Cart (Loading....) | Create Account
Close category search window
 

Low overhead high performance runtime monitoring of collective communication

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)
Bongo, L.A. ; Dept. of Comput. Sci., Tromso Univ., Norway ; Anshus, O.J. ; Bjoerndalen, J.M.

Scalability of parallel applications on clusters and multi-clusters is often limited by communication performance. Message tracing can provide data for understanding bottlenecks, and for performance tuning. However, it requires collecting, storing, analyzing, and transferring potentially gigabytes of data. We have designed the EventSpace system for low overhead and high performance runtime collective communication trace analysis. EventSpace separates the perturbation and performance requirements of data collection, analysis, gathering sand visualization. Data collection overhead is low since the minimum amount of data is recorded and stored temporarily in main memory. The recorded data is either discarded or analyzed on demand using available cluster resources. Analysis is distributed for high performance, and coscheduled with the computation and communication system threads for low perturbation. Gathering of analyzed data is done using extensible collective communication operations, which can be tuned to trade off between performance and monitoring overhead. EventSpace was used to do run-time monitoring and analysis of collective communication micro-benchmarks run on clusters, multi-clusters, and multi-clusters with emulated WAN links. Performance data was collected, analyzed and gathered with 0-3% monitoring overhead.

Published in:

Parallel Processing, 2005. ICPP 2005. International Conference on

Date of Conference:

14-17 June 2005

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.