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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
Fu
nd
am
en
tals
of
Co
re D
iscip
lin
es
The “T-model” Research&Education
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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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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
SAR
tac-com
data base
fire cntl
fire cntl
alg accelerator
data base
SP
….
Mul
tipl
e leve
ls
of m
utic
ores
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) ( )
( )
( ) Darema, Report on: CyberIfrastructures of Cyber-Applications-Systems & Cyber-Systems-Software
( ) Darema, Report on: Industrial Partnerships in Cyberinfrastructure , October 2009