Extending the Computational Horizon: Effective Distributed Resource-Bounded Computation for Intractable Problems
Harry Paarsch and
Alberto M. Segre ()
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Alberto M. Segre: University of Iowa
No 933, Computing in Economics and Finance 1999 from Society for Computational Economics
Abstract:
A number of combinatorial problems of interest to computational economists, such as some two-sided matching problems, belong to the complexity class NP. The best known solutions to these problems require exponential computation time in the size of the input, and are intractable in practice except for very small input size. We present an overview of a new distributed-computation technique called "nagging" that, while still exponential, allows one to harness multiple processors to extend the size of the largest solvable problem in a resource-bounded environment. Nagging requires relatively infrequent and brief interprocessor communication, is naturally tolerant (i.e., unaffected by the dynamic loss of processing elements), and exceptionally scalable in practice (i.e., robust in the presence of high message latencies, and, therefore, suitable for use in very large networks).
Date: 1999-03-01
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Persistent link: https://EconPapers.repec.org/RePEc:sce:scecf9:933
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More papers in Computing in Economics and Finance 1999 from Society for Computational Economics CEF99, Boston College, Department of Economics, Chestnut Hill MA 02467 USA. Contact information at EDIRC.
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