Title
Minimization of test time in system on chip using artificial intelligence-based test scheduling techniques
Abstract
System on chip (SoC) is a microchip which integrates many semiconductor devices into a single chip. The complete system that is integrated with many components and circuits has to be tested for its performance. At the same time, testing of SoC should not affect the final cost of the chip. The production cost of each and every chip can be reduced by minimizing the test time of each SoC. The testing time of each SoC can be minimized by using test scheduling techniques more efficiently and effectively. In this paper, artificial intelligence-based natural-inspired techniques such as ACO, MACO, ABC, bat and firefly algorithms are proposed to perform effective test scheduling, thereby reducing the total cost of the chip. The proposed algorithms are implemented on d695 and p22810 benchmark circuits for various values of TAM widths. The performance of the various algorithms was evaluated, and it is inferred that among the several algorithms used bat algorithm performs much better in reducing the overall testing time of SoC, and hence, the SoC cost is also reduced.
Year
DOI
Venue
2020
10.1007/s00521-019-04039-6
NEURAL COMPUTING & APPLICATIONS
Keywords
DocType
Volume
Artificial intelligence,Test scheduling,Ant colony optimization,Artificial bee colony algorithm,Bat algorithm,Firefly algorithm
Journal
32.0
Issue
ISSN
Citations 
SP9
0941-0643
3
PageRank 
References 
Authors
0.47
31
3