Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

Click here to sign up for SAGE Journal Email Alerts today!

Sign In to gain access to subscriptions and/or personal tools.
International Journal of High Performance Computing Applications
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in Web of Science
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via Google Scholar
Right arrow Citing Articles via Scopus
Google Scholar
Right arrow Articles by Ghan, S.
Right arrow Articles by Shippert, T.
Right arrow Search for Related Content
Social Bookmarking
Add to CiteULike   Add to Complore   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati   Add to Twitter  
What's this?

Load Balancing and Scalability of a Subgrid Orography Scheme in a Global Climate Model

Steven Ghan

Pacific Northwest National Laboratory Richland, WA 99352, USA, steve.ghan{at}pnl.gov

Timothy Shippert

Pacific Northwest National Laboratory Richland, WA 99352, USA

A subgrid orography scheme has been applied to the National Center for Atmospheric Research Community Atmosphere Model. The scheme applies all of the model column physics to each of up to 11 elevation classes within each grid cell. The distribution of the number of elevation classes in each grid cell is highly inhomogeneous. This could produce a serious load imbalance if the domain decomposition distributes grid cells evenly across processors. However, since the distribution of classes is static, static load balancing can be used to distribute the elevation classes uniformly across processors. The load balancing is accomplished first by distributing the number of classes evenly within each process. The number of chunks on processes is distributed uniformly across processes and the dynamics-physics transpose cost is minimized by assigning chunks to processes with the most dynamics grid cells from that chunk. Parallel efficiency with the subgrid scheme and load balancing exceeds parallel efficiency without the subgrid scheme for up to 128 processors. The load balancing across processes decreases run-time by 10-30% depending on configuration.

Key Words: Climate model • load balancing • subgrid orography

International Journal of High Performance Computing Applications, Vol. 19, No. 3, 237-245 (2005)
DOI: 10.1177/1094342005056112
Add to CiteULike CiteULike   Add to Complore Complore   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati   Add to Twitter Twitter    What's this?