Acclaimed inventors of the GPU, Nvidia Corp. is updating its AI Enterprise software platform to add production support for containerised AI workloads on VMware vSphere with Tanzu. The current update allows enterprises to use Nvidia AI Enterprise 1.1 to run accelerated AI workloads on vSphere in both Kubernetes containers and virtual machines.
The platform is a suite of Artificial Intelligence tools and frameworks that aims to be a turnkey solution for companies looking to run AI workloads in their own various data centres or in the cloud. Making it easier for companies to virtualize AI workloads and run them on Nvidia-certified servers.
As a major feature, the benefits of these workloads can be managed via a single platform. This also allows for companies to deploy AI-ready infrastructure in a manner where it is closer to the data, enabling faster AI training times.
According to Nvidia, one of the top requests from its customers was production support for running AI workloads on VMware vSphere with Tanzu, which is a service that makes it possible to deploy AI on both containers and Virtual Machines within a vSphere environment. With this update, customers gain an integrated, complete stack of containerized software and hardware that’s fully managed and optimized for AI.
Customers can also run the AI Enterprise locally on their own servers or alternatively at nine server locations globally as-a-service on bare-metal infrastructure from data centre provider Equinix Inc.
Nvidia also stated that this will be added to the Nvidia LaunchPad program, which will allow customers to test and prototype new AI jobs for free. The point of the labs is to display how common AI workloads like chatbots and recommendation engines can be developed and managed with their tools.
However, customers who do decide to get straight down to business can deploy the AI toolkit on servers from a selection of partners beyond Equinix, a partner list that includes partners such as Hewlett Packard Enterprise Co, Dell Technologies Inc, Lenovo Group Ltd, Super Micro Computer Inc, Gigabyte Technology Co. Ltd and Inspur Inc.
According to International Data Corp. Analyst, Gary Chen, most AI practitioners prefer to deploy workloads in application containers if they can. “Turnkey, full-stack AI solutions can greatly simplify deployment and make AI more accessible within the enterprise,” Chen said.
Nvidia have proven over the last year that they’re at the forefront of emerging technologies like The Metaverse and AI. Last November their CEO opened the nVidia GTC with a keynote revolving around Omniverse, their plans for a digital twin of Earth which will reportedly dwarf any individual Metaverse, and they later dived into the Avatars for that space. Combining this with their role in GPUs and AI, they’re looking to be a central pillar in the technology of the future.