Neural network computation method and apparatus using adaptive data representation

A neural network computation method using adaptive data representation, adapted for a processor to perform multiply-and-accumulate (MAC) operations on a memory having a crossbar architecture, wherein the memory comprises a plurality of input lines and a plurality of output lines crossing each other, a plurality of cells respectively disposed at intersections of the input lines and the output lines, and a plurality of sense amplifiers respectively connected to the output lines, the method comprising:

• adaptively dividing an input cycle of kth bits respectively in a plurality of input data to be inputted to the input lines into a plurality of sub-cycles, wherein a number of the divided sub-cycles is determined according to a value of k and k is an integer;
• inputting the kth bits of the plurality of input data to the input lines with the sub-cycles and sensing computation results of the output lines by the sense amplifiers;
• and
• combining the computation results sensed in each sub-cycle to obtain a plurality of output data corresponding to the kth bits of the input data.