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XOR-CiM: An Efficient Computing-in-SOT-MRAM Design for Binary Neural Network Acceleration

International Symposium on Quality Electronic Design (ISQED)

Publication Type



In this work, we leverage the uni-polar switching behavior of Spin-Orbit Torque Magnetic Random Access Memory (SOT-MRAM) to develop an efficient digital Computing-in-Memory (CiM) platform named XOR-CiM. XOR-CiM converts typical MRAM sub-arrays to massively parallel computational cores with ultra-high bandwidth, greatly reducing energy consumption dealing with convolutional layers and accelerating X(N)OR-intensive Binary Neural Networks (BNNs) inference. With a similar inference accuracy to digital CiMs, XOR-CiM achieves ∼4.5× and 1.8× higher energy-efficiency and speed-up compared to the recent MRAM-based CiM platforms.


Mehrdad Morsali, Ranyang Zhou, Sepehr Tabrizchi, Arman Roohi, Shaahin Angizi

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