NVIDIA founder and CEO Jensen Huang visited the Naval Postgraduate School in Monterey, California, to commission an NVIDIA DGX GB300 system. This deployment equips the U.S. military’s flagship graduate university with advanced AI infrastructure for model training and inference across weather prediction, cybersecurity, and disaster response.
Deploying Enterprise Hardware for Tactical and Academic Scaling
The newly commissioned DGX GB300 supercomputer operates alongside NVIDIA Mission Control software. This setup provides the university’s more than 1,500 in-resident students and 600 faculty members with direct, on-premises access to high-performance computing resources. According to school officials, the platform supports complex applied research spanning space operations, ocean science, and autonomy.
“Our nation depends on our men and women who fight on the front lines. Nothing is more valuable to you than information and insight, and information and insight in a timely way, and to understand its impact and consequence,” Huang stated during the event. “I can’t imagine anything more important.”
The deployment is part of an ongoing initiative anchored by an NVIDIA AI Technology Center located on the Monterey campus. By embedding these systems locally, researchers can train large foundation models and run high-fidelity simulations without relying entirely on remote cloud resources. Admiral Samuel Paparo, commander of the U.S. Pacific Command, emphasized the institutional shift during the school’s three-day Converge @ NPS event.
“As we modernize our technology, we must also modernize how we educate our leaders,” Paparo noted. “Access to advanced computing capability means NPS students and faculty understand the opportunities and responsibilities that come with these technologies.”
Infrastructure Partners and System Integration
Bringing a DGX GB300 cluster online requires robust enterprise-grade engineering. Several infrastructure partners contributed hardware, software, and physical plant management to support the installation:
- DDN: Provided high-performance data infrastructure designed to handle large-scale storage, efficient access, and management for demanding AI workloads.
- VAST Data: Deployed a unified data platform to secure data access and administration across edge, core, and cloud environments.
- Vertiv: Delivered the physical racks, advanced cooling loops, power distribution, fluid monitoring, and commissioning support necessary for thermal regulation and continuous operation.
This multi-vendor architecture ensures that the supercomputer maintains stable performance thresholds while running resource-intensive simulations, such as ocean condition modeling and atmospheric forecasting.
Digital Twins and Applied Research Integration
Graduate students and researchers frequently utilize hackathons and collaborative frameworks to tackle operational challenges. Through a partnership with the nonprofit organization MITRE, researchers have developed frameworks utilizing NVIDIA Omniverse libraries. These libraries allow teams to construct high-fidelity digital twins capable of simulating complex navigation and tactical decision-making under uncertain real-world conditions.
To ensure widespread adoption across various departments, NVIDIA has integrated its Deep Learning Institute into the curriculum. This expansion provides faculty with official instructor toolkits, weaving applied AI concepts directly into existing graduate programs.
“Many of you will command in AI-enabled environments. Information will move at lightning speeds, compressing response times,” Paparo said. “Our advantage will come from leaders, like you, who can use the technology to see, understand, decide and act faster while exercising the judgment, experience and leadership that machines cannot provide.”
Huang encouraged students to build familiarity with the technology directly through foundational engagement, noting that modern computing platforms are designed to lower barriers to entry for non-programmers.
