DENVER — Stack Infrastructure announced its certification as a North American colocation partner in the NVIDIA DGX-Ready Data Center program, which helps global businesses and organizations accelerate their adoption of AI by identifying data center partners who are equipped to support that journey.
Artificial intelligence is used across the data center business for data ingestion and management, network optimization, outage detections, and capacity planning. In fact, 83% of enterprises say they will expand AI infrastructure budgets next year, with 39% of those projecting an increase of 25% or more, according to 451 Research's Voice of the Enterprise: AI and Machine Learning, Infrastructure 2019. Artificial intelligence at the data center can enhance compute density and, in many cases, streamline traditional workflows as data and storage demands increase. This AI adoption requires enhanced network, storage, and compute power, and not all data centers are equipped to handle that level of complexity.
The NVIDIA DGX-Ready Data Center program certifies data centers that have the necessary infrastructure to support all NVIDIA DGX systems, including the newly announced NVIDIA DGX A100, which is purpose-built for the unique demands of all AI workloads, including training, inference, and data analytics. Stackdata centers deliver advanced, highly reliable design architecture for flexible power requirements (N+1, 2N, or N) that are required to support these devices, and customers can use the resulting increased compute density to ingest, process, and optimize elevated data volume through algorithmic inferences and machine learning.
"This certification reflects a long-standing commitment Stack has made to our clients to provide innovative digital infrastructure that supports current best practices in AI development,” said Donough Roche, senior vice president of engineering and client services at Stack. "The DGX-Ready Data Center program allows the world’s most innovative companies to think about solutions first without worrying about facility limitations.”
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