Thumbnail
Access Restriction
Subscribed

Author Lubachevsky, Boris ♦ Mitra, Debasis
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©1986
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Abstract Given a nonnegative, irreducible matrix P of spectral radius unity, there exists a positive vector π such that π = πP. If P also happens to be stochastic, then π gives the stationary distribution of the Markov chain that has state-transition probabilities given by the elements of P. This paper gives an algorithm for computing π that is particularly well suited for parallel processing. The main attraction of our algorithm is that the timing and sequencing restrictions on individual processors are almost entirely eliminated and, consequently, the necessary coordination between processors is negligible and the enforced idle time is also negligible.Under certain mild and easily satisfied restrictions on P and on the implementation of the algorithm, x(.), the vectors of computed values are proved to converge to within a positive, finite constant of proportionality of π. It is also proved that a natural measure of the $\textit{projective}$ distance of x(.) from π vanishes geometrically fast, and at a rate for which a lower bound is given. We have conducted extensive experiments on random matrices P, and the results show that the improvement over the parallel implementation of the synchronous version of the algorithm is substantial, sometimes exceeding the synchronization penalty to which the latter is always subject.
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 1986-01-02
Publisher Place New York
e-ISSN 1557735X
Journal Journal of the ACM (JACM)
Volume Number 33
Issue Number 1
Page Count 21
Starting Page 130
Ending Page 150


Open content in new tab

   Open content in new tab
Source: ACM Digital Library