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近存计算架构AI芯片中子单粒子效应

杨卫涛 胡志良 何欢 莫莉华 赵小红 宋伍庆 易天成 梁天骄 贺朝会 李永宏 王斌 吴龙胜 刘欢 时光

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近存计算架构AI芯片中子单粒子效应

杨卫涛, 胡志良, 何欢, 莫莉华, 赵小红, 宋伍庆, 易天成, 梁天骄, 贺朝会, 李永宏, 王斌, 吴龙胜, 刘欢, 时光

Neutron induced single event effects on near-memory computing architecture AI chips

Yang Wei-Tao, Hu Zhi-Liang, He Huan, Mo Li-Hua, Zhao Xiao-Hong, Song Wu-Qing, Yi Tian-Cheng, Liang Tian-Jiao, He Chao-Hui, Li Yong-Hong, Wang Bin, Wu Long-Sheng, Liu Huan, Shi Guang
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  • 利用中国散裂中子源大气中子辐照谱仪, 对某款16 nm FinFET工艺制造的近存计算架构人工智能AI芯片进行了大气中子单粒子效应辐照测试研究. 辐照测试中, 在累积中子注量为1.51×1010 n/cm2 (1 MeV以上)情况下, 共探测到5类共计35个软错误, 尤其是探测到不同于传统冯诺伊曼架构芯片单粒子效应的计算与存储单元同时发生单粒子效应新现象. 基于所探测到的两类功能单元同时单粒子效应新现象, 结合蒙特卡罗仿真模拟, 初步给出了近存计算架构AI芯片内物理布局上, 核心功能单元间可降低同时发生单粒子效应的安全间距建议. 该研究为进一步探究非传统冯诺伊曼架构芯片单粒子效应提供了参考与借鉴.
    For the near-memory computing architecture AI chip manufactured by using 16 nm FinFET technology, atmospheric neutron single event effect irradiation tests are conducted for the first time in China by using the atmospheric neutron irradiation spectrometer (ANIS) at the China Spallation Neutron Source. During the irradiation, the YOLOV5 algorithm neural network running on the AI chip is used for real-time detection of target objects, including mice, keyboard, and luggage. The purpose of the test is to investigate the new single event effect that may occur on near-memory computing architecture AI chip. Finally, at an accumulated neutron fluence of 1.51×1010 n·cm–2 (above 1 MeV), a total of 35 soft errors are detected in 5 categories. Particularly noteworthy is the observation of a new finding, where both computing and memory units experience single event effects simultaneously, which is different from the traditional von Neumann architecture chips. Based on the single event effects that occur simultaneously in these two units, combined with Monte Carlo simulation, a preliminary estimation is made of the physical layout distance between the computing unit and the memory unit on the chip. Furthermore, suggestions are proposed to simultaneously reduce the risk of single event effect in multi cells. This study provides valuable reference and insights for further exploring the single event effects in non-traditional von Neumann architecture chips.
      通信作者: 杨卫涛, yangweitao01@xidian.edu.cn
    • 基金项目: 国家自然科学基金(批准号: 12275211)、国家自然科学基金青年科学基金(批准号: 62104260)、陕西省自然科学基础研究计划(批准号: 2023-JC-QN-0015)和中央高校基本科研业务费专项资金(批准号: XJSJ23049)资助的课题.
      Corresponding author: Yang Wei-Tao, yangweitao01@xidian.edu.cn
    • Funds: Project supported by the National Natural Science Foundation of China (Grant No. 12275211), the National Natural Science Foundation of China Young Scientists Fund (Grant No. 62104260), the Natural Science Basic Research Plan of Shaanxi Province, China (Grant No. 2023-JC-QN-0015), and the Fundamental Research Funds for the Central Universities, China (Grant No. XJSJ23049).
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  • 图 1  不同架构芯片结构示意图[2,7] (a) 冯诺依曼; (b) 近存计算; (c) 存内计算

    Fig. 1.  Different chip architectures[2,7]: (a) Von Neumann; (b) near memory computing; (c) in memory computing.

