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 struc...

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Bibliographic Details
Published in:Cluster computing Vol. 22; no. 3; pp. 887 - 909
Main Authors: Haussmann, Jens, Blochinger, Wolfgang, Kuechlin, Wolfgang
Format: Journal Article
Language:English
Published: New York Springer US 01.09.2019
Springer Nature B.V
Subjects:
Cloud computing
Communication
Computer Communication Networks
Computer Science
Costs
Decomposition
Operating Systems
Optimization
Parallel processing
Processor Architectures
Utility computing
Cloud computing
Parallel computing
Irregularly structured problems
Cost model
High performance distributed computing
ISSN:1386-7857, 1573-7543
Online Access:Get full text
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Summary: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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ISSN:1386-7857
1573-7543
DOI:10.1007/s10586-018-2879-3