Paper
9 October 2000 Dynamic load balancing of parallel cellular automata
Marc Mazzariol, Benoit A. Gennart, Roger David Hersch
Author Affiliations +
Abstract
We are interested in running in parallel cellular automata. We present an algorithm which explores the dynamic remapping of cells in order to balance the load between processing nodes. The parallel application runs on a cluster of PCs connected by Fast-Ethernet. A general cellular automaton can be described as a set of cells where each cell is a state machine. To compute the next cell state, each cell needs some information from neighbouring cells. There are no limitations on the kind of information exchanged nor on the computation itself. Only the automaton topology defining the neighbours of each cell remains unchanged during the automaton's life. As a typical example of cellular automation we consider the image skeletonization problem. Skeletonization requires spatial filtering to be repetitively applied to the image. Each step erodes a thin part of the original image. After the last step, only the image skeleton remains. Skeletonization algorithms require vast amounts of computing power, especially when applied to large images. Therefore, skeletonization application can potentially benefit from the use of parallel processing. Two different parallel alogorithms are proposed, one with a static load distribution consisting in splitting the cells over several processing nodes and the other with a dynamic load balancing scheme capable of remapping cells during the program execution. Performance measurements shows that the cell migration doesn't reduce the speedup if the program is already load balanced. It greatly improves the performance if the parallel application is not well balanced.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Marc Mazzariol, Benoit A. Gennart, and Roger David Hersch "Dynamic load balancing of parallel cellular automata", Proc. SPIE 4118, Parallel and Distributed Methods for Image Processing IV, (9 October 2000); https://doi.org/10.1117/12.403602
Lens.org Logo
CITATIONS
Cited by 9 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image processing

Image segmentation

Image filtering

Parallel processing

Spatial filters

Algorithm development

C++

RELATED CONTENT


Back to Top