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Design of a Resource Management for GPGPU Supported Grid Computing

Yıl 2016, Cilt: 1 Sayı: 1, 39 - 49, 01.12.2016

Öz


In this study; we aimed to propose design of a QoS aware resource management
infrastructure for a GPGPU supported Grid computing system. This Grid system
consists of hybrid (CPU + CPU) and heterogeneous (Nvidia + AMD Radeon) GPGPU
computational nodes. It can manage both small scale unit (connections, threads,
buffer pools etc.) and large scale unit (whole computing machines). As
increasing of the network communication bandwidth and developing powerful
computer hardware (CPU, GPU etc.), distributed computing systems acquire more
and more attention day by day. Grid computing is as a major player in such kind
of distributed system environments like cloud, volunteer, hybrid and etc. Since
it supports large scale resource sharing between geographically distributed
computer clusters and even single computers. Nowadays, there is another
important technology pillar to implement high performance computing rather than
CPU, it is known as GPU computing. The GPU systems are ideal especially to data
intensive applications; such as image processing, data mining, financial
computations etc. Therefore, GPU based grids give an undertaking higher
computational performance. GPU processor consists of lots of controllable cores
which can be used for high performance demanded applications. Ultimately, the
major concerns in grid computing are particularly related to managing QoS
requirements, granularity of resources, and heterogeneous resources (both CPU
and GPU).  

Kaynakça

  • [1] S. Kounev, R. Nou, and J. Torres, Autonomic QoS-Aware resource management in grid computing using online performance models. the 2nd international conference on Performance evaluation methodologies and tools (ValueTools '07). ICST [Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering], ICST, Brussels, Belgium, Belgium, Article 48, 2007, 10 p.
  • [2] W. Cai, G. Coulson, P. Grace, G. Blair, L. Mathy, and W. K. Yeung, The Gridkit Distributed Resource Management Framework. European Grid Conference, EGC., Springer Verlag, 2005, pp. 786-796
  • [3] A. Younes, M. Essaaidi, A. El moussaoui, and A. Bendahmane, Grid computing middleware information systems: Review and synthesis study, Multimedia Computing and Systems, 2009. ICMCS '09. International Conference on, vol., no., pp.530-534, 2-4 April 2009B. Smith, “An approach to graphs of linear forms (Unpublished work style),” unpublished.
  • [4] T.-Y. Liang and Y.-W. Chang, GridCuda: A Grid-Enabled CUDA Programming Toolkit, Advanced Information Networking and Applications (WAINA), 2011 IEEE Workshops of International Conference on , vol., no., pp.141,146, 22-25 March 2011
  • [5] R. Buyya, D. Abramson, J. Giddy, Nimrod/G: an architecture for a resource management and scheduling system in a global computational grid, High Performance Computing in the Asia-Pacific Region, 2000. Proceedings. The Fourth International Conference/Exhibition on , vol.1, no., pp.283,289 vol.1, 14-17 May 2000
  • [6] J. Cao, S.A. Jarvis, S. Saini, G. R. Nudd, GridFlow: workflow management for grid computing, Cluster Computing and the Grid, 2003. Proceedings. CCGrid 2003. 3rd IEEE/ACM International Symposium on , vol., no., pp.198,205, 12-15 May 2003
  • [7] M. Murshed, and R. Buyya, Using GridSim Toolkit for Enabling Grid Computing Education, 2001
  • [8] V. Sahota, L. Maozhen, and G. Wenming, Resource Monitoring with Globus Toolkit 4, Semantics, Knowledge and Grid, 2006. SKG '06. Second International Conference on , vol., no., pp.79,79, 1-3 Nov. 2006
  • [9] H. Lee; D. Park; M. Hong; S. Yeo; S. Kim; Sk. Kim, "A Resource Management System for Fault Tolerance in Grid Computing," in Computational Science and Engineering, 2009. CSE '09. International Conference on , vol.2, no., pp.609-614, 29-31 Aug. 2009
  • [10] Z. Wei; L. Minghao; L. Jinxia; T. Yuanming; T. Ma, "Design and Implementation of National Meteorological Computing Resource Management System Based on Grid," in Information Science and Engineering (ICISE), 2009 1st International Conference on , vol., no., pp.182-185, 26-28 Dec. 2009
  • [11] M. Fukuda; Ngo Cuong; E. Mak; J. Morisaki,, "Resource Management and Monitoring in AgentTeamwork Grid Computing Middleware," in Communications, Computers and Signal Processing, 2007. PacRim 2007. IEEE Pacific Rim Conference on , vol., no., pp.145-148, 22-24 Aug. 2007
  • [12] F. Li; D. Qi; L. Zhang; X. Zhang; Z. Zhang, "Research on Novel Dynamic Resource Management and Job Scheduling in Grid Computing*," in Computer and Computational Sciences, 2006. IMSCCS '06. First International Multi-Symposiums on , vol.1, no., pp.709-713, 20-24 June 2006

