Remarks on Education and the Grid

1. Remarks onEducation and the Grid Geoffrey FoxProfessor of Computer Science, Informatics, Physics Pervasive Technology Laboratories Indiana University Bloomington IN 47401 gcf@indiana.edu http://www.infomall.org http://www.grid2002.org

2. Grid Computing: Making The Global Infrastructure a Reality • Based on work done in preparing book edited withFran Berman (director NPACI) andAnthony J.G. Hey (leader of core UK e-Science program), • ISBN: 0-470-85319-0 • Hardcover 1080 Pages • Published March 2003 • http://www.grid2002.org • Last chapter is on education and the Grid

3. Who is Geoffrey Fox? • Undergraduate degree in math, PhD Theoretical Physics at Cambridge University • Theory, Experiment, Computation, Phenomenology of particle physics Caltech for 20 years • Worked with Feynman, Hey, Wolfram • Dean for educational computing and associate provost for computing Caltech; Professor of Physics; department chair • Developed parallel computers for science • Computer Science Syracuse, Florida State, Indiana • Main area of research last 20 years • Interdisciplinary work in computational science with many fields – Earth Science/Biology at moment • Chief technologist Anabas corporation (WebEx done right) • Technology for distance education on the Grid • Will teach class from Indiana to Jackson State State next semester • Informatics, Computer Science, Physics at Indiana • Pervasive Technology Lab Information technology initiative at Indiana University funded by Lilly • Director Community Grids Laboratory

4. e-Business e-Science and the Grid • e-Business captures an emerging view of corporations as dynamic virtual organizations linking employees, customers and stakeholders across the world. • The growing use of outsourcing is one example • e-Science is the similar vision for scientific research with international participation in large accelerators, satellites or distributed gene analyses. • The Grid integrates the best of the Web, traditional enterprise software, high performance computing and Peer-to-peer systems to provide the information technology infrastructure for e-moreorlessanything. • A deluge of data of unprecedented and inevitable size must be managed and understood. • People, computers, data and instruments must be linked. • On demand assignment of experts, computers, networks and storage resources must be supported

5. So what is a Grid? • Supporting human decision making with a network of at least four large computers, perhaps six or eight small computers, and a great assortment of disc files and magnetic tape units - not to mention remote consoles and teletype stations - all churning away. (Licklider 1960) • Coordinated resource sharing and problem solving in dynamic multi-institutional virtual organizations • Infrastructure that will provide us with the ability to dynamically link together resources as an ensemble to support the execution of large-scale, resource-intensive, and distributed applications. • Realizing thirty year dream of science fiction writers that have spun yarns featuring worldwide networks of interconnected computers that behave as a single entity.

6. e-Science • e-Science is about global collaboration in key areas of science, and the next generation of infrastructure that will enable it. This is a major UK Program • e-Science reflects growing importance of international laboratories, satellites and sensors and their integrated analysis by distributed teams • CyberInfrastructure is the analogous US initiative Grid Technology supports e-Science andCyberInfrastructure

7. Database Database Classic Grid Architecture Resources Content Access Composition Middle TierBrokers Service Providers Netsolve Security Collaboration Computing Middle Tier becomes Web Services Clients Users and Devices

8. e-Business and (Virtual) Organizations • Enterprise Grid supports information system for an organization; includes “university computer center”, “(digital) library”, sales, marketing, manufacturing … • Outsourcing Grid links different parts of an enterprise together (Gridsourcing) • Manufacturing plants with designers • Animators with electronic game or film designers and producers • Coaches with aspiring players (e-NCAA or e-NFL etc.) • Customer Grid links businesses and their customers as in many web sites such as amazon.com • e-Multimedia can use secure peer-to-peer Grids to link creators, distributors and consumers of digital music, games and films respecting rights • Distance education Grid links teacher at one place, students all over the place, mentors and graders; shared curriculum, homework, live classes …

