Abstract
The high energy consumption of electronic data processors, together with physical challenges limiting their further improvement, has triggered intensive interest in alternative computation paradigms. Here we focus on network-based biocomputation (NBC), a massively parallel approach where computational problems are encoded in planar networks implemented with nanoscale channels. These networks are explored by biological agents, such as biological molecular motor systems and bacteria, benefitting from their energy efficiency and availability in large numbers. We analyse and define the fundamental requirements that need to be fulfilled to scale up NBC computers to become a viable technology that can solve large NP-complete problem instances faster or with less energy consumption than electronic computers. Our work can serve as a guide for further efforts to contribute to elements of future NBC devices, and as the theoretical basis for a detailed NBC roadmap.
Highlights
The remarkable development of semiconductor technology, guided by the International Technology Roadmap for Semiconductors (ITRS) [1] and described by Moore’s law [2] over the past five decades, has resulted in electronic processors that excel at fast and reliable processing of data in a sequential manner
We focus on network-based biocomputation (NBC), a massively parallel approach that benefits from the energy efficiency of biological agents, such as molecular motors or bacteria, and their availability in large numbers
We analyse and define the fundamental requirements that need to be fulfilled to scale up NBC computers to become a viable technology that can solve large NP-complete problem instances faster or with less energy consumption than electronic computers
Summary
The remarkable development of semiconductor technology, guided by the International Technology Roadmap for Semiconductors (ITRS) [1] and described by Moore’s law [2] over the past five decades, has resulted in electronic processors that excel at fast and reliable processing of data in a sequential manner. Parallel computers are not subject to the same, fundamental trade-off between speed and energy use as electronic processors and may be able to solve much larger combinatorial problems with acceptable energy cost. We analyse the fundamental requirements that need to be fulfilled to scale up NBC computers to become a viable technology that solves large NP problem instances faster or with less energy consumption than electronic computers. The scale-up of NBC would require scalable agents (available in large quantity) with high moving speed and energy efficiency; a scalable physical network that ensures agent motion with negligible error rate; the ability to tag the agents in the network with negligible errors and lastly, the ability to detect single agents in parallel. We briefly discuss the contents of a future, detailed NBC roadmap
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
