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Efficient evolutionary approaches for the data ordering problem with inversion

Published: 10 April 2006 Publication History

Abstract

An important aim of circuit design is the reduction of the power dissipation. Power consumption of digital circuits is closely related to switching activity. Due to the increase in the usage of battery driven devices (e.g. PDAs, laptops), the low power aspect became one of the main issues in circuit design in recent years. In this context, the Data Ordering Problem with and without Inversion is very important. Data words have to be ordered and (eventually) negated in order to minimize the total number of bit transitions. These problems have several applications, like instruction scheduling, compiler optimization, sequencing of test patterns, or cache write-back. This paper describes two evolutionary algorithms for the Data Ordering Problem with Inversion (DOPI). The first one sensibly improves the Greedy Min solution (the best known related polynomial heuristic) by a small amount of time, by successively applying mutation operators. The second one is a hybrid genetic algorithm, where a part of the population is initialized using greedy techniques. Greedy Min and Lower Bound algorithms are used for verifying the performance of the presented Evolutionary Algorithms (EAs) on a large set of experiments. A comparison of our results to previous approaches proves the efficiency of our second approach. It is able to cope with data sets which are much larger than those handled by the best known EAs. This improvement comes from the synchronized strategy of applying the genetic operators (algorithm design) as well as from the compact representation of the data (algorithm implementation).

References

[1]
Chandrakasan, A. P., Potkonjak, M., Rabaey, J., Brodersen, R. W.: HYPER-LP: a system for power minimization using architectural transformations. In Int'l Conf on CAD, pages 300-303, 1992
[2]
Cormen, T. H., Leiserson, C. E., Rivest, R. L., Stein, C.: Introduction to Algorithms, Second Edition, The MIT Press; 2nd edition (September 1, 2001)
[3]
Davis, L.: Applying adaptive algorithms to epistatic domains. In Proceedings of IJCAI, pages 162-164, 1985
[4]
Davis, L.: Handbook of Genetic Algorithms. van Nostrand Reinhold, New York, 1991
[5]
De Micheli, G.: Synthesis and Optimization of Digital Circuits. McGraw-Hill, Inc., 1994
[6]
Devadas, S., Malik, S.: A survey of optimization techniques targeting low power VLSI circuits. In Design Automation Conf., pages 242-247, 1995
[7]
Drechsler, N., Drechsler, R.: Exploiting don't cares during data sequencing using genetic algorithms. In ASP Design Automation Conf., pages 303-306, 1999
[8]
Drechsler, R.: Evolutionary Algorithms for VLSI CAD. Kluwer Academis Publisher, 1998
[9]
Drechsler, R., Drechsler, N.: Evolutionary Algorithms for Embedded System Design. Kluwer Acadmeic Publisher, 2002
[10]
Drechsler, R., Göckel, N.: A genetic algorithm for data sequencing. Electronic Letters, 33(10): 843-845, 1997
[11]
Drechsler, R., Drechsler, N.: Minimization of Transitions by Complementation and Resequencing using Evolutionary Algorithms, In Proceedings of 21st IASTED International Multi-Conference Applied Informatics (AI 2003), IASTED International Conference on Artificial Intelligence and Applications (AIA 2003), Innsbruck, 2003
[12]
Garey, M. R., Johnson, D. S.: Computers and Intractability - A Guide to NPCompleteness. Freeman, San Francisco, 1979
[13]
Goldberg, D. E., Lingle, R.: Alleles, loci, and the traveling salesman problem. In Int'l Conference on Genetic Algorithms, pages 154-159, 1985
[14]
Holland, J. H.: Adaption in Natural and Artificial Systems. The University of Michigan Press, Ann Arbor, MI, 1975
[15]
Iman, S., Pedram, M.: Multilevel network optimization for low power. In Int'l Conf. On CAD, pages 372-377, 1994
[16]
Mazumder, P., Rudnick, E.: Genetic Algorithms for VLSI Design, Layout & Test Automation. Prentice Hall, 1998
[17]
Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs. 3rd edn. Springer-Verlag, Berlin Heidelberg New York (1996)
[18]
Murgai, R., Fujita, M., Krishnan, S. C.: Data sequencing for minimum-transition transmission. In IFIP Int'l Conf. on VLSI, 1997
[19]
Murgai, R., Fujita, M., Oliveira, A.: Using complementation and resequencing to minimize transitions. In Design Automation Conf., pages 694-697, 1998
[20]
Oliver, I. M., Smith, D. J., Holland, J. R. C.: A study of permutation crossover operators on the traveling salesman problem. In Int'l Conference on Genetic Algorithms, pages 224- 230, 1987
[21]
Shen, W.-Z., Lin, J.-Y., Wang, F.-W.: Transistor reordering rules for power reduction in CMOS gates. In ASP Design Automation Conf., pages 1-6, 1995
[22]
Stan, M., Burleson, W.: Limited-weight codes for low-power I/O. Int'l Workshop on Low Power Design, 1994
[23]
Tiwari, V., Malik, S., Wolfe, A., Lee, M.: Power analysis of embedded software: A first step towards software power minimization. In Int'l Conf. on CAD, pages 384-390, 1994
[24]
Tiwari, V., Malik, S., Wolfe, A., Lee, M.: Instruction level power analysis and optimization software. In VLSI Design Conf., 1996
[25]
Tsui, C., Pedram, M., Despain, A. M.: Technology decomposition and mapping targeting low power dissipation. In Design Automation Conf., pages 68-73, 1993
[26]
Vaishnav, H., Pedram, M.: PCUBE: A performance driven placement algorithm for low power design. In European Design Automation Conf., pages 72-77, 1993
[27]
Whitley, D., Starkweather, T., Fuquay, D.: Scheduling problems and traveling salesman: The genetic edge recombination operator. In Int'l Conference on Genetic Algorithms, pages 133-140, 1989

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  • (2010)Optimal waveband switching in optical ring networksProceedings of the 29th conference on Information communications10.5555/1833515.1833628(596-604)Online publication date: 14-Mar-2010
  1. Efficient evolutionary approaches for the data ordering problem with inversion

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    Published In

    cover image Guide Proceedings
    EuroGP'06: Proceedings of the 2006 international conference on Applications of Evolutionary Computing
    April 2006
    809 pages
    ISBN:3540332375
    • Editors:
    • Franz Rothlauf,
    • Jürgen Branke,
    • Stefano Cagnoni,
    • Ernesto Costa,
    • Carlos Cotta

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    • EvoNet
    • Artpool Art Research Center, Budapest, Hungary: Artpool Art Research Center, Budapest, Hungary

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    Springer-Verlag

    Berlin, Heidelberg

    Publication History

    Published: 10 April 2006

    Author Tags

    1. complexity
    2. data ordering problem
    3. digital circuit design
    4. evolutionary algorithms
    5. graph theory
    6. low power
    7. optimization
    8. transition minimization

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    • (2010)Optimal waveband switching in optical ring networksProceedings of the 29th conference on Information communications10.5555/1833515.1833628(596-604)Online publication date: 14-Mar-2010

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