Cost-efficient parallel processing of irregularly structured problems in cloud computing environments

  • In this paper, we deal with optimizing the monetary costs of executing parallel applications in cloud-based environments. Specifically, we investigate on how scalability characteristics of parallel applications impact the total costs of computations. We focus on a specific class of irregularly structured problems, where the scalability typically depends on the input data. Consequently, dynamic optimization methods are required for minimizing the costs of computation. For quantifying the total monetary costs of individual parallel computations, the paper presents a cost model that considers the costs for the parallel infrastructure employed as well as the costs caused by delayed results. We discuss a method for dynamically finding the number of processors for which the total costs based on our cost model are minimal. Our extensive experimental evaluation gives detailed insights into the performance characteristics of our approach.

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Metadaten
Name:Haußmann, Jens; Blochinger, Wolfgang
DOI:https://doi.org/10.1007/s10586-018-2879-3
ISSN:1386-7857
eISSN:1573-7543
Erschienen in:Cluster computing : the journal of networks, software tools and applications
Publisher:Springer Science + Business Media B.V.
Place of publication:Dordrecht
Document Type:Article
Language:English
Year of Publication:2019
Tag:cloud computing; cost model; high performance distributed computing; irregularly structured problems; parallel computing
Volume:22
Issue:3
Pagenumber:23
First Page:887
Last Page:909
Catalogue entry:Im Katalog der Hochschule Reutlingen ansehen
Dewey Decimal Classification:004 Informatik
Open Access:Nein
Licence (German):License Logo  Lizenzbedingungen Springer