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A New Approach to Multi-objective Error Correcting Code Design Method

다목적 Error Correcting Code의 새로운 설계방법

  • 이희성 (연세대학교 전기전자공학부) ;
  • 김은태 (연세대학교 전기전자공학부)
  • Published : 2008.10.25

Abstract

Error correcting codes (ECCs) are commonly used to protect against the soft errors. Single error correcting and double error detecting (SEC-DED) codes are generally used for this purpose. The proposed approach in this paper selectively reduced power consumption, delay, and area in single-error correcting, double error-detecting checker circuits that perform memory error correction. The multi-objective genetic algorithm is employed to solve the non -linear optimization problem. The proposed method allows that user can choose one of different non-dominated solutions depending on which consideration is important among them. Because we use multi-objective genetic algorithm, we can find various dominated solutions. Therefore, we can choose the ECC according to the important factor of the power, delay and area. The method is applied to odd-column weight Hsiao code which is well- known ECC code and experiments were performed to show the performance of the proposed method.

Error correcting codes는 일반적으로 soft error를 막기 위해서 사용된다. single error의 수정과 double error의 검출(SEC-DED) 코드들은 이런 목적으로 사용된다. 본 논문에서는 이러한 회로의 크기, 지연시간, 전력 소비를 선택적으로 최소로 하는 SEC-DED의 설계방법을 제안한다. 이러한 SEC-DED의 설계는 비선형 최적화 문제로 포함되는데 우리는 다목적 유전자 알고리즘을 이용하여 이 문제를 해결한다. 제안하는 방법은 여러 가지 SEC-DED code들을 제공하여 사용자의 환경에 따라 알맞은 회로를 선택할 수 있도록 한다. 제안하는 방법을 효율적인 ECC코드로 알려져 있는 odd-column weight Hsiao code에 적용하여 그 효율성을 입증하였다.

Keywords

References

  1. C. L. Chen and M. Y. Hsiao, "Error-Correcting Codes for Semiconductor memory applications: A State-of-the-Art review," IBM J. Res. Develop., vol. 28, pp. 124-134, July 1984 https://doi.org/10.1147/rd.282.0124
  2. K. Favalli and C. Metra, "Design of Low-Power CMOS Two-Rail Checkers," Journal of Microelectronics Systems Integration, vol. 5, no. 2, pp. 101-110, 1997
  3. L. Davis, Handbook of Genetic Algorithms, Van Nostrand Reinhold, 1991
  4. M. Y. Hsiao, "A class of optimal minimum odd-weight-column SECDED codes," IBM J. Res. Develop., vol. 14, pp. 395-401, July 1970 https://doi.org/10.1147/rd.144.0395
  5. H. Lee, E. Kim, and M. Park, "A genetic feature weighting scheme for pattern recognition," Integrated Computer-Aided Engineering, vol. 14, pp. 161-171, 2007
  6. H. Ishibuchi and T. Murata, "A multi-objective genetic local search algorithm and its application to flowshop scheduling," IEEE Trans. Systems, Man, and Cybernetics- part c, vol. 28, pp. 392-403, 1998 https://doi.org/10.1109/5326.704576
  7. H. Lee, J. Lee, and E. Kim, "Multi-objective genetic design for error correcting code," International Symposium on advanced Intelligent Systems, pp. 792-795 Sep. 2007
  8. D. Coley, An Introduction to Genetic Algorithms for Scientists and Engineers, World Scientific, 1999
  9. H. Lee, J. Sung, and E. Kim, "Reducing power in error correcting code using genetic algorithm," in Proc. Int. Conf. Computer Information and Systems Science and Engineering, pp. 179-182, 2007
  10. S. Ghosh, S. Basu, and N. Touba, "Reducing Power Consumption in Memory ECC Checkers," International Test Conference, pp. 1322-1331, 2004
  11. T. Murata and H. Ishibuchi, "MOGA: Multi-objective genetic algorithms," in Proc. 2nd IEEE Int. Conf. Evolutionary Computat., pp. 289-294. 1995