Deep Learning on HPC Systems for Astronomy

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 dat ...

An episode of the "The Interview" with The Next Platform podcast, hosted by The Next Platform, titled "Deep Learning on HPC Systems for Astronomy" was published on February 27, 2018 and runs 23 minutes.

February 27, 2018 ·23m · "The Interview" with The Next Platform

Summary

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.

Episode Description