Reconfigurable 2T2R ReRAM Architecture for Versatile Data Storage and Computing In-Memory
Yuzong Chen, Lu Lu, Bongjin Kim, Tony Tae-Hyoung Kim
Abstract
Nonvolatile memory (NVM)-based computing in-memory (CIM) is a promising solution to data-intensive applications. This work proposes a 2T2R resistive random access memory (ReRAM) architecture that supports three types of CIM operations: 1) ternary content addressable memory (TCAM); 2) logic in-memory (LiM) primitives and arithmetic blocks such as full adder (FA) and full subtractor; and 3) in-memory dot-product for neural networks. The proposed architecture allows the NVM operations in both 2T2R and conventional 1T1R configurations. The proposed LiM full adder (LiM-FA) improves the delay, the static power, and the dynamic power by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3.2\times $ </tex-math></inline-formula> , <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1.2\times $ </tex-math></inline-formula> , and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1.6\times $ </tex-math></inline-formula> , respectively, compared with state-of-the-art LiM-FAs. Furthermore, based on different optimization techniques and robustness analysis, a lower precharge voltage is set for each mode. This reduces the TCAM search energy and 1T1R ReRAM access energy by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1.6\times $ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1.14\times $ </tex-math></inline-formula> , respectively, compared with the case without optimizations.