Authors:
Frankie Spencer
1
;
Usman Sanwal
1
;
2
and
Eugen Czeizler
3
;
4
Affiliations:
1
Department of Information Technologies,Åbo Akademi University, Turku, Finland
;
2
Malardalen University, Sweden
;
3
Faculty of Medicine, University of Helsinki, Finland
;
4
National Institute for Research and Development of Biological Sciences, Bucharest, Romania
Keyword(s):
DNA Self-assembly, Simulation Optimization, Computational Modelling, Multi-threaded Computing, Rule-based Modelling.
Abstract:
In a recent study, Spencer et al. 2021, we have proposed a computational modeling framework for DNA multi-strand dynamics implemented using the agent- and rule-based modeling methodology. While this modeling methodology allows for compact representations for systems with large numbers of different species and complexes, such as the case of self-assembly systems, one of its main drawbacks concerns its scalability. Since each agent is individually represented and modeled in the system, the framework becomes slow when dealing with tens- and hundreds of thousands of individual components. In this study we introduce a method to parallelize the computational modeling process by distributing it over several CPU’s. We show that such multi-thread models remain equivalent to their sequential counterpart, while the speedup of the computational process can reach even a one-fold increase.