9. Some Important Styles of Grids • Computational Grids were origin of concepts and link computers across the globe – high latency stops this from being used as parallel machine • Knowledge and Information Grids link sensors and information repositories as in Virtual Observatories or BioInformatics • More detail on next slide • Community Grids focus on Grids involving large numbers of peers rather than focusing on linking major resources – links Grid and Peer-to-peer network concepts • Semantic Grid links Grid, and AI community with Semantic web (ontology/meta-data enriched resources) and Agent concepts

10. Database Database Event/MessageBrokers Event/MessageBrokers Event/MessageBrokers Peer to Peer Grid Peers Service FacingWeb Service Interfaces Peers User FacingWeb Service Interfaces A democratic organization Peer to Peer Grid

11. Information/Knowledge Grids • Distributed (10’s to 1000’s) of data sources (instruments, file systems, curated databases …) • Data Deluge: 1 (now) to 100’s petabytes/year (2012) • Moore’s law for Sensors • Possible filters assigned dynamically (on-demand) • Run image processing algorithm on telescope image • Run Gene sequencing algorithm on compiled data • Needs decision support front end with “what-if” simulations • Metadata (provenance) critical to annotate data • Integrate across experiments as in multi-wavelength astronomy Data Deluge comes from pixels/year available

12. Database Database SERVOGrid – Solid Earth Research Virtual Observatory will link Australia, Japan, USA …… RepositoriesFederated Databases Sensor Nets Streaming Data Grids for Geoscience Analysis and Visualization Loosely Coupled Filters Closely Coupled Compute Nodes

13. SERVOGrid Requirements • Seamless Access to Data repositories and large scale computers • Integration of multiple data sources including sensors, databases, file systems with analysis system • Including filtered OGSA-DAI (Grid database access) • Rich meta-data generation and access with SERVOGrid specific Schema extending openGIS (Geography as a Web service) standards and using Semantic Grid • Portalswith component model for user interfaces and web control of all capabilities • Collaboration to support world-wide work • Basic Grid tools: workflow and notification

14. Virtual Observatory Astronomy GridIntegrate Experiments Radio Far-Infrared Visible Dust Map Visible + X-ray Galaxy Density Map

15. Grids in a Nutshell • Grids are by definition the best of HPCC, Web Services, Agents, Distributed Objects, Peer-to-peer networks, Collaborative environments • Grid applications are typically zero or one very large supercomputers, lots of conventional machines, with unlimited data and/or people supporting an electronic (virtual) community • Data sources and people are latency tolerant … • Multiple supercomputers (or clusters) on same Grid as in TeraGrid/ETF largely for sharing of data and by people • Grids are supported by Global Grid Forum, W3C, OASIS … setting standards • Grids are a “service oriented architecture” hiding irrelevant details • Services are electronic resources communicating by messages • Message based architecture gives scalable loosely coupled component model

16. PortalService Security Catalog A typical Web Service • In principle, services can be in any language (Fortran .. Java .. Perl .. Python) and the interfaces can be method calls, Java RMI Messages, CGI Web invocations, totally compiled away (inlining) • The simplest implementations involve XML messages (SOAP) and programs written in net friendly languages like Java and Python PaymentCredit Card Web Services WSDL interfaces Warehouse Shipping control WSDL interfaces Web Services

17. Database Typical Grid Architecture UserServices Portal Services Re-use Application ServiceLibraries ApplicationCustomization Application Service Application Service Middleware SystemServices SystemServices SystemServices Re-use “Core”Grid Raw (HPC) Resources

18. What does Community Grids Lab do? • New curricula for Grids (next semester) taught using Grid technology • Underlying Grid messaging technology supporting reliable communication • Grid Portals built with re-usable components (portlets) • Application Grids for Earth Science/Biocomplexity/supercomputer users • Integration of handheld devices with the Grid • Audio-video conferencing and collaboration with a Grid architecture • Multimedia on the Grid; http://www.undergroundfilm.org

