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Dr. Frederica Darema

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Dynamic Data Driven Application Systems (Symbiotic Measurement&Simulation Systems) A new paradigm for application simulations and a new paradigm for measurement ... – PowerPoint PPT presentation

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Title: Dr. Frederica Darema


1
Dynamic Data Driven Application
Systems (Symbiotic MeasurementSimulation
Systems) A new paradigm for application
simulations and a new paradigm for measurement
systems
Dr. Frederica Darema NSF
2
Dynamic Data Driven Application Systems, are
  • New paradigm for application simulations, where
  • the applications can accept and respond
    dynamically to new data injected at execution
    time,
  • and reversely
  • New measurement methods, where
  • the application systems will have the ability to
    dynamically control the measurement processes
  • The synergistic and symbiotic feedback
    control-loop between simulations and measurements
    can open new domains in the capabilities of
    simulations with high potential pay-off
  • Will create applications with new and enhanced
    analysis and prediction capabilities
  • Will create a new methodology for more efficient
    and effective measurement process.
  • Great potential to transform the way science and
    engineering are done, and induce a major impact
    on manufacturing, commerce, transportation,
    hazard prediction/management, and medicine

3
New Paradigm
Simulations (Math.Modeling Phenomenology Observati
on Modeling Design)
Theory (First Principles)
Simulations (Math.Modeling Phenomenology)
Theory (First Principles)
Experiment Measurements Field-Data User
Experiment Measurements Field-Data User
Dynamic Feedback Control Loop
Challenges Application Simulations
Development Algorithms Computing Systems Support
4
Examples of Applications benefiting from the new
paradigm
  • Engineering (Design and Control)
  • aircraft design
  • oil exploration
  • semiconductor mfg
  • computing systems hardware and software design
  • (performance engineering)
  • Crisis Management
  • transportation systems (planning, accident
    response)
  • weather, hurricanes/tornadoes, floods
  • fire propagation
  • Medical
  • customized radiation treatment, x-rays, NMR,
    surgery, etc
  • epidemics
  • Manufacturing/Business/Finance
  • Supply Chain (Production Planning and Control)
  • Financial Trading (Stock Mkt, Portfolio Analysis)

5
Examples of Technology Challenges
  • Application development
  • interfaces of applications with measurement
    systems
  • dynamically select appropriate application
    components
  • ability to switch to different algorithms/componen
    ts depending on streamed data
  • Algorithms
  • tolerant to perturbations of dynamic input data
  • handling data uncertainties
  • Systems supporting such dynamic environments
  • performance engineering technology
  • application development and run-time support

6
Enabling DDDAS
Dynamic Data-Driven Application
Systems -- Symbiotic MeasurementSimulation Syste
ms
Dynamic Compilers Application Composition
Performance Engineering
7
Enabling DDDAS
Dynamic Data-Driven Application
Systems -- Symbiotic MeasurementSimulation Syste
ms
Dynamic Compilers Application Composition
Performance Engineering
8
Distributed Systems Software/Hardware
Architectural Framework
Distributed Applications
Collaboration
Visualization
Environments
Authenication
/
Scalable I/O
Data Management
Authorization
Archiving/Retrieval
Dependability
Performance Engineered Design
Technology
Services
Services
. . .
Other Services
Distributed Systems Management
Distributed, Heterogeneous, Dynamic, Adaptive
Computing Platforms and Networks
Components Technology
Device
CPU
Memory
. . .
Technology
Technology
Technology
9
Multiple views of the system The applications
view
Distributed Applications
. . .
Collaboration
Visualization
Environments
Authenication
/
Scalable I/O
Data Management
Authorization
IO / File
Archiving/Retrieval
Dependability
Models
Services
Services
. . .
Other Services
OS
Scheduler
Distributed Systems Management
Models
Architecture /
Distributed, Heterogeneous, Dynamic, Adaptive
Network
Computing Platforms and Networks
Models
Memory
Device
CPU
Memory
. . .
Models
Technology
Technology
Technology
10
Multiple views of the system The Operating
Systems view
Distributed Applications
. . .
Collaboration
Visualization
Environments
Authenication
/
Scalable I/O
Data Management
Authorization
Archiving/Retrieval
Dependability
Services
Services
. . .
Other Services
Distributed Systems Management
11
Enabling DDDAS
Dynamic Data-Driven Application
Systems -- Symbiotic MeasurementSimulation Syste
ms
Dynamic Compilers Application Composition
Performance Engineering
12
New Technology for an integrated feedback and
control compiling system
Application Model

Dynamic Analysis Situation
Distributed Programming Model
Application Program
Compiler Front-End
Application Intermediate Representation
Compiler Back-End
Launch Application (s)
Architecture Models
Dynamically Link Execute
Application Components
Distributed Computing Resources
Distributed Platform
Adaptable computing Systems Infrastructure
13
Enabling DDDAS
Dynamic Data-Driven Application
Systems -- Symbiotic MeasurementSimulation Syste
ms
Dynamic Compilers Application Composition
Performance Engineering
14
Relevant Agency Efforts
  • NSF
  • NGS The Next Generation Software Program
  • Funds Reseacrh on Performance Engineering, and
    Dynamic Compilation and Application Composition
    Technologies for Adaptive Runtime Support
  • SES Scalable Enterprise Systems
  • ITR Information Technology Research
  • In addition aiming to develop a DDDAS Program
  • Symbiotic, integrated simulations and
    measurements
  • leap-ahead initiative
  • will provide a focus for new exciting work in
    applications areas,
  • algorithms and in systems areas
  • Also DARPA, NASA, DoE interested in these programs

15
What about Industry
  • Industry has history of both
  • forging new research and technology directions
    and
  • adapting and productizing technology which has
    demonstrated promise
  • Need to strengthen the joint academe/industry
    research collaborations
  • joint projects / early stages
  • Technology transfer
  • establish path for tech transfer from academic
    research to industry
  • joint projects, students, sabbaticals (academe
    lt----gt industry)
  • Initiatives from the Federal Agencies / PITAC
    Report
  • Cross-agency co-ordination
  • Effort analogous to one that pushed the frontiers
    for VLSI, Networking, and Parallel and Scalable
    computing
  • DDDAS impact akin to the impact of computers in
    the 50s

16
http//www.cise.nsf.gov/eia/dddas
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