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S-Matrix and the Grid - Community Grids Lab

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					  S-Matrix and the Grid
                  Geoffrey Fox
Professor of Computer Science, Informatics, Physics
        Pervasive Technology Laboratories
     Indiana University Bloomington IN 47401
                December 12 2003

                 gcf@indiana.edu
              http://www.infomall.org
                                                      1
                    S-Matrix and PWA
   We need an amplitude analysis to find most “interesting” resonances
   If this makes sense, we are effectively parameterizing photon-Reggeon
    amplitude with resonance at “top” vertex in full (123 in diagram) or
    partial (12, 23, 31) channel
     • Complicated as off diagonal, one “fake” particle and often more
        than 2 final particles
   This requires a lot of approximations whose effect can be estimated
    with S-Matrix Theory
     • Analyticity, Unitarity, Crossing, Regge Theory, Spin formalism,
        Duality, Finite Energy Sum Rules
                                              Regge in Top Vertex    1
                                    
                              Reggeon                                    2
Exchange                    Exchange for
                             Production
Target                                                               3
                                                                            2
     Some Lessons from the past I
   All confusing effects exist and no fundamental (correct) way to
    remove. So one should:
     • Minimize effect of the hard (insoluble) problems such as
       “particles from wrong vertex”, “unestimatable exchange
       effects” sensitive to slope of unclear Regge trajectories,
       absorption etc.
     • Carefully identify where effects are “additive” and where
       confusingly overlapping
   Note many of effects are intrinsically MORE important in
    multiparticle case than in relatively well studied π N  π N
   Try to estimate impact of uncertainties from each effect on results
     • It would be very helpful to get systematic very high statistic
       studies of relatively clean cases where spectroscopy may be less
       interesting but one can examine uncertainties
     • Possibilities are A1 A2 A3 B1 peripherally produced and even π
       N  π π N; K or π beams good
                                                                     3
                S-Matrix Approach
   S-Matrix ideas that work reasonably include:
   Regge theory for production process
   Two-component duality adding Regge dual to Regge to
    background dual to the Pomeron
    • Can help to identify if a resonance is classic qq or exotic
   Use of Regge exchange at top vertex to estimate high
    partial waves in amplitude analysis
   Finite Energy Sum Rules for top vertex as constraints
    on low mass amplitudes and most quantitative way of
    linking high and low masses
   Ignore Regge Cuts in Production
   Unitarity effects not included directly due to duality
    double counting                                                 4
         Investigate Uncertainties
   There are several possible sources of error
     • Errors in Quasi 2-body and limited number of amplitudes
       approximation
     • Unitarity (final state interactions)
     • Errors in the two-component duality picture
     • Exotic particles are produced and are just different
     • Photon beams, π exchange or some other “classic effect” not
       present in original πN analyses behaves unexpectedly
     • Failure of quasi two body approximation
     • Regge cuts cannot be ignored
     • Background from other channels
   Develop tests for these in both “easy” cases (such as “old” meson
    beam data) and in photon beam data at Jefferson laboratory
     • Investigate all effects on any interesting result from PWA
                                                                    5
    Grid Computing: Making The Global
          Infrastructure a Reality
   Note book with
    Fran Berman and
    Anthony J.G. Hey,
   ISBN: 0-470-85319-0
   Hardcover 1080 Pages
   Published March 2003
   http://www.grid2002.org
   I had more fun in days gone by; no
    more do I write
   “Skeletons in the Regge
    Cupboard” or
   “The Importance of being an
    Amplitude”                           6
                  Some Further Links
   A talk on Grid and e-Science was webcast in an Oracle
    technology series
    http://webevents.broadcast.com/techtarget/Oracle/100303/index.asp?loc=10
   See also the “Gap Analysis” survey of Grid technology
    http://grids.ucs.indiana.edu/ptliupages/publications/GapAnalysis30June03v2.pdf
   This presentation is at
    http://grids.ucs.indiana.edu/ptliupages/presentations
   Next Semester – course on “e-Science and the Grid”
    given by Access Grid
   Write up for May Conference describes proposed
    Physics Strategy
    http://grids.ucs.indiana.edu/ptliupages/publications/gluonic_gcf.pdf
    http://grids.ucs.indiana.edu/ptliupages/presentations/pwamay03.ppt


                                                                                     7
    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                           8
    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.
                                                                     9
      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”
   Service Architecture based on Web Services most
    critical feature
                                                       10
Typical Grid Architecture

                              Portal        User
                             Services     Services


          System            Application          System
          Services            Service            Services

                            Middleware

          System             System           System
          Services           Services         Services
 “Core”
  Grid
                                     Raw (HPC)
                                     Resources       Database
                                                            11
             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

       Web Services                                     Payment
                                                       Credit Card
                              WSDL interfaces

