| Title |
Sensitive Vector Search for Logic Circuit Failure Probability based on Improved Adaptive Cuckoo Algorithm |
| Authors |
(Shuo Cai) ; (Sicheng Wu) ; (Weizheng Wang) ; (Fei Yu) ; (Lairong Yin) |
| DOI |
https://doi.org/10.5573/JSTS.2022.22.2.69 |
| Keywords |
Failure probability; cuckoo algorithm; sensitivity vector; logical circuit; semiconductors |
| Abstract |
With the development of microelectronics technology, the feature size of integrated circuit continues to shrink, and circuit performance has been improved. At the same time, however, factors such as process disturbance, power noise, and particle radiation are having an increasingly serious influence on the Failure Probability of Circuits (FPC). Searching the input vectors that are sensitive to FPC can assist circuit designers in selectively reinforcing the circuit to reduce the fault-tolerant overhead and improve the fault-tolerant efficiency. In this paper, an Improved Adaptive Cuckoo Search (IACS) algorithm is proposed to search sensitive circuit vectors. The vector segmentation strategy is used to change the dimension of the input vector, the hill climbing algorithm is used to improve the quality of the initial population, and the adaptive strategy is used to control parameters such as power-law index, discovery probability and scaling factor. At the same time, a Correlation Separation Approach (COSEA) is proposed to calculate the FPC under specific vector excitation. Experimental results show that the proposed algorithm has higher accuracy and better efficiency compared with existing algorithms. |