By Topic

An approach to mapping parallel programs on hypercube multiprocessors

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Jose, A. ; Fac. de Ingenieria, Los Andes Univ., Merida, Venezuela

In this work, we propose a heuristic algorithm based on genetic algorithm for the task-to-processor mapping problem in the context of local-memory multiprocessors with a hypercube interconnection topology. Hyper-cube multiprocessors have offered a cost effective and feasible approach to supercomputing through parallelism at the processor level by directly connecting a large number of low-cost processors with local memory which communicate by message passing instead of shared variables. We use concepts of the graph theory (task graph precedence to represent parallel programs, graph partitioning to solve the program decomposition problem, etc.) to model the problem. This problem is NP-complete which means heuristic approaches must be adopted. We develop a heuristic algorithm based on genetic algorithms to solve it

Published in:

Parallel and Distributed Processing, 1999. PDP '99. Proceedings of the Seventh Euromicro Workshop on

Date of Conference:

3-5 Feb 1999