DIANNE: a modular framework for designing, training and deploying deep neural networks on heterogeneous distributed infrastructure

In this paper the DIANNE framework is proposed as an all-in-one solution for deep learning, enabling data and model parallelism though a modular design, offloading to local compute power, and the ability to abstract between simulation and real environment.