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This package provides a high-performance, backend-agnostic implementation of the Material Point Method (MPM) using the <ahref="https://julialang.org"target="_blank"><imgsrc="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 <ahref="https://landslidesim.github.io/MaterialPointSolver.jl/stable/"target="_blank">documentation</a>.
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</p>
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> If you have a GPU from Intel® and want to try on it, please [contact me 📧](mailto:zenan.huo@outlook.com).
author = {Zenan Huo and Yury Alkhimenkov and Michel Jaboyedoff and Yury Podladchikov and Ludovic Räss and Emmanuel Wyser and Gang Mei},
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keywords = {MPM, Julia language, Heterogeneous computing, Effective memory throughput}
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}
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```
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> [!CAUTION]
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> This is the latest version of `MaterialPointSover.jl`, if you want to see the examples in the paper, please move to [https://github.com/LandslideSIM/Archive_MaterialPointSolver.jl_paper](https://github.com/LandslideSIM/Archive_MaterialPointSolver.jl_paper).
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> [!TIP]
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> After the article was published, we released many new features and achieved significant performance improvements. We are currently actively working on completing the documentation. If possible, you can directly review the source code.
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> 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.
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