Design of Ultracompact Content Addressable Memory Exploiting 1T-1MTJ Cell
Cheng Zhuo, Zeyu Yang, Kai Ni, Mohsen Imani, Yuxuan Luo, Shaodi Wang, Deming Zhang, Xunzhao Yin
Abstract
Content addressable memories (CAMs) are a promising category of computing-in-memory (CiM) elements that can perform highly parallel and efficient search operations for routers, pattern matching, and other data-intensive applications. Various magnetic tunnel junction (MTJ)-based CAM designs have been proposed to realize zero standby power and high-performance search. However, due to the relatively small tunnel magneto-resistance (TMR) ratio, MTJ-based CAMs require extra transistors and differential MTJ branches to distinguish between the parallel and anti-parallel resistance states, resulting in significant area and energy overhead. In this article, we propose a device-circuit co-design approach for an ultracompact CAM design by only exploiting a 1T-1MTJ structure in each cell. We propose a 2-step search scheme to enable the parallel in-memory search operation across the proposed CAM array and demonstrate the sufficient sensing margin of the array in a successful search operation. Evaluation results suggest that our proposed 1T-1MTJ-based CAM design improves <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$179\times /301\times $ </tex-math></inline-formula> area efficiency compared with the state-of-the-art 15T-4MTJ/20T-6MTJ CAM design. Application benchmarking on hyperdimensional computing (HDC) inference shows a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$54.6\times /12.8\times $ </tex-math></inline-formula> speedup compared with GPU/20T-6MTJ CAM-based approaches.