central processing units (CPUs), which are the primary circuitry of a computer that executes instructions. These resources allow his team to take publicly available datasets and run large simulations on them. Roar also allows the team to develop new models and store large amounts of research data that otherwise wouldn’t be possible. Roar is also a resource that is used by the U.S. National Science Foundation National Synthesis Center for Emergence in the Molecular and Cellular Sciences at Penn State, which O’Brien directs. The center explores unanswered fundamental scientific questions by examining publicly available large datasets.

 

 

 

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