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Computer-Aided Design for DNA Self-Assembly: Process and Applications
Chris DwyerAssistant ProfessorDept. of Electrical and Computer EngineeringDept. of Computer ScienceDuke University
ICCAD 2005
Motivation
[Annotated with CNT technology, original source: George Bourianoff and ITRS, ca. 2003.]
log Length (m)
log Cost ($/gate)
log Switching time (s)
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Outline
• DNA Basics
• Self-assembled Nanostructures– DNA Scaffolds
– DNA Guided Self-assembly
• CAD Tool Support
• Self-assembled Systems– New Constraints
– Alternative Architectures
• Conclusions
DNA Basics
• A DNA strand:– A linear array of bases (A, T, G, and C)– Directional (one end is distinct from the other)– In nature, the source of genetic information
• DNA will form a double helix:– When the bases on each strand (aligned “head-to-
toe”) are complementary: A with T, and G with C
– But only under certain “natural” environmental conditions (low) temperatures (Tm: sequence dependent) and in an ionic solution.
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DNA Basics
• DNA hybridization is the process that forms the double helix
• Sequence and temperature control the hybridization event
∆T
DNA Basics
• A common form of the double helix (B-form) has some well-known geometric properties:– 3.4 Å per base pitch along the helix– One complete turn between every 10th and 11th base
• Flexibility: the bonds along the sugar-phosphodiester backbone of each strand can rotate– double stranded DNA has a ~50nm persistence
length (fairly rigid)– single stranded DNA has a strongly-sequence
dependent persistence length (but, it’s flexible)
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Outline
DNA Basics
• Self-assembled Nanostructures– DNA Scaffolds
– DNA Guided Self-assembly
• CAD Tool Support
• Self-assembled Systems– New Constraints
– Alternative Architectures
• Conclusions
Self-assembled Nanostructures
• Self-assembly is ubiquitous in nature• Generally defined as spontaneously generated order
• Thermodynamics drive the self-assembly process– we can guide the process by the choice of materials and
environmental conditions
A
B
∆TA·B
< 20 nmfeature sizes
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DNA Scaffolds - Geometry
• The geometric properties of double strands can form specific, controlled self-assembled nanostructures:
∆T
3.4 Å
DNA Self-assembled Tiles
9 strands
Cost ($) is proportional to the total number of unique strands (& quantity)
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DNA Scaffolds – Hierarchical Assembly
• Self-assembly can occur in hierarchies (reduces cost):– tiles (from single strands to tiles)– grids (from tiles to grids)– lattice (from grids or tiles to larger lattice)
30 nm
DNA Scaffolds - Functionalization
• Tiles can be functionalized (decorated) with nanoscale components (thus, the DNA serves as a scaffold)
• Tiles can be functionalized before OR after grid/lattice assembly
• Example chemical functionalities include:– biotin / streptavidin– DNA / nanoparticle (rods, spheres, etc.)
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DNA Scaffolds - Functionalization
• Biotin / streptavidin (protein + active chemicals)• The DNA provides a scaffold for the protein
BELOW: AFM images of some grids functionalized with streptavidin
AFM images of a 1.4 Tb/in2 ROM (barcode)
The manufacturing scale is incredible: ~1016 grids per mL!
“Letters”: ~60nm on a side(1 experiment made ~1014 of each)
Trivia: The collection of books and manuscripts in the Library of Congress contains ~1014 letters.
A Brief Interlude About Yield
• The term “yield” is well-defined in multiple fields– Chemistry/Physics/Materials Science: extrinsically (mass)– Engineering: pass/fail (devices, circuits, systems)
• Yield in DNA self-assembly is ambiguous– Reason 1: Surface deposition is the major technique used
to assay experimental results. Substrate-to-substrate variations change the deposition rate!
– Reason 2: Partial products are common but there is no functional test (unlike with current silicon processes)
– It comes down to undefined specifications
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DNA Scaffolds - Functionalization
• Perhaps in the future....
Crossed carbon nanotube“FET” / SBT DNA Self-assembly
+
• Nanotechnology,vol. 13, pp. 601-604, 2002.
