Silicon-based semiconductor transistors are approaching their physical limits due to
shrinking feature sizes. Simultaneously, traditional silicon-based von Neumann …

In this paper, we propose an energy-efficient, reliable, hybrid, 10-transistor/2-Double-Barrier-
Magnetic-Tunnel-Junction (10T2DMTJ) non-volatile (NV) ternary content-addressable …

Spin-transfer-torque magnetoresistive random-access memory (STT-MRAM) is a promising
candidate for future memory systems, however, implementing highly parallel neuro-inspired …

Using binarized neural network (BNN) as an alternative to the conventional convolutional
neural network is a promising candidate to answer the demand of using human brain …

Computing in memory (CIM) has become a promising candidate to address the Von
Neumann bottleneck in processors designed for data-intensive applications. In this article …

This paper introduces SIMPLY+, an advanced Spin-Transfer Torque Magnetic Random-
Access Memory (STT-MRAM)-based Logic-in-Memory (LIM) architecture that evolves from …

Abstract Machine learning (ML) algorithms try to learn the mapping from an input to output
from data rather than through explicit programming. ML uses algorithms that iteratively learn …

随着互补金属氧化物半导体技术的特征尺寸的不断缩小, 其面临的静态功耗问题缩越来越突出.
自旋磁随机存储器(MRAM) 由于其非易失性, 高速读写能力, 高集成密度和CMOS …

With the development of Artificial Intelligence (AI) and Binary neural networks (BNN), the
computing efficiency of the computing system is expected to be much better, however …

The spin transfer tunnel magnetic tunnel junction (STT‐MTJ) has been widely used in
computers, memory, and other fields because of its nonvolatility, low power consumption …