With Nvidia's AI Enterprise software set of tools and frameworks, enterprises using VMware vSphere can virtualize AI workloads on Nvidia-certified servers. The A100, A30, A40, A10, and T4 Nvidia GPUs are now available in systems from Atea, Carahsoft, Computacenter, Insight Enterprises, SoftServe, Dell Technologies, and SVA System.
As companies discover the benefits of automation and large data analytics, they are increasingly adopting AI. According to 451 Research, 95% of firms consider AI "critical to their digital transformation efforts." According to a McKinsey report, 30% of firms are conducting AI pilots, and nearly half have integrated AI into conventional business processes.
Using the same tools for managing large-scale datacenters and hybrid clouds, AI Enterprise enables VMware vSphere users to run traditional enterprise apps. It also has an app discovery dashboard and the ability to migrate multiple virtual machines from one host server to another.
Machines and containers can be created on demand using AI Enterprise's centrally controlled infrastructure pools. Nvidia claims that AI Enterprise has optimized vSphere to run applications like as TensorFlow, PyTorch, Nvidia's Transfer Learning Toolkit, GPU Operator, and Network Operator, Triton Inference Server, TensorRT, Cuda-X, vGPU, Magnum IO, DOCA, RAPIDS, and more.
Nvidia-certified AI Enterprise systems use Ampere hardware with Tensor Core technology to speed up AI operations. The servers also have Nvidia BlueField data processing units (DPUs), which are software-defined hardware engines for networking and security workloads.
For one year, AI Enterprise subscription licenses start at $2,000 per CPU socket. Perpetual licenses are $3,595 plus support.
"The first wave of AI was powered by specialized infrastructure that targeted industry pioneers," said Manuvir Das, Nvidia's head of enterprise computing. Using VMware and conventional data center servers, organizations throughout the world may now take advantage of Nvidia software's transformational capabilities.
In addition to the automotive industry, Das said “dozens” of other industries are early adopters of AI Enterprise. So Domino Data Lab can validate its data science platform. Cerence uses AI Enterprise to build intelligent in-car helpers and “digital copilots.” And Nvidia's software supports high-performance computing and AI training at the University of Pisa in Italy.
According to IDC, organizations will spend about $342 billion on AI software, hardware, and services like AI Enterprise in 2021 if present trends continue.
“By working closely with Nvidia, we're deepening our product integrations and validating the Domino Enterprise MLOps Platform for AI Enterprise,” Domino Data Lab CEO Nick Elprin stated. It will assist hundreds of thousands of businesses accelerate data science.
This article was summarized by an experimental AI. Original content can be found here