Journal Article10.1007/BF02434039
Data partitioning for parallel solid modelling
Kin-Chuen Hui,Y. M. Kan +1 more
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TL;DR: This work presents a method for distributing entities of solid models in an array of processors for intersection tests in evaluating boolean operations, and employs distributed boundary representation and a recursive spatial subdivision technique for data partitioning.
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Abstract: Solid modelling involves processing large amounts of geometric data. Distributed processing is a promising technique for improving the speed of computationally intensive processes. Solid modelling is thus a good candidate for parallel processing. We present a method for distributing entities of solid models in an array of processors for intersection tests in evaluating boolean operations. We employ distributed boundary representation and a recursive spatial subdivision technique for data partitioning. Parallel algorithms distribute entities among the array of processors mapped to a set of 3D rectangular regions in the object space. Entities intersecting or residing in the intersection regions of the objects are distributed. An experimental system was implemented on a DECmpp 12000/Sx/8K distributed memory SIMD computer.
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Citations
Parallel Association Rule Mining for Medical Applications
G.G. Zhang,C.Z. Xu,P.C.-Y. Sheu,Hiroshi Yamaguchi +3 more
- 24 Oct 2011
TL;DR: A suite of algorithms called GAPCM for parallel processing of massive number of rules, considering even distribution, minimal waiting time and minimal inter-processor communication is proposed, and three algorithms for subnet allocation are proposed and applied to association rule mining.
6
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