Design of an Area-Efficient Computing in Memory Platform Based on STT-MRAM

Abstract

In the era of big data, the memory wall between the processor and the memory as well as leakage current have become major bottlenecks of the traditional CMOS-based Von-Neumann computer architecture. Computing-in-memory (CiM) based on non-volatile memories (NVMs) is considered a promising method to solve the above-mentioned issues in computing systems. In this article, we propose a CiM platform based on spin-transfer torque magnetic random access memory (STT-MRAM). On the basis of the conventional CiM with AND/OR logic functions, the full-adder (FA) arithmetic operation is achieved with slight circuits modification by exploiting majority logic. Due to the parallel processing of carry and sum operations in multi-bit FA operation, the latency overhead caused by the two-step scheme is acceptable. The hybrid spintronic/CMOS simulations on the 40 nm technology node prove the functionality and performance of the proposed CiM platform.