By Topic

Automatic software interference detection in parallel applications

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)
Tabatabaee, V. ; University of Maryland at College Park ; Hollingsworth, J.K.

We present an automated software interference detection methodology for Single Program, Multiple Data (SPMD) parallel applications. Interference comes from the system and unexpected processes. If not detected and corrected such interference may result in performance degradation. Our goal is to provide a reliable metric for software interference that can be used in soft-failure protection and recovery systems. A unique feature of our algorithm is that we measure the relative timing of application events (i.e. time between MPI calls) rather than system level events such as CPU utilization. This approach lets our system automatically accommodate natural variations in an application's utilization of resources. We use performance irregularities and degradation as signs of software interference. However, instead of relying on temporal changes in performance, our system detects spatial performance degradation across multiple processors. We also include a case study that demonstrates our technique's effectiveness, resilience and robustness.

Published in:

Supercomputing, 2007. SC '07. Proceedings of the 2007 ACM/IEEE Conference on

Date of Conference:

10-16 Nov. 2007