News

ORNL researchers use Titan to accelerate design, training of deep learning networks

ORNL’s Steven Young (left) and Travis Johnston used Titan to prove the design and training of deep learning networks could be greatly accelerated with a capable computing system.
ORNL’s Steven Young (left) and Travis Johnston used Titan to prove the design and training of deep learning networks could be greatly accelerated with a capable computing system.

OAK RIDGE, Tenn., Jan. 10, 2018 – A team of researchers from the Department of Energy’s Oak Ridge National Laboratory has married artificial intelligence and high-performance computing to achieve a peak speed of 20 petaflops in the generation and training of deep learning networks on the laboratory’s Titan supercomputer.

Deep learning is a burgeoning field of artificial intelligence that uses networks modeled after the human brain to “learn” how to distinguish features and patterns in vast datasets. Such networks hold great promise in the realization of numerous technologies, from self-driving cars to intelligent robots.

Due to its ability to make sense of massive amounts of data, researchers across the scientific spectrum are eager to refine deep learning and apply it to some of today’s most challenging science problems. One such effort is ORNL’s Advances in Machine Learning to Improve Scientific Discovery at Exascale and Beyond (ASCEND) project, which aims to use deep learning to make sense of the massive datasets produced by the world’s most sophisticated scientific experiments, such as those located at ORNL.

View the Story Here