Training Generative Adversarial Models over Distributed Computing Systems
by Rich Brueckner from High-Performance Computing News Analysis | insideHPC on (#3WSBJ)
Gul Rukh Khattak from CERN gave this talk at PASC18. "We use a dataset composed of the energy deposition from electron, photons, charged and neutral hadrons in a fine grained digital calorimeter. The training of these models is quite computing intensive, even with the help of GPGPU, and we propose a method to train them over multiple nodes and GPGPU using a standard message passing interface. We report on the scalings of time-to-solution."
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