Benchmarking Resource Usage for Efficient Distributed Deep Learning
Benchmarking Resource Usage for Efficient Distributed Deep Learning
Deep learning (DL) workflows demand an ever-increasing budget of compute and energy in order to achieve outsized gains. As such, it becomes essential to understand how different deep neural networks (DNNs) and training leverage increasing compute and energy resources-especially specialized computationally-intensive models across different domains and applications. In this paper, …