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The Grid Needs You. Enlist Now!
Professor Carole GobleUniversity of Manchester, UK, [email protected]
Co-director e-Science North West UK regional centreDirector myGrid UK e-Science pilot projectCo-chair Global Grid Forum Semantic Grid Research Group
The Grid Needs You. Enlist Now!
The what and why of the Grid.
Services, data and semantics and the Grid.
Getting involved – a call to arms.
The take home
“The Grid is the next big thing” – and it isn’t just big computers and fat pipes.
The Grid is actually the latest attempt at distributed computing
If you aren’t involved yet maybe its because you don’t think its relevant, or its done already or you haven’t anything to offer
You are most likely wrong If you are already into the Grid
this is a “ra ra” exercise
Origins of the Grid
The Grid: Blueprint for a New Computing Infrastructure
Edited by Ian Foster and Carl Kesselman
July 1998, 701 pages. a proposed distributed
computing infrastructure for advanced science and engineering
pervasive and dependable
What is the Grid?
Computational power as a utility Securely and transparently sharing supercomputing
resources on demand. Fast pig iron with fat pipes for cycle intensive
scientific problems Large scale data access and transportation Making the most of what you have got
Why do it now?
Enormous quantities of data: Petabytes For an increasing number of
communities, gating step is not collection but analysis
Ubiquitous Internet: 100+ million hosts Collaboration & resource sharing the
norm Ultra-high-speed networks: 10+ Gb/s
Global optical networks Huge quantities of computing: 100+ Top/s
Moore’s law gives us all supercomputers
114 genomes735 in progress
Isn’t this just high performance computing for high energy physicists?
What is the Grid for?
Global e-Science Large-scale science and engineering are done
through the interaction of people, heterogeneous computing resources, information systems, and instruments, all of which are geographically and organizationally dispersed.
The motivation for “Grids” is to facilitate the routine interactions of these resources in order to support large-scale science and engineering.
KEYWORDS Collaboration, Democratization, Speculation
Bill Johnston, NASA July 01
9
Global Collaborative Knowledge Communities
Slide courtesy of Ian Foster
Global Knowledge Communities
Teams organised around common goals Communities: “Virtual organisations” Overlapping memberships, resources and activities
Essential diversity is a strength & challenge membership & capabilities
Geographic and political distribution No location/organisation/country possesses all required
skills and resources Dynamic: adapt as a function of their situation
Adjust membership, reallocate responsibilities, renegotiate resources
Slide derived from Ian Foster’s SSDBM 03 keynote
The Grid Opportunity“flexible, secure, coordinated resource sharing among dynamic collections of individuals, institutions, and resources - what we refer to as virtual organizations."
The Anatomy of the Grid: Enabling Scalable Virtual OrganizationsFoster, Kesselman, Tueke
KEYWORD: VIRTUALISATION
Why Grids? A biochemist exploits 10,000 computers to screen 100,000
compounds in an hour; A biologist combines a range of diverse and distributed
resources (databases, tools, instruments) to answer complex questions;
1,000 physicists worldwide pool resources for petaop analyses of petabytes of data
Civil engineers collaborate to design, execute, & analyze shake table experiments
Climate scientists visualize, annotate, & analyze terabyte simulation datasets
An emergency response team couples real time data, weather model, population data
A multidisciplinary analysis in aerospace couples code and data in four companies
Slide courtesy of Steve Tuecke
Telemicroscopy Sharing of UHVEM(Ultra High Voltage Electron Microscopy) in
Osaka University with NCMIR (National Center for Microscopy and Imaging Research) 3 Million electron volts; the most powerful microscopy facility
KEYWORDS: SHARING SCARCE RESOURCES ON DEMAND
Tokyo XP(Chicago)
STAR TAP
TransPACAPAN
vBNS
(UC San Diego)SDSC
NCMIR(San Diego)
UHVEM(Osaka, Japan)
JGN
Osaka University
Smallpox Grid
United Devices, IBM, Oxford University, Accelrys
Analysis of 35 million drug compounds against nine smallpox proteins to try to find a way to stop the replication of the virus.
Volunteers from over 190 countries donated their spare CPU power at www.grid.org, the world's largest public computing resource
Contributed over 39,000 years of computing time in less than six months.
September 30, 2003 —delivered the results of the Smallpox Research Grid project to representatives from the United States Department of Defense in an event hosted by the British Embassy in Washington, D.C.
