Cognitive Information Processing
Technology
Brief to
High Performance Embedded Computing
Workshop 2002
Mr. Zachary J. Lemnios
Information Processing Technology Office
Deputy Director
24 September 2002
Acknowledgements
•
•
•
•
•
•
•
•
•
•
Ron Brachman
Bill Dally
Bob Graybill
David Honey
Mark Horowitz
Steve Keckler
Dave Koester
Bob Leheny
Christie Marrian
Dan Radack
DARPA/IPTO
Stanford University
DARPA/IPTO
DARPA/ATO
Stanford University
University of Texas
Mitre
DARPA/MTO
DARPA/MTO
IDA
Page 2
Agenda
• Introduction
– DoD System Challenges
– DARPA Offices and Programs
• Technology Trends
– Device Performance
– High Performance Computing
• Cognitive Processing Technology
• Summary
Page 3
Asymmetric Advantage
Enabled by Information Superiority
See Further with Greater Clarity
Space Based RADAR
E-3 AWACS
Airborne Early Warning
FLTSAT
Secure Comm
GMTI, SAR, STAP, HSI
RC-135V Rivet Joint
Space-Time Adaptive Processing
SIGINT
E-2C Hawkeye
Tier II+ UAV
Standard
Missile
Cooperative engagement
Aegis Cruiser
Towed Sonar Array
Adaptive Matched-Filter processing
TEL
Wideband high linearity target discrimination
multi-angle target discrimination
Chemical biological threat detection
Small Unit Operations
Covert sensing
Power constrained operations
Secure LPI A/J communications
Page 4
Information Networks Will
Revolutionize Platforms
TODAY - Federated Architecture (Baselines 1-5)
Point-to-Point Mainframes (UYK-7/43)
Limited Growth Capability
Vulnerable to Damage
FUTURE - Distributed Processing (Future B/L)
Highly Distributed Network
Redundancy Plus Reconfigurability
Effectively Invulnerable to Battle Damage
The Upside: Agile, Adaptable, Survivable Systems
The Downside: Complexity in h/w, s/w, integration
From: www.hypocrites.com/pictures
Page 5
A New Class of
Autonomous Systems
Mission Complexity
Autonomous
Systems
UCAR
(Artist’s concept)
OAV
(Artist’s concept)
UCAV
UCAV-N
Spinner WV
(w/ 390kg fuel)
(w/ 20kg for nav)
(w/ 345kg battery)
OAV
(w/60kW generator)
(Open Terrain)
HMMWV
(w/ 390kg fuel)
(w/ 20kg for nav)
(w/ 345kg battery)
(w/ 60kW generator)
TMR
Weight w/fuel,sensors (No payload)
4,893kg
(10,764lb)
UGCV
3,736kg (8,220 lb)
1,500kg (3,300lb)
(Artist’s
concept)
945kg (2,080 lb)
6,393kg (14,064lb)
4,672kg (10,300 lb)
Payload fraction
24%
20%
Vertical obstacle
1.2m (47")
0.56m (22")
Trench
2.1m (80")
0.8m (31")
0.42m (16")
0.45m (18")
70% (35°)
70% (35°)
108 kPa (15 psi)
~220 kPa (32 psi)
Global Hawk
Cooperative
Systems
Legacy Systems
A160
Payload capacity (after imposed loads)
GVW with full payload
Power (peak)
192kW (257 hp)
139kW (186 hp)
• Human-like
sensor depth
Power/Weight ratio (peak)
43 hp/ton
39.8 hp/ton
• Persistent
engagement
CG height / Track
~0.40
~0.59
Vertical center-of-gravity
0.8m (31") constraints
1.1m (43")
• Extreme
power and volume
Width
2.5m (100")
2.3m (90")
• Effects-based
tasking
and
performance
Tire diameter
1.2m (47")
0.95m (37")
Environmental Complexity
Ground clearance
Side slope
Min ground pressure
Fording
Max road speed
1.2m (47")
~62kph (38mph)
0.9m (35")
Page 6
125kph (80mph)
DARPA Organization
Director, Tony Tether
Information Exploitation
Richard Wishner
Steven Welby / Robert Tenney
Sensors
Exploitation Systems
Command & Control
Information Awareness
John Poindexter
Robert Popp
Asymmetric Threat
Prediction
Behavior Modeling
Tactical Technology
Allen Adler
Art Morrish
Air/Space/Land Platforms
Unmanned Systems
Space Operations
Laser Systems
Future Combat Systems
Planning / Logistics
Special Projects
Amy Alving
Joe Guerci
Chem/Bio Def Systems
