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Grids: Concepts, Technologies and Applications

Grids: Concepts, Technologies and Applications. Geoffrey Fox Computer Science, Informatics, Physics Pervasive Technology Laboratories Indiana University Bloomington IN 47401 April 25 2005 gcf@indiana.edu http://www.infomall.org. So what is a Grid?.

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Grids: Concepts, Technologies and Applications

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  1. Grids: Concepts, Technologies and Applications Geoffrey FoxComputer Science, Informatics, Physics Pervasive Technology Laboratories Indiana University Bloomington IN 47401 April 25 2005 gcf@indiana.edu http://www.infomall.org

  2. 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.

  3. Internet Scale Distributed Services • Grids use Internet technology and are distinguished by managing or organizing sets of network connected resources • Classic Web allows independent one-to-one access to individual resources • Grids integrate together and manage multiple Internet-connected resources: People, Sensors, computers, data systems • Organization can be explicit as in • TeraGrid which federates many supercomputers; • Deep Web Technologies IR Grid which federates multiple data resources; • CrisisGrid which federates first responders, commanders, sensors, GIS, (Tsunami) simulations, science/public data • Organization can be implicit as in Internet resources such as curated databases and simulation resources that “harmonize a community”

  4. Different Visions of the Grid • Grid just refers to the technologies • Or Grids represent the full system/Applications • DoD’s vision of Network Centric Computing is just a Grid (linking sensors, warfighters, commanders, backend resources) and they are building the GIG (Global Information Grid) • Utility Computing or X-on-demand (X=data, computer ..) is major computer Industry interest in Grids • e-Science or Cyberinfrastructure are virtual organization Grids supporting global distributed science (note sensors, instruments are people are all distributed • Skype (Kazaa) VOIP system is a Peer-to-peer Grid (and VRVS/GlobalMMCS like Internet A/V conferencing are Collaboration Grids) • Commercial 3G Cell-phones and DoD ad-hoc network initiative are forming mobile Grids

  5. e-moreorlessanything 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 e-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

  6. More Broad Classes of Grid Applications • 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 …

  7. e-Defense and e-Crisis • Grids support Command and Control and provide Global Situational Awareness • Link commanders and frontline troops to themselves and to archival and real-time data; link to what-if simulations • Dynamic heterogeneous wired and wireless networks • Security and fault tolerance essential • System of Systems; Grid of Grids • The command and information infrastructure of each ship is a Grid; each fleet is linked together by a Grid; the President is informed by and informs the national defense Grid • Grids must be heterogeneous and federated • Crisis Management and Response enabled by a Grid linking sensors, disaster managers, and first responders with decision support

  8. Types of Computing Grids • Running “Pleasing Parallel Jobs” as in United Devices, Entropia (Desktop Grid) “cycle stealing systems” • Can be managed (“inside” the enterprise as in Condor) or more informal (as in SETI@Home) • Computing-on-demand in Industry where jobs spawned are perhaps very large (SAP, Oracle …) • Support distributed file systems as in Legion (Avaki), Globus with (web-enhanced) UNIX programming paradigm • Particle Physics will run some 30,000 simultaneous jobs • Linking Supercomputers as in TeraGrid • Pipelinedapplications linking data/instruments, compute, visualization • Seamless Access where Grid portals allow one to choose oneof multiple resources with a common interfaces

  9. Utility and Service Computing • An important business application of Grids is believed to be utility computing • Namely support a pool of computers to be assigned as needed to take-up extra demand • Pool shared between multiple applications • Natural architecture is not a cluster of computers connected to each other but rather a “Farm of Grid Services” connected to Internet and supporting services such as • Web Servers • Financial Modeling • Run SAP • Data-mining • Simulation response to crisis like forest fire or earthquake • Media Servers for Video-over-IP • Note classic Supercomputer use is to allow full access to do “anything” via ssh etc. • In service model, one pre-configures services for all programs and you access portal to run job with less security issues

  10. 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 • Education Grids link teachers, learners, parents as a VO with learning tools, distant lectures etc. • e-Science Grids link multidisciplinary researchers across laboratories and universities • 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

  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. Field Trip Data Database ? GISGrid Discovery Services RepositoriesFederated Databases Streaming Data Sensors Database Sensor Grid Database Grid Research Education SERVOGrid Compute Grid Customization Services From Researchto Education Data FilterServices ResearchSimulations Analysis and VisualizationPortal EducationGrid Computer Farm Grid of Grids: Research Grid and Education Grid

