Academic Journal
Parallelization of Network Dynamics Computations in Heterogeneous Distributed Environment
| Title: | Parallelization of Network Dynamics Computations in Heterogeneous Distributed Environment |
|---|---|
| Authors: | Oleksandr Sudakov, Volodymyr Maistrenko |
| Source: | IEEE Transactions on Parallel and Distributed Systems. 36:2030-2044 |
| Publication Status: | Preprint |
| Publisher Information: | Institute of Electrical and Electronics Engineers (IEEE), 2025. |
| Publication Year: | 2025 |
| Subject Terms: | FOS: Computer and information sciences, Chaotic Dynamics, FOS: Physical sciences, Distributed, Parallel, and Cluster Computing, Distributed, Parallel, and Cluster Computing (cs.DC), Pattern Formation and Solitons (nlin.PS), Chaotic Dynamics (nlin.CD), Pattern Formation and Solitons |
| Description: | This paper addresses the problem of parallelizing computations to study non-linear dynamics in large networks of non-locally coupled oscillators using heterogeneous computing resources. The proposed approach can be applied to a variety of non-linear dynamics models with runtime specification of parameters and network topologies. Parallelizing the solution of equations for different network elements is performed transparently and, in contrast to available tools, does not require parallel programming from end-users. The runtime scheduler takes into account the performance of computing and communication resources to reduce downtime and to achieve a quasi-optimal parallelizing speed-up. The proposed approach was implemented, and its efficiency is proven by numerous applications for simulating large dynamical networks with 10^3-10^8 elements described by Hodgkin-Huxley, FitzHugh-Nagumo, and Kuramoto models, for investigating pathological synchronization during Parkinson's disease, analyzing multi-stability, for studying chimera and solitary states in 3D networks, etc. All the above computations may be performed using symmetrical multiprocessors, graphic processing units, and a network of workstations within the same run and it was demonstrated that near-linear speed-up can be achieved for large networks. The proposed approach is promising for extension to new hardware like edge-computing devices. 15 pages, 14 figures |
| Document Type: | Article |
| ISSN: | 2161-9883 1045-9219 |
| DOI: | 10.1109/tpds.2025.3593154 |
| DOI: | 10.48550/arxiv.2410.19075 |
| Access URL: | http://arxiv.org/abs/2410.19075 |
| Rights: | IEEE Copyright arXiv Non-Exclusive Distribution |
| Accession Number: | edsair.doi.dedup.....23e34b6f31ece0cdd5177d1cc7e5e824 |
| Database: | OpenAIRE |
| ISSN: | 21619883 10459219 |
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| DOI: | 10.1109/tpds.2025.3593154 |