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Author Chang, C. S. ♦ Nelson, R.
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©1995
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Large deviations theory ♦ Synchronization
Abstract In this paper, we derive bounds on the speedup and efficiency of applications that schedule tasks on a set of parallel processors. We assume that the application runs an algorithm that consists of $\textit{N}$ iterations and before starting its $\textit{i}+1st$ iteration, a processor must wait for data (i.e., synchronize) calculated in the $\textit{i}th$ iteration by a subset of the other processors of the system. Processing times and interconnections between iterations are modeled by random variables with possibly deterministic distributions. Scientific applications consisting of iterations of recursive equations are examples of such applications that can be modeled within this formulation. We consider the efficiency of applications and show that, although efficiency decreases with an increase in the number of processors, it has a nonzero limit when the number of processors increases to infinity. We obtain a lower bound for the efficiency by solving an equation that depends on the distribution of task service times and the expected number of tasks needed to be synchronized. We also show that the lower bound is approached if the topology of the processor graph is ldquo;spread-out,” a notion we define in the paper.
ISSN 00045411
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 1995-01-03
Publisher Place New York
e-ISSN 1557735X
Journal Journal of the ACM (JACM)
Volume Number 42
Issue Number 1
Page Count 28
Starting Page 204
Ending Page 231


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Source: ACM Digital Library