Quantization for neural network computation

Abstract

A method for memory storage including storing a neural network by storing values of the neural network each as a reference to a representative value; and, in some embodiments, storing additional values of the neural network. Each of the representative values can be generated by assigning each of the values of the neural network to a cluster; and for each cluster, selecting a centroid from the cluster. The method can include performing one or more multiply-accumulate operations A1B1+ . . . +AnBn on input vectors A and input vectors B, by accumulating input vectors A to an accumulated sum of input vectors A per input vector B having the same representative value and subsequently multiplying each of the accumulated sums of input vectors A by the representative value of the input vector B. A system is also described, as well as a method for configuring memory according to a data structure.

Dependencies are inferred from the claim text.