Training ImageNet on a TPU in 12.5 hours with GKE and RiseML

Google's Tensor Processing Unit (TPU), a custom-developed accelerator for deep learning, offers a fast and cost-efficient alternative to training deep learning models in the cloud: it is capable of training a ResNet-50 model on ImageNet in 12.5 hours -- for an equivalent of $81 of TPU compute time. At RiseML, we believe that machine learning engineers shouldn't have to worry about infrastructure. Recently, Google Kubernetes Engine (GKE), the managed Kubernetes offering by Google, started providing alpha level support for provisioning TPUs. Each TPU's lifetime is automatically bound to the lifetime of its job, so you only pay for your actual use. The combination of GKE and RiseML offers a hassle-free machine learning infrastructure that is easy-to use, highly scalable, and cost-efficient.