Paper Info
Title
Factors affecting the performance of parallel mining of minimal unique itemsets on diverse architectures
Abstract
Three parallel implementations of a divide-and-conquer search algorithm (called SUDA2) for finding minimal unique itemsets (MUIs) are compared in this paper. The identification of MUIs is used by national statistics agencies for statistical disclosure assessment. The first parallel implementation adapts SUDA2 to a symmetric multi-processor cluster using the message passing interface (MPI), which we call an MPI cluster; the second optimizes the code for the Cray MTA2 (a shared-memory, multi-threaded architecture) and the third uses a heterogeneous ‘group’ of workstations connected by LAN. Each implementation considers the parallel structure of SUDA2, and how the subsearch computation times and sequence of subsearches affect load balancing. All three approaches scale with the number of processors, enabling SUDA2 to handle larger problems than before. For example, the MPI implementation is able to achieve nearly two orders of magnitude improvement with 132 processors. Performance results are given for a number of data sets. Copyright © 2009 John Wiley & Sons, Ltd.
Year
DOI
Venue
2009
10.1002/cpe.v21:9
Concurrency and Computation: Practice and Experience
Keywords
DocType
Volume
parallel implementation,MPI cluster,MPI implementation,parallel structure,symmetric multi-processor cluster,Cray MTA2,John Wiley,approaches scale,data set,divide-and-conquer search algorithm,diverse architecture,minimal unique itemsets,parallel mining
Journal
21
Issue
ISSN
Citations 
9
1532-0626
4
PageRank 
References 
Authors
0.47
27
7
Name
Order
Citations
PageRank
David J. Haglin111219.45
K. R. Mayes281.32
A. M. Manning3211.84
John Feo417721.16
John R. Gurd532353.83
M. J. Elliot6141.30
John A. Keane769592.81