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Comparative Study of Deep Learning Software Frameworks
[article]
2016
arXiv
pre-print
Deep learning methods have resulted in significant performance improvements in several application domains and as such several software frameworks have been developed to facilitate their implementation. This paper presents a comparative study of five deep learning frameworks, namely Caffe, Neon, TensorFlow, Theano, and Torch, on three aspects: extensibility, hardware utilization, and speed. The study is performed on several types of deep learning architectures and we evaluate the performance of
arXiv:1511.06435v3
fatcat:6em43mvhbjdv3hheg3y7e466y4