AI/HPC and high-density CPU racks are outpacing traditional facility–water cooling. Operators need row-scale capacity, fast transient stability, and a path from glycol today to dielectric two-phase tomorrow—without ripping and replacing infrastructure.
single module cooling capacity
scalable cooling capacity (6 modules)
single module cooling capacity
scalable cooling capacity (6 modules)
The Borealis™ CDU Facility-to-Chip™ Cooling Ecosystem addresses the escalating thermal, efficiency, and scalability demands of high-density AI/HPC deployments by linking the data center’s facility-level cooling infrastructure directly to the chip-level heat removal hardware. This end-to-end integration enables precise thermal management, maximized efficiency, and simplified scalability — all from a single intelligent platform.
Discover the innovative features that make Borealis™ CDU Platform and ThermaPod™ the ideal solutions for high-density computing environments. Our modular and scalable designs ensure efficient thermal management, reducing energy consumption and enhancing the reliability of critical electronic components.
Borealis™CDU provides efficient cooling tailored for power-dense computing environments, ensuring optimal performance and reliability. It reduces energy consumption compared to traditional cooling methods, making it an eco-friendly solution.
Unlike conventional CDUs, Borealis™CDU supports both single-phase glycol loops and two-phase dielectric refrigerant loops in the same chassis. Switching between modes requires only a heat exchanger and control logic swap — not a full hardware replacement. This flexibility eliminates the need for parallel infrastructure and future-proof facilities for emerging two-phase deployments.
Our modular design allows for easy integration and scalability, adapting to your specific needs. The flexible operation modes support both single-phase and two-phase cooling, ensuring optimal thermal management for various applications.
Borealis™ CDU integrates advanced telemetry and intelligent control at the row scale, delivering fast transient stability during workload spikes and real-time observability across both facility and IT cooling loops. Operators gain actionable insights through unified dashboards and APIs, enabling predictive maintenance, proactive anomaly detection, and seamless orchestration with data center infrastructure management (DCIM) systems.
Industry-leading motor efficiency (>92%), built-in VFDs, and peer-to-peer load sharing for up to six units without an external PLC. This design: 1. Maintains operation near the best efficiency point (BEP) for minimal parasitic load 2. Reduces system complexity by removing the need for separate staging controllers 3. Increases reliability with fewer failure points
Borealis™ CUD provides a clean migration path from today’s single-phase glycol systems to tomorrow’s two-phase dielectric solutions — without the need for parallel infrastructure or disruptive retrofits.
Borealis™ CDU is revolutionizing thermal management across various high-density computing environments. From AI and HPC to hyperscale data centers, our solutions ensure optimal performance and reliability. Discover how Borealis™ CDU can enhance your infrastructure and drive innovation in your specific application.
Optimize AI and machine learning workloads with Borealis's superior cooling capabilities, ensuring peak performance and preventing thermal throttling. Experience unparalleled efficiency and reliability.
Enhance HPC cluster performance with ThermaPod™, designed to handle the most demanding computational tasks. Benefit from reduced energy consumption and increased processing power.
Scale your data center operations with confidence using Borealis™ CDU. Our modular and scalable solutions provide efficient thermal management for hyperscale environments, ensuring maximum uptime and cost savings.
The Borealis™ CDU platform Facility-to-Chip™ Cooling Ecosystem delivers measurable benefits that extend beyond thermal performance, impacting operational efficiency, capital planning, and sustainability metrics.
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