Fast and efficient parallel coarsest refinement

The process of merging two arbitrary partitions of a given finite set U of n elements is known as coarsest refinement. In the COARSEST REFINEMENT PROBLEM we are given two arbitrary partitions X;Y of the set U such that X = fX1;X2; : : : ;Xxg and Y = fY1;Y2; : : : ;Yyg, and determine a new partition...

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Main Authors: Nopadon Juneam, Sanpawat Kantabutra
Format: Journal
Published: 2018
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http://cmuir.cmu.ac.th/jspui/handle/6653943832/57144
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-571442018-09-05T03:45:17Z Fast and efficient parallel coarsest refinement Nopadon Juneam Sanpawat Kantabutra Computer Science Mathematics The process of merging two arbitrary partitions of a given finite set U of n elements is known as coarsest refinement. In the COARSEST REFINEMENT PROBLEM we are given two arbitrary partitions X;Y of the set U such that X = fX1;X2; : : : ;Xxg and Y = fY1;Y2; : : : ;Yyg, and determine a new partition Z = fZ1;Z2; : : : ;Zzg such that each Zc 2 Z is a common non-empty subset of some Xa 2 X and some Yb 2 Y and jZj is as small as possible. This article describes a resource-efficient parallel algorithm to solve this problem. More specifically, we show that a coarsest refinement can be computed in O(t(n) + log n) parallel time using maxf n log n; p(n)g processors, where t(n) denotes the running time of a parallel stable sorting algorithm that uses p(n) processors on an EREW PRAM. This result depends on t(n) and p(n). We give a table that shows the best known time and processor complexities for a parallel stable sorting algorithm. If the parallel stable sorting algorithms by Ajtai et al., Cole, and Leighton are used, the coarsest refinement can be computed in O(log n) parallel time using n processors on an EREW PRAM. On the other hand, if the parallel stable sorting algorithm by Bahig et al. is used, the coarsest refinement can be computed in O(log n log( n log n)) parallel time using n log n processors on an EREW PRAM. In addition, we show that on, a RAM machine, our parallel algorithm runs as asymptotically efficient as the fastest known sequential algorithm. 2018-09-05T03:35:28Z 2018-09-05T03:35:28Z 2017-01-01 Journal 01692968 2-s2.0-85014593240 10.3233/FI-2017-1465 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85014593240&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/57144
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
topic Computer Science
Mathematics
spellingShingle Computer Science
Mathematics
Nopadon Juneam
Sanpawat Kantabutra
Fast and efficient parallel coarsest refinement
description The process of merging two arbitrary partitions of a given finite set U of n elements is known as coarsest refinement. In the COARSEST REFINEMENT PROBLEM we are given two arbitrary partitions X;Y of the set U such that X = fX1;X2; : : : ;Xxg and Y = fY1;Y2; : : : ;Yyg, and determine a new partition Z = fZ1;Z2; : : : ;Zzg such that each Zc 2 Z is a common non-empty subset of some Xa 2 X and some Yb 2 Y and jZj is as small as possible. This article describes a resource-efficient parallel algorithm to solve this problem. More specifically, we show that a coarsest refinement can be computed in O(t(n) + log n) parallel time using maxf n log n; p(n)g processors, where t(n) denotes the running time of a parallel stable sorting algorithm that uses p(n) processors on an EREW PRAM. This result depends on t(n) and p(n). We give a table that shows the best known time and processor complexities for a parallel stable sorting algorithm. If the parallel stable sorting algorithms by Ajtai et al., Cole, and Leighton are used, the coarsest refinement can be computed in O(log n) parallel time using n processors on an EREW PRAM. On the other hand, if the parallel stable sorting algorithm by Bahig et al. is used, the coarsest refinement can be computed in O(log n log( n log n)) parallel time using n log n processors on an EREW PRAM. In addition, we show that on, a RAM machine, our parallel algorithm runs as asymptotically efficient as the fastest known sequential algorithm.
format Journal
author Nopadon Juneam
Sanpawat Kantabutra
author_facet Nopadon Juneam
Sanpawat Kantabutra
author_sort Nopadon Juneam
title Fast and efficient parallel coarsest refinement
title_short Fast and efficient parallel coarsest refinement
title_full Fast and efficient parallel coarsest refinement
title_fullStr Fast and efficient parallel coarsest refinement
title_full_unstemmed Fast and efficient parallel coarsest refinement
title_sort fast and efficient parallel coarsest refinement
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85014593240&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/57144
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