DocumentCode :
76751
Title :
Accurate and Efficient Estimation of Logic Circuits Reliability Bounds
Author :
Ibrahim, Walid ; Shousha, Marwa ; Chinneck, John W.
Author_Institution :
Coll. of Inf. Technol., UAE Univ., Abu Dhabi, United Arab Emirates
Volume :
64
Issue :
5
fYear :
2015
fDate :
May 1 2015
Firstpage :
1217
Lastpage :
1229
Abstract :
As the sizes of CMOS devices rapidly scale deep into the nanometer range, the manufacture of nanocircuits will become extremely complex and will inevitably introduce more defects, including more transient faults that appear during operation. For this reason, accurately calculating the reliability of future designs will be extremely critical for nanocircuit designers as they investigate design alternatives to optimize the tradeoffs between area-power-delay and reliability. However, accurate calculation of the reliability of large and highly connected circuits is complex and very time consuming. This paper presents a complete solution for estimating logic circuit reliability bounds with high accuracy in reasonable time, even for very large and complex circuits. The solution combines a novel criticality scoring algorithm to rank the reliability of individual input vectors with a heuristic search to find the input vector having the lowest reliability. The solution scales well with circuit size, and is independent of the interconnect complexity or the logic depth. Extensive computational results show that the speed of our method is orders of magnitude faster than exact solutions provided by Bayesian network exact inferences, while maintaining identical or sufficiently close accuracy.
Keywords :
Bayes methods; estimation theory; logic circuits; reliability theory; vectors; Bayesian network; criticality scoring algorithm; input vector; logic circuit reliability bound estimation; Algorithm design and analysis; Circuit faults; Integrated circuit modeling; Integrated circuit reliability; Logic gates; Vectors; Reliability; evolutionary computing and genetic algorithms; heuristics design; inference engines; optimization; simulated annealing; worst-case analysis;
fLanguage :
English
Journal_Title :
Computers, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9340
Type :
jour
DOI :
10.1109/TC.2014.2315633
Filename :
6797873
Link To Document :
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