230 - Radiologists (Double Reading)50% - Workload Increase
2,000,000 - Screened every Year120,000 - Recalled for Assessment10,000 - Cancers1,250 - Lives Saved
Digital
Digital
RealityGrid http://www.realitygrid.org
Closely coupling computation and experiment to speed up scientific discovery.
Simulation, visualization and data gathering coupled
X-ray microtomography produces 3D X-ray attenuation maps of specimens at a microscopic level
Scientist remotely steers calculation from laptop
Visualization and computation use supercomputers accessed via Grid.
Collaboration Interactive
environments and virtual presence integrated with Grid middleware
SARS Combat Grid, Taiwan Emergency Access Grids Integration of patient data and
models of dissemination
http://www.accessgrid.org
Access Grid
Foundation for e-Science
sensor nets
Shared data archives
computers
software
colleagues
instruments
Grid
Diagram derived fromIan Foster’s slide
Butterfly.net Fully-distributed server
technology pioneering the use of open grid computing protocols in large-scale immersive game networks that support unlimited numbers of players and require the most demanding levels of service.
More commercial examples…
Novartis Pharmaceuticals accelerate lead identification and profiling to increase relevant targets in drug discovery, screening applications that were previously considered CPU constrained.
Nippon Life Insurance improve the performance of Financial Risk Management Applications customer project in applying Grid technology for this application. Reduced processing time for financial risk calculation from around 10 hours to about 49 minutes – a 12-fold increase in speed. Can run more complex scenarios to reduce risk exposure
Global Grid Forumhttp://www.ggf.org
Standards body for Grid Computing
Over 2000 members All the vendors 44 WGs and RGs Three meetings per
annum ~ 1000 attendees at
plenary meetings ~ 400 at “working”
meetings GGF10 Frankfurt, March
2004
Investment
UK Government invested £240 million into e-Science and Grid related research
EU invested ~€351million in FP5 and FP6 USA invested – lots! IBM invested ~10-20% R&D budget in Grid
Computing $1.5million per annum on GridFTP alone
Japan and China invested in Grids Practically every EU member has a Grid programme.
The Grid means what I say it means
The Grid – the vision of forming federations A Grid - A virtual organisation of resources
Machines – computational grid Geography – a UK Grid A field – Mouse Genome Grid A (temporary) problem – protein folding simulation
No one grid – lots of interoperating Grids Grid middleware infrastructure specification
Services stacks, policies, protocols, standards, APIs Reference implementations
Globus, Condor, Unicore, Sun Grid Engine, Avaki, United Devices...
Grid tools Portals, heartbeat monitors etc
E-Science: application of all the above for the benefit of Science
The Grid is forming federations… Infrastructure middleware for establishing, managing,
and evolving multi-organizational federations Dynamic, autonomous, domain independent On-demand, ubiquitous access to computing, data,
and services Mechanisms for resource virtualization & workflow
management within federations New capabilities constructed dynamically and
transparently from distributed services Service-oriented, virtualization
…when the federations are… Dynamic and volatile. A consortium of services
(databases, sensors, compute servers) participating in a complex analysis may be switched in and out they become available or cease to be available;
Ad-hoc. Service consortia have no central location, no central control, and no existing trust relationships;
Large Hundreds of services could be orchestrated at any time;
Potentially long-lived. A simulation could take weeks.
HOLD THESE THOUGHTS!
myGrid http://www.mygrid.org.uk
Knowledge-driven middleware for data intensive ad hoc in silico experiments in biology
Straightforward discovery, interoperation, deployment & sharing of services
Service-oriented architecture
Semantic based discovery of workflows and workflow composition
Integration and Information
Workflow & Distributed DB Queries
Experimentation
Provenance, propagating change, personalisation
Three legacy views
Grid middleware is a bag of low level protocols The Grid is about compute cycle stealing The Grid is about plumbing and has nothing to do
with semantics
Three legacy views
Grid middleware is a bag of low level protocols The Grid is about compute cycle stealing The Grid is about plumbing and has nothing to do
with semantics
This was once true. Some still hold this view (notably US programme managers)
It is not the view of the Grid visionaries or the Grid policy makers outside the US.
