By Topic

A comparison of techniques used for mapping parallel algorithms to message-passing 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

3 Author(s)
Dikaiakos, M.D. ; Dept. of Astron., Washington Univ., Seattle, WA, USA ; Steiglitz, K. ; Rogers, A.

This paper presents a comparison study of popular clustering and mapping heuristics which are used to map task-flow graphs to message-passing multiprocessors. To this end, we use task-graphs which are representative of important scientific algorithms running on data-sets of practical interest. The annotation which assigns weights to nodes and edges of the task-graphs is realistic. It reflects current trends in processor, communication channel, and message-passing interface technology and takes into consideration hardware characteristics of state-of-the-art multiprocessors. Our experiments show that applying realistic models for task-graph annotation affects the effectiveness and functionality of clustering and mapping techniques. Therefore, new heuristics are necessary that will take into account more practical models of communication costs. We present modifications to existing clustering and mapping algorithms which improve their efficiency and running-time for the practical models adopted

Published in:

Parallel and Distributed Processing, 1994. Proceedings. Sixth IEEE Symposium on

Date of Conference:

26-29 Oct 1994