    图 2  待测芯片数据流架构及AI应用示意图

    Fig. 2.  Diagram of data flow architecture and AI applications for the test chip.

    图 3  开盖后的待测芯片照片

    Fig. 3.  Photo of the de-capped test chip.

    图 4  辐照实验所用中子能谱, 其中ANIS为实验所用能谱, JEDEC为参考能谱

    Fig. 4.  Neutron spectrum applied in the irradiation test, ANIS with the utilized spectrum during irradiation test, and the JEDEC with the referred.

    图 5  辐照实验现场照片

    Fig. 5.  Photo of the irradiation worksite.

    图 6  所测试的AI芯片纵向结构信息

    Fig. 6.  Vertical structure of the tested AI chip.

    图 7  次级粒子影响多个单元示意图

    Fig. 7.  Diagram of affected cells by secondary particle.

    图 8  大气中子入射硅半导体所产生的主要次级粒子

    Fig. 8.  Secondary particles of atmospheric neutron striking silicon.

    表 1  探测到的不同类型单粒子效应

    Table 1.  Detected kinds of single event effect.

    软错误数量
    SEU/MEM30
    SEU/COMP2
    SEU/MEM+COMP1
    Timeout1
    Process-killed1
    下载: 导出CSV

    表 2  存储单元单粒子效应

    Table 2.  Single event effect in memory cell.

    翻转单元 数量 翻转单元 数量
    1 3 10 8
    2 5 11 1
    4 2 13 1
    8 10
    下载: 导出CSV

    表 3  不同单元效应截面和软错误率

    Table 3.  Cross section and soft error rate of different cells.

    单元单粒子效应截面/(10–10 cm2)软错误率/FIT
    存储20.530.40
    计算1.992.94
    控制1.321.96
    下载: 导出CSV
    Baidu
  • [1]

    周正, 黄鹏, 康晋锋 2022 71 148507Google Scholar

    Zhou Z, Huang P, Kang J F 2022 Acta Phys. Sin. 71 148507Google Scholar

    [2]

    郭昕婕, 王光燿, 王绍迪 2023 电子与信息学报 45 1888Google Scholar

    Guo X J, Wang G Y, Wang S D 2023 J. Electron. Inf. Technol. 45 1888Google Scholar

    [3]

    Sun Z, Kvatinsky S, Si X, Mehonic A, Cai Y, Huang R 2023 Nat. Electron. 6 823Google Scholar

    [4]

    康旺, 寇竞, 赵巍胜 2024 中国科学: 信息科学 54 16Google Scholar

    Kang W, Kou J, Zhao W S 2024 Sci. Sin. Inf. 54 16Google Scholar

    [5]

    Kamil K, Sudeep P, Ryan G K 2020 J. Low Power Electron. Appl. 10 30Google Scholar

    [6]

    刘伟强, 陈珂, 吴比, 邓尔雅, 王佑, 龚宇, 崔益军, 王成华 2024 中国科学: 信息科学 54 34Google Scholar

    Liu W Q, Chen K, Wu B, Deng E Y, Wang Y, Gong Y, Cui Y J, Wang C H 2024 Sci. Sin. Inf. 54 34Google Scholar

    [7]

    Wilfried H, Anand R, Kaushik R, Bhaswar C, Charudatta M P, Cheng W, Supratik G 2023 Adv. Mater. 35 2204944Google Scholar

    [8]

    胡志良, 杨卫涛, 李永宏, 李洋, 贺朝会, 王松林, 周斌, 于全芝, 何欢, 谢飞, 白雨蓉, 梁天骄 2019 68 238502Google Scholar

    Hu Z L, Yang W T, Li Y H, Li Y, He C H, Wang S L, Zhou B, Yu Q Z, He H, Xie F, Bai Y R, Liang T J 2019 Acta Phys. Sin. 68 238502Google Scholar

    [9]