  13. iSERVO in a nutshell • Designed to link data-sets (repositories and real time), computations and earthquake scientists in ACES (Asia Pacific) Cooperation • Australia China Japan USA • Exemplified by SERVOGrid in USA led by JPL • Supports simulation and datamining as services • Adopts conservative WS-I+ Web Service Interoperability standards • Builds full “Grid” in a library fashion as a Grid of Grids • GIS (Geographic Information System) Grid built as a set of OGC compatible Web Services “talking” GML • iSERVO federates separate Grids in each country/organization/function • A Grid is “just” a collection of Services aka distributed programs • Multi-scale simulations supported by Grid workflow • Portals based on NSF Middleware Initiative NMI Open Grid Computing Environment OGCE

  14. DAME In flight data ~5000 engines ~ Gigabyte per aircraft per Engine per transatlantic flight Global Network Such as SITA Ground Station Airline Engine Health (Data) Center Maintenance Centre Internet, e-mail, pager Rolls Royce and UK e-Science ProgramDistributed Aircraft Maintenance Environment

  15. It takes a distributed virtual organization to design, simulate and build a complex system like an aircraft NASA Aerospace Engineering Grid

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

  17. e-Chemistry LaboratoryExperiments-on-demand Grid-enabled Output Streams Grid Resources

  18. CERN LHC Data Analysis Grid

  19. Data Data Filter Filter Filter Data Filter Data OGSA-DAIGrid Services AnalysisControl Visualize Grid Data Filter This Type of Grid integrates with Parallel computing Multiple HPC facilities but only use one at a time Many simultaneous data sources and sinks HPC Simulation Grid Data Assimilation Other Gridand Web Services Distributed Filters massage data For simulation SERVOGrid (Complexity) Computing Model

  20. Sources of Grid Technology • Grids support distributed collaboratories or virtual organizations integrating concepts from • The Web • Agents • Distributed Objects(CORBA Java/Jini COM) • Globus, Legion, Condor, NetSolve, Ninf and other High Performance Computing activities • Peer-to-peer Networks • With perhaps the Web and P2P networks being the most important for “Information Grids” and Globus for “Compute Grids”

  21. The Essence of Grid Technology? • We will start from the Web view and assert that basic paradigm is • Meta-data rich Web Services communicating via messages • These have some basic support from some runtime such as .NET, Jini (pure Java), Apache Tomcat+Axis (Web Service toolkit), Enterprise JavaBeans, WebSphere (IBM) or GT3/4 (Globus Toolkit 3/4) • These are the distributed equivalent of operating system functions as in UNIX Shell • Called Hosting Environment or platform • W3C standard WSDL defines IDL (Interface standard) for Web Services

  22. Meta-data • Meta-data is usually thought of as “data about data” • The Semantic Web is at its simplest considered as adding meta-data to web pages • For example, the hospital web-page has meta-data telling you its location, phone-number, specialties which can be used to automate Google-style searches to allow planning of disease/accident treatment from web • Modern trend (Semantic Grid) is meta-data about web-services e.g. specify details of interface and useage • Such as that a bioinformatics service is free or bandwidth input is of limited amount • Provenance – history and ownership – of data very important

  23. 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

  24. Portal Services SystemServices SystemServices Application Service Middleware SystemServices SystemServices SystemServices Raw (HPC) Resources Database Typical Grid Architecture Each Blob is a Computer Program! UserServices “Core”Grid

  25. 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

  26. 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

  27. What is Happening? • Grid ideas are being developed in (at least) four communities • Web Service – W3C, OASIS, (DMTF) • Grid Forum (High Performance Computing, e-Science) • Enterprise Grid Alliance (Commercial “Grid Forum” with a near term focus) • Service Standards are being debated • Grid Operational Infrastructure is being deployed • Grid Architecture and core software being developed • Apache has several important projects as do academia; large and small companies • Particular System Services are being developed “centrally” – OGSA framework for this in GGF; WS-* for OASIS/W3C/Microsoft-IBM • Lots of fields are setting domain specific standards and building domain specific services • USA started but now Europe is probably in the lead and Asia will soon catch USA if momentum (roughly zero for USA) continues

  28. Technical Activities of Note • Look at different styles of Grids such as Autonomic(Robust Reliable Resilient) • New Grid architectures hard due to investment required • Program the Grid – Workflow • Access the Grid – Portals, Grid Computing Environments • Critical Services Such as • Security – build message based not connection based • Notification – event services • Metadata – Use Semantic Web, provenance • Fabric and Service Management • Databases and repositories – instruments, sensors • Computing – Submit job, scheduling, distributed file systems • Visualization, Computational Steering • Network performance Low Level WS-* High Level e.g. OGSA

  29. Web services • Web Services build loosely-coupled, distributed applications, (wrapping existing codes and databases) based on the SOA (service oriented architecture) principles. • Web Services interact by exchanging messages in SOAP format • The contracts for the message exchanges that implement those interactions are described via WSDL interfaces.

