NVIDIA Announces Release 1.1 of AI Enterprise Suite

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NVIDIA has announced release 1.1 of its AI Enterprise software suite. It includes production support for containerized AI with the NVIDIA software on VMware vSphere with Tanzu, previously available only on a trial basis.

NVIDIA said the update allows enterprises to run accelerated AI workloads on vSphere running in both Kubernetes containers and virtual machines, with AI Enterprise to support AI development on mainstream IT infrastructure. This, the company said, “provides an integrated, complete stack of containerized software and hardware optimized for AI, all fully managed by IT.”

NVIDIA said this capability will soon be added to the NVIDIA LaunchPad program, available at nine Equinix locations around the world. “Qualified enterprises can test and prototype AI workloads at no charge through curated labs designed for the AI practitioner and IT admin,” the company said in its announcement. “The labs showcase how to develop and manage common AI workloads like chatbots and recommendation systems, using NVIDIA AI Enterprise and VMware vSphere, and soon with Tanzu.”

“AI is a very popular modern workload that is increasingly favoring deployment in containers,” said Gary Chen, research director, Software Defined Compute at IDC. “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.”

NVIDIA said the 1.1 release also provides validation for the Domino Data Lab Enterprise MLOps platform with VMware vSphere with Tanzu, designed to “enable more companies to cost-effectively scale data science by accelerating research, model development, and model deployment on mainstream accelerated servers.”

“This new phase of our collaboration with NVIDIA further enables enterprises to solve the world’s most challenging problems by putting models at the heart of their businesses,” said Thomas Robinson, VP of strategic partnerships at Domino Data Lab. “Together, we are providing every company the end-to-end platform to rapidly and cost-effectively deploy models enterprise-wide.”

NVIDIA also announced it has expanded its AI Enterprise ecosystem with NVIDIA-certified systems from Cisco and Hitachi Vantara, along with qualified system integrators offering solutions for the software suite.

The first Cisco system to be certified for NVIDIA AI Enterprise is the UCS C240 M6 rack server with NVIDIA A100 Tensor Core GPUs. The two-socket, 2RU form factor is designed to power storage- and I/O-intensive applications, such as big data analytics, databases, collaboration, virtualization, consolidation and high performance computing.

The first Hitachi Vantara certified system compatible with NVIDIA AI Enterprise is the Advanced Server DS220 G2 with NVIDIA A100 Tensor Core GPUs, a general-purpose, dual-processor server.

Other server manufacturers also offer NVIDIA-certified Systems for AI Enterprise, including Atos, Dell Technologies, GIGABYTE, H3C, Hewlett Packard Enterprise, Inspur, Lenovo and Supermicro, each system featuring NVIDIA A100, NVIDIA A30 or other NVIDIA GPUs.

AMAX, Colfax International, Exxact Corporation and Lambda are other system integrators qualified for NVIDIA AI Enterprise, joining a global ecosystem of channel partners that includes Axians, Carahsoft Technology Corp., Computacenter, Insight Enterprises, NTT, Presidio, Sirius, SoftServe, SVA System Vertrieb Alexander GmbH, TD SYNNEX, Trace3 and World Wide Technology.