Stony Brook University has launched a new high-performance computing cluster, NVwulf, to support artificial intelligence (AI), machine learning (ML), and data-intensive research. The cluster became available on July 7 for advanced testing by researchers who contributed to its funding and their students.
NVwulf is described as a “sister system” to the university’s SeaWulf cluster and represents an effort to meet increasing demands for AI-powered research. Its development was made possible with backing from the Department of Technology, AI & Society (DTAS), which evolved from the former Department of Technology and Society. Funding was provided by New York Governor Kathy Hochul as part of a three-year initiative to establish a prominent interdisciplinary AI and technology program at Stony Brook.
The project is among the first major investments resulting from this initiative. It was developed in collaboration with the Research Computing and Innovation team within the Division of Information Technology (DoIT), various academic departments, and leadership from both East and West campuses.
“NVwulf is both a symbol and a catalyst for what we’re building with the new Department of Technology, AI & Society,” said Andrew Singer, dean of the College of Engineering and Applied Sciences (CEAS). “It reflects our commitment to creating the computational infrastructure and interdisciplinary ecosystem needed to lead in AI research, education, and innovation. By linking state-of-the-art GPU computing with an academic vision that spans engineering, data science, ethics, and public impact, we’re positioning Stony Brook as a national leader in responsible, cutting-edge AI.”
Firat Coskun, assistant director of advanced systems and operations at the Institute for Advanced Computational Science (IACS), said: “The cross-campus investment in NVwulf underscores our shared vision: bringing together technical excellence and academic ambition to expand access to next-generation AI resources for Stony Brook’s research community.”
Deployment will take place in phases. The first phase features 24 NVIDIA H200 NVL GPUs that can deliver up to 80 petaFLOPs (FP8) for machine learning applications and 720 teraFLOPs (FP64) for scientific computing. A second phase later this year will further increase capacity.
Unlike other resources such as SeaWulf or HIPAA-compliant ClinWulf clusters, or NSF-supported Ookami, NVwulf is currently Stony Brook’s most GPU-focused system built specifically for AI and ML workloads.
“NVwulf is a significant addition to Stony Brook University’s overall computational capacity. NVwulf will undoubtedly help accelerate AI research across many academic disciplines,” said Stony Brook Vice President for Information Technology and Chief Information Officer Simeon Ananou.
Youngwook Kee, assistant professor in radiology at the Renaissance School of Medicine at Stony Brook, noted how his group’s work relies on such computational power: “The new NVwulf GPU cluster has already become an essential computational resource for our group’s research,” he said. “Our group develops novel MRI data acquisition strategies, advanced image reconstruction algorithms, biophysical signal models, and reinforcement learning-based self-scanning methods. These projects are all computationally demanding, and with the NVwulf’s multi-node configuration of multi-way NVIDIA H200 nodes, we have been able to significantly accelerate the search for optimal parameters across vast search spaces, bringing previously impractical experiments to completion within feasible timeframes.”
David Cyrille, assistant vice president and chief research information officer at DoIT said: “This platform supports the full spectrum of research at Stony Brook, ranging from basic science to de-identified clinical and translational studies. NVwulf gives our faculty access to advanced infrastructure that enables them to work more efficiently, smarter, and stay at the forefront of their fields.”
Cyrille added that AI use now extends across disciplines including biomedical imaging, molecular modeling, social media analytics, and population health: “What sets NVwulf apart is its ability to support faculty developing their own domain-specific AI models, tools that are tuned to the nuances of their data, their questions, and their impact goals.”
Joel Saltz chairs the Department of Biomedical Informatics where researchers are using NVwulf in cancer diagnostics through pathology image analysis based on AI.
“This is about empowering Stony Brook researchers with the latest-generation GPU hardware to address today’s most pressing scientific challenges,” Cyrille added. “What used to take a month can now be done in two weeks. That kind of acceleration changes the game.”
NVwulf serves only university researchers and students for educational or research purposes.
“This cluster isn’t built to host third-party AI applications,” said David Carlson, computational scientist at IACS. “It’s meant to empower researchers—whether they’re simulating protein folding, tracking public sentiment, or developing AI-assisted diagnostics.”
Future plans include expanding capacity further through additional phases as campus needs grow.
While technical aspects were handled by DoIT’s advanced computing team, contributions came from multiple areas including materials science faculty members; teams from electrical engineering; radiology; pathology; facilities staff; senior leadership; as well as offices under CIO oversight.
Researchers interested in accessing NVwulf can find more information on the Research Computing Informatics website.