Counter Underground
Facilities
Space
Sensors/Structures
Navigation/Sensors/
Signal Processing
Advanced Technology
Tom Meyer
Dave Honey
Assured C3ISR
Maritime
Early Entry/Special
Forces
IA&S Programs
Defense Sciences
Michael Goldblatt
Steven Wax
Bio Warfare
Defense
Technologies
Biology
Materials &
Devices
Mathematics
Information Processing
Technology
Ron Brachman
Zach Lemnios
Cognitive Systems
Computational Perception
Representation &
Reasoning
Learning
Natural Communication
MicrosystemsTechnology
Robert Leheny
Electronics
Optoelectronics
MEMS
Combined
Microsystems
Focus of this brief
Page 7
DARPA/MTO
Platform Scale Information Systems
Process
Sense
Actuate
Memory
RF
w
MMW
IR
UV
Controller
Sensor(s)
Switching
Analog
Digital
Visible
Bio
I/O
HumanInterface
Interface
Human
MachineInterface
Interface
Machine
WeaponInterface
Interface
Weapon
NetworkInterface
Interface
Network
Output
Output
A/D
A/D
Processor(s)
• Highly capable sensors- sensors that are self adapting
• Enhanced extraction of signals from background, noise, and jamming
• Covert “data” into actionable “knowledge” in near real time
• Provide technology for assured communication links
Page 8
The Challenge of Complexity
1.E+11
1.E+10
Ops/sec/$
doubles every
Few months
1.E+09
1.E+06
Tubes/
Transistor
1.E+03
1.E+00
1.E-03
Mechanical/
Relays
doubles every
7.5 years
doubles
every 1.0
years
nanometer
CMOS
doubles every
2.3 years
Combination of Hans Moravac + Larry Roberts + Gordon Bell
1.E-06
1880
1900
1920
1940
1960
1980
2000 2010
2020
2030
While computational performance is increasing, productivity and effectiveness are
not keeping up:
– Users must adapt to system interfaces, rather than vice versa
– Systems have become more rigid and more fragile
– Systems have become increasingly vulnerable to attack
– The cost of building and maintaining systems is growing out of control
Page 9
DARPA/IPTO
Cognitive Systems
• DARPA IPTO will create a new generation of
cognitive computational and information
systems with capability to:
– reason, using substantial amounts of
appropriately represented knowledge
– learn from their experience so that they perform
better over time
– explain themselves and be told what to do
– be aware of their own capabilities and reflect on
their own behavior
– respond robustly to surprise
Systems that know what they’re doing
Page 10
Why Now?
• Human-level scaling of HW technology is on the horizon
• Foundations established for human neural systems
• Cognitive technology (from AI) is being applied to initial problems
Page 11
The Result Will Enable a
Revolution in Capability for DoD
More Aggressive
Threats
Adaptive and Intelligent
Data-Fused Sensors
Threats are more dynamic and in deeper hide (collapsing time lines)
System performance is outpaced by changing threat environments
Cooperative battle management requires robust information backbone
Sensor Data Flow
Overwhelming Human Analyst
Cognitive Information
Exploitation
Sensor bandwidth is increasing faster than processor capability
Target classification has become a multi sensor
The next revolution in sensing: Autonomous Adaptation
The next revolution in computing: Cognitive Processing
Page 12
Agenda
• Introduction
– DoD System Challenges
– DARPA Offices and Programs
• Technology Trends
– Device Performance
– High Performance Computing
• Cognitive Processing Technology
• Summary
Page 13
Beyond CMOS: The Road Beyond
Bulk Silicon Field Effect Transistors
10.00
Normalized Device Speed
ITRS Roadmap
Projections
Quantum
dots/Cell.
