OPTIMIZING DATA PARTITIONING AND REPLACEMENT STRATEGY FOR CONVOLUTIONAL NEURAL NETWORKS

摘要

Embodiments of the present disclosure include method for optimizing an internal memory for calculation of a convolutional layer of a convolutional neural network (CNN), the method including determining a computation cost of calculating the convolutional layer using each combination of a memory management scheme of a plurality of memory management schemes and data partition sizes of input feature map (IFM) data, kernel data, and output feature map (OFM) data to be loaded in the internal memory; identifying one combination of a memory management scheme and data partition sizes having a lowest computation cost for the convolutional layer; and implementing the CNN to use the one combination for calculation of the convolutional layer.