A reconfigurable in‐memory‐computation architecture with in‐situ update and shift capability

Abstract

Abstract This work proposes a storage element (SE) design for in‐memory computing (IMC). Using the proposed SE design, an IMC array has been constructed to enable in‐situ updates of stored weights. Compared with some existing related works which employ 2n bit cells for storing an n‐bit value, the proposed structure in this work exhibits a O(n) complexity of area overhead, which means that only n bit cells are needed to store n‐bit values, offering a significant improvement in silicon area usage. Compared to the purely digitally‐controlled weight update schemes, the approach proposed in this work demonstrates an approximate 1.47× increase in power consumption. Furthermore, it exhibits superior robustness compared to existing work. Additionally, the proposed SE design can achieve the necessary shift functionality in the cutting‐edge floating‐point (FP)‐IMC architecture through simple control mechanisms.

Keywords

• artificial intelligence
• integrated memory circuits
• memory architecture