Automata
Self-directed
assembly
metallic
particle
SiO2
Bulk-Si
Best Case
Predictions
SET
IEDM Benchmark
Technologies
1985
1990
1995
2000
2005
2010
D
2015
G
2020
G
Molecular devices
S
S
Courtesy Dimitri Antoniadis, MIT; Rob Rutenbar, CMU
silicide
Gate Oxide
Si
Gate
B
Nonplanar
Switches
1/size
Nanotubes
nFET
Gate
{
0.10
NDR,
RTD
{
1.00
pFET
Silicon
Schottky barrier
isolation
Schottky
source/drain FET
Si
(tensile)
Bulk CMOS
Double-Gate CMOS
Si0.8Ge0.2
High k gate
oxide
Metal gate
After Chart by P. Wong, IBM
Si1-xGex
Si
SiGe/Ge FETs and Structures
(strained layers)
Page 14
Memory Wall is Growing
100
Memory access times
(cycles) are increasing
based on SIA clock
frequency roadmap
180nm
130nm
100nm
70nm
50nm
10
1
1
10
100
1000
10000
Cache Capacity (KB)
Source: Keckler – Univ. of Texas
Page 15
SIA Roadmap Impact
on Computer Architectures
0.28
0.26
• 400 mm2 Die
700 MHz
0.24
0.22
Process (microns)
0.2
Single Clock Area
1.25 GHz
0.18
0.16
2.1 GHz
0.14
0.12
0.1
6 GHz
0.08
10 GHz
0.06
13.5 GHz
0.04
0.02
0
1996
1998
2000
2002
2004
2006
Year
2008
2010
2012
2014
New architectures are required to accommodate smaller clock regions
Page 16
Novel Architectures are Required to
Extend Performance Productivity
1e+7
Perf (ps/Inst)
Delay/CPUs
1e+6
1e+5
1e+4
1e+3
1e+2
30:1
1e+1
1e+0
1e-1
1e-2
30,000:1
Opportunity for Cognitive
Architectures
1e-3
1e-4
1980
1985
1990
1995
Source: ISAT Summer 2001 Study- Last Classical Computer;
Prof. Bill Dally (Stanford U) Study Lead
2000
2005
2010
2015
2020
Page 17
Embedded Computing
Performance Regions
10000
Computation Density (MOPS/cm3)
Custom VLSI
1000
Polymorphous Architectures
100
Reconfigurable
Programmable
10
1
0.1
0.01
0.1
1
10
100
1000
Computational Efficiency (GOPS/Watt)
Page 18
Polymorphous Computing
Architectures Program
MultiMission
Multiple
Sensors
(A,B,C...X)
plug & play
A B C…. X
In-Mission
Re-target
-ability
Platform
Tracking
transit Multi-sensor
processing
Goal: Computing systems (chips, networks, software) that
will morph to changing missions, sensor configurations,
and operational constraints during a mission or over the life
of the platform.
P
e
r
f
o
r
m
a
n
c
e
PCA Morph Space
Mission
Selectable
Virtual
Machines
Architecture Space
Specialized DSP
Class
Class
PPC
Class
Server
Class
Mission Aware Embedded Computing
Page 19
Agenda
• Introduction
– DoD System Challenges
– DARPA Offices and Programs
• Technology Trends
– Device Performance
– High Performance Computing
• Cognitive Processing Technology
• Summary
Page 20
DARPA/IPTO
Cognitive Systems
• DARPA IPTO will create a new generation of
cognitive computational and information
systems with capability to:
– reason, using substantial amounts of
appropriately represented knowledge
– learn from their experience so that they perform
better over time
– explain themselves and be told what to do
– be aware of their own capabilities and reflect on
their own behavior
– respond robustly to surprise
Systems that know what they’re doing
Page 21
Cognitive Systems Thrusts
Dynamic
Coordinated
Teams
Systems
Systems That Know
What They’re Doing
Core
Cognition
Cognitive Architecture
Perception
Representation
&
Reasoning
Learning
Communication
&
Interaction
Robust Software and Hardware
Foundational Science and Mathematics
Bio-inspired Computing, new approaches to Trust Management
Foundation
Page 22
Cognitive
Agent
Anatomy of a Cognitive Agent
Perception
Reflective Processes
LTM
STM
Deliberative Processes
Other reasoning
Communication
(language,
gesture,
image)
(knowledge
base)
Concepts
Sentences
Prediction,
planning
Action
Reactive Processes
Sensors
Effectors
External Environment
Page 23
Initial Challenge Context
Persistent, personal partner/associate systems
• Learn from experience
• Learn what you like and how you operate
by observation
by direct instruction or guidance, in a natural way
• Imagine possible futures, anticipate problems and needs
• Omnipresent / always available
Examples
•
•
•
•
Commander’s (C2) assistant
(Intelligence) Analyst’s associate
Personal executive assistant/secretary
Disaster response captain’s “RAP” (robot/agent/person)
team
