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Completion Probabilities and Parallel Restart Strategies under an Imposed Deadline.

ABSTRACT: Let A be any fixed cut-off restart algorithm running in parallel on multiple processors. If the algorithm is only allowed to run for up to time D, then it is no longer guaranteed that a result can be found. In this case, the probability of finding a solution within the time D becomes a measure for the quality of the algorithm. In this paper we address this issue and provide upper and lower bounds for the probability of A finding a solution before a deadline passes under varying assumptions. We also show that the optimal restart times for a fixed cut-off algorithm running in parallel is identical for the optimal restart times for the algorithm running on a single processor. Finally, we conclude that the odds of finding a solution scale superlinearly in the number of processors.

SUBMITTER: Lorenz JH

PROVIDER: S-EPMC5061357 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Completion Probabilities and Parallel Restart Strategies under an Imposed Deadline.

Lorenz Jan-Hendrik JH

PloS one 20161012 10

Let A be any fixed cut-off restart algorithm running in parallel on multiple processors. If the algorithm is only allowed to run for up to time D, then it is no longer guaranteed that a result can be found. In this case, the probability of finding a solution within the time D becomes a measure for the quality of the algorithm. In this paper we address this issue and provide upper and lower bounds for the probability of A finding a solution before a deadline passes under varying assumptions. We a ...[more]

PMID: 27732631

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