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In an announcement that might have been the most unexpected in the keynote, Huang announced NvidiaвЂ™s first-ever, Arm-based, data center CPU, called Grace in honor of the famous American programmer Grace Hopper. Grace, the First-Ever Nvidia Data Center CPU In total, over 50 servers from the world's top server makers will be certified for Nvidia EGX Enterprise.вЂќДЄmong the first Nvidia customers incorporating these new A30- and A10-based systems into their data centers are Lockheed Martin and Mass General Brigham. Finally, the 300,000 VMware enterprise customers can easily build an AI computing infrastructure that seamlessly integrates into their existing environment. вЂњThe enterprise IT ecosystem is thrilled. The complete platform, from certified servers to the Nvidia AI Enterprise software, is called the Nvidia EGX platform, according to Huang. вЂњSo AI workloads can be distributed to multiple systems and achieve bare metal performance,вЂќ giving users major benefits. вЂњAll of the Nvidia optimizations for compute and data transfer are now plumbed through the VMware stack,вЂќ he said. Some 70 percent of the world's enterprises are running VMware, he added. вЂњOne segment of computing we've not served is enterprise computing,вЂќ and thatвЂ™s where the integration with VMware vSphere 7 and the latest certified servers will help, said Huang. The first new Nvidia-Certified systems using the A30 and A10 GPUs will be available later this year from Nvidia partners including Atos, Dell Technologies, GIGABYTE, H3C,В Inspur,В Lenovo,В QCTВ andВ Supermicro.ДЄs the lure and promise of AI for enterprises continues to spread, Nvidia, like other companies, has been looking to find new ways to serve customers, Huang said. The A30 includes 24GB of HBM2 memory and a PCIe Gen4 64GB/s interconnect. Multi-Instance GPU (MIG) and FP64 Tensor Cores combine with 933 gigabytes per second (GB/s) of memory bandwidth in a low 165W power envelope, all running on a PCIe card. The Nvidia A30 GPU is built for AI inference at scale and for mainstream enterprise workloads, according to the company, making it capable of rapidly re-training AI models with TF32, as well as accelerate high-performance computing applications using FP64 Tensor Cores. We have to make AI easier to use, to turn AI from computer science to computer products.вЂќ

вЂњTrillion dollar industries can soon apply AI to improve productivity and invent new products, services and business models. вЂњThere are many challenges to overcome,вЂќ especially in industrial edge and autonomous system applications, but they also offer the largest opportunities for AI to make an impact. вЂњThe next wave is enterprise, and industrial edge where AI can revolutionize the world's largest industries, from manufacturing, logistics, agriculture, healthcare, financial services, and transportation,вЂќ said Huang.

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Navy Rear Admiral Grace Hopper, and a myriad of new AI software and services, all of which are aimed at helping customers to use AI for cybersecurity, autonomous vehicles, workflows and more.ДЄll of these components are being added to bring Nvidia together as a full stack computing platform company that can help customers solve new problems and enter new markets as AI moves from early work in theory and development into real-world uses, Huang said in his keynote. The A30 is aimed at AI inferencing and enterprise workloads, while the A10 is aimed at bringing mainstream graphics and video together with AI services.ДЄlso unveiled was the companyвЂ™s first-ever data center CPU, named Grace for the late computer programming pioneer and U.S. The new GPUs, the Nvidia A30 and the Nvidia A10 are both Tensor Core GPUs built for mainstream enterprise servers. Nvidia GTC21 вЂ“ With a goal of bringing easier AI to the enterprise, Nvidia is releasing two new AI-targeted GPUs and a line of Nvidia-certified servers from partner manufacturers that are built to run the Nvidia AI Enterprise software suite out of the box.Дetails of the new products were unveiled April 12 (Monday) by Nvidia CEO Jensen Huang in a keynote broadcast as part of NvidiaвЂ™s spring GTC21 (GPU Technology Conference), which is being held virtually due to the COVID-19 pandemic.

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