Deep Learning on HPC Systems for Astronomy episode artwork

EPISODE · Feb 27, 2018 · 23 MIN

Deep Learning on HPC Systems for Astronomy

from "The Interview" with The Next Platform

On today’s episode of “The Interview” with The Next Platform we talk about the use of petascale supercomputers for training deep learning algorithms. More specifically, how this happening in Astronomy to enable real-time analysis of LIGO detector data. We are joined by Daniel George, a researcher in the Gravity Group at the National Center for Supercomputing Applications, or NCSA. His team garnered a great deal of attention at the annual supercomputing conference in November with work blending traditional HPC simulation data and deep learning.

On today’s episode of “The Interview” with The Next Platform we talk about the use of petascale supercomputers for training deep learning algorithms. More specifically, how this happening in Astronomy to enable real-time analysis of LIGO detector data. We are joined by Daniel George, a researcher in the Gravity Group at the National Center for Supercomputing Applications, or NCSA. His team garnered a great deal of attention at the annual supercomputing conference in November with work blending traditional HPC simulation data and deep learning.

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Deep Learning on HPC Systems for Astronomy

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This episode was published on February 27, 2018.

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On today’s episode of “The Interview” with The Next Platform we talk about the use of petascale supercomputers for training deep learning algorithms. More specifically, how this happening in Astronomy to enable real-time analysis of LIGO detector...

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