Research on Progress of Computing In-Memory Based on Static Random-Access Memory

With the arrival of the "computing power era", large-scale data need to go back and forth between the memory and the processor. However, the demand for frequent access can not be achieved in the traditional Von Neumann architecture which separates the computing and storage. The Von Neumann bottleneck and the "storage wall" in the traditional computing architecture have been broken with the birth of Computing In-Memory (CIM) Static Random-Access Memory technique. Thereby, for the "computing power era" it has revolutionary significance. Due to Static Random-Access Memory (SRAM) reads data fast and has better compatibility with advanced logic technology. Therefore, the attention of scholars at domestic and international has been attracted by SRAM-based CIM technology. The application of SRAM-based CIM technology is summarized, including machine learning, coding, encryption and decryption algorithm. The various circuit structures to realize the operation function and various quantization techniques based on Analog-to-Digital Conversion (ADC) are summarized and compared in this paper. In addition, the problems and challenges of the existing CIM architectures are analyzed. Then some existing solution strategies for those issues also are presented. Finally, the technique of SRAM-based CIM is prospected from different aspects.