The cores would also be heavily biased for graphics instead of the double-precision floating point calculations datacenters need, he said. The A100 uses high-bandwidth memory for datacenter applications, but that wouldn’t be used in consumer graphics. It has 30,000 components and a kilometer of wire traces.Īs for a consumer graphics chip, Nvidia would configure an Ampere-based chip in a very different way. Huang said the DGX A100 uses the HGX motherboard, which weighs about 50 pounds and is “the most complex motherboard in the world.” (This is the board he pulled out of his home oven in a teaser video). Nvidia DGX A100 systems start at $199,000 and are shipping now through Nvidia Partner Network resellers worldwide. The chips are made by TSMC in a 7-nanometer process. And they have nine Nvidia Mellanox ConnectX-6 HDR 200Gb per second network interfaces, offering a total of 3.6 terabits per second of bi-directional bandwidth. The systems also have six Nvidia NVSwitch interconnect fabrics with third-generation Nvidia NVLink technology for 4.8 terabytes per second of bi-directional bandwidth. The company said that each DGX A100 system has eight Nvidia A100 Tensor Core graphics processing units (GPUs), delivering 5 petaflops of AI power, with 320GB in total GPU memory and 12.4TB per second in bandwidth. Nvidia also launched the Nvidia DGXpert program, which brings DGX customers together with the company’s AI experts, and the Nvidia DGX-ready software program, which helps customers take advantage of certified, enterprise-grade software for AI workflows. Among these users are some of the world’s leading businesses, including automakers, health care providers, retailers, financial institutions, and logistics companies that are adopting AI across their industries. Thousands of previous-generation DGX systems are currently being used around the globe by a wide range of public and private organizations. institution of higher learning to receive DGX A100 systems, which it will deploy to infuse AI across its entire curriculum to foster an AI-enabled workforce.Īmong other early adopters are the Center for Biomedical AI at the University Medical Center Hamburg-Eppendorf, Germany, which will leverage DGX A100 to advance clinical decision support and process optimization. The University of Florida will be the first U.S. The DGX A100 systems’ power will enable scientists to do a year’s worth of work in months or days. Rick Stevens, associate laboratory director for Computing, Environment, and Life Sciences at Argonne National Lab, said in a statement that the center’s supercomputers are being used to fight the coronavirus, with AI models and simulations running on the machines in hopes of finding treatments and a vaccine. Nvidia said a number of the world’s largest companies, service providers, and government agencies have placed initial orders for the DGX A100, with the first systems delivered to Argonne earlier this month.
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