Document Type

Article

Publication Date

10-2026

Department

Department of Computer Science

Abstract

A major revision of the ChemNetworks software (originally published in the Journal of Computational Chemistry, 2014, 35, 495–505) is presented. While the original ChemNetworks provided foundational graph construction capabilities for chemical systems, it was limited to simple distance and 3-body angular edge criteria, was not designed for high-performance computing environments or real-time operation alongside running simulations. This release addresses these limitations through three core contributions. First, a recursive Z-matrix-based search algorithm is introduced that enables chemically intuitive, arbitrarily descriptive three-dimensional structure searches, supporting geometric, energetic, and logical criteria. Second, the DataSpaces data staging framework is incorporated as an optional I/O engine, enabling in-memory data exchange between ChemNetworks and running simulations that eliminates persistent storage bottlenecks and supports real-time graph construction and analysis. Third, a modular analysis framework leveraging the igraph library is introduced, providing a straightforward plugin architecture for community-contributed workflows. Benchmark results demonstrate linear scaling with system size and efficient MPI parallelization across up to 64 cores, with total computational complexity of O(NRT/P), where N is the number of atoms, R is the Z-matrix depth, T is the number of timesteps, and P is the number of MPI processes. NEW VERSION PROGRAM SUMMARY: Program Title: ChemNetworks CPC Library link to program files: https://doi.org/10.17632/52h5ftzkfv.1 Developer's repository link: https://gitlab.com/ChemNetworks/ChemNetworks Licensing provisions: GPLv3 Programming language: C++ Supplementary material: https://chemnetworks.readthedocs.io Journal reference of previous version: A. Özkanlar, A.E. Clark, ChemNetworks: A complex network analysis tool for chemical systems, J. Comput. Chem. 35 (2014) 495–505 [1]. Does the new version supersede the previous version?: Yes Reasons for the new version: ChemNetworks was limited to simple distance and angular edge criteria, lacked HPC support, and could not operate in real-time alongside running simulations. Nature of problem:Molecular dynamics simulations generate large volumes of coordinate data requiring conversion to graph representations for network-based chemical analysis. Existing tools are limited to simple pairwise or angular criteria, cannot describe arbitrary 3D structures or stereoisomers, and are ill-suited for HPC environments. Writing simulation output to disk before graph construction creates I/O bottlenecks that worsen with system size. Solution:ChemNetworks builds graphs from standard trajectory files, with nodes representing atoms or molecules and edges defined via a recursive Z-matrix-based algorithm supporting geometric (distance, angle, dihedral), energetic (Lennard-Jones), and boolean criteria. Graph operations use the igraph C library [2]. MPI distributes timesteps across processors via round-robin partitioning. Optional DataSpaces [3] integration enables in-memory simulation coupling, and a plugin architecture supports user-contributed analyses. Summary of revisions: Complete rewrite in C++20. Key additions include: a recursive Z-matrix-based search algorithm supporting geometric, energetic, and logical edge criteria; DataSpaces integration for real-time in-memory data exchange with running simulations; a plugin architecture via the igraph library [2] for community-contributed analyses; and MPI parallelization for multi-core scaling. Additional comments:Requires a C++20-compliant compiler (GCC 13.1+). MPI and DataSpaces integration are both optional. References [1] A. Ozkanlar, A.E. Clark, ChemNetworks: A complex network analysis tool for chemical systems, J. Comput. Chem. 35 (2014) 495–505. [2] G. Csárdi, T. Nepusz, The igraph software package for complex network research, InterJournal Complex Systems (2006) 1695. [3] C. Docan, M. Parashar, S. Klasky, Enabling high-speed asynchronous data extraction and transfer using DART, Concurr. Comput. Pract. Exp. 22 (2010) 1181–1204.

Publisher's Statement

© 2026 The Authors. Published by Elsevier B.V. Publisher’s version of record: https://doi.org/10.1016/j.cpc.2026.110252

Publication Title

Computer Physics Communications

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