NDLI: Assessing the impact and limits of steady-state scheduling for mixed task and data parallelism on heterogeneous platforms

Content Provider	IEEE Xplore Digital Library
Author	Beaumont, O. Legrand, A. Marchal, L. Robert, Y.
Copyright Year	2004
Description	Author affiliation: LaBRI, UMR CNRS, Bordeaux, France (Beaumont, O.)
Abstract	In this paper, we consider steady-state scheduling techniques for mapping a collection of task graphs onto heterogeneous systems, such as clusters and grids. We advocate the use of steady-state scheduling to solve this difficult problem. Due to space limitations, we concentrate on complexity results. We show that the problem of optimizing the steady-state throughput is NP-complete in the general case. We formulate a compact version of the problem that belongs to the NP complexity class but which does not restrict the optimality of the solution. We provide many positive results in the extended version (Beaumont et al., 2004). Indeed, we show how to determine in polynomial time the best steady-state scheduling strategy for a large class of application graphs and for an arbitrary platform graphs, using a linear programming approach.
Sponsorship	Enterprise Ireland and Univ. Coll. Cork
Starting Page	296
Ending Page	302
File Size	215717
Page Count	7
File Format	PDF
ISBN	0769522106
DOI	10.1109/ISPDC.2004.12
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-07-07
Publisher Place	Ireland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Steady-state Optimal scheduling Processor scheduling Parallel processing Polynomials Grid computing Computer applications Throughput Linear programming Scheduling algorithm
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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Assessing the impact and limits of steady-state scheduling for mixed task and data parallelism on heterogeneous platforms (2004).

Assessing the impact and limits of steady-state scheduling for mixed task and data parallelism on heterogeneous platforms (2004)

Assessing the impact and limits of steady-state scheduling for mixed task and data parallelism on heterogeneous platforms (2004)

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