By Topic

Dynamic Load Balancing for Unstructured Meshes on Space-Filling Curves

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

5 Author(s)
Harlacher, D.F. ; Appl. Supercomput. in Eng., RWTH Aachen Univ., Aachen, Germany ; Klimach, H. ; Roller, S. ; Siebert, C.
more authors

Load imbalance is an important impediment on the path towards higher degrees of parallelism - especially for engineering codes with their highly unstructured problem domains. In particular, when load conditions change dynamically, efficient mesh partitioning becomes an indispensable ingredient of scalable design. However, popular graph-based methods such as those used by ParMetis require global knowledge, which effectively limits the problem size on distributed-memory machines. On such architectures, space-filling curves (SFCs) offer a memory-efficient alternative and many sophisticated schemes have already been proposed. In this paper, we present a simple strategy based on SFCs that is custom-tailored to the needs of static meshes with dynamically changing computational load. Exploiting the properties of this class of problems, it is not only easy to implement but also reduces memory requirements substantially. Moreover, exclusively relying on MPI collective operations, our load-balancing scheme also offers portable performance across a broad range of HPC systems. Experimental evaluation shows excellent scaling behavior for up to 16,384 cores on a Nehalem-Infiniband system and up to 294,912 processes on a Blue Gene/P system.

Published in:

Parallel and Distributed Processing Symposium Workshops & PhD Forum (IPDPSW), 2012 IEEE 26th International

Date of Conference:

21-25 May 2012