NVIDIA and VMware: Opening the Doors to AI for Every Enterprise

VMware and NVIDIA Partner to Make It Easier to Develop and Deploy AI Workloads for Hybrid Cloud

NVIDIA is the recognized leader in artificial intelligence (AI) solutions across every industry. It is also a Strategic partner of the VMware Technology Alliance Partner Program and an Advanced partner of the VMware Partner Connect Program.

With the majority of data centers running VMware vSphere®, NVIDIA and VMware are well positioned to partner to develop solutions. Today, the two companies work together to deliver solutions for high-performance computing, supercomputing, and more recently, AI.

A History of Partnership

The two tech leaders have a history of collaboration. Don Bradley leads NVIDIA’s strategic alliance team that works with VMware. He says, “The partnership originated from our work with VMware in accelerating their VDI desktop solutions with our virtual GPU technology. Now we’ve evolved our partnership with NVIDIA AI Enterprise software suite, offered exclusively on VMware vSphere with VMware Tanzu™.” This new offering removes barriers for enterprises to get in on the AI game and represents a first-of-its-kind partnership between NVIDIA and VMware.

The two companies work closely together, with joint engineering, product management and product marketing teams meeting regularly to develop, deliver and market the joint products. Bradley says, “We're connected from our CEO to VMware’s CEO and down to engineering in terms of alignment.”

NVIDIA also partners with VMware on NVIDIA Omniverse™ Enterprise, a platform enabled by vSphere that supports 3D design collaboration with real-time, physically accurate simulation for creators, designers, researchers and engineers. At VMworld 2021, BMW Group showcased a digital twin factory in a virtual environment using Omniverse Enterprise.

NVIDIA is one of a select few partners working with VMware on Project Monterey, VMware’s vision for a data center built to support the modern and cloud-native applications that businesses want to run. Tony Kuo, NVIDIA Alliance Director for VMware notes, “It’s a radically different way for customers to run and manage their data centers that’s optimized for these innovative applications.”

Making AI Accessible to the Enterprise

Many organizations are trying to determine how to best leverage AI, inspired by use cases already widely employed. As Anne Hecht, Senior Director of Product Marketing, Enterprise at NVIDIA says, “AI is making everything better and smarter. We’re seeing AI used for personalized product recommendations on retail sites, chatbots for customer service, bubbling up the best applicants for HR departments, predictive maintenance for more reliable operations, and better cybersecurity and fraud detection.”

But setting up the infrastructure for AI is complex, and solutions must solve the pain points of two key audiences—AI practitioners and IT administrators. AI practitioners want to work in a cloud-native environment that uses Kubernetes containers but don’t understand how to set up that environment. IT administrators need to build out that infrastructure but may lack Kubernetes expertise.

The NVIDIA AI Enterprise software suite running on vSphere with VMware Tanzu removes complexity and makes it much easier for enterprise organizations to develop and deploy AI workloads for the hybrid cloud. It’s cloud-native, includes the tools that AI practitioners use every day, and is built on the vSphere environment that IT administrators already know. Because the solution can be run on-premises, in hybrid cloud environments, or private cloud environments, companies can keep cloud costs under control and address issues specific to highly regulated industries.

Improving Patient Care and Consolidating Data Centers

NVIDIA AI Enterprise on vSphere enables organizations to explore innovative use cases for AI. For example, this blog post discusses how the Netherlands Cancer Institute (NKI), one of the world’s top-rated cancer research and treatment centers, can use high-resolution images to train its AI model to detect the size and location of cancerous tumors. That allows clinicians to better target tumors during patient treatment.

Many customers are using the joint AI-ready platform to consolidate and better utilize resources. Companies often have on-premises infrastructure purchased by one team that can’t be provisioned to others. By virtualizing all infrastructure, an organization can consolidate its resources into a virtual pool and then provision virtual machines (VM) and tools based on what an AI practitioner needs and the amount of available resources. Nothing sits idle.

A large healthcare organization employed NVIDIA AI Enterprise for this consolidation and utilization use case. The organization had research institutes associated with its hospitals and clinics, but each was investing in its own technology and buildout to develop and run AI applications. The organization used the AI Enterprise software suite to consolidate several data centers into a single deployment. It’s now getting higher utilization, and because it’s not servicing multiple data centers, upgrades can be performed quickly to get new features and software.

As the University of Pisa discovered, performance on the infrastructure running the joint solution virtualized with VMware technology was almost the same as running on bare metal infrastructure.

Taking AI for a Test Spin has Never been Easier

NVIDIA makes it easy to try out the AI Enterprise software suite in the VMware environment with NVIDIA LaunchPad, a hosted trial environment. LaunchPad offers four curated labs with common AI use cases for AI practitioners and IT administrators. Users can build a chatbot, develop a recommendations engine, perform image classification, and even classify IT tickets. Each lab takes approximately eight hours, and participants have two weeks to complete them.