An in-memory computing circuit implemented based on acceleration of a BNN algorithm

An in-memory computing circuit implemented based on acceleration of a BNN algorithm, wherein the circuit comprises:

• a storage array of a flexible RRAM, a multiplier and accumulator, a shifter, a comparator and a processor for max value comparison and output;
• according to a BNN network structure and input data, two regions configured to be selected within the storage array of the flexible RRAM as a first algorithm network and a second algorithm network respectively;
• data of a plurality of rows at each bit position configured to be input into the first algorithm network and the multiplier and accumulator;
• the first algorithm network configured to output the cumulative current from compute-in-memory units of each column to the multiplier and accumulator, the multiplier and accumulator configured to obtain the multiplication and addition results of each column based on the data of the plurality of rows and the cumulative current from each column, and input the multiplication and addition results of each column into the shifter;
• the shifter configured to, based on the bit positions input by the data of the plurality of rows, shift the multiplication and addition results of each column by the corresponding number of bits and output the shifted results to the adder-subtractor within the multiplier and accumulator;
• the adder-subtractor configured to perform addition calculation on the shifted results of different bit positions for each column and output the addition results of each column to the comparator;
• the comparator configured to binarize the addition results of each column to obtain the binarized results and output them to the second algorithm network;
• the second algorithm network configured to perform further computation to output the cumulative current from each column and send them to the processor for max value comparison and output;
• the processor for max value comparison and output configured to judge the maximum value of cumulative current from each column, the column with the maximum value is the classification result.