Challenges for Biomolecular Computing

Alvin R. Lebeck

Department of Computer Science

Duke University

+ =

Duke Computer Architecture

2© 2008 A. R. LebeckDuke Computer Architecture

Challenges

•Circuit design

•Defect tolerance

•Circuit layout

•Device characteristics

•Automating layout

My Research Goals

• To design computing systems for future technologies– High performance

– New application domains

Computer Architecture

Physics, Chemistry

(CNT, DNA self assembly)

Devices, circuit design

and layout

Challenges

•DNA Self-assembly

•Emerging devices

•Interconnect

Challenges

•Defect tolerance

•Execution model

•Instruction set

•Memory

3© 2008 A. R. LebeckDuke Computer Architecture

Challenges 1

• Infant field– No clear winner for device or fabrication method

– Self-assembly will likely be part of it

– Likely many devices in different places (Randomness)

• Scale– ~1014 letters/mL! (~1014 letters in all books in Library of Congress)

– Mole-core Computer--Avagadro (6.02x1023)

• Defects

• Abstractions– Do we maintain current or create new?

4© 2008 A. R. LebeckDuke Computer Architecture

Hardware & Software

• Designing for defects– No external defect map

– BIST

– Self-organization/self-healing

• Build a big system from small nodes (e.g., LUTs)

• Asynchronous Circuits (w/ transient faults?)

• Programming Systems with Lots of Nodes in Arbitrary Topology

• Program Robustness w/ Unknown and Changing Hardware

5© 2008 A. R. LebeckDuke Computer Architecture

Duke Nanosystems Overview

DNA-based Self-Assembly

Nanoelectronic Devices

Large Scale Interconnection

[NANONETS 2006]

Circuit Architecture [FNANO 2004]

Logical Structure & Defect Isolation [NANOARCH 2005]

A

3.6

1.01.1

1.2

1.31.4 1.5

1.7

1.6 1.T

2.H

2.0 2.1

2.2

2.32.4

2.5

2.T

2.72.6

3.H

3.0

3.4

3.5

3.73.1

3.2

3.3

3.T

1.H

VIA

SOSA - Data Parallel Architecture [NANOARCH 2006,

ASPLOS 2006, JETC 2007]

NANA - General Purpose Architecture [JETC 2006]

MA

EA