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GTC ON-DEMAND

HPC and Supercomputing
Presentation
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Deep Learning to Enable Real-Time Gravitational Wave and Multimessenger Astrophysics
Abstract:

The aLIGO Advanced Laser Interferometer Gravitational Observatory went on line last year and very rapidly produced data confirming Einstein's theory of gravitational waves. This discovery and the success of the detection device open the door for another dimension to be added to and combined with other electromagnetic detection devices (telescopes, radio telecopes, etc.) to dramatically increase the potential to understand the workings of deep space and astronomical phenomena at the origins of the universe. The project used data produced by the CACTUS HPC simulation to produce datasets that were used to train a DNN using the MXNet framework. The results were that the prediction accuracy increased over classical waveform analysis and reduced the number of processors from hundreds of CPUs to one GPU, where the prediction was achieved with a latency of 1 millisecond. The work was done on the BlueWaters supercomputer and at the Innovation Lab at NCSA. The reduction in the "pipeline size" (number of CPUs needed to make a detection) and the improved latency open up the potential for multi-messenger astrophysics, where an observation that is "heard" with the gravitational wave detector can be used to steer a detector in the visible or EM spectrum where to look.

 
Topics:
HPC and Supercomputing, Artificial Intelligence and Deep Learning, Astronomy & Astrophysics, Computational Physics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7562
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