Three legacy views
Grid middleware is a bag of low level protocols The Grid is about compute cycle stealing The Grid is about plumbing and has nothing to do
with semantics
This was once true. Some still hold this view (notably US programme managers)
It is not the view of the Grid visionaries or the Grid policy makers outside the US.
The Open Grid Service Architecture
Data Grids
Semantic Grids
Grid Evolution1st generation
Incr
ease
d fu
nctio
nalit
y,st
anda
rdiz
atio
n
Time
Customsolutions
Globus Toolkit
Defacto standardsGGF: GridFTP, GSI
X.509,LDAP,FTP, …
(based on Foster GGF7 Plenary)
• Computationally intensive• File access/transfer• Bag of various heterogeneous protocols & toolkits•Monolithic design• Recognises internet, ignores Web• Academic teams
Legion, Condor, Unicore …
Grid Evolution2nd Generation
Incr
ease
d fu
nctio
nalit
y,st
anda
rdiz
atio
n
Time
Customsolutions
Open GridServices Arch
GGF: OGSI, …(+ OASIS, W3C)
Multiple implementations,including Globus Toolkit 3
Web services
Globus Toolkit
Defacto standardsGGF: GridFTP, GSI
X.509,LDAP,FTP, …
App-specificServices
• Data intensive -> knowledge intensive• Open services-based architecture• Recognises Web services• Global Grid Forum• Industry participation
(based on Foster GGF7 Plenary)
Open Grid Services Architectureongoing since early 2002
Standard mechanisms for describing and invoking services: WSDL, SOAP, WS-Security etc
Standard interfaces and behaviours for distributed systems: naming, service state, lifetime management, notification
Standard services: agreement, data access and integration, workflow, security, policy…
Specific services: drug discovery pipeline
OGSA
OGSI
Web Services
Grid Applications
(Graphic courtesy of Savas Parastatidis )
OGSI: Standard Web Services Interfaces & Behaviours Naming and bindings (basis for virtualization)
Every service instance has a unique name (Grid Service Handle) from which can discover supported bindings which are volatile (Grid Service Reference)
Two tiered naming scheme to cope with service migration and failover
Lifecycle (basis for fault resilient state management) Service instances created by factories Destroyed explicitly or via soft state
Information model (basis for monitoring & discovery) Service data (attributes) associated with GS instances (SDEs) Operations for querying (introspecting) and setting this info Asynchronous notification of changes to service data
Service Groups (basis for registries & collective services) Group membership rules & membership management
Base Fault type All sound kind of familiar?
OGSI
Implementation
Servicedata
element
Other standard interfaces:factory,
notification,collections
Hosting environment/runtime(“C”, J2EE, .NET, …)
Servicedata
element
Servicedata
element
GridService(required)
Dataaccess
Lifetime management• Explicit destruction• Soft-state lifetime
Introspection:• What port types?• What policy?• What state?
Client
Grid ServiceHandle
Grid ServiceReference
handleresolution
(Slide courtesy of Ian Foster)
Service registry
Service requestor (e.g. user application)
Service factory
Create Service
Grid Service Handle
Resource allocation
Service instances
Register Service
Service discovery
Interactions standardized using WSDL
Service data Keep-alives Notifications Service invocation
Authentication & authorization are applied to all requests
OGSI
(Slide courtesy of Ian Foster)
Service Migration
Hosting Environment B
GSH...
hdl:1.2/abc...
GSR...
<wsdl>...
Service
Hosting Environment A
Service1. Service Migration
RequesterHandleResolver
2. new network endpoint (GSR) registration for
same GSH
3. failed access with old network
endpoint info (old GSR)
6. successful access to moved service throughnew GSR
5. new GSR with new network endpoint
4. findByHandle(GSH) GSHhdl:1.2/abc
GSR<wsdl>
Service Locator
(Slide courtesy of Ian Foster)
Sound familiar?
Layering a component-based distributed object model over a web service framework
Early OGSI implementations Globus Toolkit 3 OGSI.NET OGSI::Lite Unicore
Web ServicesLoose coupled, stateless, persistent
CORBATightly coupled, naming, stateful,
lifetime management
Grid ServicesRobust naming, stateful,
lifetime management
OGSI Status and Issues
OGSI version 1.0 in GGF proposed recommendation
Issue: compliance to Web Service Standards GWSDL changes WSDL 1.1 by
extending portType syntax to define a Service Data Element.
Why not use WS standards for state management idioms: e.g. WS-Context/Coordination?
