BASIC COMPUTING UNIT FOR CONVOLUTIONAL NEURAL NETWORK, AND COMPUTING METHOD

摘要

The present invention provides a basic computing unit for a convolutional neural network, and a computing method, the basic computing unit comprising a controller, an adder tree, an input buffer, several computing units, and an output buffer; each of the computing units comprises a block random access memory, several convolution operation units, an internal adder, and an activation and pooling unit. On the basis of the control of the controller, the input buffer loads, to the computing units, a corresponding number of lines of image data, and the block random access memory delivers an effective number of lines and a starting line number to the convolution operation units, so as to enable the convolution operation units to acquire image data of corresponding line numbers; the convolution operation units process the image data, and send same to the adder tree by means of the internal adders; the adder tree processes the image data sent from the internal adders, and sends same to an activation and pooling unit; and the activation and pooling unit processes the image data, and sends same to the output buffer. The present solution is able to implement an algorithm on the basis of hardware, making completion time of an algorithm controllable.