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Case Study Report Presentation




Grid computing: The Grid
                   (Mar 05, 2013)

    By
    Jivan Nepali, 066 BCT 517
    Laxmi Kadariya, 066 BCT 518
    Narayan Pd. Kandel, 066 BCT 520
IS There Any Computer System
that isn’t a Grid?

          Bio            Data    Knowledge
         Grids           Grids   Grids


   Commodity   Compute       Science
       Grids   Grids          Grids


         Cluster         Tera    Sensor
          Grids          Grids   Grids
Definitions
 “A computational grid is a hardware and software
 infrastructure     that     provides     dependable,
 consistent, pervasive, and inexpensive access to
 high-end computational capabilities.”
                    – Foster & Kesselman, 1998
 “Grid computing is concerned with coordinated
 resource sharing and problem solving in dynamic,
 multi-institutional virtual organizations (VOs).”
                   - Foster & Tuecke, 2000

               It is NOT a cluster Architecture!
Grid: Building Blocks
 Networks
 Link together geographically distributed resources and
  allow them to be used collectively
 Computational ‘Nodes’ on the Grid
 Networks connect resources on the Grid –
  computational resources with data storage
 Pulling it together
 It involves the coordination and partnerships among
  the remaining blocks for the complete model of a Grid
 Common Infrastructure: Standards
 Grid Standards to developers & users
 Standards on which the Grid is being built
Grid Computing: Architectural
Model
  Hourglass Model
  Thin center: few standards                Application Layer

  Wide top: many high-level
                                              Collective Layer
    behaviors can be mapped
  Wide bottom: many underlying
                              Connectivity Layer            Resource Layer
    technologies and systems

                                                     Fabric Layer
Grid Models
 Distributed Super-Computing
    Aggregate computational resources to tackle problems that cannot
     be solved by a single system
 High-throughput Computing
    Schedule large numbers of independent tasks to exploit unused
     CPU cycles
 On-demand Computing
    Use Grid capabilities to meet short-term requirements for
     resources that cannot conveniently be located locally
 Data-Intensive Computing
    Synthesize data in geographically distributed repositories
 Collaborative Computing
    Enable shared use of data archives and simulations
Grid Computing: Challenges
 No clear Standard
 Debate on Concept
 Difficult to Develop
 Limited area & Applications
 Lack of Grid-enabled Software
 Centralized Management
 Security
 Management and Administration
Grid Computing: Applications
 Life Science Application
    Computational biology, bioinformatics, genomics,
     computational neuroscience
    e.g. the Protein Data Bank, the myGrid Project, the
     Biomedical Information Research Network (BIRN),
     MCell].
 Engineering-oriented Application
    NASA operation its research through grid
 Data-oriented Application
    Data is emerging as the ‘killer application’ of the Grid.
    e.g. Distributed Aircraft Maintenance Environment
     (DAME).
Grid Computing: Applications
Cont...
  Physical Science Application
     The National Virtual Observatory Project in the United States
      is using the Grid to federate sky surveys from several
      different telescopes
  Commercial Application
           Virtual server hosting,
           Disaster recovery,
           Heterogeneous workload management,
           End-to-end systems management,
           End-to-end automation
           Reducing up-front investment
           Accessing new capability more quickly,
           Better performance
References
[1] Foster, I. & Kesselman C. (2005). “The Grid in a
Nutshell”. Mathematics and Computer Science Division,
Argonne National Laboratory, Information Sciences
Institute, University of Southern California, USA.
[2] Engelen van R. (2008). “Concepts & Architecture of
Grid Computing”. Leiden University, Netherlands.
[3] Berman F., Hey A.J.G. & Fox G.C. (2003). “Grid
Computing – Making the Global Infrastructure a
Reality”. John Wiley & Sons Ltd, Chichester, England.
[4] Abbas A. (2004). “Grid Computing: A Practical Guide
to Technology & Applications”. Firewall Media, An
Imprint of Laxmi Publications Pvt. Ltd., Golden House,
Daryaganj, New Delhi, India.
Thank You!

