Many-objective performance enhancement in computing clusters

In a heterogeneous computing cluster, cluster objectives are conflicting to each other. Selecting a right combination of machines is necessary to enhance cluster performance, and to optimize all the cluster objectives. In this paper, we perform empirical performance analyses of a real cluster with o...

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Bibliographic Details
Main Authors: Rizvi, Asm, Toha, Tarik Reza, Das, Siddhartha Shankar, Chellappan, Sriram, Alim Al Islam, A. B. M.
Format: Conference Proceeding
Language:English
Subjects:
Algorithm design and analysis
Cloud computing
Clustering algorithms
Computer science
Cooling
Energy consumption
Optimization
Online Access:Request full text
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Summary:In a heterogeneous computing cluster, cluster objectives are conflicting to each other. Selecting a right combination of machines is necessary to enhance cluster performance, and to optimize all the cluster objectives. In this paper, we perform empirical performance analyses of a real cluster with our year-long collected data, formulate a new many-objective optimization problem for clusters, and integrate a greedy approach with the existing NSGA-III algorithm to solve this problem. From our experimental results, we find our approach performs better than existing optimization approaches.
ISSN:2374-9628
DOI:10.1109/PCCC.2017.8280491