Beyond Strategic Computing:
New Directions for DARPA
ISAT Ad Hoc Working Group on DARPA Futures
Initial Draft: July 12 2000
Update: July 15 2000 x 2
Beyond Strategic Computing
• For 18 years, DARPA has successfully
pursued the Strategic Computing vision
• Building on this foundation, we are prepared
to confront the critical challenges facing us
today. These include:
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–
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Augmented cognition
High-confidence systems and software
New computational substrates
Computing and biology
The DARPA Strategic Computing Program
(1983)*
Major Goals
Military Applications
Intelligent Functional
Capabilities
HW/SW System
Architecture
Microelectronics
Infrastructure
*New-Generation
develop a broad base of
machine intelligence technology
to increase our national security
and economic strength
autonomous systems
pilot’s associate,
battle management
natural language, vision, speech,
expert systems, navigation,
planning and reasoning
high-speed signal processing, general purpose systems,
symbolic processors,
multi-processor programming and operating systems
silicon and GaAs technology
VLSI systems
networks, research machines,
rapid machine prototyping,implementation systems & foundries,
interoperability protocols, design tools
Technology: A Strategic Plan for its Development and Application to Critical Problems in Defense, DARPA, 1983.
Augmented Cognition
Challenge: The volume of information and overall complexity
of warfighting continue to grow at a rapid pace, in stark contrast
to human cognitive abilities, which remain static:
– Memory
– Attention
– Sensory bandwidth
– Comprehension
– Visualization abilities
On the other hand, computational capabilities have continued to
grow rapidly
Apply computational power to support / augment
cognitive skills, bolstering limited cognitive resources
Augmented Cognition
Opportunity: Designs and methods that leverage new
understanding about characteristic limitations in cognition:
– Enhance memory
– Support the analyst with data analysis, discovery,
visualization
– Automate new aspects of problem solving and filtering
– Modulate, triage communications, information
– Develop new visualization techniques to enhance
understanding, increase “effective human-computer
bandwidth”
– Extend abilities to monitor, control semi-autonomous
systems, robots
High-Confidence Systems and Software
Challenge: Today’s systems are fragile, difficult to
compose and maintain
– Non-robust
– Non-adaptive
– Untrustworthy
• Point failures bring down systems
• Difficult, costly to compose useful systems from multiple
components
• Poor or nonexistent means for building reliable systems
from necessarily unreliable components
• Poor understanding of vulnerabilities, performance under
characterized and uncharacterized attacks
• No clear history, pedigree on data, code
High-Confidence Systems and Software
Opportunity: Develop hardware, software, algorithms, and
overall architectures with a more fundamental approach to security
and fault tolerance
• Methods for integrating unreliable components to create reliable
systems as foundation of robust computing
• Methods for addressing, leveraging, harnessing distributed
components and resources.
• Redundancy via replication and efficient restart machinery
• Develop new approaches to model, understand, control, react to
emergent behaviors in complex computational systems at
baseline and when stressed
• Pursue understanding of robustness and adaptation exhibited by
biological systems for relevance to computing
Consider architectural issues spanning multiple layers
of networking, software, computation, hardware
New Computational Substrates
Challenge: We are nearing the end of exponential
growth in processor performance using existing
technologies
– The current silicon / fabrication paradigm leaves
us within sight of a “flatlining” of the Moore’s law
curve
– Atomic dimensions will limit scaling of silicon
technology
New Computational Substrates
Opportunity: Disruptive technologies for computing,
based upon new computational substrates, are
potentially on the horizon
• Substrates
– Computational fabric
– Smart matter, MEMS
– Quantum
– Biological approaches to computing
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•
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DNA
Molecular electronics
Microbial robotics
Engineered genetic networks
– Combinations of the above
Computing and Biology
Challenge: An explosion of knowledge about biological
systems suggests that multiple disruptive technologies lay
waiting, yet we remain mired in large amounts of data and
limited computational tools and models
Biological systems represent powerful architectures for sensing,
processing, actuating, and fabrication, and for managing
complexity in an elegant manner
– IT, computational analysis is essential for cracking key
challenges in biology
– Increased understanding and applications of knowledge about
biology will likely have significant defense implications
– Increased understanding of biology will likely reveal new
approaches to computing and materials—with significant
defense implications
Computing and Biology
Opportunity: Apply computation, modeling to pursue conceptual
foundations of biological approaches to:
robustness, uncertainty, adaptation, inference, replication,
repair, communication, transformation, distribution, selfassembly, fabrication, ontogeny / development, identify friend
vs. foe
Key conceptual challenges include understanding:
–Modeling of genetic circuits
–Proteomics
–Embryogenesis / development
–Evolvable systems
–Engineered biology
Beyond Strategic Computing
Major Goals
develop a broad base of
machine intelligence technology
to increase our national security
and economic strength
2020 Application Vision
TBD via an ISAT study
Augmented cognition
HW/SW System
Architecture
High confidence systems and
software
Computing,
Microsystems,
and
Biology
New Computing
Substrates from
Electronics,
Microsystems, & CS