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

doi:10.7498/aps.73.20240430

Abstract

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.

Keywords:

Authors and contacts

1.
School of Microelectronics, Xidian University, Xi’an 710071, China
2.
School of Nuclear Science and Technology, Xi’an Jiaotong University, Xi’an 710049, China
3.
Spallation Neutron Source Science Center, Dongguan 523803, China
4.
Aviation Engineering Institute, Air Force Engineering University, Xi’an 710000, China
5.
School of Aerospace Science and Technology, Xidian University, Xi’an 710071, China

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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References

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Cited By

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

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

DownLoad: Full-Size Img PowerPoint

图 2 待测芯片数据流架构及AI应用示意图

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

DownLoad: Full-Size Img PowerPoint

图 3 开盖后的待测芯片照片

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

DownLoad: Full-Size Img PowerPoint

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

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

DownLoad: Full-Size Img PowerPoint

图 5 辐照实验现场照片

Figure 5. Photo of the irradiation worksite.

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图 6 所测试的AI芯片纵向结构信息

Figure 6. Vertical structure of the tested AI chip.

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图 7 次级粒子影响多个单元示意图

Figure 7. Diagram of affected cells by secondary particle.

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图 8 大气中子入射硅半导体所产生的主要次级粒子

Figure 8. Secondary particles of atmospheric neutron striking silicon.

DownLoad: Full-Size Img PowerPoint

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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

DownLoad: 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

DownLoad: 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 20.5 30.40
计算 1.99 2.94
控制 1.32 1.96

DownLoad: CSV

[1]	周正, 黄鹏, 康晋锋 2022 物理学报 71 148507 Google Scholar Zhou Z, Huang P, Kang J F 2022 Acta Phys. Sin. 71 148507 Google Scholar
[2]	郭昕婕, 王光燿, 王绍迪 2023 电子与信息学报 45 1888 Google Scholar Guo X J, Wang G Y, Wang S D 2023 J. Electron. Inf. Technol. 45 1888 Google Scholar
[3]	Sun Z, Kvatinsky S, Si X, Mehonic A, Cai Y, Huang R 2023 Nat. Electron. 6 823 Google Scholar
[4]	康旺, 寇竞, 赵巍胜 2024 中国科学: 信息科学 54 16 Google Scholar Kang W, Kou J, Zhao W S 2024 Sci. Sin. Inf. 54 16 Google Scholar
[5]	Kamil K, Sudeep P, Ryan G K 2020 J. Low Power Electron. Appl. 10 30 Google 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 34 Google 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 34 Google Scholar
[7]	Wilfried H, Anand R, Kaushik R, Bhaswar C, Charudatta M P, Cheng W, Supratik G 2023 Adv. Mater. 35 2204944 Google 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 238502 Google 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 238502 Google 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. 99 119 Google 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. 60 473 Google Scholar
[11]	王勋, 张凤祁, 陈伟, 郭晓强, 丁李利, 罗尹虹 2020 物理学报 69 162901 Google Scholar Wang X, Zhang F Q, Chen W, Guo X Q, Ding L L, Luo Y H 2020 Acta Phys. Sin. 69 162901 Google Scholar
[12]	王勋, 张凤祁, 陈伟, 郭晓强, 丁李利, 罗尹虹 2019 物理学报 68 052901 Google Scholar Wang X, Zhang F Q, Chen W, Guo X Q, Ding L L, Luo Y H 2019 Acta Phys. Sin. 68 052901 Google 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 092501 Google 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 092501 Google Scholar
[14]	Wang H B, Wang Y S, Xiao J H, Wang S L, Liang T J 2021 IEEE Trans. Nucl. Sci. 68 394 Google 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. 73 771 Google Scholar
[16]	Rubens L R J, Sujit M, Carlo C, Maria K, Manon L, Christopher F, Paolo R 2022 IEEE Trans. Nucl. Sci. 69 567 Google 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 53 270 Google 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 056101 Google 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 056101 Google Scholar
[23]	Mo L H, Ye B, Liu J, Zhang Z G, Tong T, Sun Y M, Luo J 2021 Nucl. Phys. Rev. 38 327 Google 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 9685 Google Scholar
[25]	Takashi K, Masanori H, Hideya M 2020 IEEE Trans. Nucl. Sci. 67 1485 Google Scholar

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