Johnson Controls Reference Designs
Global Reference Design Guides for your AI Factories cooling needs
Johnson Controls is privileged to collaborate with leading industry partners to publish a series of Global Reference Design Guides. Focused on the emerging class of AI Factories, these guides outline how to build high-performance, scalable facilities through a rigorous Thermal Management lens.
Our Reference Guide (402) helps you plan and design a water-cooled chiller plant capable of serving a full 1 Gigawatt AI factory.
What’s included:
- Outline of a comprehensive water-based cooling architecture
- Guide and sizing references for 220 MW compute clusters
- Recommended design temperatures and operating conditions for each stage of thermal chain – from chip level heat capture to final atmospheric rejection
Reference Guide
Description
Design Guide
401: Air-cooled chiller plant for 1GW AI Factory
Full technical blueprint that outlines how to plan and design an air-cooled chiller plant capable of serving a full 1GW AI Factory. With this approach, the design can deliver critical outcomes including:
- Water-free heat rejection
- Scalable air-cooled architectures
- Thermal flexibility for next-gen GPUs
402: Water-cooled chiller plant for 1GW AI Factory
Full technical blueprint for a water-cooled chiller plant that can serve a full 1GW AI Factory to deliver the following critical outcomes:
- Zero water usage in cooling
- Future-ready for high-temp loops
- Optimized for AI workloads
403: Water-cooled chiller plant for 1GW AI Factory
Full technical blueprint for a water-cooled chiller plant that can serve a full 1GW AI Factory to deliver the following critical outcomes:
- Zero water usage in cooling
- Future-ready for high-temp loops
- Optimized for AI workloads
404: Water-cooled chiller plant for 1GW AI Factory
Full technical blueprint for a water-cooled chiller plant that can serve a full 1GW AI Factory to deliver the following critical outcomes:
- Zero water usage in cooling
- Future-ready for high-temp loops
- Optimized for AI workloads
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