By Topic

Robust resource allocation of DAGs in a heterogeneous multicore system

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
$33 $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

9 Author(s)
Luis Diego Briceño ; Colorado State University, Department of Electrical and Computer Engineering, USA ; Jay Smith ; Howard Jay Siegel ; Anthony A. Maciejewski
more authors

In this study, we consider an environment composed of a heterogeneous cluster of multicore-based machines used to analyze satellite images. The workload involves large data sets, and is typically subject to deadline constraints. Multiple applications, each represented by a directed acyclic graph (DAG), are allocated to a dedicated heterogeneous distributed computing system. Each vertex in the DAG represents a task that needs to be executed and task execution times vary substantially across machines. The goal of this research is to assign applications to multicore-based parallel system in such a way that all applications complete before a common deadline, and their completion times are robust against uncertainties in execution times. We define a measure that quantifies robustness in this environment. We design, compare, and evaluate two resource allocation heuristics that attempt to maximize robustness.

Published in:

Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW), 2010 IEEE International Symposium on

Date of Conference:

19-23 April 2010