Suppr超能文献

Enhancement of Deep Neural Network Recognition on MPSoC with Single Event Upset.

作者信息

Yang Weitao, Song Wuqing, Guo Yaxin, Li Yonghong, He Chaohui, Wu Longsheng, Wang Bin, Liu Huan, Shi Guang

机构信息

School of Microeletronic, Xidian University, Xi'an 710071, China.

School of Nuclear Science & Technology, Xi'an Jiaotong University, Xi'an 710049, China.

出版信息

Micromachines (Basel). 2023 Dec 7;14(12):2215. doi: 10.3390/mi14122215.

Abstract

This paper introduces a new finding regarding single event upsets (SEUs) in configuration memory, and their potential impact on enhancing the performance of deep neural networks (DNNs) on the multiprocessor system on chip (MPSoC) platform. Traditionally, SEUs are considered to have negative effects on electronic systems or designs, but the current study demonstrates that they can also have positive contributions to the DNN on the MPSoC. The assertion that SEUs can have positive contributions to electronic system design was supported by conducting fault injections through dynamic reconfiguration on DNNs implemented on a 16nm FinFET technology Zynq UltraScale+ MPSoC. The results of the current study were highly significant, indicating that an SEU in configuration memory could result in an impressive 8.72% enhancement in DNN recognition on the MPSoC. One possible cause is that SEU in the configuration memory leads to slight changes in weight or bias values, resulting in improved activation levels of neurons and enhanced final recognition accuracy. This discovery offers a flexible and effective solution for boosting DNN performance on the MPSoC platform.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a5e/10745775/e67a411a47c1/micromachines-14-02215-g001.jpg

相似文献

1
Enhancement of Deep Neural Network Recognition on MPSoC with Single Event Upset.
Micromachines (Basel). 2023 Dec 7;14(12):2215. doi: 10.3390/mi14122215.
2
Mapping Neural Networks to FPGA-Based IoT Devices for Ultra-Low Latency Processing.
Sensors (Basel). 2019 Jul 5;19(13):2981. doi: 10.3390/s19132981.
3
Fault Injection Emulation for Systems in FPGAs: Tools, Techniques and Methodology, a Tutorial.
Sensors (Basel). 2021 Feb 17;21(4):1392. doi: 10.3390/s21041392.
4
Real-Time Energy Efficient Hand Pose Estimation: A Case Study.
Sensors (Basel). 2020 May 16;20(10):2828. doi: 10.3390/s20102828.
5
Evaluating the Visualization of What a Deep Neural Network Has Learned.
IEEE Trans Neural Netw Learn Syst. 2017 Nov;28(11):2660-2673. doi: 10.1109/TNNLS.2016.2599820.
7
Simulation Study on the Charge Collection Mechanism of FinFET Devices in Single-Event Upset.
Micromachines (Basel). 2024 Jan 29;15(2):201. doi: 10.3390/mi15020201.
8
A High-Performance and Flexible Architecture for Accelerating SDN on the MPSoC Platform.
Micromachines (Basel). 2022 Oct 29;13(11):1854. doi: 10.3390/mi13111854.
9
A Survey of MPSoC Management toward Self-Awareness.
Micromachines (Basel). 2024 Apr 26;15(5):577. doi: 10.3390/mi15050577.
10
Improving the Accuracy of Spiking Neural Networks for Radar Gesture Recognition Through Preprocessing.
IEEE Trans Neural Netw Learn Syst. 2023 Jun;34(6):2869-2881. doi: 10.1109/TNNLS.2021.3109958. Epub 2023 Jun 1.

引用本文的文献

本文引用的文献

1
A Fast Simulation Method for Evaluating the Single-Event Effect in Aerospace Integrated Circuits.
Micromachines (Basel). 2023 Sep 30;14(10):1887. doi: 10.3390/mi14101887.
2
Compression of Deep Neural Networks based on quantized tensor decomposition to implement on reconfigurable hardware platforms.
Neural Netw. 2022 Jun;150:350-363. doi: 10.1016/j.neunet.2022.02.024. Epub 2022 Mar 8.
3
NullHop: A Flexible Convolutional Neural Network Accelerator Based on Sparse Representations of Feature Maps.
IEEE Trans Neural Netw Learn Syst. 2019 Mar;30(3):644-656. doi: 10.1109/TNNLS.2018.2852335. Epub 2018 Jul 26.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验