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QoS Oriented Enhancement based on the Analysis of Dynamic Job Scheduling in HPC

QoS Oriented Enhancement based on the Analysis of Dynamic Job Scheduling in HPC

Reshmi Raveendran, D. Shanthi Saravanan
Copyright: © 2014 |Volume: 6 |Issue: 4 |Pages: 18
ISSN: 1938-0259|EISSN: 1938-0267|EISBN13: 9781466654464|DOI: 10.4018/IJGHPC.2014100103
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MLA

Raveendran, Reshmi, and D. Shanthi Saravanan. "QoS Oriented Enhancement based on the Analysis of Dynamic Job Scheduling in HPC." IJGHPC vol.6, no.4 2014: pp.28-45. http://doi.org/10.4018/IJGHPC.2014100103

APA

Raveendran, R. & Saravanan, D. S. (2014). QoS Oriented Enhancement based on the Analysis of Dynamic Job Scheduling in HPC. International Journal of Grid and High Performance Computing (IJGHPC), 6(4), 28-45. http://doi.org/10.4018/IJGHPC.2014100103

Chicago

Raveendran, Reshmi, and D. Shanthi Saravanan. "QoS Oriented Enhancement based on the Analysis of Dynamic Job Scheduling in HPC," International Journal of Grid and High Performance Computing (IJGHPC) 6, no.4: 28-45. http://doi.org/10.4018/IJGHPC.2014100103

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Abstract

With the advent of High Performance Computing (HPC) in the large-scale parallel computational environment, better job scheduling and resource allocation techniques are required to deliver Quality of Service (QoS). Therefore, job scheduling on a large-scale parallel system has been studied to minimize the queue time, response time, and to maximize the overall system utilization. The objective of this paper is to touch upon the recent methods used for dynamic resource allocation across multiple computing nodes and the impact of scheduling algorithms. In addition, a quantitative approach which explains a trend line analysis on dynamic allocation for batch processors is depicted. Throughout the survey, the trends in research on dynamic allocation and parallel computing is identified, besides, highlights the potential areas for future research and development. This study proposes the design for an efficient dynamic scheduling algorithm based on the Quality-of-Service. The analysis provides a compelling research platform to optimize dynamic scheduling of jobs in HPC.

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