Two-terminal floating-gate transistors with a low-power memristive operation mode for analogue neuromorphic computing

神经形态工程学 CMOS芯片 晶体管 记忆电阻器 计算机科学 电子工程 阈下传导 电气工程 横杆开关 电压 光电子学 材料科学 工程类 人工神经网络 人工智能
作者
Loai Danial,Evgeny Pikhay,Eric Herbelin,Nicolás Wainstein,V.K. Gupta,Nimrod Wald,Yakov Roizin,Ramez Daniel,Shahar Kvatinsky
出处
期刊:Nature electronics [Nature Portfolio]
卷期号:2 (12): 596-605 被引量:113
标识
DOI:10.1038/s41928-019-0331-1
摘要

Metal–oxide memristive integrated technologies for analogue neuromorphic computing have undergone notable developments in the past decade, but are still not mature enough for very large-scale integration with complementary metal–oxide–semiconductor (CMOS) processes. Although non-volatile floating-gate synapse transistors are a more advanced technology embedded within CMOS processes, their performance as analogue resistive memories remains limited. Here, we report a low-power, two-terminal floating-gate transistor fabricated using standard single-poly technology in a commercial 180 nm CMOS process. Our device, which is integrated with a readout transistor, can operate in an energy-efficient subthreshold memristive mode. At the same time, it is linearized for small-signal changes with a two-orders-of-magnitude resistance dynamic range. Our device can be precisely tuned using optimized switching voltages and times, and can achieve 65 distinct resistive levels and ten-year analogue data retention. We experimentally demonstrate the feasibility of a selector-free integrated memristive array in basic neuromorphic applications, including spike-time-dependent plasticity, vector-matrix multiplication, associative memory and classification training. A floating-gate memristive device fabricated in a commercial 180 nm CMOS process can be integrated into a selector-free memristive array and used to demonstrate basic neuromorphic applications.
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