1. 1 Grid Computing Francis Dang CPSC 689, Spring 2003 Texas A&M University

2. 2 What is a Grid? “ A hardware and software infrastructure that provides dependable, consistent, pervasive, and inexpensive access to computing resources. ” [Foster]

3. 3 Why use Grids? Distributed supercomputing High throughput computing On-demand computing Data-intensive computing Collaborative computing

4. 4 Precursors to the Grid InternetIntranetClustersEndsystems  Central administration  Homogeneous resources  Tightly coupled  Central administration  Homogeneous resources  Loosely coupled  Reduced communication performance  Co-scheduling  Central or separate administration  Heterogeneous resources  Within a single organization  Lack of resource discovery  Lack of central administration  Heterogeneous resources  Geographical distribution  Spans multiple organizations

5. 5 Taxonomy of Grid Technologies FAFNER Dist. object Systems SETI@homeDistributed.Net I-WAYGlobusLegion Grid portals Integrated grid systems Resource managers Grid solutions 1 st generation 2 nd generation Peer-to-peer computing Service-oriented architectures Metadata information Live information systems 3 rd generation

6. 6 FAFNER By Bellcore Labs, Syracuse University, and Co- Operating Systems Factoring project via the Web Allocated tasks to clients for computation Trivially parallel algorithms used, so no communication needed after setup. Integrated low-end systems as clients

7. 7 Experience with FAFNER Poor scalability due to manual computation distribution and result collection. Fine grain tasks allowed use of low-end systems Not dependent on a fast interconnect Client setup required building software and running a FAFNER daemon

8. 8 I-WAY Developed at Argonne National Laboratory Integrated existing high bandwidth networks, high performance computers and visualization systems with ATM networks. Used a gateway server (I-POP) and software environment (I-Soft) for each site. I-Soft addressed heterogeneity, scalability, performance, and security.

9. 9 Experience with I-WAY Required a fast interconnect Poor scalability due to I-POP and I-soft design I-POP used a centralized resource manager Use of only one I-POP server was not fault tolerant

10. 10 Globus Toolkit Provides basic services and capabilities needed for building computational grids. High-level services, tools, and programming models built from these low-level services. Used by many Grid projects. Joint development by Argonne National Laboratory, University of Chicago, and USC.

11. 11 Grid Architecture Resources and resource- specific operations Communication and authentication protocols Information and management protocols Multi-resource protocols FabricConnectivity Application ResourceCollective

12. 12 Legion Grid components encapsulated as objects Inheritance and other object-oriented techniques can be used to specialize object behavior. Developed at University of Virginia Commercial version is known as Avaki.

13. 13 Distributed Object Systems Used mainly within a single organization Resource sharing provided with standard interfaces, remote invocation, and trading services Sharing was relatively static and restricted Examples: CORBA Java RMI

14. 14 Resource Managers Schedule and manage batch jobs for locally parallel and distributed computing systems. PBS LSF Condor Sun Grid Engine Grid software should interface to existing resource managers rather than replace them.

15. 15 Grid Portals Consolidate access to grid resources and services Simplify use of grid resources via a web interface Uses existing grid technologies

16. 16 Integrated Grid Systems Integrate existing and develop new grid technologies into coherent systems. Targeted for high-performance wide area applications Examples: Cactus DataGrid UNICORE Webflow

17. 17 Peer-to-Peer Computing Addresses scalability and fault tolerance with decentralization Decentralization introduces its own challenges: Communication and security overhead shifted to clients Security issues Need to handle issues with heterogeneity Resource discovery is more difficult

18. 18 Third Generation Grids Service-oriented architecture Service defined as any networked resource that provides a capability Divide grid services into service interfaces and protocols Use Internet-based web services standards for better interoperability Open Grid Services Architecture Framework combines web services and grid computing Agents provide autonomy to computation for adaptation to changes Live information systems Real-time information and collaboration over distributed systems

19. 19 Grid Technology Summary First generation introduced proprietary systems for sharing computing resources. Second generation consisted of middleware to cope with heterogeneity and scalability. Third generation involves a service-oriented approach, distributed collaboration, and autonomy.

20. 20 Issues for the Grid Heterogeneity Interoperability between heterogeneous resources Scalability Services need to scale without manual intervention Fault tolerance and dependability Software and hardware failure is more probable in a Grid environment.

21. 21 Issues for the Grid Resource information Maintain various details about grid resources Information services Storage and retrieval must be extendable, fast, reliable, secure, and scalable Resource discovery Query resources by certain characteristics Must be fast and robust

22. 22 Issues for the Grid Synchronization and coordination Management of computation across resources Security Mechanisms must be scalable and automated. Concurrency and consistency Need to maintain data consistency in concurrent, heterogeneous environments

23. 23 Issues for the Grid Issues of non-local access to resources Use caching and replication for to improve locality Programming models Adapt existing models or develop new models for grid architectures Performance analysis Need techniques for collection, analysis, and explanation

24. 24 Grid Programming Models ModelExamplesProsCons Datagram/stream communication UDP, TCP, MulticastLow overheadLow level Shared memory, multithreading POSIX Threads, DSMHigh levelScalability Data parallelismHPF, HPC++Automatic parallelizationRestricted applicability Message passingMPI, PVMHigh performanceLow level Object orientedCORBA, DCOM, Java RMI Support for large system design Performance Remote procedure callDCE, ONCSimplicityRestricted applicability High throughputCondor, LSF, NimrodEase of useRestricted applicability Group orderedIsis, TotemRobustnessPerformance, scalability AgentsAglets, TelescriptFlexibilityPerformance, robustness

25. 25 Types of Grid Users ClassPurposeUser ofConcerns End usersSolve problemsApplicationsTransparency, performance Application developers Develop applicationsProgramming models, tools Ease of use, performance Tool developersDevelop tools, programming models Grid servicesAdaptivity, performance, security Grid developersProvide basic grid servicesLocal system servicesLocal simplicity, connectivity, security System administrators Manage grid resourcesManagement toolsBalancing local and global concerns

26. 26 References Computational Grids., I. Foster, C. Kesselman. Chapter 2 of "The Grid: Blueprint for a New Computing Infrastructure", Morgan-Kaufman, 1999. I. Foster, C. Kesselman, and S. Tuecke. The Anatomy of the Grid: Enabling Scalable Virtual Organizations. International Journal of High Performance Computing Applications, 15(3), 2001. The Physiology of the Grid: An Open Grid Services Architecture for Distributed Systems Integration. I. Foster, C. Kesselman, J. Nick, S. Tuecke, Open Grid Service Infrastructure WG, Global Grid Forum, June 22, 2002. H. Casanova. Distributed Computing Research Issues in Grid Computing. ACM SIGACT News, 33(3):50-70, 2002. D. de Roure, M. Baker, N. R. Jennings and N. Shadbolt. "The Evolution of the Grid" Int. J. of Concurrency and Computation: Practice and Experience 15(11), 2003. D.B. Skillicorn. Motivating Computational Grids. In Proceedings of the 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid (CCGrid2002), pages 401-406, May 2002.