1. Grid Computing
Colton Lewis

2. Agenda This presentation: introduce grid computing
What it is
Examples
Challenges
Next presentation: address the job scheduling challenge

3. Components of Grid Computing
Multiple computers
Independently functioning hardware
Multiple locations and/or owners
Shared computational goal
Distributed resources over a network
Typically an already existing network

4. Differences from Cluster Computing
Resources are more loosely coupled
Clusters resources are often all in one location
Direct physical connections
Clusters may be part of grids

5. Benefits of Grid Computing
Large pool of resources
Large grids are comparable in FLOP/s to top 500 supercomputers
Distributed costs
Administration
Maintenance
Electricity
Space
Utilize existing infrastructure and avoid specialized hardware

6. Inherent Parallelism
Large numbers of computers means lots of possible parallelism
Great for handling large numbers of easily separable tasks
Easily parallelizable problems with little communication
Signal processing, graphics and animation, search and simulation, etc.
High volume of very similar tasks
Services or websites handling large numbers of users

7. Grid Computing Users Businesses Universities
Create company wide resources
As a replacement to old mainframes
Universities
Computationally intensive projects

8. Basic Grid Computing Layout
Grid is software defined
Server program run by master
Client program run by workers
Master assigns tasks to workers
Long running jobs reduce communication overhead
Job assignment and collection may be different physical computers

9. Example: SETI@home Search for Extra-terrestrial Intelligence
Analyze radio waves from space
Look for evidence of intentional communication
High-power narrow-band signals

10. Why SETI uses a Grid
Extra power is needed to cover many possible scenarios
Doppler correction for many different speeds
Radio spectrum can easily be divided and searched independently
Popular appeal makes it easy to find volunteers

11. SETI Architecture

12. Other Volunteer Grid Computing Projects
Protein folding
Prime number search
Physics simulations
Breaking cryptographic ciphers

13. Challenges Getting resources Using existing resources
Social problem which is outside the scope of this presentation
Using existing resources
Portability
Job Scheduling

14. Portability Use existing software
BOINC is commonly used for grid computing projects
Berkeley Open Infrastructure for Network Computing
Open Source
Used by both universities and industry

15. Job Scheduling Hard computer science problem
Optimality is computationally intractable in general
Grids must consider even more factors

16. Heterogeneous Machines
Machines on the grid may have vastly different resources
Dedicated clusters
Desktop computer donating spare cycles
Embedded devices
Must account for this to balance load

17. Dynamic Network Resources may not be up constantly
Jobs may need to be scheduled redundantly

18. General Strategies Know as much as possible Use Heuristics
Job intensity
Client capabilities
Use Heuristics
Will go into detail next presentation

19. Works Consulted
A. L. Beberg, D. L. Ensign, G. Jayachandran, S. Khaliq and V. S. Pande, Lessons from eight years of volunteer distributed computing," Parallel & Distributed Processing, IPDPS IEEE International Symposium on, Rome, 2009, pp. 1-8.
E. Korpela, D. Werthimer, D. Anderson, J. Cobb and M. Leboisky, distributed computing for SETI," in Computing in Science & Engineering, vol. 3, no. 1, pp , Jan/Feb 2001.
Y. Hao and G. Liu, "Evaluation of nine heuristic algorithms with data- intensive jobs and computing-intensive jobs in a dynamic environment," in IET Software, vol. 9, no. 1, pp. 7-16,
Jacob, Bart, et al. Introduction to Grid Computing. United States: IBM, International Technical Support Organization, Web. <

20. Questions?