A survey on resource allocation in high performance distributed computing systems |
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| Authors: | Hameed Hussain Saif Ur Rehman Malik Abdul Hameed Samee Ullah Khan Gage Bickler Nasro Min-Allah Muhammad Bilal Qureshi Limin Zhang Wang Yongji Nasir Ghani Joanna Kolodziej Albert Y Zomaya Cheng-Zhong Xu Pavan Balaji Abhinav Vishnu Fredric Pinel Johnatan E Pecero Dzmitry Kliazovich Pascal Bouvry Hongxiang Li Lizhe Wang Dan Chen Ammar Rayes |
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| Affiliation: | 1. COMSATS Institute of Information Technology, Islamabad 44000, Pakistan;2. North Dakota State University, Fargo, ND, USA;3. Institute of Software, Chinese Academy of Sciences, Beijing, China;4. University of South Florida, Tampa, Florida 33620-5399, USA;5. Cracow University of Technology, Cracow, Poland;6. University of Sydney, Sydney, NSW, Australia;g Wayne State University, Detroit, MI, USA;h Argonne National Laboratory, Argonne, IL, USA;i Pacific Northwest National Laboratory, Richland, WA, USA;j University of Luxembourg, Coudenhove-Kalergi, L1359, Luxembourg;k University of Louisville, Louisville, KY, USA;l Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, Beijing, China;m China University of Geosciences, Wuhan, China;n CISCO Systems, San Jose, CA, USA |
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| Abstract: | An efficient resource allocation is a fundamental requirement in high performance computing (HPC) systems. Many projects are dedicated to large-scale distributed computing systems that have designed and developed resource allocation mechanisms with a variety of architectures and services. In our study, through analysis, a comprehensive survey for describing resource allocation in various HPCs is reported. The aim of the work is to aggregate under a joint framework, the existing solutions for HPC to provide a thorough analysis and characteristics of the resource management and allocation strategies. Resource allocation mechanisms and strategies play a vital role towards the performance improvement of all the HPCs classifications. Therefore, a comprehensive discussion of widely used resource allocation strategies deployed in HPC environment is required, which is one of the motivations of this survey. Moreover, we have classified the HPC systems into three broad categories, namely: (a) cluster, (b) grid, and (c) cloud systems and define the characteristics of each class by extracting sets of common attributes. All of the aforementioned systems are cataloged into pure software and hybrid/hardware solutions. The system classification is used to identify approaches followed by the implementation of existing resource allocation strategies that are widely presented in the literature. |
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| Keywords: | Scheduling Resource allocation Resource management |
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