            Portal
            Service        Security         Catalog


                          WSDL interfaces              Warehouse
        Web Services                                   Shipping
                                                        control
                                                                     12
            What is Happening?
   Grid ideas are being developed in (at least) two
    communities
    • Web Service – W3C, OASIS
    • Grid Forum (High Performance Computing, e-Science)
   Service Standards are being debated
   Grid Operational Infrastructure is being deployed
   Grid Architecture and core software being developed
   Particular System Services are being developed
    “centrally” – OGSA framework for this in
   Lots of fields are setting domain specific standards and
    building domain specific services
   There is a lot of hype
   Grids are viewed differently in different areas
    • Largely “computing-on-demand” in industry (IBM, Oracle,
      HP, Sun)
    • Largely distributed collaboratories in academia        13
        Technical Activities of Note
   Look at different styles of Grids such as Autonomic (Robust
    Reliable Resilient)
   New Grid architectures hard due to investment required
   Critical Services Such as
     • Security – build message based not connection based
     • Notification – event services
     • Metadata – Use Semantic Web, provenance
     • Databases and repositories – instruments, sensors
     • Computing – Submit job, scheduling, distributed file
       systems
     • Visualization, Computational Steering
     • Fabric and Service Management
     • Network performance
   Program the Grid – Workflow
   Access the Grid – Portals, Grid Computing Environments
                                                            14
        Issues and Types of Grid Services
       1) Types of Grid                               7) Information Grid Services
    •        R3                                          • OGSA-DAI/DAIT
    •        Lightweight                                 • Integration with compute resources
    •        P2P                                         • P2P and database models
    •        Federation and Interoperability
       2) Core Infrastructure and Hosting             8) Compute/File Grid Services
        Environment                                      • Job Submission
    •        Service Management                          • Job Planning Scheduling
    •        Component Model                                 Management
    •        Service wrapper/Invocation                  • Access to Remote Files, Storage and
    •        Messaging                                       Computers
       3) Security Services                             • Replica (cache) Management
    •        Certificate Authority                       • Virtual Data
    •        Authentication                              • Parallel Computing
    •        Authorization
    •        Policy                                    9) Other services including
       4) Workflow Services and Programming             • Grid Shell
           Model                                         • Accounting
    •        Enactment Engines (Runtime)                 • Fabric Management
    •        Languages and Programming                   • Visualization Data-mining and
    •        Compiler                                        Computational Steering
    •        Composition/Development                     • Collaboration
       5) Notification Services                       10) Portals and Problem Solving
       6) Metadata and Information Services                Environments
    •        Basic including Registry
    •        Semantically rich Services and meta-      11) Network Services
             data                                        • Performance
    •        Information Aggregation (events)            • Reservation
                                                                                            15
    •        Provenance                                  • Operations
    OGSA OGSI & Hosting Environments
   Start with Web Services in a hosting environment
   Add OGSI to get a Grid service and a component model
   Add OGSA to get Interoperable Grid “correcting” differences in base platform
    and adding key functionalities



                  Not OGSA                    Domain -specific services


                                          More specialized services: data
               Possibly OGSA              replication, workflow, etc., etc.

                                        Broadly applicable services: registry,
                  OGSA                     authorization, monitoring, data
                                                 access, etc., etc.
                Environment
                                             OGSI on Web Services

                                           Hosting Environment for WS
       Given to us from on high
                                                     Network                     16
    Integration of Data and Filters
   One has the OGSA-DAI Data repository interface
    combined with WSDL of the (Perl, Fortran, Python
    …) filter
   User only sees WSDL not data syntax
   Some non-trivial issues as to where the filtering
    compute power is
    • Microsoft says filter next to data

                 WSDL                      OGSA-DAI
                             Filter
                                                       DB
                 Of Filter                 Interface



                                                            17
    Remote Grid Service                                 Remote Grid Service



10: Job                1: Job Management Service
Status       (Grid Service Interface to user or program client)

                 1: Plan Execution                  4: Job Submittal


                         2: Schedule and control Execution

                                                                         8: Virtual
                          3: Access to Remote Computers
                                                                            Data



                   7: Cache                             6: File and
          Data       Data        5: Data Transfer        Storage
                   Replicas                               Access        Data

           9: Grid MPI
                               Technology Components of (Services in)
                                        a Computing Grid                          18
                   Grid Strategy
   LHC Computing will be very well established and
    handling 10-100 times as much data as GlueX when we
    need to go into production
   GriPhyn iVDGL EDG EGEE PPDG GridPP will
    customize core Grid technology for accelerator-based
    experiments
    • Transport Data
    • Cache Data
    • Manage initial data analysis and Monte Carlo
   Not clear if GT2, GT3, OGSI but will certainly be Web
    Service based
   Need to keep in close touch with these activities
   Build GlueX physics analysis consistent with this
    infrastructure
                                                       19
                     Implementing Grids
    Need to design a service architecture for GlueX
      • Build on services from HEP and other fields
      • Need some specific gluexML meta-data specifying services
        and properties specific to GlueX
      • Specify data structures and method interfaces in XML
    Use portlets for user-interfaces as in http://www.ogce.org
    Break-up into services where-ever possible but only if
     “coarse-grain”
    Closely coupled Java/Python …      Coarse Grain Service Model

        Module      Module          Service                    Service
                                                Messages
          B           A               B                          A
           Method Calls              0.1 to 1000 millisecond latency
        .001 to 1 millisecond                                            20
Collage of Portals
                 Earthquakes – NASA
                 Fusion – DoE
                 OGCE Components – NSF
                 Publications -- CGL




                                21
                                                 Application WS
                        Approach
   Convert every code into a Web Service
   Convert every utility like
    “visualization” into a Web service               WS linking
                                                     to user and
   Have good support for authoring and               Other WS
                                                   (data sources)
    manipulating meta-data
   Use existing code/database technology
    (SQL/Fortran/C++) linked to “Application
    Web/OGSA services”
                                                      Typical
     • XML specification of models,                   codes
       computational steering, scale supported
       at “Web Service” level as don’t need
       “high performance” here
     • Allows use of Semantic Grid technology
                                                                    22
      User
    Services         Portal              Grid
                    Services
                                      Computing
                                     Environments
                  Visualization
Modeling             Service       Fitting
Services                           Service
                  Data Access
     Middleware     Service

System            System          System
                                              “Core”
Services          Services        Services     Grid
                                             (Globus)
                         Raw Data and
                           Compute
                          Resources Database
                                                        23
CERN LHC Data Analysis Grid




                              24

				
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