The AI boom will create a path to exascale computing, one of the supercomputing world’s loftiest goals, NVIDIA CEO Jen-Hsun Huang told a packed house Monday at the SC16 annual supercomputing show in Salt Lake City, Utah.
“Several years ago deep learning came along, like Thor’s hammer falling from the sky, and gave us an incredibly powerful tool to solve some of the most difficult problems in the world,” Jen-Hsun said. “Every industry has awoken to AI.”
2016 has been a great year for deep learning and GPU computing, he explained. There are now more than 400 GPU-optimized high-performance computing applications, and all of the top 10 applications are now GPU optimized. The number of deep learning developers has tripled in two years to 400,000. And the launch of our new Pascal GPU architecture means all these applications will run more quickly, and efficiently, than ever.
SaturnV is organized into five 3U boxes per rack, with 15 kilowatt of power on each rack and some 25 racks total. While the press photo of SaturnV indicates 10 servers per rack, this is not reflective of what’s inside. “We could not put that many in ours,” said Capps. “We put this in a datacenter which is not HPC. It was an IT datacenter originally.”
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