research to reality – the darpa perspective · approved for public release, distribution...

Research to Reality – The DARPA Perspective

Dr. Todd Hylton

Program Manager

Defense Advanced Research Projects Agency

Northeastern University, Boston, MA

October 19, 2010

Approved for Public Release, Distribution Unlimited

What makes DARPA unique…

Formed in 1958 to PREVENT and CREATE strategic surprise

As the DoD’s innovation engine, weare committed to the boldest, creative leaps…


Capabilities, mission focused

Finite duration projects

Diverse Performers

Multi-disciplinary approach…from basic research to system engineering

Creative leaps require…

Bold, best-in-class technical experts and knowledgeable, lean, adaptable support staff…

…who recognize opportunities and are empowered to act rapidly…

…and are unafraid to challenge conventional viewpoints or methods.

Protect the Fragile/FleetingBest Jumpers Challenge One’s

World View


Regina E. Dugan, DirectorKaigham J. Gabriel, Deputy Director

Adaptive Execution

Dick UrbanRyan Patterson

Strategic Technology

Don WoodburyLarry Stotts, Brent Appleby

Tactical Technology

Dave Neyland Roger Hall

Information Innovation

Dan KaufmanMark Luettgen, Norman Whitaker

Defense Sciences

Leo ChristodoulouJon Mogford

Microsystems Technology

Greg KovacsMark Rosker


DARPA Technical Offices

DARPA's Defense Sciences Office (DSO) Pursues and Exploits Fundamental Science and Innovation for

National Security


Characteristics of a DARPA Program


• Revolutionary change (not extensions or incremental gains)

• Empowered by ideas

• Project centric ̶ not investigator centric

• Creates opportunities, “encourages” teams

• Flexible, rapid review and contracting

• Actively managed by the Program Manager

• Driven by technical goals and milestones

Example Program - SyNAPSE

7

SyNAPSE Motivation and Objective

von Neumann Machines

Neuromorphic Machines

Machine Complexity

e.g. Gates;Memory;Neurons;Synapses

Power;Size

[log]

• Human level performance• Dawn of a new age

Dawn of a new paradigm

“simple” “complex”

Environmental Complexitye.g. Input Combinatorics

[log]

Program Objective

What is the difference?

Problem

• As compared to biological

systems, today’s

computing machines are

less efficient by a factor

of a million to a billion in

complex environments.

GOAL

Create biologically-inspired, neuromorphic electronic circuits with small physical dimensions, low power consumption, and the ability to understand and respond to their environments.


SyNAPSE Concept


5X108

transistors/ cm2

@ 500 transistors/ neuron

~1010

intersections/cm2

@ 100 nm pitch

~1010

synapses /cm2

Multi-Gbit/sec digital comms

~106

Neurons /cm2

~5X108

long range axons @ 1 Hz

NeuromorphicElectronic System

CROSSBAR JUNCTION

CMOS SUBSTRATE

LAMINAR CIRCUIT

HIGH SPEED BUS

~104

Neurons / cortical column

Human Brain

SyNAPSE Program Approach

Hardware

Architecture

Simulation

Environment

CMOS based electronic neuronal

circuitry

Neuro-anatomically inspired electronic architecture e.g. spiking neural network with activity dependent

synaptic plasticity and network connectivity.

Circuit design and large-scale simulation for system validation

and functional testing.

Virtual, scalable environment to train, test, evaluate and benchmark electronic neural systems ability to

sense, learn, adapt, and respond


SyNAPSE Program Plan

Phase 1 Phase 2 Phase 3 Phase 4

Emul

atio

n&

Sim

ulat

ion

Simulate Large Neural Subsystem Dynamics

~106 neuron level Benchmark

Har

dwar

e

Component Synapse Development

Process and Component Circuit Development

~106 neuron single chip implementation

Arch

itect

ure

& T

ools

Microcircuit Architecture Development

106 Neuron Design for Simulation and Hardware Layout

~108 neuronmulti-chip robot

108 neuron design for simulation and hardware layout

~108 neuron level Benchmark

“Human” level Design (~1010 neuron)

Build Expand & Refine Expand & Sustain SustainEnvi

ronm

ent

Comprehensive Design Capability

Phase 0

CMOS Process Integration

system I/O

environment

high-speed global communication system

interface

dire

ct

prog

ram

min

g

interface interface

System Level Architecture Development

11

SyNAPSE Perspective

~1.5 yr

IC Transistor µProcessor Algorithmicmachines

60 + years

NeuralMicrocircuit

Synapse Neural “Fabric” Intelligentmachines

• Increased scalability• Defect tolerant• Self-adapting, learning • Path to biologically

competit ive intelligence0.75 yr

DARPA SyNAPSE

PE: XXX – Front Office to Fill InXXX – Front Office to Fill In

~1.5 yr ~1.5 yr ~1.5 yr

phase 0 phase 1 phase 2 phase 3 phase 4

today

• End of scaling• Defect intolerant• Software limited• No path to biologically

competit ive intelligence

Doing business with DARPA…


• Become familiar with the challenges and opportunities of National

Security.

• Approach a program manager; they are the key to working with DARPA.

• Put your ideas in writing. Draft a white paper.

• Look for Requests for Proposals (RFPs) and Broad Agency

Announcement (BAAs) solicitations at www.darpa.mil ,

www.darpa.mil/sbir , or www.fedbizopps.gov .

• Think boldly. Embrace risk.

http://www.darpa.mil/�

http://www.darpa.mil/sbir�

http://www.fedbizopps.gov/�

Please Keep in Mind


• DARPA programs start quickly and END. Just because we have an

on-going program in a given domain does not imply we will continue

to invest in that area.

• We are looking for revolutionary ideas that provide new capability

• “Old problems” CAN be revisited if there is a compelling reason, e.g.,

if a technological breakthroughs or great ideas have emerged

• We are looking for focus, commitment and dogged persistence

What would you attempt to do

if you knew you could not fail?


www.darpa.mil


research to reality – the darpa perspective · approved for public release, distribution...

Documents