Transcript Remarks on Education and the Grid Geoffrey Fox Professor of Computer Science, Informatics, Physics Pervasive Technology Laboratories Indiana University Bloomington IN 47401 [email protected] http://www.infomall.org http://www.grid2002.org.

Remarks on
Education and the Grid
Geoffrey Fox
Professor of Computer Science, Informatics, Physics
Pervasive Technology Laboratories
Indiana University Bloomington IN 47401
[email protected]
http://www.infomall.org
http://www.grid2002.org
Grid Computing: Making The Global
Infrastructure a Reality
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Based on work done in
preparing book edited with
Fran Berman (director
NPACI) and
Anthony 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
Who is Geoffrey Fox?
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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
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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
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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
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Informatics, Computer Science, Physics at Indiana
• Pervasive Technology Lab Information technology initiative at Indiana University
funded by Lilly
• Director Community Grids Laboratory
e-Business e-Science and the Grid
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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 Peerto-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
So what is a Grid?
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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.
e-Science
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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
and
DATA
ACQUISITION
CyberInfrastructure
ADVANCED
VISUALIZATION
,ANALYSIS
QuickTime™ and a
decompressor
are needed to see this picture.
IMAGING INSTRUMENTS
COMPUTATIONAL
RESOURCES
LARGE-SCALE DATABASES
Classic Grid Architecture
Resources
Database
Database
Composition
Content Access
Netsolve
Security
Collaboration
Middle Tier
Brokers
Service Providers
Computing
Middle Tier becomes Web Services
Clients
Users and Devices
e-Business and (Virtual) Organizations
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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 …
Some Important Styles of Grids
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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
Peers
Database
Database
Service Facing
Web Service Interfaces
Event/
Message
Brokers
Event/
Message
Brokers
Event/
Message
Brokers
Peer to Peer Grid
Peers
User Facing
Web Service Interfaces
A democratic organization
Peer to Peer Grid
Information/Knowledge Grids
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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
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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
SERVOGrid – Solid Earth Research Virtual
Observatory will link Australia, Japan, USA ……
Repositories
Federated Databases
Database
Sensor Nets
Streaming Data
Database
Grids for Geoscience
Analysis and
Visualization
Loosely Coupled
Filters
Closely Coupled Compute Nodes
SERVOGrid Requirements
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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)
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Rich meta-data generation and access with
SERVOGrid specific Schema extending openGIS
(Geography as a Web service) standards and using
Semantic Grid
Portals with component model for user interfaces and
web control of all capabilities
Collaboration to support world-wide work
Basic Grid tools: workflow and notification
Virtual Observatory Astronomy Grid
Integrate Experiments
Radio
Far-Infrared
Visible
Dust Map
Visible + X-ray
Galaxy Density Map
Grids in a Nutshell
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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
A typical Web Service
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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
Web Services
WSDL interfaces
Portal
Service
Security
WSDL interfaces
Web Services
Payment
Credit Card
Catalog
Warehouse
Shipping
control
Typical Grid Architecture
Re-use
Application
Customization
User
Services
Application
Service
Portal
Services
Application
Service
Libraries
Application
Service
Middleware
Re-use
“Core”
Grid
System
Services
System
Services
System
Services
Raw (HPC)
Resources
Database
What does Community Grids Lab do?
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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
Why Grids for Education
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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
SERVOGrid for Education Content
Field Trip Data
Repositories
Federated Databases
Database
Sensors
Streaming
Data
Database
Sharing Grid Services
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Loosely Coupled
Filters
Discovery
Services
Analysis and
Visualization
Coarse grain simulations
Grid Learning Model
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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
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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
Grid Services for the Education Process
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“Learning Object” XML standards already exist
Registration
Performance (grading)
Authoring of Curriculum
Online laboratories for real and virtual instruments
Homework submission
Quizzes of 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
Implementing Grids for Education I
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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”
Closely coupled Java/Python …
Module
B
Module
A
Method Calls
.001 to 1 millisecond
Coarse Grain Service Model
Service
B
Messages
Service
A
0.1 to 1000 millisecond latency
Implementing Grids for Education II
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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 Analysis
http://grids.ucs.indiana.edu/ptliupages/publications/GapAnalysis30June03v2.pdf
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Develop curriculum in Grids, e-Science and CyberInfrastructure
Conclusions
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Grids/CyberInfrastructures are inevitable and pervasive
Education can benefit from Grids and vice-versa
Can expect Web Services, 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
Discussion
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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