Deep Learning with GPUs

Justin Sirignano, University of Illinois at Urbana-Champaign

Usage Details

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An allocation for the Fall 2016 course "IE 598: Neural Networks and Deep Learning" is requested. This is a graduate-level course (PhD and Masters) at the University of Illinois at Urbana-Champaign which will cover recent exciting advances in deep learning. Deep learning has produced state-of-the-art results in a number of areas such as image classification, natural language processing, and reinforcement learning. In typical applications, neural networks may have millions of parameters and are trained on large datasets. Consequently, training is very computationally expensive. Fortunately, neural network training can be highly parallelized via GPUs. The allocation on Blue Waters will allow students to implement state-of-the-art deep neural networks for important applications. Without Blue Waters, implementing and learning about these deep neural networks would be impossible. This would be one of the first machine learning courses of its kind (nationwide) which would allow students to replicate state-of-the-art results by providing access to GPUs.