Introduction to Grids for CTS05 GlobalMMCS Tutorial

1. Introduction to Grids for CTS05 GlobalMMCS Tutorial CTS05 St. Louis May 17 2005 Geoffrey Fox CTO Anabas Corporation and Computer Science, Informatics, Physics Pervasive Technology Laboratories Indiana University Bloomington IN 47401 gcf@indiana.edu http://www.infomall.org

2. Summary • This presentation describes Grids as they are being developed to support commercial enterprise and research (e-Science) applications • We explain the Web Service Grid architecture • We develop the Grid of Grids concepts and suggest one important subgrid is a Collaboration Grid • We contrast typical (today’s Grid) “compute/file” operation with streaming data Grids needed to support both collaboration and sensor Grids • We discuss important component services in a collaboration Grid • We contrast DoD’s Network Centric Computing and its GiG architecture with current Grid technologies • We show how to make application Web Services collaborative

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 can be considered 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 and this is key part of enterprise or campus 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. 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

7. 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 • Typically Compute/File Grids where information (messages) exchanged by writing and reading files • Knowledge and Information Grids link sensors and information repositories as in Virtual Observatories or BioInformatics • 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 • Collaboration Grids support the linkage of multiple people and electronic resources (often peer-to-peer architecture)

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. 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

11. 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

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

13. 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

14. 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/File Grids”

15. 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

16. 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

17. 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

18. 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

19. 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

20. 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

21. 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

22. 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

23. 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 SOAPformat • The contracts for the message exchanges that implement those interactions are described via WSDL interfaces.

24. 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

25. Plethora of Standards • Javais 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

26. 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, UDDIin 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

27. 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

28. WS-* implies 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

29. 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

30. 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 (pre Web Service) 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

31. 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

32. Component Grids? • So we build collections of Web Services which we package as component Grids • Visualization Grid • Sensor Grid • Utility Computing Grid • Collaboration Grid • Earthquake Simulation Grid • Control Room Grid • Crisis Management Grid • Intelligence Data-mining Grid • We build bigger Grids by composing component Grids using the Service Internet

33. 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

34. The WS-* Infrastructure • Core Grid Services build on and/or extend the 60 or so WS-* Infrastructure specifications which define • Container Model, XML, WSDL … • Service Internet ( (Reliable) Messaging, Addressing) including extensions for high performance transport and representation. This is natural basis for streaming applications • Service Discovery • Workflow and Transactions • Security • Metadata and State including lifetime • Notification • Policy, Agreements • Management (service interactions) • Portals and User Interfaces

35. Core (Commonly Used) Grid Services (OGSA) • Higher level discovery and metadata – Registries, catalogs, Semantic Grid, Provenance • Higher level security with fine grain authorization, session level security etc. • Higher level execution services building on workflow and including job management for simulations • Infrastructure services giving common interfaces to heterogeneous resource such as storage and computers • Data and Information services including federated databases and use of CIM • Self and distributed (resource) management for autonomic features, configuration • Not OGSA: Collaboration, Sensors, Visualization, GIS

36. TTV Emerging Technology Categories Mission-Specific Applications Information Assurance Policy-Based Management Collaborative Computing* Autonomous Computing* Grid Computing* Service Oriented Computing* Computing Infrastructure Transport Infrastructure Information Modeling Data Strategy * Sub-categories of Computing Infrastructure Relation to GiG Architecture • GiG and NCOW (Net-Centric Operations and Warfare) define services and laud SOA but don’t seem to use either industry or GGF “stacks” • Note Grids and “Service Oriented Computing” placed as part of computing infrastructure – I think this is inappropriate • Identified features can be mapped to previous Grid service categories

37. NCOW Reference Model • All of these areas and their defined sub-areas are naturally defined as services

38. NCES: Network Centric Enterprise Services I

39. NCES: Network Centric Enterprise Services II

40. Implications for Collaboration Grids • As with all Grids, we will use a SOA and identify what core Grid (WS) services one needs and build on top of this • Core collaboration interface specification XGSP • Common collaboration services such as session management and secure software multicast • Customized collaboration services in particular domains • Support asynchronous and synchronous collaboration • Most Grids naturally support asynchronous sharing • Need to see how to link to existing SIP and H323 capabilities • Need to examine current monolithic collaboration architectures and divide into simple services • MCU becomes multiple services

41. Collaboration and Web Services • Collaboration has • Mechanism to set up members (people, devices) of a “collaborative sessions” • Shared generic tools such as text chat, white boards, audio-video conferencing • Shared applications such as Web Pages, PowerPoint, Visualization, maps, (medical) instruments …. • b) and c) are “just shared objects” where objects could be Web Services but rarely are at moment • We can port objects to Web Services and build a general approach for making Web services collaborative • a) is a “Service” which is set up in many different ways (H323 SIP JXTA are standards supported by multiple implementations) – we should make it a WS

42. Shared Event Collaboration • All collaboration is about sharing events defining state changes • Audio/Video conferencing shares events specifying in compressed form audio or video • Shared display shares events corresponding to change in pixels of a frame buffer • Instant Messengers share updates to text message streams • Microsoft events for shared PowerPoint (file replicated between clients) as in Access Grid • Finite State Change NOT Finite State Machine architecture • Using Web services allows one to expose update events of all kinds as message streams • Need publish/subscribe approach to share messages (NB) plus • System to control “session” – who is collaborating and rules • XGSP is XML protocol for controlling collaboration building on H323 and SIP

43. Web Services and M-MVC • Web Services are naturally M-MVC – Message based Model View Controller with • Model is Web Service • Controller is Messages (NaradaBrokering) • View is rendering As Controller

44. Desktop and Web Services with MMVC • Most desktop applications are in fact roughly MVC with controller formed by “system interrupts” with View and Model communicating by “post an event” and define a “listener” programming mode • We propose to integrate desktop and Web Service approach by systematic use of MMVC and NaradaBrokering • Allows easier porting to diverse clients and automatic collaboration • Attractive for next generation of Linux desktop clients • We have demonstrated for SVG Browser (Scalable Vector Graphics), OpenOffice and PowerPoint • “Glob” programming style makes hard

45. Events Per 0.5 ms NB on RipvanwinkleNB on ViewNB on Model Mean ms Mean Mouseup Mean Mousemove Mean Mousedown 15 runs each split over 3 days

46. SM-MV Collaboration Shared Output portSingle Model, Multiple View SM-MV CollaborativeWeb Service XGSPSession Control

47. MM-MV Collaboration Shared Input portMultiple Model, Multiple View MM-MV Collaborative Web Service