Implementation of Stochastic Computing-based Image Compression System Using Probabilistic Switching Behavior of RRAM

In this work, a Discrete Cosine Transform (DCT) operation circuit based on highly fault-tolerant stochastic computing paradigm is designed and built to realize image compression. In order to generate stochastic bit streams with high efficiency and low cost, the resistance random access memory (RRAM) is used as stochastic number generator by employing its probabilistic switching behavior. The factors affecting the quality of image compression based on stochastic computing are studied. The results are compared with that of traditional binary image compression method, showing that the longer the length of the stochastic bit stream, the more accurate the stochastic number generated by the RRAM, the better the image compression quality. The speed, energy and hardware resources consumed by the circuit and the image compression quality are evaluated. Compared with the traditional method, the area reduces 55% and the energy reduces 46% in the RRAM-based stochastic computing method. The effect of different error flip rates on the image compression quality is studied. The stochastic computing compression is highly error-tolerant compared to traditional binary compression.