Method and system of controlling computing operations based on early-stop in deep neural network

Abstract

A method of controlling computing operations in a deep neural network (DNN) is provided. A network structure of the DNN including a plurality of layers is analyzed. A hyper parameter is set based on the network structure and real-time context information of a system configured to drive the DNN. The hyper parameter is used for performing an early-stop function. Depth-wise jobs are assigned to resources included in the system based on the hyper parameter to execute the depth-wise jobs. Each of the depth-wise jobs includes at least a part of the computing operations. When an early-stop event for a first layer among the layers is generated while the plurality of depth-wise jobs are executed, a subset computing operations included in at least one second layer are performed and a remainder of the computing operations are stopped. The at least one second layer is arranged prior to the first layer.