PRECISION TUNING FOR THE PROGRAMMING OF ANALOG NEURAL MEMORY IN A DEEP LEARNING ARTIFICIAL NEURAL NETWORK
Abstract:
Numerous examples of a precision tuning algorithm and apparatus are disclosed for precisely and quickly depositing the correct amount of charge on the floating gate of a non-volatile memory cell within a vector-by-matrix multiplication (VMM) array in an artificial neural network. In one example, a method for performing a read or verify operation in a vector-by-matrix multiplication system comprising an input function circuit, a memory array, and an output circuit block is disclosed, the method comprising receiving, by the input function circuit, digital bit input values; converting the digital input values into an input signal; applying the input signal to control gate terminals of selected cells in the memory array; and generating, by the output circuit block, an output value in response to currents received from the memory array.
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