By eliminating a new mandatory infrastructure (OGSI), can use conventional tooling.
But it needs to meet the requirements of Grid
Service Implementation
OGSA Operations
Service specific
operations
WS-Context and/or
other WS-*
https://forge.gridforum.org/projects/ogsi-wg
(Graphic courtesy of Savas Parastatidis)
300 pound gorillas
If you want to use standards then you have to use them or work with them
W3C and OASIS are big gorillas
E.g. GSH/GSR, Handle.net, Life Science Identifer and WS-address
Grid Applications On The MoveThe rise of the Information Grid
Large scale dataLarge number of machinesComputationally intensiveSimple semanticsSmall homogeneous communities
Smaller scale dataData intensiveComplex heterogeneous applicationsComplex semanticsLarge diverse communities
High Energy Physics Functional GenomicsOceanographyBiodiversityEarth ScienceNeuroscience …
Data-intensive integration:what the e-scientist REALLY wants Scientists do data
integration Actually they do
application and model integration too!
Cooperative information systems
Workflows Data virtualisation
Integrating Across Biological Systems
… & Types of Information
ID MURA_BACSU STANDARD; PRT; 429 AA.DE PROBABLE UDP-N-ACETYLGLUCOSAMINE 1-CARBOXYVINYLTRANSFERASEDE (EC 2.5.1.7) (ENOYLPYRUVATE TRANSFERASE) (UDP-N-ACETYLGLUCOSAMINEDE ENOLPYRUVYL TRANSFERASE) (EPT).GN MURA OR MURZ.OS BACILLUS SUBTILIS.OC BACTERIA; FIRMICUTES; BACILLUS/CLOSTRIDIUM GROUP; BACILLACEAE;OC BACILLUS.KW PEPTIDOGLYCAN SYNTHESIS; CELL WALL; TRANSFERASE.FT ACT_SITE 116 116 BINDS PEP (BY SIMILARITY).FT CONFLICT 374 374 S -> A (IN REF. 3).SQ SEQUENCE 429 AA; 46016 MW; 02018C5C CRC32; MEKLNIAGGD SLNGTVHISG AKNSAVALIP ATILANSEVT IEGLPEISDI ETLRDLLKEI GGNVHFENGE MVVDPTSMIS MPLPNGKVKK LRASYYLMGA MLGRFKQAVI GLPGGCHLGP RPIDQHIKGF EALGAEVTNE QGAIYLRAER LRGARIYLDV VSVGATINIM LAAVLAEGKT IIENAAKEPE IIDVATLLTS MGAKIKGAGT NVIRIDGVKE LHGCKHTIIP DRIEAGTFMI
Data on the Grid pre: OGSA
Chiefly files!
LDAP as a query language
No RDBMS access from Globus 1.1
MDS and MCAT catalogs
Honorable exception
Storage Resource Broker
“Support data-intensive applications that manipulate very large data sets by building upon object-relational database technology and archival storage technology”
OGSA-Data Access and IntegrationGGF OGSA-DAIS WG
Data Grid applications benefit from many lower level services: Data movement. Data Replication. Data Virtualisation Database access and
integration. Work underway on designing,
developing and standardising many core Grid Data Management services.
Designing services in a dynamic and heterogeneous environment is non-trivial,
Plenty to be done!!
OGSA-DAI Basic Services
OGSA-DAI Distributed Query
Database, Communication, OS… Technology
Resource Grid Infrastructure – OGSA…
Data Grid Infrastructure –Location, Delivery, Replication…
Clever semantic integration stuff here
Infrastructure Architecture
OGSA
OGSI: Interface to Grid Infrastructure
Data Intensive Applications for X-ology Research
Compute, Data & Storage Resources
Distributed
Simulation, Analysis & Integration Technology for X-ology
Data Intensive X-ology Researchers
Virtual Integration Architecture
Generic Virtual Data Access and Integration Layer
Structured DataIntegration
Structured Data Access
Structured Data Relational XML Semi-structured-
Transformation
Registry
Job Submission
Data Transport Resource Usage
Banking
Brokering Workflow
Authorisation
(Slide Courtesy Malcolm Atkinson, UK National e-Science Centre
OGSA-DAIS, OGSA-DAIS, OGSA-DAIT
DB2
Oracle 10g
Part of Globus Toolkit 3
Data can be XML, RDBMS and ODBMS
UK dominance
1a. Request to Registry for sources of data about “x”
1b. Registry responds with
Factory handle2a. Request to Factory for access to database
2c. Factory returns handle of GDS to client
3a. Client queries GDS with XPath, SQL, etc
3b. GDS interacts with database
3c. Results of query returned to client as XML
SOAP/HTTP
service creation
API interactions
Registry
Factory
2b. Factory creates GridDataService to manage access
Grid Data Service
Client
XML / Relational database
Data Access & Integration Services
Slide Courtesy Malcolm Atkinson, UK eScience Center
Virtual Data Concept Capture and manage information about
relationships among Data (of widely varying representations) Programs (& their execution needs) Computations (& execution
environments) Apply this information to, e.g.