Outline
DNA Basics
Self-assembled NanostructuresDNA Scaffolds
• DNA Guided Self-assembly
• CAD Tool Support
• Self-assembled Systems– New Constraints
– Alternative Architectures
• Conclusions
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DNA Guided Self-assembly
• Nanoparticles (rods, spheres, etc.) can be functionalized with DNA
• DNA hybridization stabilizes interactions between particles if the strands are complementary
• Sequence design and particle choice yields controlled nanostructure formation
DNA Guided Self-assembly
• Example: A two particle tether
∆T
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DNA Guided Self-assembly
• An active component:– ring-gate FETs (RG-FETs) (or surrounding-gate
FETs)
DNA Guided Self-assembly
• Active components for circuitry: Au – CdSe – Au (metal, semiconductor, metal or MSM) rods
500 nm wide
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DNA Guided Self-assembly
• IEEE Trans. on VLSI, vol. 12, pp. 1214-1220, 2004.
• IEEE Trans. on Nano.,2 (2): pp. 69-74, 2003.
• Nanotechnology,vol. 13, pp. 601-604, 2002.
• Perhaps in the future...– The fabrication of integrated electronic systems
Self-assembled Nanostructures
• Recap: Two Fabrication Methods– Scaffolds– DNA Guided Assemblies
Scaffolds
Nanorod assemblies
30 nm
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Outline
DNA Basics
Self-assembled NanostructuresDNA Scaffolds
DNA Guided Self-assembly
• CAD Tool Support
• Self-assembled Systems– New Constraints
– Alternative Architectures
• Conclusions
• New technology fabric : New tool support– Goal: apply conventional circuit design approaches to
these new technologies
• First, identify a design context:– Tool flow– Layout tools– DNA sequence design
• The big picture: Moving towards full system design...
CAD Tool Support
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Power & Timing Estimate
Device-levelDescription
SystemDescription
Synthesis Tools
ArchitecturalSimulator (custom)
BehavioralVerification
FunctionalVerification
SPICE
Layout Tools (custom) Layout
Tool Flow
Assembly Order &DNA Sequences
Assembler(custom)
Extractor(custom)
Back-annotatedCircuit
SPICE (custom)
Timing & PowerVerification
Self-assembledFabrication
LayoutOrders
Tool Flow
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CAD Tool Support – Circuit Layout
DNA scaffold layout tool DNA-rod layout tool
• Bootstrap the automated / cell layout systems with manual layout tools and standard cell designs
CAD Tool Support – Optimized Fabrication
• The new aspects for the process tools: – DNA sequence design– Assembly orders (unique per design)
Assembly Order &DNA Sequences
Assembler(custom)
Self-assembledFabrication
LayoutOrders
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CAD Tool Support: Wrap-up
• Current tool status:Cluster-based sequence optimizationLayout toolsCarbon-nanotube & MSM device models for a custom SPICE kernel (semi-empirical)Assembly orders / “artwork” gen. (for large circuits)
• Tool wish list: 1. yield-aware design optimizations, 2. refined (high ω) device models,3. better automated full custom support.
Outline
DNA Basics
Self-assembled NanostructuresDNA Scaffolds
DNA Guided Self-assembly
CAD Tool Support
• Self-assembled Systems– New Constraints
– Alternative Architectures
• Conclusions
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Self-assembled Systems
• There are a variety of self-assembled systems– crossbars, micron-scale assemblies, biological
systems...
• The Systems Focus:
self-assembled computer architectures
New Constraints
• Self-assembly imposes:– chaos / randomness at some length scale (>1-10 µm)
• DNA hybridization imposes:– order at some length scale (< 1-5 µm)
• The two can work together but some fundamental assumptions must change:– Wire / bus interconnect
• No large-scale interconnect networks / limited local– Severe area / cost tradeoff
• Large (> 1-10 µm on a side) circuit footprints are impractical– Reliability
• The substrate can be defective• The devices can be defective
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Alternative Architectures
• The task: Given a device technology, design a system– The new constraints prevent wholesale adoption of
conventional architectures / system designs
• Two common solutions given a defect-prone technology: – reconfigurable resources– redundant components (e.g. TMR, n-MR,
multiplexing, etc.)
