A novel scalable high performance diffusion solver for multiscale cell simulations

Fuente: arXiv
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Hauptverfasser: Estragues-Muñoz, Jose-Luis, Alvarez, Carlos, Montagud, Arnau, Jimenez-Gonzalez, Daniel, Valencia, Alfonso
Format: Preprint
Veröffentlicht: 2026
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author Estragues-Muñoz, Jose-Luis
Alvarez, Carlos
Montagud, Arnau
Jimenez-Gonzalez, Daniel
Valencia, Alfonso
author_facet Estragues-Muñoz, Jose-Luis
Alvarez, Carlos
Montagud, Arnau
Jimenez-Gonzalez, Daniel
Valencia, Alfonso
contents Agent-based cellular models simulate tissue evolution by capturing the behavior of individual cells, their interactions with neighboring cells, and their responses to the surrounding microenvironment. An important challenge in the field is scaling cellular resolution models to real-scale tumor simulations, which is critical for the development of digital twin models of diseases and requires the use of High-Performance Computing (HPC) since every time step involves trillions of operations. We hereby present a scalable HPC solution for the molecular diffusion modeling using an efficient implementation of state-of-the-art Finite Volume Method (FVM) frameworks. The paper systematically evaluates a novel scalable Biological Finite Volume Method (BioFVM) library and presents an extensive performance analysis of the available solutions. Results shows that our HPC proposal reach almost 200x speedup and up to 36% reduction in memory usage over the current state-of-the-art solutions, paving the way to efficiently compute the next generation of biological problems.
format Preprint
id arxiv_https___arxiv_org_abs_2602_05017
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle A novel scalable high performance diffusion solver for multiscale cell simulations
Estragues-Muñoz, Jose-Luis
Alvarez, Carlos
Montagud, Arnau
Jimenez-Gonzalez, Daniel
Valencia, Alfonso
Distributed, Parallel, and Cluster Computing
Cell Behavior
Agent-based cellular models simulate tissue evolution by capturing the behavior of individual cells, their interactions with neighboring cells, and their responses to the surrounding microenvironment. An important challenge in the field is scaling cellular resolution models to real-scale tumor simulations, which is critical for the development of digital twin models of diseases and requires the use of High-Performance Computing (HPC) since every time step involves trillions of operations. We hereby present a scalable HPC solution for the molecular diffusion modeling using an efficient implementation of state-of-the-art Finite Volume Method (FVM) frameworks. The paper systematically evaluates a novel scalable Biological Finite Volume Method (BioFVM) library and presents an extensive performance analysis of the available solutions. Results shows that our HPC proposal reach almost 200x speedup and up to 36% reduction in memory usage over the current state-of-the-art solutions, paving the way to efficiently compute the next generation of biological problems.
title A novel scalable high performance diffusion solver for multiscale cell simulations
topic Distributed, Parallel, and Cluster Computing
Cell Behavior
url https://arxiv.org/abs/2602.05017