Cyxtera’s AI/ML Compute as a Service, powered by NVIDIA DGX A100 systems, enables AI/ML-powered workloads to be deployed with great agility and speed. Provisioning of AI and ML is made easier through our as-a-service model that eliminates the need for large capital outlays and over provisioning.
Subscription-based model allows you to manage costs as operational expenses, avoiding the burden to outlay large sums of capital
Cyxtera shortens your implementation time leading to faster time-to-market for your solutions.
Provision your way easily through our point-and-click approach. Plus, you can select from a rich ecosystem of service providers and technology solutions, including StaaS, connectivity, and security.
Manage resources, including power and cooling. Cyxtera is leading the way to more efficiencies through our engineered solutions that meet your deployment and maintenance expectations.
Expand your AI/ML program. Cyxtera offers the consistency and reliability you need with data centers in Asia, Europe and North America that meet or exceed DGX-Ready program requirements.
Cyxtera has supported customers across the world for years, implementing IT infrastructure. We offer on-demand colocation approaches that will accelerate your deployment of AI/ML workloads.
You can manage access to your NVIDIA DGX systems through the Cyxtera Command Center. No more expensive staffing to install the stations. As a result, you’ll manage your workloads with the security and control provided by single tenant, dedicated infrastructure combined with the flexibility and agility of cloud.
AI/ML Compute as a Service, Powered by NVIDIA DGX™ A100
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The Universal System for Every AI/ML Workload.
With the fastest I/O architecture of any NVIDIA DGX system, NVIDIA DGX A100 is the universal system for all AI workloads, from analytics to training to inference. It sets a new bar for compute density, packing 5petaFLOPS of AI performance into a 6U form factor and replaces legacy compute infrastructure with a single, unified system that can do it all. Its 8 NVIDIA A100 Tensor Core GPUs can be used together to run the largest jobs or divided into as many as 56 separate and fully isolated instances with dedicated high bandwidth memory, cache, and compute cores. The combination of dense compute power and complete workload flexibility makes DGX A100 ideal for both single node deployments and large-scale clusters.
