Open this publication in new window or tab >>Show others...
2022 (English)In: ACS Nanoscience Au, ISSN 2694-2496, Vol. 2, no 5, p. 396-403Article in journal (Refereed) Published
Abstract [en]
Information processing by traditional, serial electronic processors consumes an ever-increasing part of the global electricity supply. An alternative, highly energy efficient, parallel computing paradigm is network-based biocomputation (NBC). In NBC a given combinatorial problem is encoded into a nanofabricated, modular network. Parallel exploration of the network by a very large number of independent molecular-motor-propelled protein filaments solves the encoded problem. Here we demonstrate a significant scale-up of this technology by solving four instances of Exact Cover, a nondeterministic polynomial time (NP) complete problem with applications in resource scheduling. The difficulty of the largest instances solved here is 128 times greater in comparison to the current state of the art for NBC.
Place, publisher, year, edition, pages
American Chemical Society (ACS), 2022
Keywords
parallel computing, computational nanotechnology, molecular motors, biocomputation, nanobiotechnology, biofunctionalization
National Category
Nano Technology Computer Systems
Identifiers
urn:nbn:se:kth:diva-316529 (URN)10.1021/acsnanoscienceau.2c00013 (DOI)001093907700002 ()36281252 (PubMedID)2-s2.0-85136696094 (Scopus ID)
Funder
EU, Horizon 2020
Note
QC 20250513
2022-08-222022-08-222025-05-13Bibliographically approved