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On Enforced Convergence of ACO and its Implementation on the Reconfigurable Mesh Architecture Using Size Reduction Tasks

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Abstract

In this paper we show that size reduction tasks can be used for executing iterative randomized metaheuristics on runtime reconfigurable architectures so that an improved throughput and better solution qualities are obtained compared to conventional architectures that do not allow runtime reconfiguration. In particular, the problem of executing ant colony optimization (ACO) algorithms on a dynamically reconfigurable mesh architecture is studied. It is shown how ACO can be implemented such that the convergence behavior of the algorithm can be used to dynamically reduce the size of the submesh that is needed for execution. Furthermore we propose a method to enforce the convergence of ACO leading to a faster reduction process. This increases the throughput of ACO algorithms on runtime reconfigurable meshes. The increased throughput is used for repeated runs of ACO algorithms on a given set of problem instances which significantly improves the obtained solution quality.

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References

  1. A. Bauer, B. Bullnheimer, R. F. Hartl, and C. Strauss. An ant colony optimization approach for the single machine total tardiness problem. In Proceedings of the 1999 Congress on Evolutionary Computation (CEC99), pp. 1445–1450. Washington D.C., 1999.

  2. Y. Ben-Asher, K.-J. Lange, D. Peleg, and A. Schuster. The complexity of reconfiguring network models. Information and Computation, 121:41–58, 1995.

    Google Scholar 

  3. M. L den Besten, T. Stützle, and M. Dorigo. Ant colony optimization for the total weighted tardiness problem. In M. Schoenauer et al., eds., Parallel Problem Solving from Nature: 6th Int. Conf., vol. 1917 pp. 611–620. Springer, Berlin, LNCS, 2000.

    Google Scholar 

  4. V. Bokka, K. Nakano, S. Olariu, J. L. Schwing, and L. Wilson. Optimal algorithms for the multiple query problem on reconfigurable meshes, with applications. IEEE Transactions on Parallel and Distributed Systems, 12:875–887, 2001.

    Google Scholar 

  5. K. Bondalapati and V. K. Prasanna. Reconfigurable meshes: Theory and practice. In R. W. Hartenstein and Viktor K. Prasanna, eds., Proceedings Reconfigurable Architectures Workshop, Geneva, Switzerland. Bruchsal, ITpress Verlag.

  6. R. E. Burkard, S. E. Karisch, and F. Rendl. QAPLIB-A quadratic assignment problem library. Journal of Global Optimization, 10:391–403, 1997. QAPLIB: http://www.opt.math.tu-graz.ac.at/qaplib/

    Google Scholar 

  7. O. Diessel, H. ElGindy, M. Middendorf, B. Schmidt, and H. Schmeck. Dynamic scheduling of tasks on partially reconfigurable FPGAs. IEE-Proceedings-Computer and Digital Techniques, 147:181–188, 2000.

    Google Scholar 

  8. M. Dorigo and G. Di Caro. The ant colony optimization meta-heuristic. In D. Corne, M. Dorigo, and F. Glover, eds., New Ideas in Optimization, pp. 11–32. McGraw-Hill, 1999.

  9. M. Dorigo and L. M. Gambardella. Ant colonies for the QAP. Technical Report IDSIA-4-97, IDSIA, Lugano, 1997.

    Google Scholar 

  10. M. Dorigo and L. M. Gambardella. Ant colony system: A cooperative learning approach to the traveling salesman problem. IEEE Trans. Evol. Comput., 1:53–66, 1997.

    Google Scholar 

  11. B. Echermann and H. J. Wunderlich. Optimized synthesis of self-testable finite state machines. In 20th Int. Symp. on Fault-Tolerant Computing (FFTCS 20), Newcastle upon Tyne, 1990.

  12. L. M. Gambardella, E. Taillard, and M. Dorigo. Ant colonies for the quadratic assignment problem. Journal of the Operational Research Society, 50:167–176, 1999.

    Google Scholar 

  13. J.-W. Jang, M. Nigam, V. K. Prasanna, and S. Sahni. Constant time algorithms for computational geometry on the reconfigurable mesh. IEEE Transactions on Parallel and Distributed Systems, 8:1–12, 1997.

    Google Scholar 

  14. V. Maniezzo. Exact and approximate nondeterministic tree-search procedures for the quadratic assignment problem. INFORMS Journal on Computing, 11:358–368, 1999.

