1. Ali YILDIRIM Emre UZUNCAKARA
Grid Computing
Ali YILDIRIM
Emre UZUNCAKARA

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

3. What Is Grid Computing?

4. 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.

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

7. 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

9. Goals of Grid Computing

10. 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)

11. Simple Grid Example

12. Sun Grid As Utility

13. Sun Grid as Utility

14. Pros and Cons of Grid Computing

15. 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)

16. Examples of Grid Computing

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

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

20. Oracle uses grid Structure

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

22. Grid Softwares

23. Grid Softwares Globus Management Software
Java Technology : Custom programming

24. Globus Grid Management Software

25. 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

26. Java Technology

27. 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

28. Application Suitability

29. 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

30. Academic Researches

31. 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)

32. Conclusion

33. 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.

34. References en.wikipedia.org/wiki/Grid_computing
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

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