Sparse and Robust RRAM-based Efficient In-memory Computing for DNN Inference

Resistive random-access memory (RRAM)-based in-memory computing (IMC) recently became a promising paradigm for efficient deep neural network acceleration. The multi-bit RRAM arrays provide dense storage and high throughput, whereas the physical non-ideality of the RRAM devices impairs the retention characteristics of the resistive cells, leading to accuracy degradation. On the algorithm side, vari...