A novel scalable high performance diffusion solver for multiscale cell simulations

TL;DR

This paper introduces a scalable high-performance diffusion solver for multiscale cell simulations, significantly improving speed and memory efficiency for large-scale tissue modeling using HPC and an advanced finite volume method.

Contribution

The paper presents a novel scalable BioFVM library that enhances diffusion modeling efficiency, enabling real-scale tumor simulations with high performance and reduced memory usage.

Findings

Achieved nearly 200x speedup over existing solutions.

Reduced memory usage by up to 36%.

Enabled efficient large-scale biological simulations.

Abstract

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.