1. Introduction to Grid Computing and Applications in Computational Sciences Barry Wilkinson Department of Mathematics and Computer Science Western Carolina University WSSU September 13, 2004

2. 2 Talk Outline  What is Grid Computing?  Applications  Evolution of Grid Computing  Grid Computing Course

3. 3 Grid Computing  Using usually geographically distributed and interconnected computers together for high performance computing and/or for resource sharing. Notice “usually”, “and/or” - many definitions of grid computing and applications.

4. 4 The interconnection - now “usually” made through the Internet to multiple administrative domains. Resource sharing - can involve geographically distributed resources in addition to computers such as software, experimental equipment etc.

5. 5 Some think that grid computing is just cluster computing in the “large”

6. Local Cluster Inter Planet Grid 2100 Personal Device SMPs or SuperComputers Global Grid PERFORMANCE+QoSPERFORMANCE+QoS Individual Group Department Campus State National Globe Inter Planet Universe Administrative Barriers Enterprise Cluster/Grid Scalable Computing Figure due to Rajkumar Buyya, University of Melbourne, Australia, www.gridbus.org

7. 7 But grid computing is more than this. It offer the potential of virtual organizations – groups of people both geographically and organizationally distributed working together on a problems sharing computers AND other resources such as databases and experimental equipment.

8. 8 The grid virtualizes heterogeneous geographically disperse resources From "Introduction to Grid Computing with Globus," IBM Redbooks

9. 9 Distributed Collaborative Experiment Figure from M. Faramawi and B. Ramamurthy, SUNY- Buffalo

10. 10 Some Grid Projects & Initiatives  Australia – Nimrod-G – Gridbus – GridSim – Virtual Lab – DISCWorld – GrangeNet. –..etc  Europe – UK eScience – EU Data Grid – Cactus – XtremeWeb –..etc.  India – I-Grid  Japan – Ninf – DataFarm  Korea... N*Grid  Singapore NGP  USA – AppLeS – Globus – Legion – Sun Grid Engine – NASA IPG – Condor-G – Jxta – NetSolve – AccessGrid – and many more...  Cycle Stealing &.com Initiatives – Distributed.net – SETI@Home, …. – Entropia, UD, SCS,….  Public Forums – Global Grid Forum – Australian Grid Forum – IEEE TFCC – CCGrid conference – P2P conference http://www.gridcomputing.com Figures due to Rajkumar Buyya, University of Melbourne, Australia, www.gridbus.org

11. 11 Example Grid Networks  Numerous very high performance computing projects developed in late 1990’s and 2000’s.  Examples: USA TeraGrid, UK e-Science Grid, and others

12. 12 TeraGrid

13. 13 TeraGrid

14. 14 UK e-Science Grid

15. 15 EU grid

16. 16 Computational Grid Applications  Biomedical research  Industrial research  Engineering research  Studies in Physics and Chemistry

17. 17 Some “Computational” Grid Projects  Large Hadron Collider experimental facility for complex particle experiments at CERN (European Center for Nuclear Research, near Geneva Switzerland).  DOE Particle Physics Data grid  DOE Science grid  AstroGrid Project  Comb-e-Chem project

18. 18 CERN grid

19. 19 Key aspects of these grids  State-of-the-art interconnection networks.  Sharing resources.  Community of scientists.

20. 20 Shared Resources Can be much more than just computers:  Storage  Sensors for experiments at particular sites in the grid  Application Software  Databases,...

21. 21 Resource sharing and collaborative computing  Grid computing is about collaborating and resource sharing as much as it is about high performance computing.  Many projects

22. 22 Key aspects  Using distributed computers and resources collectively.  Often crossing organizational boundaries  Fueled by the Internet providing communication network.

23. 23 Evolution of grid computing  Started as a form of distributed computing.  Previous distributed computing systems: – 1980’s - Remote Procedure calls (RPC) client -server model with a service registry. – 1990’s - Distributed objects systems: CORBA (Common Request Broker Architecture) Java RMI (Remote Method Invocation)

24. 24 Internet-Based Grid computing  Grid Computing is now based upon Internet.  Enables using existing Internet protocols,security mechanisms, etc.  Uses a form of web services.

25. 25 Applications  Originally e-Science applications – Computational intensive, not necessarily one big problem but a problem that has to be solved repeatedly. – Data intensive. – Experimental collaborative projects  Now also e-Business applications to improve business models and practices.

26. 26 Background  Emergence and immense success of the Internet and the world-wide web, with agreed upon Internet standards for communication and access.  Continual improvement on computer and network technology and speeds.

27. 27 Need to harness computers  Original driving force behind Internet same as grid computing! – the need for high performance computing by connecting computers at distributed sites.

28. 28 Economic Development  Cohen report: September 2003, – projected impact of grid computing on NC’s economy - could lead to 240,000 new jobs and $10 billion in economic growth in North Carolina by 2010.

