ML Anthology

Optimal Schedules for Parallelizing Anytime Algorithms: The Case of Independent Processes

Lev Finkelstein, Shaul Markovitch, Ehud Rivlin
AAAI 2002 pp. 719-724
doi:10.5555/777092.777203 /aaai/2002/finkelstein2002aaai-optimal/

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.

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Text

Finkelstein et al. "Optimal Schedules for Parallelizing Anytime Algorithms: The Case of Independent Processes." AAAI Conference on Artificial Intelligence, 2002. doi:10.5555/777092.777203

Markdown

[Finkelstein et al. "Optimal Schedules for Parallelizing Anytime Algorithms: The Case of Independent Processes." AAAI Conference on Artificial Intelligence, 2002.](https://mlanthology.org/aaai/2002/finkelstein2002aaai-optimal/) doi:10.5555/777092.777203

BibTeX

@inproceedings{finkelstein2002aaai-optimal,
  title     = {{Optimal Schedules for Parallelizing Anytime Algorithms: The Case of Independent Processes}},
  author    = {Finkelstein, Lev and Markovitch, Shaul and Rivlin, Ehud},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2002},
  pages     = {719-724},
  doi       = {10.5555/777092.777203},
  url       = {https://mlanthology.org/aaai/2002/finkelstein2002aaai-optimal/}
}