A Generic Block-Level Error Confinement Technique for Memory Based on Principal Component Analysis
A Generic Block-Level Error Confinement Technique for Memory Based on Principal Component Analysis
复制标题
基于主成分分析的通用内存块级错误限制技术
DOI：
10.3390/app9224733
复制
发表时间：
2019
影响因子：
2.7
通讯作者：
Fang Jiayan
中科院分区：
文献类型：
--
作者：
Shao Cuiping;Li Huiyun;Wang Zheng;Fang Jiayan
纳米级CMOS技术遇到了严重的可靠性问题，特别是在片上存储器中。诸如纠错码（ECC）之类的常规字级错误恢复技术遭受高物理开销并且不能纠正越来越多地报告的多位翻转错误。另一方面，图像处理和机器学习等最先进的应用放松了对数据保护级别的要求，这导致了近似容错的专用技术。在这项工作中，我们引入了一种新的内存错误保护方案，通过主成分分析和模块化的技术，以分割PCA之前的数据的特征提取的基础上。通过用平均约束向量替换故障向量，可以保护提取的特征。这种方法通过对通用数据块进行单比特或多比特翻转来限制错误，同时与传统ECC技术相比，在执行时间和内存使用方面实现了显著节省。图像处理的实验结果表明，所提出的技术的结果在重建图像的PSNR超过30 dB，而对单比特和多比特翻转错误的鲁棒性，与传统的ECC为基础的技术相比，减少内存存储仅为22.4%。
Nanoscale CMOS technology has encountered severe reliability issues especially in on-chip memory. Conventional word-level error resilience techniques such as Error Correcting Codes (ECC) suffer from high physical overhead and inability to correct increasingly reported multiple bit flip errors. On the other hands, state-of-the-art applications such as image processing and machine learning loosen the requirement on the levels of data protection, which result in dedicated techniques of approximated fault tolerance. In this work, we introduce a novel error protection scheme for memory, based on feature extraction through Principal Component Analysis and the modular-wise technique to segment the data before PCA. The extracted features can be protected by replacing the fault vector with the averaged confinement vectors. This approach confines the errors with either single or multi-bit flips for generic data blocks, whilst achieving significant savings on execution time and memory usage compared to traditional ECC techniques. Experimental results of image processing demonstrate that the proposed technique results in a reconstructed image with PSNR over 30 dB, while robust against both single bit and multiple bit flip errors, with reduced memory storage to just 22.4% compared to the conventional ECC-based technique.