The ideal platform provides all of this, allowing teams to focus on targeted innovation while using proven solutions for the rest.
NVLink Fusion is supported by an ecosystem designed for rapid development, integration and deployment, spanning ASIC design, CPU, and IP and optical interconnect partners.
“NVLink Fusion gives customers the ability to choose the CPU architecture, the performance level, the software capabilities that best meet their needs for the workloads that they care about,” said Tim Wilson, vice president and general manager of data center silicon engineering at Intel.
NVLink Fusion adopters can also use the NVIDIA MGX rack-scale architecture and the same supply chain used for MGX-based systems such as NVIDIA Vera Rubin NVL72 . Manufacturing partners manage design and integration, while MGX suppliers provide the building blocks for rack, cooling, power and emerging 800 VDC designs .
“With Vera Rubin [NVL72], we are looking at almost 100% automation of system builds in the manufacturing line,” said Jack Luoh, head of product and solution at QCT and Quanta Computer. “Most of those investments can be leveraged if the XPU leverages NVLink Fusion.”
AI factory planning doesn’t wait for silicon. Power procurement, facility design, cooling, rack layout and network architecture begin long before the final accelerator mix is available. A data center locked to one chip can become a schedule risk.
Different workloads may favor different accelerators, including XPUs, GPUs, CPUs and LPUs. GPU systems may work alongside semi-custom systems for training, post-training, reasoning, retrieval and serving.
“The value of the NVLink Fusion program is … [customers] can deploy their rack-level solution with the NVIDIA GPU, and then they can decouple the development of their XPU and put it at a different pace,” said Vince Hu, corporate senior vice president and general manager of the data center and computing business group at MediaTek.
NVLink Fusion addresses these challenges through a unified architecture. XPU- and GPU-based systems such as Vera Rubin NVL72 can share rack footprints, networking, cooling, power delivery and management systems. Operators can move forward with buildout while deferring the precise silicon mix, then reprovision capacity as workload demand, silicon supply and business priorities change.
“NVLink Fusion allows the hyperscalers or the custom ASIC designers to integrate their own custom CPU or XPU and bridges the NVIDIA technology with a third-party process to create a unified rack-scale architecture,” said Lie-Szu Juang, chair and chief strategy officer at GUC.
Factory buildout is expensive, and mistakes can require costly rework. Infrastructure must be validated before construction begins. NVLink Fusion aligns with the NVIDIA DSX reference architecture for AI factories: codesigning buildings, power, cooling, compute and networking. The NVIDIA Omniverse DSX AI Factory Blueprint provides a digital twin and open reference design for gigawatt-scale AI factories, enabling partners to model facilities and technology together before deployment.
At the rack level, serviceability is part of performance. Reference compute trays feature 100% liquid cooling with no fans, cables or hoses, and allow trays to be removed while the rest of the rack remains operational. NVLink Switch trays are also liquid cooled and support continued operation during service.
“With NVLink Fusion we can use proven NVL72 rack design to have time-to-market, and we can have access to multiple suppliers to help us to deliver more into the hands of our customers,” said CC Lee, senior hardware development manager at Annapurna Labs, an Amazon company.
Software completes the factory. NVIDIA NCCL for distributed workloads, NVIDIA Dynamo and NIXL for disaggregation and NVIDIA Mission Control for cluster management, telemetry and debugging help operators run mixed AI infrastructure as a coordinated system.
With NVLink Fusion, XPUs can now meet a world-class AI platform, enabling hyperscalers and AI-native companies to build unified, semi-custom AI factories that combine the strengths of many builders into infrastructure no one company could build alone.
Key considerations
- Investor positioning can change fast
- Volatility remains possible near catalysts
- Macro rates and liquidity can dominate flows
Reference reading
- https://blogs.nvidia.com/blog/nvlink-fusion-xpu-ai-factory/#primary
- https://blogs.nvidia.com/blog/author/jesseclayton/
- https://blogs.nvidia.com/blog/nvlink-fusion-xpu-ai-factory/#disqus_thread
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Informational only. No financial advice. Do your own research.