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MaterialPointSolver.jl

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🧮 High-performance Material Point Method (MPM) Solver in Julia.

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# *MaterialPointSolver* <img src="docs/src/assets/logo.png" align="right" height="126" />

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<p>
This package provides a high-performance, backend-agnostic implementation of the Material Point Method (MPM) using the <a href="https://julialang.org" target="_blank"><img src="https://raw.githubusercontent.com/JuliaLang/julia-logo-graphics/master/images/julia.ico" width="16em"> Julia Language</a>. It is lightweight and user-friendly, allowing efficient execution on various hardware accelerators with a single codebase. Please check here for the <a href="https://landslidesim.github.io/MaterialPointSolver.jl/stable/" target="_blank">documentation</a>.
</p>

## Installation ⚙️

Just type <kbd>]</kbd> in Julia's `REPL`:

```julia
julia> ]
(@1.11) Pkg> add MaterialPointSolver
```

## Design Philosophy 🧠

- [x] A high-performance MPM solver for flexible scientific prototyping
- [x] Supports user-defined fields and custom logic (e.g. acoustics, heat)
- [x] Can be used in production environments with care to avoid performance regressions
- [x] All MPM algorithms are modularized as plugins for easy modification and sharing

## Citation 🔥

If you find `MaterialPointSolver.jl` useful or have used it in your research, please cite it as follows:

```bib
@article{HUO2025107189,
    title = {A high-performance backend-agnostic Material Point Method solver in Julia},
    journal = {Computers and Geotechnics},
    volume = {183},
    pages = {107189},
    year = {2025},
    issn = {0266-352X},
    doi = {https://doi.org/10.1016/j.compgeo.2025.107189},
    url = {https://www.sciencedirect.com/science/article/pii/S0266352X25001387},
    author = {Zenan Huo and Yury Alkhimenkov and Michel Jaboyedoff and Yury Podladchikov and Ludovic Räss and Emmanuel Wyser and Gang Mei},
    keywords = {MPM, Julia language, Heterogeneous computing, Effective memory throughput}
}
```
> [!CAUTION]
> This repo is the LATEST version of `MaterialPointSover.jl`. After the article was published, we released many new features and achieved significant performance improvements. Please move to [https://github.com/LandslideSIM/Archive_MaterialPointSolver.jl_paper](https://github.com/LandslideSIM/Archive_MaterialPointSolver.jl_paper) for the code used in the paper.

## Acknowledgement 👍

This project is sponsored by [Risk Group | Université de Lausanne](https://wp.unil.ch/risk/) and [China Scholarship Council [中国国家留学基金管理委员会]](https://www.csc.edu.cn/).

## MPM ➕ Julia

* [📦 [package]: elastoPlasm.jl](https://github.com/ewyser/elastoPlasm.jl) is fully witten in Julia, it solves explicit elasto-plastic problems within a finite deformation framework.

* [📦 [package]: Tesserae.jl](https://github.com/KeitaNakamura/Tesserae.jl) is an MPM-related Julia package, it provides some useful functions that can be used for MPM, such as convenient macros for transferring data between grids and particles.

* [✍️ [code]: MPM-Julia](https://github.com/vinhphunguyen/MPM-Julia) is the code for the paper: Sinai, V.P. Nguyen, C.T. Nguyen and S. Bordas. Programming the Material Point Method in Julia. Advances in Engineering Software,105: 17--29, 2017.

* [✍️ [code]: jump](https://github.com/vinhphunguyen/jump) is for the theory of the MPM described in the book 'The Material Point Method: Theory, Implementations and Applications (Scientific Computation) 1st ed. 2023 Edition'. 
[https://link.springer.com/book/10.1007/978-3-031-24070-6](https://link.springer.com/book/10.1007/978-3-031-24070-6)

MaterialPointSolver.jl

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