UltraScale Computing Program Vision DARPA

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DARPA Approved for Public Release, Distribution Unlimited 1 UltraScale Computing Program Vision Machines with Human- Like Cleverness Humans with Machine- Like Precision “What the ancients called a clever fighter is one who not only wins, but excels in winning with ease” -- Sun Tsu E.D. (Sonny) Maynard, Jr. Information Technology Office

Transcript of UltraScale Computing Program Vision DARPA

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UltraScale ComputingProgram Vision

Machines with Human-Like Cleverness

Humans with Machine-Like Precision

“What the ancients called a clever fighter is one who notonly wins, but excels in winning with ease” -- Sun Tsu

E.D. (Sonny) Maynard, Jr.Information Technology Office

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Enable Computation

Based OnBiological

Material

Explore TheUpper

Reaches Of ComputerComplexity

Swarm Computing

Artificial Nervous System

Quantum Computing

InorganicMachine

Inference & Creativity

DNA Computing

Cellular Engineering

Living Neuronal Networks

OrganicBiology

ThatComputes

UltraScale ComputingProgram Structure

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Warrior Robots

Disposable Supercomputers

Materials That Think

Fly-By-Thought

Instant Training

Why Is UltraScale ComputingImportant to DOD?

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SwarmComputing

Expected Results:Simulation & testshow >1,000,000cellular automatacan solve partial

differential equations

The Inorganic WorldSwarm Computing

Artificial Nervous System

Quantum Computing

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Swarm ComputingTwo Representative Projects

Context: Applications with very highI/O bandwidth requirements such asimage and signal processing includingSAR, passive and active SONAR, andsatellite reconnaissance images.

Continuum Computer ArchitectureCalifornia Institute of Technology

Context: To reliably obtain a desiredbehavior by engineering the cooperationof many parts, without assuming anyprecision interconnect or precisiongeometrical arrangement of the parts

Amorphous ComputingMassachusetts Institute of Technology

The Inorganic world

Swarm Computing

Artificial Nervous System

Quantum Computing

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ArtificialNervous System

Expected Results:Machine inferenceand creativity resultfrom interaction with

the environment

The Inorganic WorldSwarm Computing

Artificial Nervous System

Quantum Computing

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ANS NeuronFour Compartment

Structure

750nm

500nm

500nm

Tuft

Neck

Soma

Base

3.5nm

3.5nm

10nm

6nm

Top DownInputs

ModulatoryInputs

Bottom-UpInputs

Active Currents

Local InhibitionLocal Excitation

Spike Output

Context: Construct realistic electronicnervous system that acquires a worldview through sensory motor controlsto provide the central nervous systemfor battlefield robots.

Artificial Nervous System, Raytheon/TI

Context: Demonstrates the abilityto encode desired machine input tothat region so it is correctlyinterpreted by the rest of the brain

NeuroModem HNC Software Inc./Robert Hecht-Nielsen

Artificial Nervous SystemsTwo Representative Projects

The Inorganic world

Swarm Computing

Artificial Nervous System

Quantum Computing

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QuantumComputing

Expected Results:An N-bit quantumprocessor solves aproblem of order 2N

The Inorganic WorldSwarm Computing

Artificial Nervous System

Quantum Computing

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• Information (qubits) = Nuclear spinsNuclear spins

• Interactions = Chemical bondsChemical bonds

• Circuits = Electromagnetic field pulsesElectromagnetic field pulses

0 =

1 =

Single MoleculeSingle MoleculeQuantum ComputerQuantum Computer

(Gershenfeld and Chuang, Science 275, p.350, 1997)

Quantum ComputingThe Inorganic world

Swarm Computing

Artificial Nervous System

Quantum Computing

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= ?=

1 = 0 =

Quantum ComputingThe Inorganic world

Swarm Computing

Artificial Nervous System

Quantum Computing

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0 + 11

2

1

2= =Superposition

of 0 and 1!

• Two spins: four states in superposition

1 = 0 =

c c c c0 1 2 3+ + + 1100 01 10

Quantum ComputingThe Inorganic world

Swarm Computing

Artificial Nervous System

Quantum Computing

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• N spins -- 2N states in superposition

. . .0...00 + 0…01 + … + 1…11

1 = 0 =

Quantum ComputingThe Inorganic world

Swarm Computing

Artificial Nervous System

Quantum Computing

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Why don’t we have Quantum computerstoday?

• Coupling between quantum computation medium andphysical world

• Must be isolated during computation

• Must be coupled for input/output

• Error correction

• Large scale packaging

Quantum ComputingThe Inorganic world

Swarm Computing

Artificial Nervous System

Quantum Computing

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Context: Desktop quantumcomputer with NMR I/O.

Bulk Quantum Computation with NMRStanford, MIT, U-California-Berkeley

Quantum ComputingTwo Representative Projects

Quantum Information Computation CalTech, U-Southern California, MIT

Context: Quantum computers solveproblems impossible for classicalcomputers; quantum computationimpacts cryptographic security;quantum communication enables newsecure cryptographic protocols

The Inorganic world

Swarm Computing

Artificial Nervous System

Quantum Computing

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DNA Computing

01011011001110110101.....

