Calculation error correction device and method applied to resistive memory-based neural network accelerator

Abstract

The present disclosure provides a calculation error correction device including a first learning unit that trains an effective weight value prediction model for outputting an effective weight value matrix by using learning data in response to an input of the random weight value matrix, an effective weight value calculation unit that inputs a first weight value matrix into the effective weight value prediction model to derive the effective weight value matrix, a second learning unit that applies a second input vector to a target neural network as an input value, applied the effective weight value matrix as a weight value, and trains the weight value such that an output vector follows a result of multiplication of the second input vector and the first weight value matrix, and a control unit that performs matrix-vector multiplication by mapping the first input vector and the trained weight value matrix to the resistive memory.