Nvidia unveils AI software suite to support enterprises
Enterprises can add modern workloads to their mainstream servers using the latest release of the Nvidia AI Enterprise software suite, says the company. The software is generally available, optimised, certified and supported by Nvidia and includes updates such as production support for containerised AI with the software on VMware vSphere with Tanzu; this was previously only available on a trial basis. Enterprises can run accelerated AI workloads on vSphere, running in both Kubernetes containers and virtual machines to support advanced AI development on the mainstream IT infrastructure.
Nvidia has also announced that it will soon add VMware vSphere with Tanzu support to the Nvidia LaunchPad program for Nvidia AI Enterprise, 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 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.
Containerised development for AI adds complexity to workloads which requires orchestration across many layers of infrastructure, explained Nvidia on the introduction of the AI-ready enterprise platform.
The 1.1 release also provides validation for the Domino Data Lab Enterprise MLOps Platform with VMware vSphere with Tanzu. This new integration enables more companies to cost-effectively scale data science by accelerating research, model development, and model deployment on mainstream accelerated servers.
The company also announced an industry ecosystem which is expanding with the first Nvidia-certified systems from Cisco and Hitachi Vantara. There is also a growing roster of newly qualified system integrators.
The first Cisco system to be Nvidia-certified for Nvidia AI Enterprise is the Cisco UCS C240 M6 rack server with Nvidia A100 Tensor Core GPUs. The two-socket, 2RU form factor can power a range of storage and I/O-intensive applications, such as big data analytics, databases, collaboration, virtualisation, consolidation and high-performance computing.
From Hitachi Vantara, there is the Hitachi Advanced Server DS220 G2 with Nvidia A100 Tensor Core GPUs. The general purpose, dual processor server delivers a balance of compute and storage with the flexibility to power a wide range of solutions and applications, said the company.
“For many enterprises, cost is an important consideration when deploying new technologies like AI-powered quality control, recommender systems, chatbots and more,” said Dan McConnell, senior vice president, Product Management at Hitachi Vantara. “Accelerated with Nvidia A100 GPUs and now certified for Nvidia AI Enterprise, Hitachi Unified Compute Platform (UCP) solutions using the Hitachi Advanced Server DS220 G2 give customers an ideal path for affordably integrating powerful AI-ready infrastructure to their data centres,” he commented.
Server manufacturers offering Nvidia-certified systems for Nvidia AI Enterprise include Atos, Dell Technologies, GIGABYTE, H3C, Hewlett Packard Enterprise, Inspur, Lenovo and Supermicro, all of whose systems feature Nvidia A100, Nvidia A30 or other Nvidia GPUs. Customers can also choose to deploy Nvidia AI Enterprise on their own servers or on as-a-service bare metal infrastructure from Equinix Metal across nine regions globally.
AMAX, Colfax International, Exxact and Lambda are system integrators qualified for Nvidia AI Enterprise, joining an ecosystem that includes Axians, Carahsoft Technology, Computacenter, Insight Enterprises, NTT, Presidio, Sirius, SoftServe, SVA System Vertrieb Alexander GmbH, TD SYNNEX, Trace3 and World Wide Technology.
