Wafer-scale fabrication of memristive passive crossbar circuits for brain-scale neuromorphic computing.

IF 15.7 1区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Sanghyeon Choi, Sai Sukruth Bezugam, Tinish Bhattacharya, Dongseok Kwon, Dmitri B Strukov
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引用次数: 0

Abstract

Memristive passive crossbar circuits hold great promise for neuromorphic computing, offering high integration density combined with massively parallel operation. However, scaling up the integration complexity of such circuits remains challenging due to low device yield, stemming from the intrinsic properties of filamentary switching and limitations in current crossbar fabrication technologies. Here, we report a scalable passive crossbar device technology achieved through a co-design approach for memristors and crossbar structures. The proposed hardware platform is fabricated using CMOS-compatible processes without complex and high-temperature steps, enabling high device yield along with reliable and multibit operation. Importantly, the fabrication process is successfully scaled to a 4-inch wafer, maintaining an average device yield (>~95%) and preserving key switching characteristics. The potential of this platform is showcased by implementing image classification of the fashion MNIST benchmark with an ex-situ trained spiking neural network. We believe that our work represents a significant step toward brain-scale neuromorphic computing systems.

用于脑级神经形态计算的记忆无源交叉电路的晶圆级制造。
忆阻无源交叉电路具有高集成密度和大规模并行运算的特点,在神经形态计算领域具有广阔的应用前景。然而,由于丝状开关的固有特性和当前交叉棒制造技术的局限性,由于器件成品率低,扩大此类电路的集成复杂性仍然具有挑战性。在这里,我们报告了一种可扩展的无源交叉栅器件技术,该技术通过记忆电阻器和交叉栅结构的协同设计方法实现。所提出的硬件平台采用cmos兼容工艺制造,无需复杂和高温步骤,可实现高器件良率以及可靠的多比特操作。重要的是,制造工艺成功地扩展到4英寸晶圆,保持了平均器件良率(>~95%)并保留了关键的开关特性。通过使用非原位训练的峰值神经网络实现时尚MNIST基准的图像分类,展示了该平台的潜力。我们相信,我们的工作代表了迈向脑级神经形态计算系统的重要一步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Nature Communications
Nature Communications Biological Science Disciplines-
CiteScore
24.90
自引率
2.40%
发文量
6928
审稿时长
3.7 months
期刊介绍: Nature Communications, an open-access journal, publishes high-quality research spanning all areas of the natural sciences. Papers featured in the journal showcase significant advances relevant to specialists in each respective field. With a 2-year impact factor of 16.6 (2022) and a median time of 8 days from submission to the first editorial decision, Nature Communications is committed to rapid dissemination of research findings. As a multidisciplinary journal, it welcomes contributions from biological, health, physical, chemical, Earth, social, mathematical, applied, and engineering sciences, aiming to highlight important breakthroughs within each domain.
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