Discovery: Data and program discovery Workflow: for organizing, locating,
specifying, & requesting data Explanation: provenance Planning and scheduling
mass = 200decay = WWstability = 1event = 8
mass = 200decay = WWstability = 1plot = 1
mass = 200decay = WWplot = 1
mass = 200decay = WWevent = 8
mass = 200decay = WWstability = 1
mass = 200decay = WWstability = 3
mass = 200
mass = 200decay = WW
mass = 200decay = ZZ
mass = 200decay = bb
mass = 200plot = 1
mass = 200event = 8
mass = 200decay = WWstability = 1LowPt = 20HighPt = 10000
Search for WW decays of the Higgs Boson for which only stable, final state particles are recorded?
Workflow by Rick Cavanaugh and Dimitri Bourilkov, University of Florida
Grid intelligence: semantics A gap between grid computing
endeavours and the vision of Grid computing
To support the full richness of the grid computing vision we need to explicitly assert & explicitly use semantics (knowledge) throughout the Grid software stack
The Grid has always had lots of semantics embedded in Schema and Directory services, and used by schedulers and brokers Globus MDS2 -> Globus Information
Service Condor ClassAds
Semantic Grid http://www.semanticgrid.org
Semantic Web Services -> Semantic Grid Services
GGF SEM-GRD RG bringing semantic web technologies and techniques to the Grid Ontologies & RDF
Knowledge Services
Semantic Information Services
Base Services: Data/computation Services
e-Scientist environment
Problem Solving Environments
Application PortalsCollaboratories
Grids are driven by metadata
The semantics might be buried but they are there nonetheless!
Grid Applications Operational know-how of the domain.
a query or workflow; the annotation of results, parameters, personal notes, provenance data describing sources and derivation paths of information, etc
Knowledge about the domain: its data and its processes
A Multi-Hierarchical Rock Classification Ontology (GSC)
Composition
Genesis
Fabric
Texture
Slide courtesy of Bertram Ludascher
Grids are driven by metadatathe semantics might be buried but they are there nonetheless!
Grid infrastructure the classification of
computational and data resources, performance metrics, job control; schema integration, workflow descriptions, resource brokering, resource scheduling, service state, event notification topics, typing service inputs and outputs, provenance trails; access rights to databases, personal profiles and security groupings; charging infrastructure …
problem solving selection and intelligent portals;
Managing and operating a Grid intelligently requires the
interpretation of knowledge about the state and properties of
Grid components, and their configurations for solving
problems
Knowledge permeates the GridData elementsService descriptions (service data elements)Protocols (e.g. policy, provisioning)
Semantics in myGrid http://www.mygrid.org.uk
Service discovery
Service discovery
Workflow construction
Workflow construction
Workflow discoveryWorkflow discovery
Semantic mark up of results and logs
Semantic mark up of results and logs
GridGridGrid
workflow executor(DAGman)Execution
WorkflowPlanning
Globus ReplicaLocation Service
Globus Monitoringand Discovery
Service
Information andModels
Metadata CatalogService
Resource Models
detector
Raw data
Co
nc
rete
Wo
rkfl
ow
High-level specs ofdesired results andintermediate data
products
Dy
na
mic
info
rma
tio
n
Request Manager
CurrentState
Generator
Submission andMonitoring System
AI-basedPlanner
Pegasus planning environment for LIGO Pulsar search
Slide courtesy of Jim Blyth
NJSNJSNJSNJS
BrokerBrokerBrokerBroker
Unicore BrokerUnicore Broker Globus BrokerGlobus Broker
IDBIDBTranslatorTranslator
FilterFilterOntology engineOntology engine
Resource DiscoveryResource DiscoveryServiceService
Delegates resource checkDelegates resource check
LookupLookupresourcesresources
Delegates Delegates translationtranslation Uses to drive Uses to drive
MDS searchMDS search
HierarchicalHierarchicalGrid SearchGrid Search
DiagramDiagramOf Broker Of Broker ArchitectureArchitecture
Grid Interoperability ProjectGrid Interoperability ProjectInteroperable Resource BrokerInteroperable Resource Broker
