  We demonstrate that training ResNet-50 on ImageNet for 90 epochs can be
achieved in 15 minutes with 1024 Tesla P100 GPUs. This was made possible by
using a large minibatch size of 32k. To maintain accuracy with this large
minibatch size, we employed several techniques such as RMSprop warm-up, batch
normalization without moving averages, and a slow-start learning rate schedule.
This paper also describes the details of the hardware and software of the
system used to achieve the above performance.
