Series-Parallel Hybrid SOT-MRAM Computing-in-Memory Macro with Multi-Method Modulation for High Area and Energy Efficiency
Weiliang Huang, Jinyu Bai, Wang Kang, Zhaohao Wang, Kaihua Cao, Hongxi Liu, He Zhang, Weisheng Zhao
Abstract
Computing-in-memory (CIM) shows its superiority in lots of applications like neural network inference. Recently, there are lots of exploration of the application of Magnetic Random-Access Memory (MRAM) in CIM. This paper aims to investigate the potential of Spin-Orbit-Torque-MRAM (SOT-MRAM) in CIM and proposes a high area and energy efficiency SOT-MRAM CIM macro based on a 6T-4J weight group. The bit-cell array adopts series-parallel hybrid architecture, which combines both serial and parallel configurations of Magnetic Tunnel Junction (MTJ) to solve the problem of high energy cost and low flexibility caused by MRAM-series and MRAM-parallel architecture, respectively. Additionally, the proposed SOT-MRAM CIM macro incorporates a multi-method modulation scheme, ranging from input unit to array, which meanwhile allows for configurable input precision (2/4/6/8-bit). The SOT-MRAM CIM macro is designed and verified in both 180nm and 28nm nodes, based on the verified electrical performance of the SOT-MRAM array in a 200-nm wafer pre-fabricated. The simulation results in 28nm show that this macro can achieve energy efficiency of 23.7 29.6 Tops/W at 8-bit input and output precision.
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