Shortest path computing in directed graphs with weighted edges mapped on random networks of memristors
Visualitza/Obre
Cita com:
hdl:2117/332095
Tipus de documentArticle
Data publicació2020-03-01
Condicions d'accésAccés obert
Tots els drets reservats. Aquesta obra està protegida pels drets de propietat intel·lectual i
industrial corresponents. Sense perjudici de les exempcions legals existents, queda prohibida la seva
reproducció, distribució, comunicació pública o transformació sense l'autorització del titular dels drets
Abstract
To accelerate the execution of advanced computing tasks, in-memory computing with resistive memory provides a promising solution. In this context, networks of memristors could be used as parallel computing medium for the solution of complex optimization problems. Lately, the solution of the shortest-path problem (SPP) in a two-dimensional memristive grid has been given wide consideration. Some still open problems in such computing approach concern the time required for the grid to reach to a steady state, and the time required to read the result, stored in the state of a subset of memristors that represent the solution. This paper presents a circuit simulation-based performance assessment of memristor networks as SPP solvers. A previous methodology was extended to support weighted directed graphs. We tried memristor device models with fundamentally different switching behavior to check their suitability for such applications and the impact on the timely detection of the solution. Furthermore, the requirement of binary vs. analog operation of memristors was evaluated. Finally, the memristor network-based computing approach was compared to known algorithmic solutions to the SPP over a large set of random graphs of different sizes and topologies. Our results contribute to the proper development of bio-inspired memristor network-based SPP solvers.
Descripció
Electronic version of an article published as [Fernandez, Carlos, Ioannis Vourkas, and Antonio Rubio. "Shortest Path Computing in Directed Graphs with Weighted Edges Mapped on Random Networks of Memristors." Parallel Processing Letters 30.01 (2020): 2050002] [https://doi.org/10.1142/S0129626420500024] © [copyright World Scientific Publishing Company] [https://www.worldscientific.com/worldscinet/ppl]
CitacióFernández, C.; Vourkas, I.; Rubio, A. Shortest path computing in directed graphs with weighted edges mapped on random networks of memristors. "Parallel processing letters", 1 Març 2020, vol. 30, núm. 1, p. 2050002:1-2050002:17.
ISSN0129-6264
Versió de l'editorhttps://www.worldscientific.com/doi/abs/10.1142/S0129626420500024
Fitxers | Descripció | Mida | Format | Visualitza |
---|---|---|---|---|
X.pdf | Article principal | 1,497Mb | Visualitza/Obre |