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Dr. Frederica Darema

Air Force Office of Scientific Research

October 26, 2011 Illinois Institute of Technology

Computer Sciences Department 40th Anniversary

-- Transformation Inducing Directions--

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Transformation Inducing Directions

-> the Next Wave of Computing

• Multidisciplinary Research Expanding Fundamental Research Opportunities Unification Paradigms – Multidisciplinary Thematic Areas InfoSymbiotic Systems

The Power of DDDAS – Dynamic Data Driven Applications Systems Multicore-based Systems

Unification of HEC w RT Data Acquisition & Control Systems Systems Engineering

Engineering Systems of Information (design-operation-maintenance-evolution) Understanding the Brain and the Mind

From Cellular Networks to Human Networks Network Systems Science (Network Science) Discover Foundational/Universal Principles across Networks

• Academe-Industry Partnerships – “R, E, D” Fostering Transformative Innovations

New Capabilities and Advanced CyberInfrastructures

Partnership models: Incubators for Transformative Innovations , …

-> the Next Wave of Computer Science

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Education

Cross-Disciplines

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The “T-model” Research&Education

4 F. Darema

Experiment

Measurements

Field-Data

(on-line/archival)

User Dynamic

Feedback & Control

Loop

Challenges: Application Simulations Methods Algorithmic Stability Measurement/Instrumentation Methods Computing Systems Software Support

DDDAS: ability to dynamically incorporate additional data into an executing application, and in reverse, ability of an application to dynamically steer the measurement process

Software Architecture Frameworks Synergistic, Multidisciplinary Research

Dynamic Integration of Computation & Measurements/Data

(from the Real-Time to the High-End) Unification of

Computing Platforms & Sensors/Instruments DDDAS – architect & adaptive mngmnt of sensor systems

Measurements Experiments Field-Data

User a “revolutionary” concept enabling to design, build, manage and understand complex

systems

Dynamic Data Driven Applications Systems (DDDAS)

InfoSymbiotic Systems

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6 F. Darema

Examples of Areas of DDDAS Impact

• Physical, Chemical, Biological, Engineering Systems

– Chemical pollution transport (atmosphere, aquatic, subsurface), ecological systems, molecular bionetworks, protein folding..

• Medical and Health Systems

– MRI imaging, cancer treatment, seizure control

• Environmental (prevention, mitigation, and response)

– Earthquakes, hurricanes, tornados, wildfires, floods, landslides, tsunamis, …

• Critical Infrastructure systems

– Electric-powergrid systems, water supply systems, transportation networks and vehicles (air, ground, underwater, space);

condition monitoring, prevention, mitigation of adverse effects, …

• Homeland Security, Communications, Manufacturing

– Terrorist attacks, emergency response; Mfg planning and control

• Dynamic Adaptive Systems-Software

– Robust and Dependable Large-Scale systems

– Large-Scale Computational Environments

List of Projects/Papers/Workshops in www.cise.nsf.gov/dddas, www.dddas.org

(+ recent/August2010 MultiAgency InfoSymbtiotics/DDDAS Workshop)

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“revolutionary” concept enabling to design, build, manage and understand complex systems

NSF/ENG Blue Ribbon Panel (Report 2006 – Tinsley Oden)

“DDDAS … key concept in many of the objectives set in Technology Horizons”

Dr. Werner Dahm, (former) AF Chief Scientist

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DDDAS: Beyond Grid Computing “Extended Grid” – “SuperGRID”:

the Application Platform is the unified computational&measurement system

Measurement Grids

Applications

Computational Grids

SuperGrids:

Dynamically Coupled Networks of Data and Computations

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Sensors EveryWhere!!!

Swimming in Sensors and Drowning in Data – LtGenDeptula (2010)

Microprocessors - The Attack of the Killer Micros – Eugene Brooks (1992)

Sensors – The Attack of the Killer “Micros” – WAVE#2 – Frederica Darema (2011)

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Multicore-based Systems

Multicores in High-End Platforms •Multiple levels of hierarchies of processing nodes, memories, interconnects, latencies

Multicores in “measurement/data” Systems •Instruments/Sensors, Controllers, Networks, Storage

SuperGrids: Dynamically Coupled Networks of Data and Computations

MPP NOW

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Integrated/Unified Application Platforms

Multidisciplinary Research and Technology Development for: Adaptable Computing Systems Infrastructure

from the high-end to real-time data-acquisition & control systems supporting applications adaptive mapping and optimized runtime

heterogeneous multilevel distributed parallelism system architectures – software architectures

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Systems Engineering (Engineering Systems of Information)

• System-level methods to design, build, and manage the operation, maintenance, extensibility, and interoperability of complex systems

in ways where the systems’ performance, fault-tolerance, adaptability, interoperability and extensibility is considered throughout this cycle

(limited component level, design level approaches – not sufficient!)

• Such complex systems include (examples): – heterogeneous and distributed sensor networks

– large platforms & other complex instrumentation systems & collections thereof

which need to satisfy/exhibit:

– adaptability and fault tolerance under evolving internal and external conditions

– extensibility/interoperability with other systems in dynamic and adaptive ways

• Systems engineering requires novel methods that can: – model, monitor, & analyze all components of such systems

– at multiple levels of abstraction

– individually and composed as a system architectural framework

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Performance Models & Resource Monitoring <->Operation Cycle, System Evolution

Multidisciplinary Research

& Technology Development

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Transformation Inducing Directions in Academe and Industry

• Fostering Transformative Innovations

• Drivers for Industry-University Partnerships Changing Landscape – New Application Systems Paradigms and ensuing CyberInfrastructures

– Multidisciplinary Research and Education

– Globalization and Industry

• New Partnership Modalities – Academe-Industry

– the catalytic role of Government

– Partnership Models

• R, E, D; tripartite U-I-G; tetrapartite U-I-G-P

• Incubators of Transformative Innovations

• Research Institutes

• …

Technology

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What will drive the U-I partnerships?

Addressing and Solving Hard Problems

that

Industry alone cannot do

Universities alone cannot do

Combine broad expertise in Academe

With Industry know-how for building robust systems (prototypes)

Methods and Tools to enable Advanced Research in Academe Methods and Tools for New Capabilities for Industry

Examples: CyberInfrastructures for Complex Applications Systems

(Need comprehensive systems frameworks – not just system components)

New Capabilities - New Directions through Advanced CyberInfrastructures

“Innovation through CyberInfrastructure Excellence” (ICIE) ( )

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( ) Darema, Report on: CyberIfrastructures of Cyber-Applications-Systems & Cyber-Systems-Software

( ) Darema, Report on: Industrial Partnerships in Cyberinfrastructure , October 2009