Accelerate training of deep neural networks with MxNet on AWS P3 instances
(WorldNews Spain)

Deep Learning techniques are providing amazing results on several Machine Learning fields, but training a complex deep neural network on a large dataset can take a significant amount of time. Therefore accelerate training of Deep Learning models is really crucial, but also challenging. At BEEVA Labs we performed some internal benchmarks testing several data-parallel implementations of well-known image classification models: on Tensorflow, Keras+Tensorflow and MxNet. Our first experiments were focused on typical MNIST and CIFAR10 datasets, comparing different GPU-enabled cloud infrastructures, and we shared our first conclusions on factors that affect performance and efficiency of training....