DocumentCode
3544603
Title
A built-in self-test design with low power consumption based on genetic algorithm
Author
Tan, Enmin ; Wang, Li
Author_Institution
Sch. of Electron. Eng., Guilin Univ. of Electron. Technol., Guilin, China
fYear
2009
fDate
16-19 Aug. 2009
Abstract
A low peak power consumption built-in self-test (BIST) design based on genetic algorithm (GA), which is denoted by GAITPG, has been proposed in our previous study. This paper presents an improved performance of GAITPG, which also aims at the reduction of the changes between successive test patterns. (m-1) vectors were inserted between two successive n-bit pseudorandom test patterns generated by the original linear feedback shifted register (LFSR), while m and the element of groups were optimized by GA. Experimental results based on ISCAS´85 benchmark circuits show that the test pattern generator (TPG) with low power consumption proposed in this paper is efficient, without losing stuck-at fault coverage. Also, a comparison of reduction of power consumption between GAITPG and other scheme (such as inserted TPG (ITPG)) was reported.
Keywords
benchmark testing; built-in self test; circuit feedback; genetic algorithms; low-power electronics; random number generation; shift registers; (m-1) vectors; GAITPG; ISCAS´85 benchmark circuits; built-in self-test design; genetic algorithm; linear feedback shifted register; low peak power consumption; n-bit pseudorandom test patterns; stuck-at fault coverage; test pattern generator; Algorithm design and analysis; Benchmark testing; Built-in self-test; Circuit testing; Energy consumption; Feedback circuits; Genetic algorithms; Registers; Test pattern generators; Vectors; BIST; GA; LFSR; TPG; low power consumption design; weighted switching activity (WSA);
fLanguage
English
Publisher
ieee
Conference_Titel
Electronic Measurement & Instruments, 2009. ICEMI '09. 9th International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4244-3863-1
Electronic_ISBN
978-1-4244-3864-8
Type
conf
DOI
10.1109/ICEMI.2009.5274527
Filename
5274527
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