    Yang W T, Li Y H, Li Y, Hu Z L, Xie F, He C H, Wang S L, Zhou B, He H, Khan W, Liang T J 2019 Microelec. Reliab. 99 119Google Scholar

    [10]

    Hu Z L, Yang W T, Zhou B, Liu Y N, He C H, Wang S L, Yu Q Z, Liang T J 2023 J. Nucl. Sci. Technol. 60 473Google Scholar

    [11]

    王勋, 张凤祁, 陈伟, 郭晓强, 丁李利, 罗尹虹 2020 69 162901Google Scholar

    Wang X, Zhang F Q, Chen W, Guo X Q, Ding L L, Luo Y H 2020 Acta Phys. Sin. 69 162901Google Scholar

    [12]

    王勋, 张凤祁, 陈伟, 郭晓强, 丁李利, 罗尹虹 2019 68 052901Google Scholar

    Wang X, Zhang F Q, Chen W, Guo X Q, Ding L L, Luo Y H 2019 Acta Phys. Sin. 68 052901Google Scholar

    [13]

    曹嵩, 殷雯, 周斌, 胡志良, 沈飞, 易天成, 王松林, 梁天骄 2024 73 092501Google Scholar

    Cao S, Yin W, Zhou B, Hu Z L, Shen F, Yi T C, Wang S L, Liang T J 2024 Acta Phys. Sin. 73 092501Google Scholar

    [14]

    Wang H B, Wang Y S, Xiao J H, Wang S L, Liang T J 2021 IEEE Trans. Nucl. Sci. 68 394Google Scholar

    [15]

    Dimitris A, Nikos F, Aitzan S, Vasileios V, Ioanna S, Mihalis P, Ye R, John G, Mikel L, Maria K, Carlo C, Chris F 2024 IEEE Trans. Reliab. 73 771Google Scholar

    [16]

    Rubens L R J, Sujit M, Carlo C, Maria K, Manon L, Christopher F, Paolo R 2022 IEEE Trans. Nucl. Sci. 69 567Google Scholar

    [17]

    Jordan D A, Jennings C L, Michael J W 2018 IEEE Radiation Effects Data Workshop (REDW) Waikoloa, HI, USA

    [18]

    Avi B, Givat S, Or D, Kiryat O, Daniel C, Ramat G, Gilad N, Modiin-Maccabim R 2023 US Patent 11551028 B2

    [19]

    Hailo-8 AI Accelerator. https://hailo.ai/products/ai-accelerators/hailo-8-ai-accelerator/. [2023-10-1]

    [20]

    Measurement and Reporting of Alpha Particle and Terrestrial Cosmic Ray-induced Soft Errors in Semiconductor Devices. https://www.jedec.org/document_search?search_api_views_fulltext=JESD89A. [2024-2-11]

    [21]

    Allison J, Amako K, Apostolakis J, et al. 2006 IEEE Trans. Nucl. Sci 53 270Google Scholar

    [22]

    张战刚, 雷志锋, 童腾, 李晓辉, 王松林, 梁天骄, 习凯, 彭超, 何玉娟, 黄云, 恩云飞 2020 69 056101Google Scholar

    Zhang Z G, Lei Z F, Tong T, Li X H, Wang S L, Liang T J, Xi K, Peng C, He Y J, Huang Y, En Y F 2020 Acta Phys. Sin. 69 056101Google Scholar

    [23]

    Mo L H, Ye B, Liu J, Zhang Z G, Tong T, Sun Y M, Luo J 2021 Nucl. Phys. Rev. 38 327Google Scholar

    [24]

    Yang S H, Zhang Z Z, Lei Z F, Tong T, Li X H, Xi K, Wu F G 2022 Appl. Sci. 12 9685Google Scholar

    [25]

    Takashi K, Masanori H, Hideya M 2020 IEEE Trans. Nucl. Sci. 67 1485Google Scholar

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出版历程
  • 收稿日期:  2024-03-25
  • 修回日期:  2024-05-07
  • 上网日期:  2024-05-22
  • 刊出日期:  2024-07-05

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