OPTIMIZATION OF PERFORMANCE AND SCHEDULING OF HPC APPLICATIONS IN CLOUD USING CLOUDSIM AND SCHEDULING APPROACH

被引:0
|
作者
Muralitharan, D. Boobala [1 ]
Reebha, S. Arockia Babi [2 ]
Saravanan, D. [3 ]
机构
[1] Saranathan Coll Engn, Dept MCA, Tiruchirappalli, India
[2] PavendarBharathidasan Coll Engn & Technol, Dept Comp Sci & Engn, Tiruchirappalli, India
[3] PavendarBharathidasan Coll Engn & Technol, Tiruchirappalli, India
关键词
Cloud computing; High-Performance Computing (HPC); Job scheduling; CloudSim;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Cloud computing is emerging as a promising alternative to supercomputers for some High Performance Computing (HPC) applications. CloudcomputingisanessentialcomponentofthebackboneofiheInternetofThings(IoT).Cloudsareneededto supporthugenumbersofinteractionswithvaryingqualityrequirements Hence, Servicequalitywillhea vitaldifferentiatoramongcloudproviders.Inordertodifferentiatethemselvesfromtheircompetitors,cloudproviderss houldofferbestservicesthatmeetcustomers'expectations.Aquality modelcan heusedto represent,measureandcomparethequalityoftheproviders, suchthatamutualunderstandingcanbee stab lishedamongc loudstakeholders.With cloud as an additional deployment option, HPC users and providers faces the challenges of dealing with highly heterogeneous resources, where the variability spans across a wide range of processor configurations, interconnects, virtualization environments, and pricing models. HPC applications are increasingly being used in academia and laboratories for scientific research and in industries for business and analytics. Cloud computing offers the benefits of virtualization, elasticity of resources and elimination of cluster setup cost and time to HPC applications users. Effort was taken for holistic viewpoint to answer the questions - why and who should choose cloud for HPC, for what applications and how the cloud can be used for HPC? Comprehensive performance and cost evaluation and analysis of running a set of HPC applications on a range of platforms, varying from supercomputers to clouds was carried out. Further, performance of HPC applications is improved in cloud by optimizing HPC applications' characteristics for cloud and cloud virtualization mechanisms for HPC. In this paper, a novel heuristics for online application-aware job scheduling in multi platform environments is presented. Experimental results and Simulations using CloudSim show that current clouds cannot substitute supercomputers hut can effectively complement them.
引用
收藏
页数:5
相关论文
共 50 条
  • [1] Evaluating and Improving the Performance and Scheduling of HPC Applications in Cloud
    Gupta, Abhishek
    Faraboschi, Paolo
    Gioachin, Filippo
    Kale, Laxmikant V.
    Kaufmann, Richard
    Lee, Bu-Sung
    March, Verdi
    Milojicic, Dejan
    Suen, Chun Hui
    [J]. IEEE TRANSACTIONS ON CLOUD COMPUTING, 2016, 4 (03) : 307 - 321
  • [2] INVESTIGATION OF CLOUD SCHEDULING ALGORITHMS FOR RESOURCE UTILIZATION USING CLOUDSIM
    Hussain, Altaf
    Aleem, Muhammad
    Iqbal, Muhammad Azhar
    Islam, Muhammad Arshad
    [J]. COMPUTING AND INFORMATICS, 2019, 38 (03) : 525 - 554
  • [3] TPS: An Efficient VM Scheduling Algorithm for HPC Applications in Cloud
    Wang, Duoqiang
    Dai, Wei
    Zhang, Chi
    Shi, Xuanhua
    Jin, Hai
    [J]. GREEN, PERVASIVE, AND CLOUD COMPUTING (GPC 2017), 2017, 10232 : 152 - 164
  • [4] iCiRe: Optimal Scheduling of HPC Applications in Multi-Cloud
    Kulkarni, Rajesh
    Gameria, Pradeep
    Chahal, Dheeraj
    [J]. 16TH IEEE/ACM INTERNATIONAL CONFERENCE ON UTILITY AND CLOUD COMPUTING, UCC 2023, 2023,
  • [5] An Optimization Scheduling Approach for Cloud Computing
    Chen, Chih-Yung
    Tu, Jih-Fu
    Ou, Chien-Min
    [J]. JOURNAL OF INTERNET TECHNOLOGY, 2016, 17 (03): : 531 - 536
  • [6] Optimization of Performance and Scalability Measures across Cloud Based IoT Applications with Efficient Scheduling Approach
    Natarajan Nithiyanandam
    Manoharan Rajesh
    Ramachandran Sitharthan
    Dhanabalan Shanmuga Sundar
    Krishnasamy Vengatesan
    Karthikeyan Madurakavi
    [J]. International Journal of Wireless Information Networks, 2022, 29 : 442 - 453
  • [7] Optimization of Performance and Scalability Measures across Cloud Based IoT Applications with Efficient Scheduling Approach
    Natarajan, Nithiyanandam
    Manoharan, Rajesh
    Ramachandran, Sitharthan
    Dhanabalan, Shanmuga Sundar
    Krishnasamy, Vengatesan
    Karthikeyan, Madurakavi
    [J]. INTERNATIONAL JOURNAL OF WIRELESS INFORMATION NETWORKS, 2022, 29 (04) : 442 - 453
  • [8] CLOUDRB: A framework for scheduling and managing High-Performance Computing (HPC) applications in science cloud
    Somasundaram, Thamarai Selvi
    Govindarajan, Kannan
    [J]. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2014, 34 : 47 - 65
  • [9] An Efficient Scheduling of HPC Applications on Geographically Distributed Cloud Data Centers
    Rajabi, Aboozar
    Faragardi, Hamid Reza
    Nolte, Thomas
    [J]. COMPUTER NETWORKS AND DISTRIBUTED SYSTEMS, CNDS 2013, 2014, 428 : 155 - 167
  • [10] Improved Scheduling Algorithm In VCL Cloud Computing Environment On CloudSim
    Khedher, Omar
    Jarraya, Mohamed
    [J]. PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING & SIMULATION (HPCS 2015), 2015, : 254 - 261