Paper Info
Title
AnthillSched: a scheduling strategy for irregular and iterative I/O-intensive parallel jobs
Abstract
Irregular and iterative I/O-intensive jobs need a different approach from parallel job schedulers. The focus in this case is not only the processing requirements anymore: memory, network and storage capacity must all be considered in making a scheduling decision. Job executions are irregular and data dependent, alternating between CPU-bound and I/O-bound phases. In this paper, we propose and implement a parallel job scheduling strategy for such jobs, called AnthillSched, based on a simple heuristic: we map the behavior of a parallel application with minimal resources as we vary its input parameters. From that mapping we infer the best scheduling for a certain set of input parameters given the available resources. To test and verify AnthillSched we used logs obtained from a real system executing data mining jobs. Our main contributions are the implementation of a parallel job scheduling strategy in a real system and the performance analysis of AnthillSched, which allowed us to discard some other scheduling alternatives considered previously.
Year
DOI
Venue
2005
10.1007/11605300_5
JSSPP
Keywords
Field
DocType
data mining
Fair-share scheduling,I/O scheduling,Computer science,Flow shop scheduling,Two-level scheduling,Real-time computing,Job scheduler,Rate-monotonic scheduling,Dynamic priority scheduling,Round-robin scheduling,Distributed computing
Conference
Volume
ISSN
ISBN
3834
0302-9743
3-540-31024-X
Citations 
PageRank 
References 
3
0.39
23
Authors
8
Name
Order
Citations
PageRank
Luís Fabrício Wanderley Góes1448.41
Pedro Henrique Calais Guerra2182.62
Bruno Coutinho3714.66
Leonardo Rocha413910.85
Wagner Meira Jr52039188.06
R Ferreira661168.80
Dorgival Guedes720917.61
Cirne, Walfredo8139580.29