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AI is rapidly transforming industries, driving explosive growth in compute power and data center demand. With AI workloads requiring up to 200 kW per rack—far beyond traditional capacities—data centers must evolve to support this shift.
At Cologix, we build and retrofit data centers designed for AI’s unique needs, delivering advanced power density, innovative cooling solutions, and low-latency connectivity. Our infrastructure meets the rising demands of AI while addressing scalability, reliability, and sustainability, helping businesses stay ahead in the fast-paced AI revolution.
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AI infrastructure and Data Center FAQs
1. What makes Cologix’s data centers AI-ready compared to traditional facilities?
Traditional data centers typically handle up to 45 kW per rack, but AI workloads now demand densities up to 135 kW — with some projections reaching 200 kW per rack. Cologix addresses this through purpose-built infrastructure featuring advanced Direct-to-Chip (DTC) cooling systems that support 60-120 kW per rack, multi-megawatt ScalelogixSM campuses for hyperscale deployments and strategic edge locations across 45+ data centers in 12 North American markets. Our facilities incorporate extended cold aisle designs, comprehensive power planning and robust connectivity ecosystems specifically engineered for AI workloads’ unique requirements.
2. How does Cologix solve the power challenges facing AI deployments?
AI’s explosive growth is driving data center power consumption from 4.4% of total U.S. electricity in 2023 to a projected 6.7-12% by 2028. Cologix tackles this through a comprehensive energy strategy featuring diverse power sources, with over 60% of our footprint already carbon-free and Canadian sites operating with 98% renewable energy. We partner strategically with utilities like AEP Ohio, invest in innovative energy technologies and design flexible power solutions that accommodate both AI startups scaling incrementally and established providers with consistent high-density power demands across our scalable campus environments.
3. What cooling solutions does Cologix offer for high-density AI workloads?
High-density AI servers generate significant heat that overwhelms traditional air cooling methods. Cologix implements advanced cooling technologies including Direct-to-Chip (DTC) cooling, which circulates liquid coolant directly to high-power components like GPUs and TPUs. This targeted approach enables safe, efficient operation at power densities between 60-120 kW per rack while maintaining operational stability. We complement DTC systems with extended cold aisle designs and leverage Computational Fluid Dynamics (CFD) analysis to optimize cooling layouts for each customer’s specific configuration, ensuring maximum infrastructure efficiency and reliability.
4. How does Cologix support GPU as a Service (GPUaaS) providers?
The GPUaaS market is reshaping cloud computing by providing scalable, high-performance computing specifically for AI, machine learning and deep learning applications. Cologix enables this transformation through infrastructure that delivers the power density, advanced cooling, and robust connectivity that GPUaaS providers require. Our facilities offer direct onramps, diverse carrier options and low-latency connectivity essential for distributed AI workloads. With strategically positioned edge locations and hyperscale campuses, we provide the flexible foundation GPUaaS companies need to scale efficiently while meeting demanding bandwidth and latency requirements.
5. What sustainability initiatives does Cologix implement for AI infrastructure?
Recognizing AI’s growing energy demands, Cologix maintains a strong commitment to environmental responsibility with over 60% of our power footprint already carbon-free and Canadian facilities operating with 98% renewable energy. Our comprehensive energy strategy deploys diverse power sources, strategic utility partnerships and investments in innovative technologies to ensure reliable, lower-emission power delivery. We work closely with regional utilities to optimize power solutions and adapt to local energy needs while supporting customers’ long-term sustainability goals, proving that high-performance AI infrastructure and environmental stewardship can coexist effectively.
