Paper Info
Title
Shortest Path Computing in Directed Graphs with Weighted Edges Mapped on Random Networks of Memristors.
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.
Year
DOI
Venue
2020
10.1142/S0129626420500024
PARALLEL PROCESSING LETTERS
Keywords
DocType
Volume
Memristor network,resistive switching,shortest path,computational memory,resistive computing
Journal
30
Issue
ISSN
Citations 
1
0129-6264
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Carlos Fernandez121.87
Ioannis Vourkas29916.26
Antonio Rubio300.34