Fault Tolerance Method for Memory Based on Inner Product Similarity and Experimental Study on Heavy Ion Irradiation

Author:

Shao Cuiping1,Li Huiyun1,Du Guanghua2,Guo Jinlong2,Miao Zujia1,Zhu Hongmei3

Affiliation:

1. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen University Town, Shenzhen 518055, P. R. China

2. Institute of Modern Physics (IMP), Chinese Academy of Sciences, 509 Nanchang Road, Lanzhou 730000, P. R. China

3. Shenzhen Polytechnic, 7098 Liuxian Avenue, Nanshan District, Shenzhen 518055, P. R. China

Abstract

As the feature sizes of integrated circuits are reduced to the nanometer scale, the total soft error rate (SER) in memory and the proportion of multiple bit upsets (MBUs) are significantly increasing. In order to ensure the information reliability, many error correction codes with strong error correction ability were proposed, such as Reed–Somolon (RS) code and Bose–Chaudhuri–Hocquenghem (BCH) code. However, these error correction codes have limited error correction capability, high algorithm complexity and large data redundancy. In this paper, a novel fault tolerance method for locating and correcting multiple bit errors in memory is proposed based on data similarity. The proposed method uses the inner product as the metric to analyze the similarity of the pre-protected data from the vertical and horizontal dimensions, respectively, and to construct the model of error location and correction. This method performs encoding and decoding in units of blocks and detecting and correcting in units of words, so it can correct any number of bits in a corrupted word with low redundancy overhead. Finally, irradiation tests were conducted on a commercial SRAM, and the feasibility of the proposed method is verified by using heavy ion [Formula: see text]Kr[Formula: see text] as irradiation source.

Funder

National Natural Science Foundation of China

Shenzhen S&T Funding

Guangdong Basic and Applied Basic Research Project

Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems

Publisher

World Scientific Pub Co Pte Ltd

Subject

Electrical and Electronic Engineering,Hardware and Architecture,Media Technology

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