Xilinx, Inc.
TRAINING OF NEURAL NETWORKS BY INCLUDING IMPLEMENTATION COST AS AN OBJECTIVE

Abstract:

An example method of implementing a neural network includes selecting a first neural network architecture from a search space and training the neural network having the first neural network architecture to obtain an accuracy and an implementation cost. The implementation cost is based on a programmable device of an inference platform. The method further includes selecting a second neural network architecture from the search space based on the accuracy and the implementation cost, and outputting weights and hyperparameters for the neural network having the second neural network architecture.