The Georgia Institute of Technology has been awarded $20 million by the National Science Foundation (NSF) to build and host a supercomputer dubbed Nexus.

Expected to be completed by Spring 2026, Nexus has been designed specifically for AI and high-performance computing (HPC) workloads, and will help support drug discovery, climate modeling, and robotics innovation, the university said.

No information about which vendors will provide the system’s hardware has been announced, but Georgia Tech said the system will “crank out over 400 quadrillion operations per second.” This means it will offer 400 petaflops of computer performance, in addition to having 330TB of memory and 10PB of flash storage.

Nexus will be built in partnership with the National Center for Supercomputing Applications at the University of Illinois Urbana-Champaign, which runs several of the top academic supercomputers in the US. Once Nexus is complete, the two institutions will link their systems through a new high-speed network, creating a national research infrastructure.

Scientists from any US institution will be able to apply to use Nexus. Ten percent of the system’s capacity will be reserved for the university’s own research.

“This supercomputer will help level the playing field,” said Suresh Marru, principal investigator of the Nexus project and director of Georgia Tech’s new Center for AI in Science and Engineering (ARTISAN). “It’s designed to make powerful AI tools easier to use and available to more researchers in more places.”

Srinivas Aluru, Regents’ Professor and senior associate dean in the College of Computing, added: “With Nexus, Georgia Tech joins the league of academic supercomputing centers. This is the culmination of years of planning, including building the state-of-the-art CODA data center and Nexus’ precursor supercomputer project, HIVE."

In April 2024, Georgia Tech partnered with Nvidia to deploy an AI supercomputer hub for student use. Deployed by Penguin Solutions (formerly Penguin Computing), that system comprises 20 Nvidia HGX H100 systems and 160 Nvidia H100 Tensor Core GPUs.