19. Why Grids for Education • Education is a classic distributed organization • New multi-disciplinary curricula in emerging fields (information technology, informatics, biocomplexity, nanotechnology) require distributed experts interacting with mentors and students • Grids support component model for content allowing re-use of research services in education • Education fits the service model for both “process” and “Curriculum” • Education wants rich integration of data sources and people and some computing – Grids can do this • Grids democratize resources as enable universal (ubiqitous) access • In terms of geographic distribution, level (K-12 through lifelong learning)and disparate clients • Grids support the Internet generation • WebCT, Blackboard, Placeware, WebEx, Groove, Learning Management systems all have natural Grid implementations

20. Database Database SERVOGrid for Education Content Streaming Data Field Trip Data Sensors RepositoriesFederated Databases Sharing Grid Services ? Analysis and Visualization Discovery Services Loosely Coupled Filters Coarse grain simulations

21. Grid Learning Model • Education and Research Grids share some services both for content and “process” • For example collaboration services are largely identical • Research will use much larger simulation engines to get high resolution results • Maybe a researcher uses a CAVE to visualize; education a Macintosh • But both can share data services but run through different filters to select for precision (research) or pedagogical value (education) • Education has “digital textbook” frontend to resources of the research Grid • Both use same workflow technologies to link services together

22. Grid Services for the Education Process • “Learning Object” XML standards already exist • Registration • Performance (grading) • Authoring of Curriculum • Online laboratories for real and virtual instruments • Homework submission • Quizzesof various types (multiple choice, random parameters) • Assessment data access and analysis • Synchronous Delivery of Curricula including Audio/Video Conferencing and other synchronous collaborative tools as Web Services • Scheduling of courses and mentoring sessions • Asynchronous access, data-mining and knowledge discovery • Learning Plan agents to guide students and teachers

23. Closely coupled Java/Python … Coarse Grain Service Model Service B Service A Module B Module A Messages 0.1 to 1000 millisecond latency Method Calls.001 to 1 millisecond Implementing Grids for Education I • Need to design a service architecture for education • Build on services from broader fields • Need some specific EducationML specifying services and properties • Note IMS (http://www.imsproject.org/) and ADL have a lot of education property metadata but no services • Need more use of standards outside education but much of IMS can be used • Use services where-ever possible but only if “coarse-grain”

24. Implementing Grids for Education II • Build a Education Grid prototype addressing content and process • Focus education grid on a curriculum area (using Grids!) such as Geoscience or even e-Science/Information Technology/Science Informatics • Re-use Grid services in systems area (portals, security, collaboration ..) and from application domain • What research Grid services can be re-used; what need to be significantly changed or customized • Develop some “Education process” services • Supply leadership in use of CyberInfrastructure/Grids in education • Feed Education needs to CyberInfrastructure and vice-versa • Perform a requirement analysis analogous to Gap Analysishttp://grids.ucs.indiana.edu/ptliupages/publications/GapAnalysis30June03v2.pdf • Develop curriculum in Grids, e-Science and CyberInfrastructure

25. Conclusions • Grids/CyberInfrastructures are inevitable and pervasive • Education can benefit from Grids and vice-versa • Can expect WebServices, P2P networks and Grids to merge with a common set of general principles but different implementations with different scaling and functionality trade-offs • We will be flooded with data, information and purported knowledge • One should be preparing Grid strategies; understanding relevant Web and Grid standards and developing new domain specific standards • Note many existing (standards) efforts assume client-server and not a brokered service model; these will need to change! • Enough is known that one can start today with prototypes

26. Discussion • The following additional points were made in discussion • Connect to Citizen Science as at http://www.ebird.org and projects like SETI@Home • Role of Science museums on a Grid • Role of Grid services to provide knowledge transformations for education or research • Use “resources-on-demand” and so knowledge broadly available if resources supplied as a national facility • Does Grid technology enhance or mitigate the digital divide • Need to explain role of teachers in an Education Grid and train them to take it • Explain difference between Internet and the Grid • Describe role of Access Grid type technology • Some new textbook’s have embedded URL’s