By Topic

On finding optimal clusterings of task graphs

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

2 Author(s)
Lowe, W. ; Fakultat fur Inf., Karlsruhe Univ., Germany ; Zimmermann, W.

Currently, many parallel algorithms are defined for shared memory architectures. The preferred machine model is the PRAM, but this model does not take into account properties of existing architectures that have a distributed memory and an asynchronous execution model. A transformation of PRAM programs into distributed, asynchronous ones is known. In order to produce not only correct but also efficient code the tasks have to be clustered. We introduce a parallel algorithm producing an optimal clustering for coarse grained task graphs with respect to the execution time on an asynchronous distributed random access machine, the A-DRAM. This machine model assumes distributed memory, asynchronous execution of tasks, computation costs, and communication delay

Published in:

Parallel Algorithms/Architecture Synthesis, 1995. Proceedings., First Aizu International Symposium on

Date of Conference:

15-17 Mar 1995