Title
On partitioning and mapping for hypercube computing
Abstract
Designing efficient parallel algorithms in a message-based parallel computer should consider both time-space tradeoffs and computation-communication tradeoffs. In order to balance these tradeoffs and achieve the optimal performance of an algorith, one has to consider various design parameters such as the number of processors required and the size of partitions. In this paper, we demonstrate that, for certain data parallel algorithms, it is possible to determine these design parameters analytically. To serve as a basis for the discussions that follow, a simple model for the NCUBE hypercube computer is introduced. Using this model, we use two examples, array summation and matrix multiplication, to illustrate how their performance can be modeled. By optimizing these expressions, one is able to determine optimal design parameters which arrive at efficient execution. Experiments on a 64-node NCUBE verified the accuracy of the analytic results and are used to further support the discussions.
Year
DOI
Venue
1988
10.1007/BF01407815
International Journal of Parallel Programming
Keywords
Field
DocType
performance analysis,hypercube multiprocessors.,algorithm modeling,algorithm design,hypercube computing,parallel algorithms,Parallel algorithms,hypercube multiprocessors
Algorithmics,Algorithm design,Expression (mathematics),Computer science,Parallel algorithm,Parallel computing,Algorithm,Multiprocessing,Optimal design,Theoretical computer science,Matrix multiplication,Hypercube
Journal
Volume
Issue
ISSN
17
6
0885-7458
Citations 
PageRank 
References 
6
1.51
10
Authors
2
Name
Order
Citations
PageRank
Lionel M. Ni19462802.67
King CT282.23