ENOS: Energy Aware Network Operator Search

Until recent times, DNNs have been designed using conventional high-precision operator which gives maximum accuracy but is not energy efficient. With the invent of new computationally efficient correlation operators, accuracy deterioration becomes a problem. In addition, all DNNs use a single correlation operator for end-to-end processing. In these cases, using only a high precision operator might not be energy efficient and using alternate operators might affect the accuracy. Thus, an optimal solution would be to systematically combine these operators to maintain the energy-accuracy tradeoff. This is the main goal of my framework called ENOS : Energy Aware Network Operator Search where if the energy constraints for an application is established, the operator sequence for different layers can be automatically synthesized while maximizing the prediction accuracy.