Parallel computation with molecular-motor-propelled agents in nanofabricated networks

The combinatorial nature of many important mathematical problems, including nondeterministic-polynomial-time (NP)-complete problems, places a severe limitation on the problem size that can be solved with conventional, sequentially operating electronic computers. There have been significant efforts i...

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Published inProceedings of the National Academy of Sciences - PNAS Vol. 113; no. 10; pp. 2591 - 2596
Main Authors Nicolau, Dan V., Lard, Mercy, Korten, Till, van Delft, Falco C. M. J. M., Persson, Malin, Bengtsson, Elina, Månsson, Alf, Diez, Stefan, Linke, Heiner
Format Journal Article
LanguageEnglish
Published United States National Academy of Sciences 08.03.2016
National Acad Sciences
Subjects
Annan fysik
biocomputation
Biological Sciences
Chemistry
Combinatorics
Computer and Information Science
Computer Engineering
Data- och informationsvetenskap (Datateknik)
Datorteknik
Energy efficiency
Fysik
Kemi
Mathematical problems
molecular motors
nanotechnology
Natural Sciences
Naturvetenskap
NP complete
Other Physics Topics
parallel computing
Parallel processing
Physical Sciences
Polynomials
Proof theory
Scalability
nanotechnology
NP complete
biocomputation
molecular motors
parallel computing
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Summary:The combinatorial nature of many important mathematical problems, including nondeterministic-polynomial-time (NP)-complete problems, places a severe limitation on the problem size that can be solved with conventional, sequentially operating electronic computers. There have been significant efforts in conceiving parallel-computation approaches in the past, for example: DNA computation, quantum computation, and microfluidics-based computation. However, these approaches have not proven, so far, to be scalable and practical from a fabrication and operational perspective. Here, we report the foundations of an alternative parallel-computation system in which a given combinatorial problem is encoded into a graphical, modular network that is embedded in a nanofabricated planar device. Exploring the network in a parallel fashion using a large number of independent, molecular-motor-propelled agents then solves the mathematical problem. This approach uses orders of magnitude less energy than conventional computers, thus addressing issues related to power consumption and heat dissipation. We provide a proof-of-concept demonstration of such a device by solving, in a parallel fashion, the small instance {2, 5, 9} of the subset sum problem, which is a benchmark NP-complete problem. Finally, we discuss the technical advances necessary to make our system scalable with presently available technology.
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Edited by Hillel Kugler, Microsoft Research, Cambridge, United Kingdom, and accepted by the Editorial Board January 18, 2016 (received for review June 5, 2015)
1Dan V. Nicolau Jr., M.L., and T.K. contributed equally to this work.
Author contributions: Dan V. Nicolau Jr. and Dan V. Nicolau conceived the calculation method and designed the overall network; F.C.M.J.M.v.D designed the junctions; M.L., T.K., F.C.M.J.M.v.D, A.M., S.D., and H.L., designed the device layouts; M.L. and F.C.M.J.M.v.D fabricated the devices; M.L., T.K., M.P., and E.B. ran motility experiments and analyzed motility data; Dan V. Nicolau Jr., T.K., and A.M. carried out numerical simulations; Dan V. Nicolau initiated the project; Dan V. Nicolau and H.L. coordinated the project; and Dan V. Nicolau Jr., M.L., T.K., F.C.M.J.M.v.D., M.P., E.B., A.M., S.D., H.L., and Dan V. Nicolau contributed to planning the work, to data interpretation, and to writing the manuscript.
2Present address: Molecular Sense, Ltd., Wallasey CH44 1AJ, United Kingdom.
ISSN:0027-8424
1091-6490
1091-6490
DOI:10.1073/pnas.1510825113