Genetic-Algorithm-based Test Pattern Generation for Crosstalk Faults between On-Chip Aggressor and Victim

作者：Duganapalli Kishore^*; Palit Ajoy K; Anheier Walter

来源：Journal of Circuits, Systems, and Computers, 2016, 25(3): 1640018.

DOI：10.1142/S0218126616400181

• Crosstalk
• genetic algorithms
• ATPG

With the shrinking feature size and increasing aspect ratios of interconnects in DSM chips, the coupling noise between adjacent interconnects has become a major signal integrity (SI) issue, giving rise to crosstalk failures. In older technologies, SI issues have been ignored because of high noise immunity of the CMOS circuits and the process technology. However, as CMOS technologies lower down the supply voltage as well as the threshold voltage of a transistor, digital designs are more and more susceptible to noise because of the reduction of noise margin. The genetic algorithms (GAs) have been applied earlier in different engineering disciplines as potentially good optimization tools and for various applications in VLSI design, layout, EDIF digital system testing and also for test automation, particularly for stuck-at-faults and crosstalk-induced delay faults. In this paper, an elitist GA has been developed that can be used as an ATPG tool for generating the test patterns for crosstalk-induced faults between on-chip aggressor and victim and as well as for stuck-at-faults. It has been observed that the elitist GA, when the fitness function is properly de defined, has immense potential in extracting the suitable test vectors quickly from randomly generated initial patterns.

• 出版日期2016-3