NVIDIA DGX SuperPOD
5 use cases using this technology
MediaTek Accelerates AI Development With an AI Factory
MediaTek
MediaTek established an on-premises AI factory powered by NVIDIA DGX SuperPOD with NVIDIA Blackwell-based systems to accelerate enterprise AI efforts, including development of its Breeze series LLMs and a 480-billion-parameter traditional-Chinese model. The AI factory processes approximately 60 billion tokens per month for inference and completes over 24,000 model-training iterations monthly, training models exceeding 480 billion parameters within one week (versus 7-billion-parameter models in a week previously). Using NVIDIA NIM and TensorRT-LLM, MediaTek achieved a 40% improvement in inference speed and 60% increase in token throughput. NVIDIA Mission Control consolidated GPU provisioning and system monitoring, while AI-assisted code completion and an AI agent for chip design documentation reduced documentation time from weeks to days. NVIDIA Riva was integrated into NVIDIA DGX Spark for agentic voice control features like internet search, calendar and messaging.
Penn Advanced Research Computing Center (PARCC)
University of Pennsylvania
Flexential and the University of Pennsylvania's Penn Advanced Research Computing Center (PARCC) launched a phased deployment of an NVIDIA DGX SuperPOD with DGX B200 systems and NVIDIA Quantum-2 InfiniBand networking, housed at Flexential's Philadelphia-Collegeville, Pennsylvania colocation data center, to support the university's next-generation research computing infrastructure. AHEAD, a longtime provider of enterprise IT services for Penn, handled off-site rack integration and on-site cabling.
Boosting Innovation and Cutting Costs Through Lockheed Martin's AI Factory
Lockheed Martin
Lockheed Martin centralized compute resources, MLOps tools and best practices into the Lockheed Martin AI Factory, built on an NVIDIA DGX SuperPOD reference architecture, to build and deploy trustworthy AI at scale on-premises under strict data governance requirements. Developers can now get GPU-backed environments running in minutes instead of weeks, and training times dropped from weeks to days. The AI factory processes over one billion tokens per week and now serves 7,000 engineers and developers, supporting internal chatbots and coding assistants such as Lockheed Martin Text Navigator, and has consolidated 30+ models on-premises.
Mayo Clinic deploys NVIDIA DGX SuperPOD to accelerate pathology foundation models
Mayo Clinic
Mayo Clinic deployed an NVIDIA DGX SuperPOD with NVIDIA DGX B200 systems to support foundation model development for pathomics, drug discovery and precision medicine. In partnership with Aignostics, Mayo Clinic built the Atlas pathology foundation model, trained on more than 1.2 million histopathology whole-slide images. The new infrastructure is reducing four weeks of pathology slide analysis work to one week.
MITRE's Federal AI Sandbox accelerates government AI research with NVIDIA DGX SuperPOD
MITRE
Nonprofit MITRE built the Federal AI Sandbox, powered by NVIDIA DGX SuperPOD, to give federal sponsors an affordable, centralized space to test and deploy AI and machine learning across domains such as weather forecasting, cybersecurity, and public benefits administration. The DGX SuperPOD delivers a 300-fold performance increase over MITRE's previous AI computing capabilities and supports thousands of researchers; MITRE is using it with NVIDIA Omniverse and NVIDIA Earth-2 to develop 1-kilometer precision weather forecasts with NOAA and the National Weather Service, plus a foundational model for cybersecurity threat analysis across 190 nations.