Performance evaluation of list based scheduling on heterogeneous systems

Authors:
Hamid Arabnejad;Jorge G. Barbosa
Affiliations:
Faculdade de Engenharia, Dep. de Engenharia Informática, Laboratório de Intelegência Artificial e Ciência dos Computadores, Universidade do Porto, Porto, Portugal;Faculdade de Engenharia, Dep. de Engenharia Informática, Laboratório de Intelegência Artificial e Ciência dos Computadores, Universidade do Porto, Porto, Portugal
Venue:
Euro-Par'11 Proceedings of the 2011 international conference on Parallel Processing
Year:
2011

Citing 10
Cited 0

Scheduling parallel program tasks onto arbitrary target machines

Journal of Parallel and Distributed Computing - Special issue: software tools for parallel programming and visualization
A two-pass scheduling algorithm for parallel programs

Parallel Computing
Dynamic Critical-Path Scheduling: An Effective Technique for Allocating Task Graphs to Multiprocessors

IEEE Transactions on Parallel and Distributed Systems
Characterization and Theoretical Comparison of Branch-and-Bound Algorithms for Permutation Problems

Journal of the ACM (JACM)
Ant algorithms for discrete optimization

Artificial Life
Static scheduling algorithms for allocating directed task graphs to multiprocessors

ACM Computing Surveys (CSUR)
Performance-Effective and Low-Complexity Task Scheduling for Heterogeneous Computing

IEEE Transactions on Parallel and Distributed Systems
An integrated technique for task matching and scheduling onto distributed heterogeneous computing systems

Journal of Parallel and Distributed Computing - Problems in parallel and distributed computing: Solutions based on evolutionary paradigms
A Comparison of General Approaches to Multiprocessor Scheduling

IPPS '97 Proceedings of the 11th International Symposium on Parallel Processing
Ant colony system: a cooperative learning approach to the traveling salesman problem

IEEE Transactions on Evolutionary Computation

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper addresses the problem of evaluating the schedules produced by list based scheduling algorithms, with metaheuristic algorithms. Task scheduling in heterogeneous systems is a NP-problem, therefore several heuristic approaches were proposed to solve it. These heuristics are categorized into several classes, such as list based, clustering and task duplication scheduling. Here we consider the list scheduling approach. The objective of this study is to assess the solutions obtained by list based algorithms to verify the space of improvement that new heuristics can have considering the solutions obtained with metaheuritcs that are higher time complexity approaches. We concluded that for a low Communication to Computation Ratio (CCR) of 0.1, the schedules given by the list scheduling approach is in average close to metaheuristic solutions. And for CCRs up to 1 the solutions are below 11% worse than the metaheuristic solutions, showing that it may not be worth to use higher complexity approaches and that the space to improve is narrow.