Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

CiteULike is a free service for managing and discovering scholarly references - click here to get started.

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 HighWire
Right arrow Citing Articles via Web of Science (16)
Right arrow Citing Articles via Google Scholar
Right arrow Citing Articles via Scopus
Google Scholar
Right arrow Articles by Allen, G.
Right arrow Articles by Shalf, J.
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?

The Cactus Worm: Experiments with Dynamic Resource Discovery and Allocation in a Grid Environment

Gabrielle Allen

Max-Planck-Institute for Gravitational Physics

David Angulo

University of Chicago

Ian Foster

University of Chicago, Argonne National Laboratory

Gerd Lanfermann

Max-Planck-Institute for Gravitational Physics

Chuang Liu

University of Chicago

Thomas Radke

Max-Planck-Institute for Gravitational Physics

Ed Seidel

Max-Planck-Institute for Gravitational Physics

John Shalf

Lawrence Berkeley National Laboratory

The ability to harness heterogeneous, dynamically available grid resources is attractive to typically resource-starved computational scientists and engineers, as in principle it can increase, by significant factors, the number of cycles that can be delivered to applications. However, new adaptive application structures and dynamic runtime system mechanisms are required if we are to operate effectively in grid environments. To explore some of these issues in a practical setting, the authors are developing an experimental framework, called Cactus, that incorporates both adaptive application structures for dealing with changing resource characteristics and adaptive resource selection mechanisms that allow applications to change their resource allocations (e.g., via migration) when performance falls outside specified limits. The authors describe the adaptive resource selection mechanisms and describe how they are used to achieve automatic application migration to "better" resources following performance degradation. The results provide insights into the architectural structures required to support adaptive resource selection. In addition, the authors suggest that the Cactus Worm affords many opportunities for grid computing.

International Journal of High Performance Computing Applications, Vol. 15, No. 4, 345-358 (2001)
DOI: 10.1177/109434200101500402


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?


This article has been cited by other articles:


Home page
International Journal of High Performance Computing ApplicationsHome page
K. E. Maghraoui, T. J. Desell, B. K. Szymanski, and C. A. Varela
The Internet Operating System: Middleware for Adaptive Distributed Computing
International Journal of High Performance Computing Applications, November 1, 2006; 20(4): 467 - 480.
[Abstract] [PDF]


Home page
International Journal of High Performance Computing ApplicationsHome page
O. Sievert and H. Casanova
A Simple MPI Process Swapping Architecture for Iterative Applications
International Journal of High Performance Computing Applications, August 1, 2004; 18(3): 341 - 352.
[Abstract] [PDF]