NVIDIA has revealed widespread adoption of the NVIDIA EGX edge AI platform, bringing a new wave of secure, GPU-accelerated software, services and servers to enterprise and edge data centers.
According to the announcement, hundreds of vision AI, 5G, CloudRAN, security and networking companies are teaming with major server manufacturers, including Dell Technologies, Inspur, Lenovo and Supermicro, as well as software infrastructure providers, including Canonical, Cloudera, Red Hat, SUSE and VMware, to leverage the NVIDIA EGX platform to help businesses bring AI to the edge.
The world’s largest industries — manufacturing, healthcare, retail, logistics, agriculture, telco, public safety and broadcast media — are able to benefit from the EGX platform to quickly and efficiently deploy AI at scale.
NVIDIA also announced that the EGX platform is expanding to combine the NVIDIA Ampere GPU and BlueField-2 DPU capabilities on a single PCIe card, giving enterprises a common platform to build secure, accelerated data centers. BlueField-2 DPUs include powerful Arm CPU cores that can be used to create a trusted enclave for AI inference models running on the GPU.
“Companies around the world will come to use AI to improve virtually every aspect of their business,” said Jensen Huang, founder and CEO of NVIDIA, who unveiled the news in his keynote at the GPU Technology Conference. “To support this massive shift, NVIDIA has created an accelerated computing platform that helps companies modernize their data centers and deploy AI anywhere.”
At the heart of the EGX platform is an optimized AI software stack available on NVIDIA NGC, a software catalog offering a range of industry-specific AI toolkits and pre-trained models to make it easier to build and deploy AI applications on NVIDIA-Certified systems.
NVIDIA AI application frameworks are used by leading AI software vendors such as Deep North, Everseen and Whiteboard Coordinator to build and deploy healthcare, retail, logistics and smart cities solutions.
NVIDIA vGPU software products and GPUDirect RDMA technologies give NVIDIA GPUs the ability to send and receive data at full bandwidth to unlock the highest performance.
To help enterprises deploy AI at scale, NVIDIA is working with leading platform companies, including Canonical, Cloudera, Red Hat, SUSE and VMware, to enable their flagship virtualization, operating systems, Kubernetes and data analytics platforms are fully optimized for NVIDIA AI software when running in bare metal or virtualized environments.
Rather than having 10,000 servers in one location, future enterprise data centers will have one or more servers across 10,000 different locations, including inside office buildings, factories, warehouses, cell towers, schools, stores and banks.
To simplify and secure the deployment and management of AI applications and models on these servers at scale, NVIDIA announced an early access program for a new service called NVIDIA Fleet Command. This hybrid cloud platform combines the security and real-time processing capabilities of edge computing with the remote management and ease of software-as-a-service.
Through a unified control plane, Fleet Command centralizes the management of servers spread across vast areas, including factories, hospitals, retail stores and even city streets. Fleet Command’s one-touch provisioning, over-the-air software updates, remote management and detailed monitoring dashboards make it easier for operational teams to reduce the burden of IT to get the most out of their AI applications and drive the highest operational efficiency.
Among the first companies provided early access to Fleet Command is KION Group, a leader in global supply chain solutions, which is using the NVIDIA EGX AI platform to develop AI applications for its intelligent warehouse systems, increasing the throughput and efficiency in retail distribution centers.
Additionally, Northwestern Memorial Hospital, the No. 1 hospital in Illinois and top 10 in the nation, is working with Whiteboard Coordinator to use Fleet Command for its IoT sensor platform, which includes computer vision, voice recognition and Bluetooth tracking capabilities inside its clinics and medical centers.
“Whiteboard Coordinator works with leading healthcare providers to organize their applications, servers and software deployments from anywhere at any time from the cloud,” said Andrew Gostine, MD, CEO of Whiteboard Coordinator. “We’re using NVIDIA Fleet Command to remotely deploy and securely manage a suite of healthcare AI applications across multiple hospital locations with a few clicks. That frees us to focus more on providing value to patients, instead of spending hours managing infrastructure.”
AI/ML | ARM | chip | CPU | edge AI | GPU | Nvidia | processor