NVIDIA and VMware are collaborating to develop an AI-ready enterprise platform that brings the world’s leading AI stack and optimized software to the infrastructure used by hundreds of thousands of enterprises worldwide.
VMware announced an upcoming update to VMware vSphere with Tanzu, a leading virtualization platform that enables IT teams to get started with Kubernetes workloads on existing infrastructure.
Enterprises can now run trials of their AI projects using vSphere with Tanzu in conjunction with the NVIDIA AI Enterprise software suite.
NVIDIA AI Enterprise is an end-to-end, cloud-native suite of AI and data analytics frameworks and tools optimized, certified and supported by NVIDIA to enable the rapid deployment, management and scaling of AI applications?in the modern hybrid cloud.
By bridging the gap between the worlds of IT operations, data scientists and application developers, NVIDIA AI Enterprise simplifies the AI development lifecycle to help customers get projects into production faster.
NVIDIA AI Enterprise and VMware vSphere with Tanzu enable developers to run AI workloads on Kubernetes containers within their VMware environments, leveraging infrastructure easily managed by IT.
The software runs on mainstream, NVIDIA-Certified Systems from leading server manufacturers, providing an integrated, complete stack of software and hardware optimized for AI.
“VMware serves enterprises by simplifying infrastructure complexity, and our collaboration with NVIDIA enables customers to develop and deploy advanced AI applications on their hybrid clouds,” said Lee Caswell, vice president of marketing for the cloud infrastructure business group at VMware. “With NVIDIA AI Enterprise and VMware vSphere with Tanzu, customers can manage AI development and deployment on mainstream data center servers and clouds, making it easy to integrate the AI applications powering growth in every industry.”
NVIDIA AI Enterprise provides developer-optimized AI software such as PyTorch, TensorFlow, NVIDIA TensorRT, NVIDIA Triton Inference Server, and NVIDIA RAPIDS.
These tools make it easy for AI developers and data scientists to access tools and frameworks needed to build a host of enterprise AI applications such as conversational AI, computer vision and recommender systems, according to the vendors.
The cloud-native architecture of NVIDIA AI Enterprise enables IT to centrally manage all clusters and apps across their hybrid cloud infrastructure. The software delivers near-bare-metal AI performance—even in virtualized environments—so that IT teams can help developers be able to rapidly explore ideas and iterate as they build their models.
For more information about this news, visit www.nvidia.com.