Addressing Infrastructure Constraints in AI Factories

As the demand for high-performance computing grows, the construction of an [AI Factory](https://blogs.nvidia.com/blog/tag/ai-factory/) has become an increasingly complex engineering challenge. Beyond raw processing power, developers must manage significant constraints related to power, cooling, water, site logistics, and grid capacity. To address these hurdles, NVIDIA has introduced [NVIDIA DSX Ready](https://www.nvidia.com/en-us/data-center/products/dsx/dsx-ready/), a new qualification program designed to help builders identify third-party products that align with the requirements of the [NVIDIA DSX](https://blogs.nvidia.com/blog/tag/nvidia-dsx/) reference design architecture.

The primary goal of the program is to assist builders in turning theoretical computing capacity into useful output. By selecting qualified components that are specifically verified for their platform, organizations can lower integration risks and move more efficiently toward full-scale deployment.

Initial Focus on Power and Cooling

The [NVIDIA Blog](https://blogs.nvidia.com/blog/dsx-ready-ai-factories-power-cooling/) outlines that the program is launching with two critical categories: battery energy storage systems (BESS) and cooling distribution units (CDUs). These systems are vital for maintaining the stability and performance of high-density computing clusters. Because optimizing one segment of a data center can shift bottlenecks to another, this unified approach ensures that power systems and liquid-cooling infrastructure are treated as cohesive parts of the overall facility design.

Qualified Partners and Technologies

At the program's inception, several industry leaders have already achieved qualification for their hardware. For BESS solutions, NVIDIA has qualified offerings from Hitachi Energy, LG Energy Solution, and Tesla. On the thermal management front, qualified CDUs are available from LG Electronics, LiquidStack, and Vertiv. These providers have undergone rigorous review processes to ensure their equipment meets the specific functional benchmarks required by the NVIDIA platform.

The validation path differs based on the hardware category. For BESS providers, the process involves running mandatory qualification tests and submitting supporting data for NVIDIA’s review. For CDU manufacturers, partners utilize a self-qualification suite to determine if their products meet established functional requirements. NVIDIA clarifies that passing these qualifications does not replace the need for site-level engineering or imply site-level stability, but it does provide a clearer path for procurement teams to evaluate their options.

Future Expansion of the Ecosystem

While the current rollout focuses on power and cooling, the company plans to expand the initiative over time. Future updates are expected to include additional categories covering broader infrastructure components and software solutions. This evolution is aimed at ensuring that as [AI](https://blogs.nvidia.com/blog/category/generative-ai/) infrastructure demands become more sophisticated, the tools available to builders remain in sync with the latest technological standards.

Sources

• NVIDIA BlogNVIDIA Launches DSX Ready to Qualify Power and Cooling Products for AI Factories