Optimal Schedules for Parallelizing Anytime Algorithms: the Case of Independent Processes
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Optimal Schedules for Parallelizing Anytime Algorithms: The Case of Independent Processes.
In AAAI/IAAI, 719-724, 2002
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Abstract
The performance of anytime algorithms having a nondeterministic nature can be improved by solving simultaneously several instances of the algorithm-problem pairs. These pairs may include different instances of a problem (like starting from a different initial state), different algorithms (if several alternatives exist), or several instances of the same algorithm (for nondeterministic algorithms). In this paper we present a general framework for optimal parallelization of independent processes. We show a mathematical model for this framework, present algorithms for optimal scheduling, and demonstrate its usefulness on a real problem.
Co-authors
Bibtex Entry
@inproceedings{FinkelsteinMR02i,
title = {Optimal Schedules for Parallelizing Anytime Algorithms: The Case of Independent Processes.},
author = {Lev Finkelstein and Shaul Markovitch and Ehud Rivlin},
year = {2002},
booktitle = {AAAI/IAAI},
pages = {719-724},
abstract = {The performance of anytime algorithms having a nondeterministic nature can be improved by solving simultaneously several instances of the algorithm-problem pairs. These pairs may include different instances of a problem (like starting from a different initial state), different algorithms (if several alternatives exist), or several instances of the same algorithm (for nondeterministic algorithms). In this paper we present a general framework for optimal parallelization of independent processes. We show a mathematical model for this framework, present algorithms for optimal scheduling, and demonstrate its usefulness on a real problem.}
}