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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.
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Keywords:
- near memory computing /
- AI chip /
- spallation neutron source /
- atmospheric neutron /
- single event effect
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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/MEM 30 SEU/COMP 2 SEU/MEM+COMP 1 Timeout 1 Process-killed 1 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 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 20.5 30.40 计算 1.99 2.94 控制 1.32 1.96 -
[1] 周正, 黄鹏, 康晋锋 2022 物理学报 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 物理学报 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 物理学报 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 物理学报 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 物理学报 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 物理学报 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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