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Parallel and distributed local search in COMET. (English) Zbl 1179.90288
Summary: The availability of commodity multiprocessors and high-speed networks of workstations offer significant opportunities for addressing the increasing computational requirements of optimization applications. To leverage these potential benefits, it is important, however, to make parallel and distributed processing easily accessible to a wide audience of optimization programmers. This paper addresses this challenge by proposing parallel and distributed programming abstractions that keep the distance from sequential local search algorithms as small as possible. The abstractions, including parallel loops, interruptions, thread pools, and shared objects, are compositional and cleanly separate the optimization program and the parallel instructions. They have been evaluated experimentally on a variety of applications, including warehouse location and coloring, for which they provide significant speedups.

MSC:
90C27 Combinatorial optimization
68M20 Performance evaluation, queueing, and scheduling in the context of computer systems
68W10 Parallel algorithms in computer science
90B40 Search theory
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