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VLSI Placement Problem Based on Ant Colony Optimization Algorithm

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Artificial Intelligence Perspectives in Intelligent Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 464))

Abstract

The paper discusses a modified algorithm based on the ants’ behavior in nature. We suggest to apply this algorithm for solving the element placement problem—one of the most difficult problem in the VLSI design. This problem belongs to the NP-class problem that is there are no precise methods to solve this problem. Also we formulate the placement problem and choose an optimization criterion. The developed ant colony optimization (ACO) algorithm obtains optimal and quasi-optimal solutions during polynomial time. The distinguish feature of the algorithm is that alternative solution are represented as an undirected graph with weighted edges. Besides, at each generation the algorithm creates a taboo-list to eliminate the quantity of agent (ant) which is wrong from the point of view the using of Reverse Polish notation. To compare obtained results with known analogous algorithms we developed software which allows to carry out experiments on the basis of IBM benchmarks. Conducted experiments shown that the ACO algorithm is better than the other algorithms an average of 9 %.

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References

  1. Kureichik, V.V., Kureichik, V.M., Malioukov, S.P., Malioukov, A.S.: Algorithms for Applied CAD Problems, p. 487. Springer, Heidelberg (2009)

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  2. Alpert, C.J., Dinesh, P.M., Sachin, S.S.: Handbook of Algorithms for Physical design Automation. Auerbach Publications Taylor & Francis Group, USA (2009)

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  3. Kureichik, V.V., Zaruba D.V.: Partitioning of ECE schemes components based on modified graph coloring algorithm. In: 12th IEEE East-West Design and Test Symposium, EWDTS 2014 (2014)

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  4. IBM-PLACE 2.0 benchmark suits http://er.cs.ucla.edu/¬benchmarks/¬ibm-place2/bookshelf/¬ibm-place2-all-bookshelf-nopad.tar.gz

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Acknowledgments

This research is supported by grants of the Ministry of Education and Science of the Russian Federation, the project # 8.823.2014.

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Correspondence to Daria Zaruba .

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© 2016 Springer International Publishing Switzerland

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Zaruba, D., Zaporozhets, D., Kureichik, V. (2016). VLSI Placement Problem Based on Ant Colony Optimization Algorithm. In: Silhavy, R., Senkerik, R., Oplatkova, Z., Silhavy, P., Prokopova, Z. (eds) Artificial Intelligence Perspectives in Intelligent Systems. Advances in Intelligent Systems and Computing, vol 464. Springer, Cham. https://doi.org/10.1007/978-3-319-33625-1_12

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  • DOI: https://doi.org/10.1007/978-3-319-33625-1_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-33623-7

  • Online ISBN: 978-3-319-33625-1

  • eBook Packages: EngineeringEngineering (R0)

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