1

(+5V) 1

NAND

(+5V)

+5V

0

1 (+5V)

+5V

0 (0V)

(0V) 0

NOR

AGGTCAGCGTAGCCGATC

GuanineCytosineAdenine Thymine

Expected Results: Datahas been stored &

retrieved from DNA & asimulated problem, order

>256, is solved

The Organic WorldThe Organic WorldDNA Computing

Cellular Engineering

Living Neuronal Networks

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● Draw a path from the first city to the last while passing through all citiesonly once

– This is known to be a hard problem● When the number of cities is > 70, the problem is too complex for even

a supercomputer to solve

● Generate all possible paths

● Keep only those paths that go from “start” to “end”

● Find the ones passing through 7 cities

● Isolate paths with 7 different cities

DNA ComputingRepresentative Project

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2233

44

77

6655

Theoretical & Experimental Aspects of Biomolecular ComputingUniversity of Southern California

The Organic world

DNA Computing

Cellular Engineering

Living Neuronal Networks

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DNA Mk 1The Stickers Model

• Memory Strand for Breaking DES– 11580 bases in length– Subdivided into 579 non-overlapping regions, 20 bases long

• Stickers– Each sticker is 20 bases long– Complementary to one and only one of the 579 memory regions

• Each Region is One Bit– Bit On: Sticker is annealed to memory strand– Bit Off: No sticker

Memory Strand

ACGGTTAACGCAGGATCCCAATACACTGACTCCCAATAGGCCCTGCAAGCTAACGTTAGCCTGCCAATTGCGTCCTAGGGT GGACGTTCGATTGCAATCGG

StickerOn

StickerOn

1 10Sticker

Off

The Organic world

DNA Computing

Cellular Engineering

Living Neuronal Networks

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DNA + Robotics =DNA Computing

Robotic Refinery

00 11

0 000 101 001 10

Bo

1 0 01 1 0

00 11

B1

1 1 0

0 0 00 1 0

00 110 0 0

B1

1 0 00 1 0

S2

1 0 1

S2

0 0 0 1 1 00 1 1 1 0 10 1 1

0 000 11

Context: If the biochemical errorrate is <1:10,000 and unit operationis one second, then a computer of<1m3 breaks DES in 2 hours.

The Organic world

DNA Computing

Cellular Engineering

Living Neuronal Networks

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CellularEngineering

Expected Results:Finite state machinesimplemented via gene

expression &transcription of a

bacterium

The Organic WorldThe Organic WorldDNA Computing

Cellular Engineering

Living Neuronal Networks

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Cellular Engineering

Embedded Process-control Computation

novel, patterned materials

New ComputationalParadigms

Programming Technology

engineered cell

FSM

Create and exploit a novel technology for information processing andmanufacturing by controlling processes in living cells

DNA Computing

Cellular Engineering

Living Neuronal Networks

The Organic world

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Context: Establish the viability of animplantable electrical to chemicaltransducer.

Oscillating Channels and SensorsHarvard University

Cellular EngineeringTwo Representative Projects

Gene Regulatory ModelingStanford University

Context: Model the interior processesof bacteria to demonstrate externalcontrol of internal computation.

DNA Computing

Cellular Engineering

Living Neuronal Networks

The Organic world

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Living NeuronalNetworks

Expected Results:Hybrid information

appliances, such ascomputers, peripherals,

and storage devices.

The Organic WorldThe Organic WorldDNA Computing

Cellular Engineering

Living Neuronal Networks

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Living Neuronal NetworksTwo Representative Projects

Context: Form neuronal circuitsconnected to electronics so thatpowerful, cheap signal processingis enabled.

Electrode patterns

axon pattern

neuron body

Schematic of Neuraonl element

A Hybrid Neuron-SiliconComputational System

University of Southern California

Context: Develop novel, hybridneuron-silicon technology to harnesscomputational capacity of culturednetworks of hippocampal neurons fortemporal and spatio-temporal patternrecognition applications.

Interfacing Directed NeuronSystems with Silicon Electronics

Cornell University, WadsworthCenter, and U-Va

DNA Computing

Cellular Engineering

Living Neuronal Networks

The Organic world

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Context: Deliver synthetic inputs directly into sensory andmemory systems of the brain; demonstrate direct, remoteaccess to the outputs of these systems in biologicalorganisms performing high level information processing.

Responses of 80monitored hippocampalcells

Decoding patterned neuralactivity for location

Detection of novel environment through neuralmonitoring

Interfacing with Large-Scale Neuronal EnsemblesMassachusetts Institute of Technology

Living Neuronal NetworksRepresentative Project

DNA Computing

Cellular Engineering

Living Neuronal Networks

The Organic world

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Warrior Robots

Disposable Supercomputers

Materials That Think

Fly-By-Thought

Instant Training

How Can DoD UseUltraScale Computing?