  30. Philosophy of Web Service Grids • Much of Distributed Computing was built by natural extensions of computing models developed for sequential machines • This leads to the distributed object (DO) model represented by Java and CORBA • RPC (Remote Procedure Call) or RMI (Remote Method Invocation) for Java • Key people think this is not a good idea as it scales badly and ties distributed entities together too tightly • Distributed Objects Replaced by Services • Note CORBA was considered too complicated in both organization and proposed infrastructure • and Java was considered as “tightly coupled to Sun” • So there were other reasons to discard • Thus replace distributed objects by services connected by “one-way” messages and not by request-response messages

  31. Plethora of Standards • Java is very powerful partly due to its many “frameworks” that generalize libraries e.g. • Java Media Framework • Java Database Connectivity JDBC • Web Services have a correspondingly collections of specifications that represent critical features of the distributed operating systems for “Grids of Simple Services” • About 60 WS-* specifications introduced in last 2-3 years • These are low level with higher level standards such as access database (OGSA-DAI) or “Submit a job” built on top of these • Many battles both between standard bodies and between companies as each tries to set standards they consider best; thus there are multiple standards for many of key Web Service functionalities • Microsoft a key player and stands to benefit as Web Services open up enterprise software space to all participants • e.g. MQSeries (IBM) and Tibco have to change their messaging systems to support new open standards

  32. WS-I Interoperability • Critical underpinning of Grids and Web Services is the gradually growing set of specifications in the Web Service Interoperability Profiles • Web Services Interoperability (WS-I) Interoperability Profile 1.0a." http://www.ws-i.org. gives us XSD, WSDL1.1, SOAP1.1, UDDI in basic profile and parts of WS-Security in their first security profile. • We imagine the “60 Specifications” being checked out and evolved in the cauldron of the real world and occasionally best practice identifies a new specification to be added to WS-I which gradually increases in scope • Note only 4.5 out of 60 specifications have “made it” in this definition

  33. Application Specific Grids Generally Useful Services and Grids Workflow WSFL/BPEL Service Management (“Context etc.”) Service Discovery (UDDI) / Information Service Internet Transport  Protocol Service Interfaces WSDL Higher Level Services ServiceContext ServiceInternet Base Hosting Environment Protocol HTTP FTP DNS … Presentation XDR … Session SSH … Transport TCP UDP … Network IP … Data Link / Physical Bit level Internet (OSI Stack) Layered Architecture for Web Services and Grids

  34. WS-* implies the The Service Internet • We have the classic (CISCO, Juniper ….) Internet routing the flood of ordinary packets in OSI stack architecture • Web Services build the “Service Internet” or IOI (Internet on Internet) with • Routing via WS-Addressing not IP header • Fault Tolerance (WS-RM not TCP) • Security (WS-Security/SecureConversation not IPSec/SSL) • Data Transmission by WS-Transfer not HTTP • Information Services (UDDI/WS-Context not DNS/Configuration files) • At message/web service level and not packet/IP address level • Software-based Service Internet possible as computers “fast” • Familiar from Peer-to-peer networks and built as a software overlay network defining Grid (analogy is VPN) • SOAP Header contains all information needed for the “Service Internet” (Grid Operating System) with SOAP Body containing information for Grid application service

  35. Consequences of Rule of the Millisecond • Useful to remember critical time scales • 1) 0.000001 ms – CPU does a calculation • 2a) 0.001 to 0.01 ms – Parallel Computing MPI latency • 2b) 0.001 to 0.01 ms – Overhead of a Method Call • 3) 1 ms – wake-up a thread or process • 4) 10 to 1000 ms – Internet delay • 2a), 4) implies geographically distributed metacomputing can’t in general compete with parallel systems • 3) << 4) implies a software overlay network is possible without significant overhead • We need to explain why it adds value of course! • 2b) versus 3) and 4) describes regions where method and message based programming paradigms important

