Uttarakhand's First NVIDIA AI-HPC Hub Opens at Graphic Era University

Uttarakhand's first NVIDIA-based AI-HPC hub launches at Graphic Era University

A new Centre of Excellence for Artificial Intelligence, Skill Development, and Innovation has opened at Graphic Era University, Dehradun. The 1.5 lakh sq. ft. facility hosts Uttarakhand's first NVIDIA AI and High-Performance Computing hub built on an NVIDIA DGX B200 system with eight GPUs and 1.74 TB of GPU memory. Developed at a cost of over ₹10 crore, the centre targets applied research in healthcare, agriculture, environment, smart cities, and advanced industries. It also includes an Apple iOS Development Centre in collaboration with Apple and Infosys.

Why this matters for IT and development teams

This hub gives researchers and engineering teams local access to serious GPU throughput for training, fine-tuning, and inference at scale. Expect shorter iteration cycles for prototypes, more ambitious multimodal experiments, and faster transitions from POC to pilot. With an on-campus iOS centre, teams can also close the loop from AI models to production-grade mobile apps.

Hardware snapshot

• NVIDIA DGX B200 system (institutional-scale GPU compute)
• 8 GPUs with a combined 1.74 TB of GPU memory
• Built for large-scale model training, multi-GPU orchestration, and high-throughput data pipelines
• Campus positioned as Generative AI-ready, built on AWS services

High-impact workloads to consider

• Healthcare: fine-tune domain LLMs for triage and clinical summarization; deploy hybrid AI-human telemedicine flows for rural outreach.
• Agriculture: vision models for crop health, pest detection, and yield forecasting; geospatial segmentation for irrigation planning.
• Environment: time-series forecasting for air and water quality; wildfire and flood risk modeling.
• Smart cities: video analytics for traffic management; anomaly detection for utilities and urban operations.
• Advanced industries: defect detection, predictive maintenance, and simulation-backed optimization.

MLOps and HPC practices that will save time

• Scheduling: standardize on Slurm or Kubernetes with the NVIDIA GPU Operator for repeatable job orchestration.
• Parallelism: plan for tensor/pipeline data parallel strategies and mixed precision to maximize throughput.
• Model tuning: use parameter-efficient methods (LoRA/QLoRA) to cut GPU hours for domain adaptation.
• Data: implement a feature store and lineage tracking early; enforce PII policies and dataset versioning.
• Observability: track GPU utilization, memory pressure, and I/O bottlenecks; institute model/performance monitoring from day one.
• Security: isolate workloads, scan containers, and enforce role-based access; log access to sensitive datasets.

Ethics and governance: non-negotiable

The minister emphasized that technology without accountability will not meet public expectations. He warned about deepfakes and misinformation, and stressed that integrity must guide research and deployment. For teams, that means commit to audits, documented data consent, red-teaming, content provenance (watermarking/signing), and clear user disclosures. Build model cards, set escalation paths for grievance redressal, and make ethics checks part of the release checklist.

Momentum for India's tech stack

The announcement ties into national programs like Digital India, Startup India, and Skill India. Linking academia with industry and startups will help convert research outputs into deployable systems that serve citizens and markets faster.

Getting involved

For developers, this facility is an opportunity to run larger experiments, share reusable pipelines, and co-build with domain experts. Teams can prototype on AWS and graduate heavy training to the DGX cluster, then ship lean inference services back to production environments.

If you're upskilling for AI engineering and large-scale training, explore practical certification paths: AI Certification for Coding.

Technical reference

• NVIDIA DGX platform overview: nvidia.com

Graphic Era University reports it is India's first Generative AI-ready campus built on AWS, and is ranked 48th in NIRF 2025 with NAAC A+ accreditation.