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2017 GTC San Jose

S7549 - Deep Learning Acceleration of Progress toward Delivery of Fusion Energy

Session Speakers
Session Description

Expediting delivery of fusion power -- identified by the 2015 CNN "Moonshots for the 21st Century" series as one of six grand challenges for the modern world -- can be enabled by engaging big-data-driven machine/deep learning predictive methods. Princeton's associated project has access to over a half-petabyte of the EUROFUSION/JET disruption database, and it's new FRNN (Fusion Recurrent Neural Net) code exhibits excellent scaling to nearly 200 GPUs. We'll target extending this exciting trend on NVIDIA's powerful SATURN V to its nearly 1,000 GPUs (124 nodes with eight Pascal P100 GPUs per node) in time for presentation at GTC 2017.


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Talk
Computational Physics Deep Learning and AI HPC and Supercomputing
Higher Education / Research
50 minutes
Session Schedule