MATILDA.FT, a Mesoscale Simulation Package for Inhomogeneous Soft Matter

TL;DR

MATILDA.FT is a GPU-accelerated, versatile simulation software that uniquely combines coarse-grained molecular dynamics and field-theoretical methods for mesoscale modeling of inhomogeneous soft matter.

Contribution

It is the first software to integrate both simulation approaches on a GPU platform, enabling efficient mesoscale modeling of complex soft matter systems.

Findings

Successfully modeled polymer solutions and nanoparticle-polymer interfaces.

Achieved significant speedup through GPU parallelism.

Provided a flexible, extendable simulation framework.

Abstract

In this paper we announce the public release of a massively-parallel, GPU-accelerated software, which is the first to combine both coarse-grained molecular dynamics and field-theoretical simulations in one simulation package. MATILDA.FT (Mesoscale, Accelerated, Theoretically-Informed, Langevin, Dissipative particle dynamics, and Field Theory) was designed from the ground-up to run on CUDA-enabled GPUs, with the Thrust library acceleration, enabling it to harness the possibility of massive parallelism to efficiently simulate systems on a mesoscopic scale. MATILDA.FT is a versatile software, enabling the users to use either Langevin dynamics or Field Theory to model their systems - all within the same software. It has been used to model a variety of systems, from polymer solutions, and nanoparticle-polymer interfaces, to coarse-grained peptide models, and liquid crystals. MATILDA.FT is written in CUDA/C++ and is object oriented, making its source-code easy to understand and extend. The software comes with dedicated post-processing and analysis tools, as well as the detailed documentation and relevant examples. Below, we present an overview of currently available features. We explain in detail the logic of parallel algorithms and methods. We provide necessary theoretical background, and present examples of recent research projects which utilized MATILDA.FT as the simulation engine. We also demonstrate how the code can be easily extended, and present the plan for the future development. The source code, along with the documentation, additional tools and examples can be found on GitHub repository.