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Grid computing the grid

  • 1. Case Study Report Presentation Grid computing: The Grid (Mar 05, 2013) By Jivan Nepali, 066 BCT 517 Laxmi Kadariya, 066 BCT 518 Narayan Pd. Kandel, 066 BCT 520
  • 2. IS There Any Computer System that isn’t a Grid? Bio Data Knowledge Grids Grids Grids Commodity Compute Science Grids Grids Grids Cluster Tera Sensor Grids Grids Grids
  • 3. Definitions  “A computational grid is a hardware and software infrastructure that provides dependable, consistent, pervasive, and inexpensive access to high-end computational capabilities.” – Foster & Kesselman, 1998  “Grid computing is concerned with coordinated resource sharing and problem solving in dynamic, multi-institutional virtual organizations (VOs).” - Foster & Tuecke, 2000 It is NOT a cluster Architecture!
  • 4. Grid: Building Blocks  Networks  Link together geographically distributed resources and allow them to be used collectively  Computational ‘Nodes’ on the Grid  Networks connect resources on the Grid – computational resources with data storage  Pulling it together  It involves the coordination and partnerships among the remaining blocks for the complete model of a Grid  Common Infrastructure: Standards  Grid Standards to developers & users  Standards on which the Grid is being built
  • 5. Grid Computing: Architectural Model  Hourglass Model  Thin center: few standards Application Layer  Wide top: many high-level Collective Layer behaviors can be mapped  Wide bottom: many underlying Connectivity Layer Resource Layer technologies and systems Fabric Layer
  • 6. Grid Models  Distributed Super-Computing  Aggregate computational resources to tackle problems that cannot be solved by a single system  High-throughput Computing  Schedule large numbers of independent tasks to exploit unused CPU cycles  On-demand Computing  Use Grid capabilities to meet short-term requirements for resources that cannot conveniently be located locally  Data-Intensive Computing  Synthesize data in geographically distributed repositories  Collaborative Computing  Enable shared use of data archives and simulations
  • 7. Grid Computing: Challenges  No clear Standard  Debate on Concept  Difficult to Develop  Limited area & Applications  Lack of Grid-enabled Software  Centralized Management  Security  Management and Administration
  • 8. Grid Computing: Applications  Life Science Application  Computational biology, bioinformatics, genomics, computational neuroscience  e.g. the Protein Data Bank, the myGrid Project, the Biomedical Information Research Network (BIRN), MCell].  Engineering-oriented Application  NASA operation its research through grid  Data-oriented Application  Data is emerging as the ‘killer application’ of the Grid.  e.g. Distributed Aircraft Maintenance Environment (DAME).
  • 9. Grid Computing: Applications Cont...  Physical Science Application  The National Virtual Observatory Project in the United States is using the Grid to federate sky surveys from several different telescopes  Commercial Application  Virtual server hosting,  Disaster recovery,  Heterogeneous workload management,  End-to-end systems management,  End-to-end automation  Reducing up-front investment  Accessing new capability more quickly,  Better performance
  • 10. References [1] Foster, I. & Kesselman C. (2005). “The Grid in a Nutshell”. Mathematics and Computer Science Division, Argonne National Laboratory, Information Sciences Institute, University of Southern California, USA. [2] Engelen van R. (2008). “Concepts & Architecture of Grid Computing”. Leiden University, Netherlands. [3] Berman F., Hey A.J.G. & Fox G.C. (2003). “Grid Computing – Making the Global Infrastructure a Reality”. John Wiley & Sons Ltd, Chichester, England. [4] Abbas A. (2004). “Grid Computing: A Practical Guide to Technology & Applications”. Firewall Media, An Imprint of Laxmi Publications Pvt. Ltd., Golden House, Daryaganj, New Delhi, India.