NVIDIA Software Gives Hundreds of Thousands of Enterprises Worldwide Ability to Run AI on VMware vSphere and Industry-Standard Servers
NVIDIA announced the availability of NVIDIA AI’s Enterprise, a comprehensive software suite of AI tools and frameworks that enables the hundreds of thousands of companies running VMware vSphere to virtualize AI workloads on NVIDIA-Certified Systems™.
Leading manufacturers Atos, Dell Technologies, GIGABYTE, Hewlett Packard Enterprise, Inspur, Lenovo and Supermicro are offering NVIDIA-Certified Systems optimized for AI workloads on VMware vSphere with NVIDIA AI’s Enterprise. Separately, Dell Technologies today announced Dell EMC VxRail as the first hyperconverged platform to be qualified as an NVIDIA-Certified System for NVIDIA AI Enterprise.
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To help teams of data scientists run their AI workloads most efficiently, Domino Data Lab today announced it is validating its Domino Enterprise MLOps Platform with NVIDIA AI Enterprise, which runs on mainstream NVIDIA-Certified Systems.
“The first wave of AI has been powered by specialized infrastructure that focused adoption on industry pioneers,” said Manuvir Das, head of Enterprise Computing at NVIDIA. “Today is the beginning of a new chapter in the age of AI, as NVIDIA software brings its transformative power within reach for enterprises around the world that run their workloads on VMware with mainstream data center servers.”
“As AI applications become critical, customers want to run them on their enterprise infrastructure for manageability, scalability, security and governance,” said Krish Prasad, senior vice president and general manager of the Cloud Platform Business Unit at VMware. “Running NVIDIA AI’s Enterprise on VMware vSphere delivers a certified, end-to-end AI-Ready enterprise platform that’s easy to deploy and operate.”
“Partnering closely with NVIDIA, we’re deepening our product integrations by enabling the Domino Enterprise MLOps Platform to run with a broader range of NVIDIA GPUs and validating it for NVIDIA AI’s Enterprise,” said Nick Elprin, CEO and co-founder of Domino Data Lab. “This new offering will help hundreds of thousands of enterprises accelerate data science at scale.”
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Customers Simplify, Scale with NVIDIA AI Enterprise
Dozens of automotive, education, finance, healthcare, manufacturing and technology companies worldwide are among the early adopters using NVIDIA AI’s Enterprise. Many are midsize companies that can now develop a broad range of applications using the world’s most widely used servers to deploy and scale data science, conversational AI, computer vision, recommender systems and more.
Among the earliest to use NVIDIA AI’s Enterprise is Cerence Inc., a leading provider of conversational AI for automotive and mobility markets with nearly 400 million Cerence-powered vehicles shipped worldwide. The company is using AI Enterprise to develop intelligent in-car assistants and digital co-pilots.
Additionally, University of Pisa, an Italian public research university, is supporting HPC and AI training across multiple disciplines to advance scientific studies with the NVIDIA software.
“NVIDIA AI’s Enterprise allowed us to expand our support for our researchers and students who utilize data analytics and AI deep learning and machine learning, while making these applications easier to deploy and manage,” said Maurizio Davini, chief technology officer at the University of Pisa. “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.”
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Powerful AI Performance on Mainstream Servers
NVIDIA AI’s Enterprise enables IT professionals that use VMware vSphere to run traditional enterprise applications to easily and cost-effectively support AI workloads while using the same tools they use to manage large-scale data centers and hybrid clouds.
NVIDIA-Certified Systems from Atos, Dell Technologies, GIGABYTE, Hewlett Packard Enterprise, Inspur, Lenovo and Supermicro for NVIDIA AI’s Enterprise feature a wide range of NVIDIA GPUs, including the A100, A30, A40, A10 and T4. These mainstream accelerated systems provide customers with a broad selection of options for scale-out, multinode, AI application performance on vSphere that is virtually indistinguishable from bare-metal servers.
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