{"id":21,"date":"2020-08-17T07:53:06","date_gmt":"2020-08-17T07:53:06","guid":{"rendered":"https:\/\/machine-learning.webcloning.com\/2020\/08\/17\/ai-of-the-storm-how-we-built-the-most-powerful-industrial-computer-in-the-u-s-in-three-weeks-during-a-pandemic\/"},"modified":"2020-08-17T07:53:06","modified_gmt":"2020-08-17T07:53:06","slug":"ai-of-the-storm-how-we-built-the-most-powerful-industrial-computer-in-the-u-s-in-three-weeks-during-a-pandemic","status":"publish","type":"post","link":"https:\/\/salarydistribution.com\/machine-learning\/2020\/08\/17\/ai-of-the-storm-how-we-built-the-most-powerful-industrial-computer-in-the-u-s-in-three-weeks-during-a-pandemic\/","title":{"rendered":"AI of the Storm: How We Built the Most Powerful Industrial Computer in the U.S. in Three Weeks During a Pandemic"},"content":{"rendered":"
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In under a month amid the global pandemic, a small team assembled the world\u2019s seventh-fastest computer.<\/p>\n

Today that mega-system, called Selene<\/a>, communicates with its operators on Slack, has its own robot attendant and is driving AI forward in automotive, healthcare and natural-language processing.<\/p>\n

While many supercomputers tap exotic, proprietary designs that take months to commission, Selene is based on an open architecture NVIDIA shares with its customers.<\/p>\n

The Argonne National Laboratory, outside Chicago, is using a system based on Selene\u2019s DGX SuperPOD design<\/a> to research ways to stop the coronavirus. The University of Florida will use the design to build the fastest AI computer in academia<\/a>.<\/p>\n

DGX SuperPODs are driving business results for companies like Continental in automotive<\/a>, Lockheed Martin in aerospace and Microsoft in cloud-computing services.<\/p>\n

Birth of an AI System<\/b><\/h2>\n

The story of how and why NVIDIA built Selene starts in 2015.<\/p>\n

NVIDIA engineers started their first system-level design with two motivations. They wanted to build something both powerful enough to train the AI models their colleagues were building for autonomous vehicles and general purpose enough to serve the needs of any deep-learning researcher.<\/p>\n

The result was the SATURNV cluster<\/a>, born in 2016 and based on the NVIDIA Pascal GPU. When the more powerful NVIDIA Volta GPU debuted a year later, the budding systems group\u2019s motivation and its designs expanded rapidly.<\/p>\n