Page 24
Summary
DoD is facing immense challenges
• New and dynamic threats in much deeper hide
• Collapsing timeliness, rapidly changing threat environments
New classes of autonomous systems require
• Platform Scale Integration (DARPA/MTO)
• Cognitive Capabilities (DARPA/IPTO)
Systems that Know what they are doing
• can reason
• can learn from their experience
• can explain themselves
• can be aware of their own capabilities
• can respond robustly to surprise
Page 25
Challenge
•Send us your best ideas:
IPTO BAA 02-21, http://www.darpa.mil/ipto/Solicitations/PIP_02-21.html
MTO BAA Solicitation http://www.darpa.mil/mto/solicitations/index.html
•Take a tour as a DARPA Program Manager
rleheny@darpa.mil
rbrachman@darpa.mil
zlemnios@darpa.mil
(703) 696-2268
(703) 696-2264
(703) 696-2234
Page 26
Backup
Page 27
Memory Issues Lead to
Inefficient Performance
Year of Introduction (Cray)
1988
1994
2000
Cray
C90
Y-MP
T90
J90
Intel
Alpha
SGI MIPS
Sun
Cray
EL-90
10.00%
SV1
Microprocessors
Measured %peak (STREAMS ADD)
100.00%
1.00%
10
100
1000
10000
Clock Speed MHz
STREAMS ADD: Computes A + B for long vectors A and B (historical data available)
Page 28
Today’s Systems - Collection
of Rigid Embedded Subsystems
Static Mission
Scripts
System-of-Systems
Micro-Systems
SubSubSystem System
Sense
……….
SubSystem
Micro-Systems
SubSubSystem System
SubSystem
Sense Process Actuate
Process Actuate
Single Instance, Point-Design
Implementations
Mode
Driven
Configuration
Predefined
Functional
Capability
DoD Systems must Move from Integration
Driven Architectures to Capability Driven Architectures
Page 29
High Performance Embedded
Cognitive Systems
System-of-Systems
Cognitive Information Extraction
Cognitive
micro-Systems
SubSubSystem System
Sense
……….
SubSystem
Process Actuate
Cognitive
micro-Systems
SubSubSystem System
Sense
Local Hard Real-Time
Cognitive Agents
SubSystem
Process Actuate
Goal(s)
Driven
Missions
Cognitive
Guided
Cognitive
“Enabled”
Agile
Subsystem
(e.g. PCA)
Systems with Human Like Capability
Page 30
Intelligent Systems
for Mission Agility
Cognitive Processing & Adaptation
Resource Aware
Resource Aware
Resource Aware
u
Sense
Process
Actuate
Systems with Human Like Capability
Page 31
DARPA/IPTO
Cognitive Systems
• While computational performance is increasing, productivity
and effectiveness are not keeping up
–
–
–
–
Users must adapt to system interfaces, rather than vice versa
Systems have become more rigid and more fragile
Systems have become increasingly vulnerable to attack
The cost of building and maintaining systems is growing out of
control
Systems That Know
What They’re Doing
Perception
Representation
And
Reasoning
Learning
Communications
And
Interactions
Robust Software and Hardware
Foundational Science and Mathematics
(incl. Bio-inspired Computing, new approaches to Trust Management,…)
Page 32
Information Technology
• Information Exploitation Office
– Detection, Precision ID, Tracking, and Destruction
of Elusive Surface Targets
• Information Awareness Office
– Detect & Defeat Terrorist Networks
• Information Processing Technology Office
– Cognitive Systems
• Advanced Technology Office
– Robust, Secure Self-Forming Tactical Networks
Page 33
Feature Size Trends
Intel8080
Feature size (nanometers)
1000nm
Intel386
Intel486
Pentium
PentiumPro
100nm
Pentium IV
Synchronous
(clocked)
DARPA
10nm
1nm
1970
?
1980
1990
2000
CMOS
2010
2020
2030
“Beyond
CMOS”
2040
2050
Page 34
High Productivity
Computing Systems Program
Goal:
Provide a new generation of economically viable high productivity computing
systems for the national security and industrial user community (2007 – 2010)
Approach:
Implement productive high-end systems with high effective bandwidth, low latency,
balanced system architecture, robustness, application responsive tailorability,
performance measurement and prediction
Applications:
 Intelligence/surveillance, reconnaissance, cryptanalysis, weapons analysis,
airborne contaminant modeling and biotechnology
Fill the Critical Technology and Capability Gap
Today (late 80’s HPC technology)…..to…..Future (Quantum/Bio Computing)
Page 35