Cluster Computing Comes to Millersville

Millersville University is the recent recipient of a $290,000 grant from the National Science Foundation to support the acquisition of a computing cluster for research and training in numerical modeling and artificial intelligence (AI) applications for earth and space system sciences. A computer cluster is a set of connected computers that work together.

“Professors from the Earth Sciences and Computer Science Departments collaborated on writing the successful proposal to bring game-changing computer technology to bear on research questions that require the computational resources that haven’t been available on this campus,” says Dr. Richard Clark, lead principal investigator on the grant.

“We want to intimately involve our students in cluster-computing-enabled cross-disciplinary research,” says Clark and “examples abound!”  Examples of how students will be able to use the computer cluster include:

• Improve precipitation forecasts for agriculture and road weather.
• Help students visualize solar coronal mass ejections and their influence on the near-earth space environment.
• Study the links between agricultural runoff and summertime hypoxia events in the Chesapeake Bay.

In addition, the meteorology program can now run its operational Weather Research and Forecasting model at a higher resolution without increasing the computer time needed to run the model.

The hardware has been installed in the Boyer Computer Center by Information Technology staff led by George Ciarrocchi and will be ready to enable scientific investigations starting in Spring 2021.

There is a potential for rich cross-disciplinary research that extends well beyond the earth sciences disciplines of meteorology, ocean sciences and geology, and into solar physics and space weather, environmental sciences, environmental chemistry and air quality, data science, algorithm development, feature extraction, machine learning, AI, and autonomous technology.

“This computer cluster will significantly expand our ability to engage students in research and research training involving numerical models and other forms of computational and data science,” says Clark.