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We present a work-in-progress snapshot of learning with a 15 billionparameter deep learning network on HPC architectures applied to the largestpublicly available natural image and video dataset released to-date. Recentadvancements in unsupervised deep neural networks suggest that scaling up suchnetworks in both model and training dataset size can yield significantimprovements in the learning of concepts at the highest layers. We train ourthree-layer deep neural network on the Yahoo! Flickr Creative Commons 100Mdataset. The dataset comprises approximately 99.2 million images and 800,000user-created videos from Yahoo's Flickr image and video sharing platform.Training of our network takes eight days on 98 GPU nodes at the HighPerformance Computing Center at Lawrence Livermore National Laboratory.Encouraging preliminary results and future research directions are presentedand discussed.

Large-Scale Deep Learning on the YFCC100M Dataset