Meta and Oracle are modernizing their artificial intelligence (AI) data centres by integrating NVIDIA’s Spectrum-X Ethernet switches, a cutting-edge networking technology designed to meet the escalating demands of large-scale AI systems. This strategic adoption is part of a larger open networking framework aimed at improving AI training efficiency and accelerating deployment across vast compute clusters.
The Rise of AI Data Centres and NVIDIA Spectrum-X
NVIDIA’s founder and CEO, Jensen Huang, describes the emergence of trillion-parameter AI models as transforming data centres into “giga-scale AI factories.” In this vision, Spectrum-X functions as the “nervous system” that interconnects millions of graphics processing units (GPUs), facilitating the training of some of the most complex AI models ever built.
Both Oracle and Meta have outlined their specific plans to utilize Spectrum-X technology. Oracle, through its Vera Rubin architecture, plans to connect millions of GPUs efficiently, accommodating the surging computational needs of AI model training. Mahesh Thiagarajan, Executive Vice President of Oracle Cloud Infrastructure, emphasized that this infrastructure will help customers rapidly build and deploy AI solutions.
Meta is integrating Spectrum-X Ethernet into its Facebook Open Switching System (FBOSS) — Meta’s proprietary platform for managing large-scale network switches. Gaya Nagarajan, Meta’s Vice President of Networking Engineering, highlights the necessity of an open and efficient network infrastructure to support exponentially growing AI models and deliver consistent services to billions of users.
Key Features Enabling Flexible and Scalable AI Infrastructure
Modular Design with NVIDIA MGX System
- Modularity: NVIDIA’s MGX system provides a flexible, building-block architecture allowing organizations to combine CPUs, GPUs, storage, and networking components tailored to their specific needs.
- Interoperability: The design ensures compatibility across different generations of hardware, which accelerates deployment and future-proofs infrastructure investments.
- Scalability: MGX supports both scale-up (enhancing power within a rack) and scale-out (expanding across racks and data centres) strategies through NVLink and Spectrum-X Ethernet connectivity.
Power Efficiency and Advanced Energy Management
As AI workloads intensify, energy consumption and cooling present substantial challenges. NVIDIA is advancing power efficiency from the silicon chip level to grid management by collaborating with key industry partners.
- 800-volt DC Power Delivery: This shift reduces heat loss and enhances electrical efficiency in AI data centres.
- Power-Smoothing Technology: Designed to minimize power spikes, this approach can decrease peak power requirements by up to 30%, thereby increasing density without expanding the data centre footprint.
- Holistic Design Collaboration: NVIDIA works alongside Onsemi, Infineon, Delta, Flex, Lite-On, Schneider Electric, and Siemens to optimize power components, rack-level systems, and data centre designs.
Optimized Networking for the Trillion-Parameter Model Era
Spectrum-X Ethernet is the first Ethernet platform purpose-built specifically for AI’s unique networking demands. It is engineered to connect millions of GPUs with:
- High Bandwidth Utilization: Spectrum-X achieves up to 95% effective bandwidth, significantly surpassing traditional Ethernet averages of 60%, thanks to advanced congestion control technologies.
- Adaptive Routing and Telemetry: These features help eliminate network hotspots, providing stable and predictable performance for demanding AI training workloads.
- Multi-Site Integration: XGS, Spectrum-X’s complement for inter-data centre communication, enables linking facilities across regions into unified AI supercomputers with minimal latency.
Software and Hardware Co-Design for Maximum Efficiency
NVIDIA emphasizes the synergy between hardware advancements and software optimization to maximize AI system performance. Ongoing developments include:
- Integration of FP4 precision kernels that boost computational throughput.
- Enhancements in AI frameworks such as Dynamo and TensorRT-LLM to optimize inferencing and training processes.
- Implementation of innovative algorithms like speculative decoding to accelerate AI model performance.
These advancements collectively empower platforms like NVIDIA’s Blackwell system, delivering consistent and scalable AI performance for hyperscalers like Meta.
Industry Impact and Future Developments
With an increasing number of trillion-parameter AI models in production, the necessity for high-performance, scalable, and energy-efficient data centre networking architectures is more critical than ever. NVIDIA’s Spectrum-X and MGX systems not only meet today’s needs but also anticipate future expansions.
Oracle’s Vera Rubin architecture, expected to launch commercially in the second half of 2026, along with the Rubin CPX, exemplifies next-generation AI infrastructure powered by Spectrum-X. This collaboration reflects a broader industry trend toward open networking standards, interoperability, and energy-efficient designs.
Conclusion
The deployment of NVIDIA’s Spectrum-X Ethernet technology by industry leaders Meta and Oracle marks a pivotal advancement in AI data centre infrastructure. By enhancing connectivity, flexibility, and power efficiency, these solutions are addressing the complex demands of training and deploying massive AI models at scale.
As AI continues to revolutionize various sectors, robust and scalable networking technologies like Spectrum-X will be essential to sustain innovation, maintain system performance, and enable the next generation of AI breakthroughs.
Image Credit: NVIDIA
References
- NVIDIA Official Blog and Product Briefs, 2025.
- Oracle Cloud Infrastructure Press Release, 2025.
- Meta Networking Updates, 2025.
- “Data centre power and cooling trends,” Uptime Institute, 2025.
- “Networking requirements for AI workloads,” IEEE Communications Surveys & Tutorials, 2024.