Nvidia broadens support for enterprises' containerized AI workloads

Nvidia spent much of 2021 on a series of projects and products designed to nurture AI development and usage across more enterprises. In recent months, it’s been talking much more about metaverses, but metaverses may not get very far in the enterprise world if enterprises don’t master AI first.

With that in mind, the latest release of Nvidia’s AI Enterprise software is now generally available, and with it the ability for more enterprises to support containerized AI workloads.

Nvidia AI Enterprise 1.1 includes production support for containerized AI with the Nvidia software on VMware vSphere with Tanzu, which Nvidia made available on a trial basis last fall when it announced expanded offerings through its existing partnership with VMware. Now, more enterprises will be able to develop, run and manage accelerated AI workloads in vSphere environments in both Kubernetes containers and virtual machines.

Nvidia also plans to add VMware vSphere with Tanzu support to the Nvidia LaunchPad program it announced last summer with Equinix as a way to make Nvidia AI enterprise offerings easier to consume via the cloud. LaunchPad is now available through nine Equinix data center locations around the world. 

These moves should help ease some of the complexity around orchestrating containerized AI workloads through many layers of infrastructure, leading more enterprises to pursue containerized AI projects. 

“AI is a very popular modern workload that is increasingly favoring deployment in containers,” said Gary Chen, research director, Software Defined Compute at IDC, in a statement in an Nvidia blog post. “However, deploying AI capabilities at scale within the enterprise can be extremely complex, requiring enablement at multiple layers of the stack, from AI software frameworks, operating systems, containers, VMs, and down to the hardware. Turnkey, full-stack AI solutions can greatly simplify deployment and make AI more accessible within the enterprise.”

The AI Enterprise 1.1 release also provides validation for the Domino Data Lab Enterprise MLOps Platform with VMware vSphere with Tanzu. Nvidia hyped this integration last summer when it released Version 1.0 of the AI Enterprise software. It allows more companies to cost-effectively scale data science by accelerating research, model development, and model deployment on mainstream accelerated servers.

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