In recent years, major breakthroughs were achieved in Computer Vision using Deep Neural Networks (DNN).
Performance of image classification, segmentation, localization have reached levels not seen before.
After a brief introduction to deep learning on GPUs, we will address a selection of open questions physicists may face when using deep learning for their HPC work. Research is making progress towards answering these questions but there remains plenty to be done in the field by the deep learning and HPC communities.
Gunter Roeth joined NVIDIA as a Solution Architect in October 2014 having previously worked at Cray, HP, Sun Microsystems and most recently BULL. He has a Master in geophysics from the Institut de Physique du Globe (IPG) in Paris and has completed a PhD in seismology on the use of neural networks (artificial intelligence) for interpreting geophysical data.