FilterFilter
Uses to Uses to Drive MDSDrive MDSSearchSearch
Nodal Nodal Grid SearchGrid Search
OtherOtherBrokersBrokers
Resource DiscoveryResource DiscoveryServiceService
Slide courtesy of John Brooke
Semantics for integration and scientific workflows “Semantic registration” of data sets; How to employ semantic information in data discovery, workflow
discovery, service discovery, data binding, query and workflow planning and execution;
Semantic matchmaking of grid resources to satisfy requirements of application components in workflows, and indeed substituting whole workflows;
Intelligent reasoners for grid computing (semantic matchmakers, planners, resource brokers, etc.) that exploit knowledge of scientific applications as well as grid resources;
Scientific workflow design and execution; Scientific workflow lifecycle & methodology (authoring,
publishing, discovering, personalising, enacting, validating, modifying of workflows)
The list goes on….
Semantic Grid
Web Services
GridSemantic
Web
Semantic Grid
Grid services
Semantic WebServices
Semantics for the Grid
Grid-ware Semantic Services
Semantic Grid
ClassicalWeb
ClassicalComputational Grid
SemanticWeb
Dat
a an
d S
eman
tics
com
plex
ity
Computational complexity
DynamicWeb
Info/DataWeb
Web Services
Grid Services
An attempt at a context picture
Reality Check!
Official production request of the CMS collaboration of 1,200,000 Monte Carlo simulation data with Grid resources.
“We encountered many problems during the run, and fixed many of them, including integration issues arising from the integration of legacy CMS software tools with Grid tools, bottlenecks arising from operating system limitations, and bugs in both the grid middleware and application software.
Every component of the software contributed to the overall "problem count" in some way. However, we found that with the current level of functionality, we were able to operate the US-CMS Grid with 1.0 FTE effort during quiescent times over and above normal system administration and up to 2.5 FTE during crises.”
“The Grid in Action: Notes from the Front” G. Graham,R. Cavanaugh, P. Couvares, A. DeSmet, M. Livny, 2003
Slide courtesy of Miron Livny
Benefits
Effort
Goal
IntraGrids You are here
One ofa kind… or here
Ok, what’s the reality? The Grid is in the same state as the Web
was 10 years ago Few production grids and not many killer
demos - something you couldn’t have done before.
Middleware hard to use and incomplete (and certainly not invisible!)
OGSA in its infancy. Varying degrees of maturity, but people
use it anyway! Deployment, research, development,
applications and standardisation all happening together
Danger of half-baked solutions, premature standardisation, a Grid Winter
Pioneering spirit! It’s the Wild West!!It’s all very
exciting and rather
daunting
Are you involved in Grid?
There is hardly a paper at OTM that isn’t relevant. But participation in Grid is largely from the “Grid
Community” When the database people came to town they
rocked it! But there are not so many that take part, and it’s the
vendors that dominate though there are many research problems to overcome.
Reinvention, muddle, confusion ensues. Why aren’t you involved?
Why you should be involved in Grid
Established communities can be hard work to get involved in the latest thing
DCOM, CORBA, WS…we have seen it all before! So your history is valuable. And its not just rehashing
your history either (crossing out agents and crayoning in grid ain’t gonna work!)
An amazing, open and active community. With tons of real applications and users who really
need this stuff. GridPP had better work!!
Some substantial industry and government backing.
Between community travellers Pioneers on tour!
The Web
The GridThe Semantic Web
WWW2002 Waikiki, Hawaii
SSDBM2003 ISWC2002 WWW2002 VLDB2003 OTM2003 AIMA2003
Grid Middleware On The Move
Open Service
Architecture
Data and Information
Grids
Semantic GridsSecond
Generation Grid
Computing
The Grid Needs You! Enlist Now!
http://www.ggf.org
The Grid
Now with added services architecture, data
management and semantics!!
