Canonical announced today a partnership with Nvidia to certify its Ubuntu 18.04 LTS (Bionic Beaver) operating system on the NVIDIA DGX-2 AI systems in an atempt to accelerate the adoption of AI and ML in multi-cloud environments and at the edge.
Canonical and Nvidia have formed a new alliance to prove that the adoption and implementation of Artificial Intelligence and Machine Learning isn’t a major challenge for enterprises due to the fact that AI-based workloads require greater compute power, security, and flexibility. As such, they’ve certified Ubuntu 18.04 LTS for NVIDIA DGX-2 AI systems to help organizations take advantage of AI’s vast potential.
The Ubuntu 18.04 LTS update with NVIDIA DGX-2 AI system certification will allow for containerized and cloud-native development of GPU-accelerated workloads due to NVIDIA DGX-2 AI systems deliver 2 petaFLOPS of AI performance. The combination of Ubuntu 18.04 LTS and NVIDIA DGX-2 allows data scientists and engineers to work faster and at a greater scale while using their preferred operating system.
“Ubuntu is the preferred AI and ML platform for developers and the No. 1 operating system for Kubernetes deployments on-premises and in the public cloud. This collaboration with NVIDIA enables enterprises to enhance their developers’ productivity and incorporate AI more quickly through development stages to production,” said Stephan Fabel, Director of Product at Canonical.Delivering portable AI workloads on-premises
While enterprises appear to encounter issues with the adoption and integration of AI and ML into their operations at scale, the combination of Ubuntu 18.04 LTS and NVIDIA DGX-2 AI promises unprecedented flexibility, performance, and security to enterprises’ AI and ML operations. Additionally it allows engineers to deliver portable AI workloads on-premises, in the cloud and at the edge.
Enterprises will be able to run the entire line of NVIDIA DGX-2 AI systems either as part of a Charmed Kubernetes cluster running on Ubuntu 18.04 LTS or standalone to unlock the full advantage of containerized and cloud-native development. Canonical’s Kubernetes is capable of fully automating the installation and enablement of Nvidia GPUs, which Ubuntu offers a unique portable multi-cloud experience for AI and ML use cases.