设计策略40纳米分隔门NOR闪存设备用于低功耗内存计算应用程序的设计策略
Chan-Gi Yook1, Jung Nam Kim2, Yoon Kim2
1Department of Electrical and Information Engineering, Seoul National University of Science and Technology, Seoul 01811, Republic of Korea.
Micromachines
|September 28, 2023
概括
为人工智能 (AI) 计算优化分割门NOR闪存,提高能源效率. 这项研究提出了设备设计策略,以提高内存计算 (CIM) 的准确性,并降低人工智能硬件的功耗.
科学领域:
- 半导体设备物理学 半导体设备物理
- 人工智能硬件是人工智能的硬件.
- 非挥发性内存技术的技术.
背景情况:
- ·诺伊曼架构面临着人工智能的功率和内存限制.
- 计算在内存 (CIM) 技术提供了一个有前途的替代方案.
- 分隔门NOR闪光灯是成熟的CIM候选者,具有高密度和低功率潜力.
研究的目的:
- 优化分门NOR闪光装置设计,以提高CIM推理芯片的高能效和精度.
- 解决影响CIM准确性的设备导电率变化和低开关电流比问题.
- 为了实现设备层面的低功耗和系统层面的高精度.
主要方法:
- 通过调整氧化物厚度和结构参数,为最佳设备设计提出了战略建议.
- 调查了电导率变化和电力消耗的电流之间的权衡.
- 模拟设备性能与优化的参数.
主要成果:
- 在电流低于2μA时实现了除,在程序电流低于10 pA时实现了除,在关闭电流低于1 pA时实现了关闭.
- 通过优化设备参数 (例如,T_ox = 13.4 nm,T_ins = 4.6 nm) 保持了超过92%的推断准确度.
- 在保持高精度的同时,显著降低了功耗.
结论:
- 优化的分割门NOR闪存设备可以克服传统AI架构的局限性.
- 拟议的设计策略使有效和准确的CIM推断成为可能.
- 这项工作为低功耗,高性能AI硬件铺平了道路.
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