A Fast Weight Control Strategy for Programmable Linear RAM Based on the Self-Calibrating Erase Operation

Abstract

Computing-in-memory (CIM) has attracted great attention due to the need for breaking through the “memory wall”. Programmable linear random-access memory (PLRAM) for high-precision weight control is proposed to tear down the wall. However, the slow programming algorithm to tune cells limits its application in multi-level memory. Herein, a fast weight control strategy for PLRAM based on the self-calibrating erase operation is presented. The unique sidewall tunneling oxide utilized in PLRAM for bi-directional Fowler–Nordheim tunneling results in the corner-enhanced poly-to-poly tunneling effect and the self-calibrating capability during the erase process. By adopting this strategy, the efficiency of weight tuning in the PLRAM array is improved by 51% compared with the current method. The worst case is 4.9 ms for erasure, which only needs to be verified 10 times. The improvement of weight tuning efficiency means further development in CIM for PLRAM and also shows the significant prospect of PLRAM used in multi-level memory.