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IEEE Transactions on Software Engineering
Article . 1989 . Peer-reviewed
License: IEEE Copyright
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Article . 2017
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Optimal partitioning of random programs across two processors

Authors: David M. Nicol;

Optimal partitioning of random programs across two processors

Abstract

Recent works by \textit{B. Indurkhya}, \textit{H. S. Stone} and \textit{X.-Ch. Lu} [ibid. SE-12, 483-495 (1986; Zbl 0587.68025)], discusses the optimal partitioning of random distributed programs. They conclude that the optimal partitioning of a homogeneous random program over a homogeneous distributed system either assigns all modules to a single processor, or distributes the modules as evenly as possible among all processors. Their analysis rests heavily on the approximation that equates the expected maximum of a set of independent random variables with the set's maximum expectation. We strengthen their results by providing an approximation-free proof of this result for two processors under general conditions on the module execution time distribution. However, we show that additional rigor leads to a different characterization of the optimality points. We also show that under a rigorous analysis one is led to different conclusions in the general P-processor case than those reached using Indurkhya et al.'s, \textit{H. S. Stone} and \textit{X.-Ch. Lu} [ibid. SE-12, 483-495 (1986; Zbl 0587.68025)] approximation.

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Keywords

random distributed programs, partitioning, multiprocessors, random graphs, Theory of operating systems

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
19
Average
Top 10%
Top 10%
bronze