NVIDIA partners with VMware to enable GPU-accelerated AI across enterprise datacenters for all workload types.

Nvidia Corp. and VMware Inc. have launched Nvidia AI Enterprise, a suite of artificial intelligence tools and frameworks that enables companies to virtualize AI workloads and run them on Nvidia-certified server systems. The platform allows enterprises to manage AI workloads through a single platform and deploy AI-ready infrastructure close to where their data resides, whether in the cloud, data center, or network edge. One of the platform's key components is Nvidia GPU Cloud, a catalog of optimized software tools for deep learning and high-performance computing that leverages Nvidia's graphics processing units, which integrates with VMware's vSphere to simplify AI workload deployment on existing servers.

The Nvidia AI Enterprise platform can run on VMware vSphere-certified systems sold by Dell Technologies Inc., Hewlett Packard Enterprise Co., Inspur Inc., Lenovo Group Ltd., Gigabyte Technology Co. Ltd., and Super Micro Computer Inc., supporting a range of Nvidia GPUs including the A100, A30, A40, A10, and T4 processors. Dell announced separately that Dell EMC VxRail is the first hyperconverged platform to be qualified as an Nvidia-Certified System for Nvidia AI. Manuvir Das, head of enterprise computing at Nvidia, emphasized the significance of the launch, stating that "Nvidia AI is now ready for every enterprise. Now, every business function can be infused with AI."

Nvidia has partnered with Domino Data Lab Inc. to validate the Domino Enterprise MLOps platform on Nvidia AI Enterprise, providing companies with an organized approach to machine learning. Domino Data Lab Chief Executive Nick Elprin explained that "This new offering will help hundreds of thousands of enterprises accelerate data science at scale." Dozens of companies across industries including automotive, education, finance, healthcare, manufacturing, and technology have tested the platform as early adopters to create applications for conversational AI, computer vision, and recommender systems.

The University of Pisa is among the early adopters, using the platform to support HPC and AI training across multiple disciplines to advance scientific studies. According to University of Pisa Chief Technology Officer Maurizio Davini, "Our testing has shown that these latest collaborations between NVIDIA and VMware deliver the full potential of our GPU-accelerated virtualized infrastructure at near bare-metal speeds." Nvidia AI Enterprise is now available worldwide from channel partners, with pricing starting at $2,000 per CPU socket for one year with Business Standard Support, while perpetual licenses are priced at $3,595 per year with additional support purchase required.