TY - JOUR

T1 - Design of network-based biocomputation circuits for the exact cover problem

AU - Korten, Till

AU - Diez, Stefan

AU - Linke, Heiner

AU - Nicolau, Dan V.

AU - Kugler, Hillel

N1 - Publisher Copyright:
© 2021 The Author(s).

PY - 2021/8

Y1 - 2021/8

N2 - Exact cover is a non-deterministic polynomial time (NP)-complete problem that is central to optimization challenges such as airline fleet planning and allocation of cloud computing resources. Solving exact cover requires the exploration of a solution space that increases exponentially with cardinality. Hence, it is time- and energy consuming to solve large instances of exact cover by serial computers. One approach to address these challenges is to utilize the inherent parallelism and high energy efficiency of biological systems in a network-based biocomputation (NBC) device. NBC is a parallel computing paradigm in which a given combinatorial problem is encoded into a graphical, modular network that is embedded in a nanofabricated planar device. The network is then explored in parallel using a large number of biological agents, such as molecular-motor-propelled protein filaments. The answer to the combinatorial problem can then be inferred by measuring the positions through which the agents exit the network. Here, we (i) show how exact cover can be encoded and solved in an NBC device, (ii) define a formalization that allows to prove the correctness of our approach and provides a mathematical basis for further studying NBC, and (iii) demonstrate various optimizations that significantly improve the computing performance of NBC. This work lays the ground for fabricating and scaling NBC devices to solve significantly larger combinatorial problems than have been demonstrated so far.

AB - Exact cover is a non-deterministic polynomial time (NP)-complete problem that is central to optimization challenges such as airline fleet planning and allocation of cloud computing resources. Solving exact cover requires the exploration of a solution space that increases exponentially with cardinality. Hence, it is time- and energy consuming to solve large instances of exact cover by serial computers. One approach to address these challenges is to utilize the inherent parallelism and high energy efficiency of biological systems in a network-based biocomputation (NBC) device. NBC is a parallel computing paradigm in which a given combinatorial problem is encoded into a graphical, modular network that is embedded in a nanofabricated planar device. The network is then explored in parallel using a large number of biological agents, such as molecular-motor-propelled protein filaments. The answer to the combinatorial problem can then be inferred by measuring the positions through which the agents exit the network. Here, we (i) show how exact cover can be encoded and solved in an NBC device, (ii) define a formalization that allows to prove the correctness of our approach and provides a mathematical basis for further studying NBC, and (iii) demonstrate various optimizations that significantly improve the computing performance of NBC. This work lays the ground for fabricating and scaling NBC devices to solve significantly larger combinatorial problems than have been demonstrated so far.

KW - Biological computation

KW - Exact cover

KW - NP-complete problems

KW - Network based biocomputation

UR - http://www.scopus.com/inward/record.url?scp=85113336642&partnerID=8YFLogxK

U2 - 10.1088/1367-2630/ac175d

DO - 10.1088/1367-2630/ac175d

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AN - SCOPUS:85113336642

SN - 1367-2630

VL - 23

JO - New Journal of Physics

JF - New Journal of Physics

IS - 8

M1 - 085004

ER -