CASSER: A Closed-Form Analysis Framework for Statistical Soft Error Rate

CMOS designs in the deep submicrometer era require statistical methods to accurately estimate the circuit soft error rate (SER). However, process variation increases the complexity of statistical characteristics related to transient faults, leading to considerable uncertainty in the behavior of soft...

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Bibliographic Details
Published in:IEEE transactions on very large scale integration (VLSI) systems 2013-10, Vol.21 (10), p.1837-1848
Main Authors: Chang, Austin C-C, Huang, Ryan H-M, Wen, Charles H-P
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Applied sciences
Circuit faults
Computer simulation
Design. Technologies. Operation analysis. Testing
Electronics
Errors
Exact sciences and technology
Exact solutions
Integrated circuit modeling
Integrated circuits
Logic gates
Mathematical analysis
Random variables
Reliability
Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices
single event upset
Soft errors
Statistical methods
statistical SER (SSER)
statistical static timing analysis (SSTA)
Studies
Syntax
Timing
Transient analysis
transient fault
Very large scale integration
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Summary:CMOS designs in the deep submicrometer era require statistical methods to accurately estimate the circuit soft error rate (SER). However, process variation increases the complexity of statistical characteristics related to transient faults, leading to considerable uncertainty in the behavior of soft errors. Regardless of the methods used, current statistical SER (SSER) frameworks invariably involve a tradeoff between accuracy and efficiency. This paper presents accurate cell models in first-order closed form to overcome this problem, thereby enabling the analysis of SSERs in a block-based fashion similar to statistical static timing analysis. These cell models are derived as a closed form in the proposed framework named CASSER, and remain precise under the assumption of a normal distribution for the process parameters. Experimental results demonstrate the efficiency (> 2-order times faster than the latest framework) and accuracy ( error) of CASSER in estimating circuit SERs, when compared with the Monte Carlo SPICE simulation.
ISSN:1063-8210
1557-9999
DOI:10.1109/TVLSI.2012.2220386