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

被引:2
|
作者
Yang, Weitao [1 ,2 ,3 ]
Song, Wuqing [1 ]
Guo, Yaxin [2 ]
Li, Yonghong [2 ]
He, Chaohui [2 ]
Wu, Longsheng [1 ]
Wang, Bin [1 ]
Liu, Huan [4 ]
Shi, Guang [4 ]
机构
[1] Xidian Univ, Sch Microeletron, Xian 710071, Peoples R China
[2] Xi An Jiao Tong Univ, Sch Nucl Sci & Technol, Xian 710049, Peoples R China
[3] Politecn Torino, Dipartimento Automat & Informat, I-10129 Turin, Italy
[4] Xidian Univ, Sch Aerosp Sci & Technol, Xian 710071, Peoples R China
基金
中国国家自然科学基金;
关键词
Zynq UltraScale plus MPSoC; single event upset; deep neural network; fault injection; enhancement; RELIABILITY; EMULATION; SYSTEM; IMPACT; SRAM;
D O I
10.3390/mi14122215
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
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.
引用
收藏
页数:13
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