Fault Coverage Re-Evaluation of Memory Test Algorithms With Physical Memory Characteristics

A memory fault model (FM) is an abstraction of the physical mechanism of memory failure. When the physical failure mechanisms are not fully represented in FMs, the coverage of the FMs can be different from that of the failure mechanisms. However, it is impractical (or impossible) to model every elec...

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Bibliographic Details
Published in:IEEE access 2021, Vol.9, p.124632-124639
Main Authors: Lee, Kiseok, Kim, Jeonghwan, Baeg, Sanghyeon
Format: Article
Language:English
Subjects:
address scrambling
Algorithms
Circuit faults
Computational modeling
electrical masking
electrical neighborhood
Failure analysis
Failure mechanisms
Fault coverage (FC) re-evaluation
Faults
Frequency modulation
Heuristic algorithms
Integrated circuit modeling
Masking
memory fault model (FM)
New technology
Physical properties
Random access memory
Reduction
Simulation
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Summary:A memory fault model (FM) is an abstraction of the physical mechanism of memory failure. When the physical failure mechanisms are not fully represented in FMs, the coverage of the FMs can be different from that of the failure mechanisms. However, it is impractical (or impossible) to model every electrical aspect of the failure mechanisms with one or more FMs. This problem has become even worse with emerging technologies. Thus, in this study, the fault coverage (FC) consequences are investigated when the physical memory characteristics are not properly linked to the FMs or even test algorithms. Three physical characteristics were considered for this exploration: electrical masking, address scrambling, and electrical neighborhoods. To this end, memory fault simulations were performed, and the test algorithms were re-evaluated in terms of FC. Simulations were performed on the 1 kB area of the example SRAM model; three classes of FMs (56 static faults (SFs), 126 dynamic faults (DFs), and 192 neighborhood pattern-sensitive faults (NPSFs)) were simulated for FC evaluation; and March MSS, March MD2, and March 12N were used to re-evaluate the FCs of SFs, DFs, and NPSFs, respectively. From the simulation results, we observed the negative impact of physical characteristics on FC. When masking was considered, FC reductions of 10.72% SFs and 9.52% DFs were observed; when address scrambling was not available, an FC reduction of 80.21% NPSFs was observed. Finally, considering electrical neighborhood changes depending on the physical memory structure, an FC reduction of 41.67% NPSFs was observed.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2021.3110594