NVIDIA AI Enterprise 2.1 Is Now in GA
July 25, 2022 -- Today, NVIDIA announced general availability of NVIDIA AI Enterprise 2.1. This latest version of the end-to-end AI and data analytics software suite is optimized, certified, and supported for enterprises to deploy and scale AI applications across bare metal, virtual, container, and cloud environments.
Release highlights: New containers, public cloud support
The NVIDIA AI Enterprise 2.1 release offers advanced data science with the latest NVIDIA RAPIDS and low code AI model development using the most 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. These are the first NVIDIA virtual GPU instances offered from the public cloud, which enables affordable GPU sharing.
Support for the latest AI frameworks
NVIDIA AI Enterprise enables you to stay current with the latest AI tools for development and deployment, along with enterprise support and regular updates from NVIDIA. Support will continue for those relying on earlier versions of NVIDIA AI frameworks, ensuring the flexibility to manage infrastructure updates.
NVIDIA TAO Toolkit 22.05
The NVIDIA TAO Toolkit is a low code solution of NVIDIA TAO, a framework that enables developers to create custom, production-ready models to power speech and vision AI applications.
The latest version of the TAO Toolkit is now supported through NVIDIA AI Enterprise, with new key features including REST APIs integration, pre-trained weights import, TensorBoard integration, and new pre-trained models.
NVIDIA RAPIDS 22.04
The RAPIDS 22.04 release provides more support for data workflows through the addition of new models, techniques, and data processing capabilities across all the NVIDIA data science libraries.
Red Hat OpenShift support in the public cloud
Red Hat OpenShift, the industry’s leading 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.
Azure NVads A10 v5 support
The Azure NVads A10 v5 series, powered by NVIDIA A10 Tensor Core GPUs, offers unprecedented 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 optimized performance for deep learning inferencing, maximizing the utility and cost efficiency of at-scale deployments in the cloud.
Domino Data Lab Enterprise MLOps Platform Certification
NVIDIA AI Accelerated partner Domino Data Lab’s enterprise MLOps platform is now certified for NVIDIA AI Enterprise. This level of certification mitigates deployment risks and ensures reliable, 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.
Try NVIDIA AI Enterprise
NVIDIA LaunchPad provides organizations around the world with immediate, short-term access to the NVIDIA AI Enterprise software suite in a private accelerated computing environment that includes hands-on labs.
Experience the latest NVIDIA AI frameworks and tools, running on NVIDIA AI Enterprise, through new 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.
Check out these new LaunchPad labs for NVIDIA AI Enterprise 2.1:
- Multi-Node Training for Image Classification on VMware vSphere with Tanzu
- Deploy a Fraud Detection XGBoost Model using NVIDIA Triton
- Develop a Custom Object Detection Model with NVIDIA TAO Toolkit and Deploy with NVIDIA DeepStream
Source: Phoebe Lee, NVIDIA
