Parallel decomposition of combinatorial optimization problems using electro-optical vector by matrix multiplication architecture

  • Authors:

  • Dan E. Tamir;Natan T. Shaked;Wilhelmus J. Geerts;Shlomi Dolev

  • Affiliations:

  • Department of Computer Science, Texas State University, San Marcos, USA 78666;Department of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel 84105;Department of Physics, Texas State University, San Marcos, USA 78666;Department of Computer Science, Ben-Gurion University of the Negev, Beer-Sheva, Israel 84105

  • Venue:
  • The Journal of Supercomputing
  • Year:
  • 2012

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Abstract

A new state space representation for a class of combinatorial optimization problems, related to minimal Hamiltonian cycles, enables efficient implementation of exhaustive search for the minimal cycle in optimization problems with a relatively small number of vertices and heuristic search for problems with large number of vertices. This paper surveys structures for representing Hamiltonian cycles, the use of these structures in heuristic optimization techniques, and efficient mapping of these structures along with respective operators to a newly proposed electrooptical vector by matrix multiplication (VMM) architecture. Record keeping mechanisms are used to improve solution quality and execution time of these heuristics using the VMM. Finally, the utility of a low-power VMM based implementation is evaluated.