Design of a Resource Management for GPGPU Supported Grid Computing

Yıl 2016, Cilt: 1 Sayı: 1, 39 - 49, 01.12.2016

Öz


In this study; we aimed to propose design of a QoS aware resource management
infrastructure for a GPGPU supported Grid computing system. This Grid system
consists of hybrid (CPU + CPU) and heterogeneous (Nvidia + AMD Radeon) GPGPU
computational nodes. It can manage both small scale unit (connections, threads,
buffer pools etc.) and large scale unit (whole computing machines). As
increasing of the network communication bandwidth and developing powerful
computer hardware (CPU, GPU etc.), distributed computing systems acquire more
and more attention day by day. Grid computing is as a major player in such kind
of distributed system environments like cloud, volunteer, hybrid and etc. Since
it supports large scale resource sharing between geographically distributed
computer clusters and even single computers. Nowadays, there is another
important technology pillar to implement high performance computing rather than
CPU, it is known as GPU computing. The GPU systems are ideal especially to data
intensive applications; such as image processing, data mining, financial
computations etc. Therefore, GPU based grids give an undertaking higher
computational performance. GPU processor consists of lots of controllable cores
which can be used for high performance demanded applications. Ultimately, the
major concerns in grid computing are particularly related to managing QoS
requirements, granularity of resources, and heterogeneous resources (both CPU
and GPU).  

Kaynakça

  • [1] S. Kounev, R. Nou, and J. Torres, Autonomic QoS-Aware resource management in grid computing using online performance models. the 2nd international conference on Performance evaluation methodologies and tools (ValueTools '07). ICST [Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering], ICST, Brussels, Belgium, Belgium, Article 48, 2007, 10 p.
  • [2] W. Cai, G. Coulson, P. Grace, G. Blair, L. Mathy, and W. K. Yeung, The Gridkit Distributed Resource Management Framework. European Grid Conference, EGC., Springer Verlag, 2005, pp. 786-796
  • [3] A. Younes, M. Essaaidi, A. El moussaoui, and A. Bendahmane, Grid computing middleware information systems: Review and synthesis study, Multimedia Computing and Systems, 2009. ICMCS '09. International Conference on, vol., no., pp.530-534, 2-4 April 2009B. Smith, “An approach to graphs of linear forms (Unpublished work style),” unpublished.
  • [4] T.-Y. Liang and Y.-W. Chang, GridCuda: A Grid-Enabled CUDA Programming Toolkit, Advanced Information Networking and Applications (WAINA), 2011 IEEE Workshops of International Conference on , vol., no., pp.141,146, 22-25 March 2011
  • [5] R. Buyya, D. Abramson, J. Giddy, Nimrod/G: an architecture for a resource management and scheduling system in a global computational grid, High Performance Computing in the Asia-Pacific Region, 2000. Proceedings. The Fourth International Conference/Exhibition on , vol.1, no., pp.283,289 vol.1, 14-17 May 2000
  • [6] J. Cao, S.A. Jarvis, S. Saini, G. R. Nudd, GridFlow: workflow management for grid computing, Cluster Computing and the Grid, 2003. Proceedings. CCGrid 2003. 3rd IEEE/ACM International Symposium on , vol., no., pp.198,205, 12-15 May 2003
  • [7] M. Murshed, and R. Buyya, Using GridSim Toolkit for Enabling Grid Computing Education, 2001
  • [8] V. Sahota, L. Maozhen, and G. Wenming, Resource Monitoring with Globus Toolkit 4, Semantics, Knowledge and Grid, 2006. SKG '06. Second International Conference on , vol., no., pp.79,79, 1-3 Nov. 2006
  • [9] H. Lee; D. Park; M. Hong; S. Yeo; S. Kim; Sk. Kim, "A Resource Management System for Fault Tolerance in Grid Computing," in Computational Science and Engineering, 2009. CSE '09. International Conference on , vol.2, no., pp.609-614, 29-31 Aug. 2009
  • [10] Z. Wei; L. Minghao; L. Jinxia; T. Yuanming; T. Ma, "Design and Implementation of National Meteorological Computing Resource Management System Based on Grid," in Information Science and Engineering (ICISE), 2009 1st International Conference on , vol., no., pp.182-185, 26-28 Dec. 2009
  • [11] M. Fukuda; Ngo Cuong; E. Mak; J. Morisaki,, "Resource Management and Monitoring in AgentTeamwork Grid Computing Middleware," in Communications, Computers and Signal Processing, 2007. PacRim 2007. IEEE Pacific Rim Conference on , vol., no., pp.145-148, 22-24 Aug. 2007
  • [12] F. Li; D. Qi; L. Zhang; X. Zhang; Z. Zhang, "Research on Novel Dynamic Resource Management and Job Scheduling in Grid Computing*," in Computer and Computational Sciences, 2006. IMSCCS '06. First International Multi-Symposiums on , vol.1, no., pp.709-713, 20-24 June 2006
Toplam 12 adet kaynakça vardır.

Ayrıntılar

Bölüm PAPERS
Yazarlar

Emrah Dönmez

Yayımlanma Tarihi 1 Aralık 2016
Gönderilme Tarihi 19 Nisan 2017
Kabul Tarihi 27 Ekim 2016
Yayımlandığı Sayı Yıl 2016 Cilt: 1 Sayı: 1

Kaynak Göster

APA Dönmez, E. (2016). Design of a Resource Management for GPGPU Supported Grid Computing. Computer Science, 1(1), 39-49.

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