Abstract: The importance of Model Parallelism in Distributed Deep Learning continues to grow due to the increase in the Deep Neural Network (DNN) scale and the demand for higher training speed.
Abstract: Virtualization environments (e.g., containers and hypervisors) achieve isolation of multiple runtime entities but result in two mutually isolated guest and host layers. Such cross-layer ...