By Topic

A Hybrid CPU-GPU Local Search Heuristic for the Unrelated Parallel Machine Scheduling Problem

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

5 Author(s)
Igor Machado Coelho ; Inst. of Comput. Fluminense, Fed. Univ., Niteroi, Brazil ; Matheus Nohra Haddad ; Luiz Satoru Ochi ; Marcone Jamilson Freitas Souza
more authors

This work addresses the development of a hybrid CPU-GPU local search heuristic for the unrelated parallel machine scheduling problem. In this scheduling problem setup times are sequence-dependent and also machine-dependent. The objective is to minimize the maximum completion time of the schedule, known as make span. Since the problem belongs to the NP-hard class there is no known polynomial time algorithm to solve it, so metaheuristics and local search heuristics are usually developed to find good near optimal solutions. In general, the local search is the most expensive part of the heuristic method, so our algorithm harnesses the tremendous computing power of the GPU to decrease the local search computational time. We use the local search based on swapping jobs in different machines, since it is able find good near optimal solutions as we report from previous results in literature. We show that the hybrid CPU-GPU local search achieves average speedups from 10 to 27 times in relation to the pure CPU local search.

Published in:

Applications for Multi-Core Architectures (WAMCA), 2012 Third Workshop on

Date of Conference:

24-25 Oct. 2012