NDLI: Market-inspired dynamic resource allocation in many-core high performance computing systems

Content Provider	IEEE Xplore Digital Library
Author	Singh, A.K. Dziurzanski, P. Indrusiak, L.S.
Copyright Year	2015
Description	Author affiliation: Dept. of Comput. Sci., Univ. of York, York, UK (Singh, A.K.; Dziurzanski, P.; Indrusiak, L.S.)
Abstract	Many-core systems are envisioned to fulfill the increased performance demands in several computing domains such as embedded and high performance computing (HPC). The HPC systems are often overloaded to execute a number of dynamically arriving jobs. In overload situations, market-inspired resource allocation heuristics have been found to provide better results in terms of overall profit (value) earned by completing the execution of a number of jobs when compared to various other heuristics. However, the conventional market-inspired heuristics lack the concept of holding low value executing jobs to free the occupied resources to be used by high value arrived jobs in order to maximize the overall profit. In this paper, we propose a market-inspired heuristic that accomplish the aforementioned concept and utilizes design-time profiling results of jobs to facilitate efficient allocation. Additionally, the remaining executions of the held jobs are performed on freed resources at later stages to make some profit out of them. The holding process identifies the appropriate jobs to be put on hold to free the resources and ensures that the loss incurred due to holding is lower than the profit achieved by high value arrived jobs by using the free resources. Experiments show that the proposed approach achieves 8% higher savings when compared to existing approaches, which can be a significant amount when dealing in the order of millions of dollars.
Starting Page	413
Ending Page	420
File Size	931392
Page Count	8
File Format	PDF
ISBN	9781467378123
e-ISBN	9781467378130
DOI	10.1109/HPCSim.2015.7237070
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-20
Publisher Place	Netherlands
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	High Performance Computing High performance computing Biological system modeling Heuristic algorithms Many-core Resource allocation Value curves Dynamic scheduling Profit Resource management Time factors Genetic algorithms
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
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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