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

Research output: Contribution to journalArticle

Abstract

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.

Details

Authors
  • Dan V Nicolau
  • Mercy Lard
  • Till Korten
  • Falco C M J M van Delft
  • Malin Persson
  • Elina Bengtsson
  • Alf Månsson
  • Stefan Diez
  • Heiner Linke
  • Dan V Nicolau
Organisations
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Computer Engineering
Original languageEnglish
Pages (from-to)2591-2596
JournalProceedings of the National Academy of Sciences
Volume113
Issue number10
Early online date2016 Feb 22
Publication statusPublished - 2016
Publication categoryResearch
Peer-reviewedYes