    Google Scholar 

  15. V. Maniezzo and A. Colorni. The ant system applied to the quadratic assignment problem. IEEE Transactions on Knowledge and Data Engineering, 11:769–778, 1999.

    Google Scholar 

  16. V. Maniezzo, A. Colorni, and M. Dorigo. The Ant System applied to the quadratic assignment problem. Tech. Rep. IRIDIA/94-28, Universit Libre de Bruxelles, Belgium, 1994.

    Google Scholar 

  17. P. Martin. A hardware implementation of a genetic programming system using FPGAs and Handel-C. Genetic Programming and Evolvable Machines, 2:317–343, 2001.

    Google Scholar 

  18. G. M. Megson and I. M. Bland. A generic systolic array for genetic algorithms. IEEE Proceedings on Computers and Digital Techniques, 144:107–121, 1997.

    Google Scholar 

  19. D. Merkle and M. Middendorf. An ant algorithm with global pheromone evaluation for scheduling a single machine, to appear in Applied Intelligence.

  20. D. Merkle and M. Middendorf. Fast ant colony optimization on runtime reconfigurable processor arrays, to appear in Genetic Programming and Evolvable Machines, 3(4), 2002.

  21. D. Merkle, M. Middendorf, and H. Schmeck. Ant colony optimization for resource-constrained project scheduling. IEEE Transactions on Evolutionary Computation, 6:333–346, 2002.

    Google Scholar 

  22. M. Middendorf, H. Schmeck, H. Schröder, and G. Turner. Multiplication of matrices with different sparseness properties on dynamically reconfigurable meshes. VLSI Design, 9:69–81, 1999.

    Google Scholar 

  23. M. Middendorf, F. Reischle, and H. Schmeck. Multi colony ant algorithms. Journal of Heuristics, 8:305–320, 2002.

    Google Scholar 

  24. R. Miller, V. K. Prasanna-Kumar, D. I. Reisis, and Q. F. Stout. Parallel computations on reconfigurable meshes. IEEE Trans. Comput., 42:678–692, 1993.

    Google Scholar 

  25. K. Nakano and K. Wada. Integer summing algorithms on reconfigurable meshes. Theoretical Computer Science, 197:57–77, 1998.

    Google Scholar 

  26. T. Stützle. An ant approach for the flow shop problem. In Proc. 6th European Congress on Intelligent Techniques & Soft Computing (EUFIT '98), vol. 3, pp. 1560–1564. Verlag Mainz, Aachen, 1998.

    Google Scholar 

  27. T. Stützle and M. Dorigo. ACO algorithms for the quadratic assignment problem. In D. Corne, M. Dorigo, and F. Glover, eds., New Ideas in Optimization, pp. 33–50. McGraw-Hill, 1999.

  28. T. Stützle and H. H. Hoos. The MAX-MIN ant system. Future Generation Computer Systems, 16:889–914, 2000.

    Google Scholar 

  29. J. Teich, S. P. Fekete, and J. Schepers. Optimization of dynamic hardware reconfigurations. The Journal of Supercomputing, 19:57–75, 2001.

    Google Scholar 

  30. H. Walder and M. Platzner. Non-preemptive multitasking on FPGAs: Task placement and footprint transform. In Proceedings of the 2nd International Conference on Engineering of Reconfigurable Systems and Algorithms (ERSA '02), pp. 24–30. CSREA Press, Las Vegas, Nevada, USA, 2002.

    Google Scholar 

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Authors and Affiliations

  1. Parallel Computing and Complex Systems Group, University of Leipzig, Augustusplatz 10–11, D-04109, Leipzig, Germany

    Stefan Janson, Daniel Merkle & Martin Middendorf*

  2. School of Computer Science and Engineering, The University of New South Wales, Sydney, 2052, Australia

    Hossam Elgindy

  3. AIFB Institute, University of Karlsruhe, D-76128, Karlsruhe, Germany

    Hartmut Schmeck

Authors
  1. Stefan Janson
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  2. Daniel Merkle
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  3. Martin Middendorf*
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  4. Hossam Elgindy
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  5. Hartmut Schmeck
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Correspondence to Stefan Janson.

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Janson, S., Merkle, D., Middendorf*, M. et al. On Enforced Convergence of ACO and its Implementation on the Reconfigurable Mesh Architecture Using Size Reduction Tasks. The Journal of Supercomputing 26, 221–238 (2003). https://doi.org/10.1023/A:1025642930419

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