Ali YILDIRIM Emre UZUNCAKARA Grid Computing Ali YILDIRIM Emre UZUNCAKARA

Agenda What is Grid Computing Goals of Grid Computing Pros and Cons Examples Of Grid Systems Grid Softwares Application Suitability Example Researches Conclusion

What Is Grid Computing?

What is Grid Computing Emerging computing model; that provides the ability to perform higher throughput computing by taking advantage of many networked computers to model a virtual computer architecture that is able to distribute process execution accross a parallel infra-structure.

What is Grid Computing Heterogeneous and Distributed enviroment It is NOT a cluster architecture!

Parts of Grid Computing Infrastructure Grid: Hardware resources such as processors, storage and network Applications Grid: Packaged or custom applications used for business logic and process flow within application software

Goals of Grid Computing

Goals Of Grid Computing Pervasive, uniform, and reliable access to data, storage capacity and computation power Resource utilization Delivery of computer power as a utility. (City Water, electricity systems)

Simple Grid Example

Sun Grid As Utility

Sun Grid as Utility

Pros and Cons of Grid Computing

Pros And Cons PROS CONS Time Saving Resource Management (Who is Prior?) Resource Saving Security problem (Data is remote) Space Saving Schedule Problem (Who , when?) Money Saving Resource management >>> Different algorithm researches for different Job Types. ( Data intensive jobs, Cpu Intensive Jobs)

Examples of Grid Computing

Examples Of Grid Systems Seti@Home is the most popular(1st). Climateprediction, Einstein@Home etc. All uses BOINC software Over 18 projects working using BOINC Berkeley Open ınfrastructure for Network Computing

Seti@Home

Examples (Continued...) Enterprise grids Oracle grid Blade Servers Sun

Oracle uses grid Structure

Blade Servers For power, heat and space savings Includes processors, memory, network cards and storage

Grid Softwares

Grid Softwares Globus Management Software Java Technology : Custom programming

Globus Grid Management Software

Globus Grid Management Software Product for managing grids Supported by many large vendors GRAM Grid Resource Allocation Manager “gatekeeper” process that controls execution of job managers MDS Monitoring and Directory Service GRIS (Grid Resource Information Service) collects local info GIIS (Grid Index Information Service) collects GRIS info GASS (Global Access to Secondary Storage) GRAM : Grid Resource Allocation Manager MDS : Monitoring and Directory Service GRIS : Grid Resource Information Service GIIS : Global Index Information Service GASS : Global Acces to Secondary Storage

Java Technology

Java Technology RMI, Web Services and JNDI RMI : Remote Method Invocation Web Services : Software As Services, Soap Packages over HTTP Orchestration of Services E-commerce, Online Community Servers J2EE Application Servers > Load Balancing, Fail Over mechanisms

Application Suitability

Application Suitability For a grid system to perform applications must have some criteria. Best Suitable > Large Batch jobs that requires minimum inter process communication and synchronization

Academic Researches

Academic Researches In 2004, Genaud : Algorithm for load balancing. Allock Et. Al. : Data transfer problem in high performance grid environments. (Replica management Service that uses an FTP-like protocol to make replicas of data elements accross the grid to improve performance)

Conclusion

Conclusion In summary, Grid computing is; cooperation of different computers, for a specific task, so that the user acquires better performance for that specific task. “The Load” is on remote machines rather than clients. Like: Transfer of CPU power as electricity power.

References en.wikipedia.org/wiki/Grid_computing www.oracle.com/technologies/grid/index.html Web Services and Service Oriented Architectures: A Savvy Manager’s Guide, Douglas K Barry, Elsevier Science, 2003. Loosely Coupled: The Missing Pieces of Web Services, Doug Kaye, RDS Press, 2003. Intel White Paper, Changing the IT Paradigm: Blade Server Computing, 2003 Allock B. Et al. Data management and transfer in high performance computational grid environments. Parallel Computing 28, 2002, pp 749-771

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