29. 29 Grid Computing Course Fall 2004 Barry Wilkinson Western Carolina University and Clayton Ferner UNC-Wilmington

30. 30  Originates from WCU on NCREN network and broadcast to students and faculty at 8 participating institutions: – UNC-Wilmington – NC State University – UNC-Asheville – UNC-Greensboro – Appalachian State University – NC Central University – Cape Fear Community College – Elon University

31. 31 Listed as an undergraduate course but can be taken for graduate credit. Graduate students expected to do more demanding work. Most students are undergraduate, but there are a few graduate students at NCSU and UNC-W. Level

32. 32 Prerequisites  Preferably programming skills in Java on a Linux system.  Some later work involves C/C++ programming.

33. 33 Topics  Review of Internet technologies  Introduction to grid computing  Web services  Grid services  Security, Public Key Infrastructure  Open Grid Services Architecture (OGSA)  Globus 3.2  Condor-G  MPI and grid-enabled MPI  UNC-W workflow editor and other GUI tools  Grid computing applications

34. 34 Assessment  6 “simple” programming tasks – Creating a web service – Creating a grid service – Submitting a Globus job – Submitting a CondorG job – MPI-G2 program – Using UNC-W GUI workflow editor  Programming Project  Class tests (1 or 2)  Final test  Small print: Subject to change. The instructor reserves the right to change the assignments to make it easier or harder.

35. 35 Grid computingVirtual organizations, computational grid projects, grid computing networks, TeraGrid, grid projects in the US and around the world, grid challenges Internet TechnologiesIP addresses, HTTP, URL, HTTP, XML, Telnet, FTP, SSL Web Services I.Service-Oriented Architecture (SOA), service registry, XML documents, XML schema, namespaces, SOAP, XML/SOAP examples, Axis Web Services II.WSDL, portType, message definition, WSDL to/from code Assignment 1"Simple" Web service Java programming assignment. Tomcat environment, axis, JWS facility Weeks 1 - 3

36. 36 Weeks 3 - 4 Grid ServiceConcepts, differences to Web services, stateful/stateless/transient/non- transient, Open Grid Services Architecture (OGSA), OGSI, grid service factory, Web Services Resource Framework (WSRF) Assignment 2"Simple" grid service Java programming assignment. Globus 3.2 environment.Tools: ant

37. 37 Weeks 4 - 6 SecuritySecure connection, authorization requirements, symmetric and asymmetric (public/private) key cyptography, non- repudiation, digital signatures, certificates, certificate authorities, X509 certificate Globus: Part 1Basic structure (version 3.2), grid service container, service browser, Globus Resource Allocation Manager (GRAM), job submission with managed-job-globusrun, Grid Security Infrastructure (GSI), Globus certificates, simpleCA, proxies, creating a proxy Globus: Part IIResource management, Master Managed Job Factory Service (MMJFS), more on managed- job-globusrun. Resource Specification Language (RSL and RSL-2), syntax and examples in RSL and RSl-2 Assignment 3Submitting a Job to the Grid, GT3 mangaged-job-globusrun, job specified in RSL-2 (XML file)

38. 38 Weeks 6 - 7 Globus: Part IIIInformation Directory Services, LDAP, resource discovery Schedulers andCondor, submit description file, resource brokers DAGMan, Checkpointing, ClassAd, Condor-G, other systems Assignment 4Submitting a Condor-G Job

39. 39 Weeks 7 - 8 High performance Grand challenge problems, parallel computing (HPF)computing, potential speed-up, types of parallel computers, shared memory multiprocessors, programming, message-passing multicomputers Parallel ProgrammingTechniques suitable for a Grid, embarrassingly parallel computations, Monte Carlo, parameter studies, sample "big" problems, gravitational N-body problem Cluster ComputingBasic message passing techniques, History, Beowulf clusters, system software, programming models (MPMD, SPMD), synchronous message passing, asynchronous message passing, message tags, collective routines

40. 40 Weeks 8 - 9 MPIProcess creation, communicators, unsafe message passing, point-to-point message- passing, blocking, non-blocking, communication modes, collective communication, running an MPI program on a cluster Grid-enabled MPIMPI-G2 internals, mpirun command, RSL script Assignment 5Running a simple MPI-G2 program

41. 41 Weeks 10 to 15 Grid portals UNC-W GUI Scientific and business applications Guest Speaker: Professor Dan Reed,University of North Carolina, Chapel, NC State University, and Duke University.

42. 42 Course Text  There is no assigned course textbook  Materials and links are provided on the home page.

43. 43 Course Home Page http://www.cs.wcu.edu/~abw/CS493F04 for announcements, slides, assignments, reading materials, tests dates, etc.

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50. 50 Acknowledgements This course is a team effort of: M ountain A rea G rid I nnovation C ollaborative (MAGIC) Faculty: Barry Wilkinson and Mark Holliday Students (Wizards): Jeffrey House and Sam Daoud http://www.cs.wcu.edu/~abw/MAGIC and: University of North Carolina at Wilmington

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55. 55 Acknowledgements Partial support for this work was provided by the National Science Foundation’s Course, Curriculum, and Laboratory Improvement program under grant 0410667 and by two grants from University of North Carolina, Office of the President. MAGIC gratefully acknowledges their support.