  36. Closely coupled Java/Python … Coarse Grain Service Model Service B Service A Module B Module A Messages Service B Service A 0.1 to 1000 millisecond latency Method Calls.001 to 1 millisecond Linking Modules • From method based to RPC to message based to event-based publish-subscribe Message Oriented Middleware “Listener”Subscribe to Events Publisher Post Events Message Queue in the Sky

  37. What is a High Performance Computer? • We might wish to consider three classes of multi-node computers • 1) Classic MPP with microsecond latency and scalable internode bandwidth (tcomm/tcalc ~ 10 or so) • 2) Classic Cluster which can vary from configurations like 1) to 3) but typically have millisecond latency and modest bandwidth • 3) Classic Grid or distributed systems of computers around the network • Latencies of inter-node communication – 100’s of milliseconds but can have good bandwidth • All have same peak CPU performance but synchronization costs increase as one goes from 1) to 3) • Cost of system (dollars per gigaflop) decreases by factors of 2 at each step from 1) to 2) to 3) • One should NOT use classic MPP if class 2) or 3) suffices unless some security or data issues dominates over cost-performance • One should not use a Grid as a true parallel computer – it can link parallel computers together for convenient access etc.

  38. What is a Simple Service? • Take any system – it has multiple functionalities • We can implement each functionality as an independent distributed service • Or we can bundle multiple functionalities in a single service • Whether functionality is an independent service or one of many method calls into a “glob of software”, we can always make them as Web services by converting interface to WSDL • Simple services are gotten by taking functionalities and making as small as possible subject to “rule of millisecond” • Distributed services incur messaging overhead of one (local) to 100’s (far apart) of milliseconds to use message rather than method call • Use scripting or compiled integration of functionalities ONLY when require <1 millisecond interaction latency • Apache web site has many projects that are multiple functionalities presented as (Java) globs and NOT (Java) Simple Services • Makes it hard to integrate sharing common security, user profile, file access .. services

  39. CPUs Clusters Compute Resource Grids Overlay and Compose Grids of Grids MPPs Methods Services Component Grids Federated Databases Databases Data Resource Grids Sensor Sensor Nets Grids of Grids of Simple Services • Link via methods  messages  streams • Services and Grids are linked by messages • Internally to service, functionalities are linked by methods • A simple service is the smallest Grid • We are familiar with method-linked hierarchyLines of Code  Methods  Objects  Programs  Packages

  40. Component Grids? • So we build collections of Web Services which we package as component Grids • Visualization Grid • Sensor Grid • Utility Computing Grid • Person (Community) Grid • Earthquake Simulation Grid • Control Room Grid • Crisis Management Grid • We build bigger Grids by composing component Grids using the Service Internet

  41. Gas CIGrid Flood CIGrid … … Gas Servicesand Filters Flood Servicesand Filters Electricity CIGrid Portals Collaboration Grid Visualization Grid Sensor Grid GIS Grid Compute Grid Data Access/Storage Registry Metadata Core Grid Services Physical Network Security Notification Workflow Messaging Critical Infrastructure (CI) Grids built as Grids of Grids

  42. Service Data Two-level Programming I • The paradigm implicitly assumes a two-level Programming Model • We make a Service (same as a “distributed object” or “computer program” running on a remote computer) using conventional technologies • C++ Java or Fortran Monte Carlo module • Data streaming from a sensor or Satellite • Specialized (JDBC) database access • Such services accept and produce data from users files and databases • The Grid is built by coordinating such services assuming we have solved problem of programming the service

  43. Service1 Service3 Service2 Service4 Two-level Programming II • The Grid is discussing the composition of distributed serviceswith the runtime interfaces to Grid as opposed to UNIX pipes/data streams • Familiar from use of UNIX Shell, PERL or Python scripts to produce real applications from core programs • Such interpretative environments are the single processor analog of Grid Programming • Some projects like GrADS from Rice University are looking at integration between service and composition levels but dominant effort looks at each level separately

  44. What Should One Do? • Grids and Service Oriented Architectures will • Change landscape in mature areas like enterprise software • Support new distributed applications in Science, Government, Education, Business and Community areas • Encourage trends like outsourcing and globalization in all activities • Web Service/Grid standards and infrastructure are still in their infancy but broad principles reasonably clear • Many large scale software development activities are inconsistent with modern architectures • Development of Application specific (XML-based) standards is an important “safe” area

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