Scheduled System Maintenance:
Some services will be unavailable Sunday, March 29th through Monday, March 30th. We apologize for the inconvenience.
By Topic

Work Stealing on Hybrid Architectures

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)
Pinto, V.G. ; Parallel & Distrib. Process. Group (GPPD), Fed. Univ. of Rio Grande do Sul (UFRGS), Porto Alegre, Brazil ; Maillard, N.

Parallel computing systems have been based on multicore CPUs and specialized coprocessors, like GPUs. Work-stealing is a scheduling technique that has been used to distribute and redistribute the workload among resources in an efficient way. This work aims to propose, implement and validate a scheduling approach based on work stealing in parallel systems with CPUs and GPUs simultaneously. Results show that our approach, called WORMS, presents competitive performance when compared to reference tool for multicore CPUs (Cilk). In hybrid scenario, WORMS with multicore+GPU outperforms WORMS and Cilk with multicore only and also the GPU reference tool (Thrust).

Published in:

Computer Systems (WSCAD-SSC), 2012 13th Symposium on

Date of Conference:

17-19 Oct. 2012