Accelerating DNN Architecture Search at Scale Using Selective Weight Transfer

Deep learning applications are rapidly gaining traction both in industry and scientific computing. Unsurprisingly, there has been significant interest in adopting deep learning at a very large scale on supercomputing infrastructures for a variety of scientific applications. A key issue in this context is how to find an appropriate model architecture that is suitable to solve the problem. We call t...