Alternative Architectures
• (Self-) Reconfigurability is key, however....
• The large number of simple processing nodes in a system (as many as we can assemble, ~1014 +) precludes the use of an explicit defect map
• The goal: To stitch a sufficient number of computational resources together to execute application code
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Alternative Architectures
• Four systems: Oracles, DAMP, NANA, and nSIMD:– Oracles: DNA computing with a device twist that
enables rapid (electrical) re-use of a DNA computation– DAMP: Decoupled Array Multi-processor, SIMD without
an interconnection network- embarrassingly parallel codes – only
– NANA: Nanoscale Active Network Architecture, general purpose but imbalanced due to a large communication/execution ratio- under utilized resources
– nSIMD: (nano) SIMD, similar to NANA but applies a SIMD model onto a reconfigurable network topology. Utilization is high due to a depth first network traversal.
Alternative Architectures
Self-assembledComputational nodes
Self-assembledInterconnect
Defect model includes:• Rotation, position• Connectivity• Fail-stop nodes (unrealistic)
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Wrap-up
• DNA Basics
• Self-assembled Nanostructures– DNA Scaffolds
– DNA Guided Self-assembly
• CAD Tool Support
• Self-assembled Systems– New Constraints
– Alternative Architectures
• Conclusions
Conclusions
Shell
Arm
Core
Self-assembled device theory
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Conclusions
Some demonstrations of self-assembled devicesThis technology is on its way...
30 nm
Conclusions
Self-assembled computer architectures and systems
– Oracles: Re-useable DNA computations– DAMP: Decoupled Array Multi-processor– NANA: Nanoscale Active Network Architecture– nSIMD: (nano) SIMD
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Acknowledgements
Vijeta JohriVincent MaoJaidev PatwardhanConstantin Pistol
Juan BermudezLauren CohenCurt HartingJosh JohnsonJoe Tadduni
• Graduate students
• Undergraduate students
Research Sponsors
• AFRL FA8750-05-2-0018• NSF CCR-0326157• NSF EIA-9972879
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Basic system criteria – a framework
(i) Linear signal transduction
(ii) Non-linear signal modulation by another signal
(iii) Signal amplification / restoration
(iv) Signal noise immunity
(v) Circuit patterning and interconnect
(vi) Scale of device integration
(vii) Energy consumption
(viii) Application runtime performance
10X
• DNA computing• Oracles
• ASICs, FPGAs, etc.
• Conventional serial & parallel machines• Decoupled array multi-processor (DAMP)
Assembly-time
Run-time
Temporal spectrum of Computation
IEEE Computer, vol. 38, pp. 56-64, 2005.
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Organization & Architecture
R0* R1* R2 R3 R4ACC*
OperationB C D S
Status bitsWR
• Nanotechnology,vol. 15, 1688-1694, 2004.
• Ph.D. dissertation, Univ. of North Carolina, Chapel Hill, 2003.
• IEEE Computer, vol. 38, pp. 56-64, 2005.
• IEEE Trans. on VLSI, vol. 12, pp. 1214-1220, 2004.
Question0 Answer0
log2(n) bits. .
.
Questionn-1 Answern-1
Oracles Decoupled array multiprocessor (DAMP)
• Truth table defines binding rules
• Each tile is implemented by a self-assembled circuit
AA BB CCii CCooSS
Addition oracle example
0 0 000
0 0 110
1 1 001
0 1 100
0 1 011
1 1 111
1 0 011
1 0 100
A B SCiCo
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0 0 11
0
1 1 00
1
0 1 01
1
1 0 01
1
LSB
MSB
A = 0 0 1 1B = 0 1 0 1
Sum = 1 0 0 0
S = 1 0 0 0
“3 + 5 = 8”
Addition oracle example
A B SCi
Co
• Each tile implemented using logic circuitry
Bit from the truth table
A B SCiCo
Addition oracle example
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Organization & Architecture
R0* R1* R2 R3 R4ACC*
OperationB C D S
Status bitsWR
• Nanotechnology,vol. 15, 1688-1694, 2004.
