Non-uniform quantization for flexible power-of-two computations in neural networks

Abstract

Devices, systems, and methods for improving operation of a memory device that uses a deep neural network (DNN), based on using non-uniform quantization for flexible power-of-two computations, are described. An example method includes receiving a plurality of initial weights of the DNN configured to determine a value of a read voltage associated with memory device, wherein the plurality of initial weights comprises at least one non-power-of-two quantized value or at least one floating point value. The method then aggregates the plurality of initial weights to generate a plurality of quantization functions, determines each of a plurality of quantized weights for a corresponding one of the plurality of quantization functions such that each of the plurality of quantized weights is a sum of powers-of-two, and configures the DNN to use the plurality of quantized weights to generate an updated value of the read voltage for retrieving information from the memory device.