High Performance Computing (HPC) Capabilities
With AI’s need for massive computational power, Intelliscale™ data centers are designed to handle specialized, high-performance hardware, including GPUs and TPUs optimized for parallel processing and matrix operations for modeling, accelerated training, and inference.
Scalability
As AI workloads can vary in intensity, with demands ranging from lightweight inference tasks to heavy-duty model training, Intelliscale™ is designed to allow organizations to easily scale up or down their computational resources.
Energy Efficiency and Cooling
Building on CyrusOne’s sustainability commitment, Intelliscale™ leverages CyrusOne's zero water use design to efficiently provide cooling to demanding AI gear by means of air and/or liquid.
Optimized Network Infrastructure
Intelliscale™ is designed with high-speed interconnects and optimized networking infrastructure to ensure fast data transfer between servers.
Customization and Optimization
With the ability to customize hardware and software stacks, Intelliscale™ ensures that the infrastructure is tailored to the unique needs of customers both in new builds and retrofitting of current data centers.
Reduced Latency and Resource Isolation
Intelliscale™ is designed to minimize network latency for rapid response with time sensitive tasks, and ensures workloads run concurrently allowing for consistent and predictable execution.
Intelliscale™ Design
The Future of AI Data Centers
Intelliscale™ Design is focused on the particular needs of AI and the unique needs of each company’s AI applications. Our dynamic, scalable AI infrastructure solutions meet the needs of the massive amounts of computing power, data storage, modeling and training needed to power the future of AI. With advanced security and compliance, CyrusOne continues to protect both the data and computational infrastructure, as well as support compliance with relevant data protection regulations.
Why CyrusOne
CyrusOne’s Intelliscale™ data centers supply the computational power, scalability, energy efficiency, and specialized infrastructure needed to support the demanding requirements of AI workloads, enabling organizations to develop and deploy advanced AI applications more efficiently.
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