• Ph.D. dissertation, Univ. of North Carolina, Chapel Hill, 2003.
• IEEE Computer, vol. 38, pp. 56-64, 2005.
• IEEE Trans. on VLSI, vol. 12, pp. 1214-1220, 2004.
Question0 Answer0
log2(n) bits. .
.
Questionn-1 Answern-1
Oracles Decoupled array multiprocessor (DAMP)
Basic system criteria
10X
Device-level simulationAND
Real-device parameter extraction
Interconnect & integration (SPICE, etc.)
Organization / architecture& application performance
(SimpleScalar, custom, etc.)
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• Electrical behavior very similar to conventional MOSFETs
• E.g., the ring-gated FET
-1.6x10-6
-1.4x10-6
-1.2x10-6
-1.0x10-6
-8.0x10-7
-6.0x10-7
-4.0x10-7
-2.0x10-7
0.0x100
-1 -0.9 -0.8 -0.7 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0
Dra
in-t
o-so
urce
Cur
rent
Drain-to-source Voltage
Ids(Vgs= 0.00)Ids(Vgs=-0.05)Ids(Vgs=-0.10)Ids(Vgs=-0.25)
P-FET IV Curves
0.0x100
5.0x10-7
1.0x10-6
1.5x10-6
2.0x10-6
2.5x10-6
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Dra
in-t
o-so
urce
Cur
rent
Drain-to-source Voltage
Ids(Vgs=1.00)Ids(Vgs=0.90)Ids(Vgs=0.80)Ids(Vgs=0.75)
N-FET IV Curves
Case study: Silicon nanowires to DAMP
IEEE Trans. Nano, 2 (2): pp. 69-74, 2003.
Interconnect & IntegrationCase study: Silicon nanowires to DAMP
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Organization & Architecture
R0* R1* R2 R3 R4ACC*
OperationB C D S
Status bits
WR
Decoupled array multiprocessor (DAMP)
Case study: Silicon nanowires to DAMP
COST(R1, R2) // Save last ∆X, copy F into accADDI(∆fi) // Accumulate the next intervalSTORE(R2) // Save itLOAD(Mi-1) // Load the correction factor for this intervalCOST(R0, R1) // Save the correction, load the specific Ti valueADDI(-∆Xi) // Subtract the current interval's end value (T)WAITNLT // any processor that didn't end the integration at T...SETB // all processors that DID end at T, set the B bit...RESUME // all-aboardWAITB
Application Performance (DES)Case study: Silicon nanowires to DAMP
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0123456789
10
DAMP IBM BlueGene/L NEC EarthSimulator
SETI@Home Intel Pentium 4
Log
sear
ch ti
me
(sec
)
Application Performance (DES)Case study: Silicon nanowires to DAMP
0
2
4
6
8
10
DAMP IBM BlueGene/L NEC EarthSimulator
SETI@Home Intel Pentium 4
Log
scal
e
Energy/op (fJ)
Application Performance (DES)Case study: Silicon nanowires to DAMP
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Electrolyte gated carbon nanotubes
S. Rosenblatt, Y. Yaish, J. Park, J. Gore, andP. L. McEuen, 2002.
Electrolyte gated carbon nanotubes• CMOS vs. CNT ring oscillators (per inverter)
2.91.6~55018nm‡
59.03.4929.670.1µm*
0.170.179524CNT-20nm
27.51.6730.445nm*
47.02.6928.765nm*
74.52.6617.820.13µm*
3058.8714.530.18µm†
Trans. Energy (aJ)Power (uW)fmax (GHz)Technology
† – Verified against MOSIS reference device T3AZ, Dec. 2003.‡ – ITRS 2003 prediction.* – Berkeley predictive technology models, Y. Cao et al., 2000-2002.
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