On partitioning and mapping for hypercube computing

Document Type

Article

Publication Date

12-1-1988

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. © 1988 Plenum Publishing Corporation.

Identifier

34250086152 (Scopus)

Publication Title

International Journal of Parallel Programming

External Full Text Location

https://doi.org/10.1007/BF01407815

e-ISSN

15737640

ISSN

08857458

First Page

475

Last Page

495

Issue

6

Volume

17

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