Sign up for our newsletter and get the latest big data news and analysis.
Daily
Weekly

NVIDIA Announces GA of AI Enterprise 2.1

NVIDIA today announced the general availability of NVIDIA AI Enterprise 2.1., an updated version of its AI and data analytics software suite designed to help enterprises deploy and scale AI applications across bare metal, virtual, container, and cloud environments.

NVIDIA said AI Enterprise 2.1 offers advanced data science with the latest NVIDIA RAPIDS and low code AI model development using the recent release of NVIDIA TAO Toolkit.

“Making enterprise AI even more accessible across hybrid or multi-cloud environments, AI Enterprise 2.1 includes added support for Red Hat OpenShift running in the public cloud and the new Microsoft Azure NVads A10 v5 series,” the company said in its announcement. “These are the first NVIDIA virtual GPU instances offered from the public cloud, which enables affordable GPU sharing.”

NVIDIA said the updated version  enables customers to stay current with AI development and deployment tools, along with  support and  updates from NVIDIA. Support will continue for those relying on earlier versions of NVIDIA AI frameworks, designed for managing infrastructure updates.

The NVIDIA TAO Toolkit 22.05 is a low code solution of NVIDIA TAO, a framework for developers to create production-ready models to power speech and vision AI applications. The latest version of the toolkit is now supported through NVIDIA AI Enterprise, with new features including REST APIs integration, pre-trained weights import, TensorBoard integration, and new pre-trained models.

The RAPIDS 22.04 release provides more support for data workflows through the addition of new models, techniques, and data processing capabilities across NVIDIA data science libraries, the company said.

In addition, Red Hat OpenShift, an enterprise Kubernetes platform with integrated DevOps capabilities, is now certified and supported for the public cloud with NVIDIA AI Enterprise, in addition to bare metal and VMware vSphere-based deployments. This enables a standardized AI workflow in a Kubernetes environment to scale across a hybrid-cloud environment.

The Azure NVads A10 v5 series, powered by NVIDIA A10 Tensor Core GPUs, offers GPU scalability and affordability with fractional GPU sharing for flexible GPU sizes ranging from one-sixth of an A10 GPU to two full A10 GPUs.

As part of the supported platforms, the NVads A10 v5 instances are certified with NVIDIA AI Enterprise to deliver performance for deep learning inferencing, maximizing the utility and cost efficiency of at-scale deployments in the cloud.

NVIDIA AI Accelerated partner Domino Data Lab’s enterprise MLOps platform is now certified for NVIDIA AI Enterprise. This level of certification is designed to mitigate deployment risks and high-performance integration with the NVIDIA AI platform. This partnership pairs the Enterprise MLOps benefits of workload orchestration, self-serve infrastructure, and collaboration with cost-effective scale from virtualization on mainstream accelerated servers, according to NVIDIA.

NVIDIA LaunchPad provides organizations with short-term access to the NVIDIA AI Enterprise software suite in a private accelerated computing environment that includes hands-on support: NVIDIA LaunchPad labs. Hosted on NVIDIA-accelerated infrastructure, the labs enable enterprises to speed up the development and deployment of modern, data-driven applications and quickly test and prototype the entire AI workflow on the same complete stack available for deployment.

Leave a Comment

*

Resource Links: