Giter Club home page Giter Club logo

mars's Introduction

License Build status

M.A.R.S

Mesh Adaptive Refinement for Supercomputing

MARS is an open-source mesh management library designed to handle N-dimensional elements (N <= 4). MARS is developed in C++ and makes use of template meta-programming to have compile time dimensions of elements and vectors, thus allowing for both compile time performance optimizations and concise and reusable code.

The main features of MARS consist of:

  1. Parallel mesh generation

  2. Adaptive mesh refinement using bisection algorithms

  3. Conforming mesh data-structure

  4. Mesh quality estimators to study the output of different mesh-refinement strategies

  5. Performance portable algorithms and data-structures targetting different accelerators

  6. Performance portable space filling curves algorithms for efficient mesh management.

MARS targets multi-core CPUs and GPUs using the C++ Kokkos programming model. The mesh is entirely constructed and stored on the device (GPUs). This enables libraries using MARS to perform further operations directly on the device, avoiding going through the host.

Currently, MARS supports as its performance portable, parallel, adaptive refinement based algorithm the LEPP (Longest edge propagation path) from Rivara. Mesh generation is fully supported in parallel.

Performance portable forest of octrees and space filling curves algorithms for adaptive mesh refinement are being planned.

Downloading MARS and its dependencies

Clone the repository and its submodules. MARS relies on googletest and google/benchmark.

git clone --recurse-submodules https://bitbucket.org/zulianp/mars.git or for older git versions

git clone https://bitbucket.org/zulianp/mars.git && cd mars && git submodule update --init --recursive

Compiling M.A.R.S for serial usage:

- cd mars/
- mkdir build
- cd build
- cmake ..
- make

MARS Kokkos requirements

Mars depends on both Kokkos and Kokkos Kernels libraries.

It will automatically find Kokkos if installed into your system. It can work with kokkos standalone or with kokkos from the Trilinos library.

Mars looks for KOKKOS_DIR or TRILINOS_DIR into the environment variables. When using Trilinos it will find them from Trilinos in $TRILINOS_DIR otherwise it will look for kokkos and kokkos kernels installations at $KOKKOS_DIR.

Use -DMARS_ENABLE_KOKKOS=ON to use the feature. For more details check CMakeLists.txt.

The default when compiling MARS with Kokkos without specifing any other CMAKE flag is the Kokkos/OpenMP execution space. Kokkos should also be compiled with OpenMP support. Otherwise the default is the serial execution space.

To compile for CUDA the Cmake flag needs to be set: MARS_ENABLE_CUDA=ON. An example would be:

cmake -DCMAKE_VERBOSE_MAKEFILE=ON -DCMAKE_BUILD_TYPE=Release -DMARS_ENABLE_KOKKOS=ON -DMARS_ENABLE_CUDA=ON ..

If compiled for CUDA then Kokkos should also be compiled with CUDA (Kokkos_ENABLE_CUDA=ON) and CUDA_LAMBDA (Kokkos_ENABLE_CUDA_LAMBDA=ON) support.

Contributors

Zulian Patrick, Ganellari Daniel and Ramelli Dylan.

License

The software is realized with NO WARRANTY and it is licenzed under BSD 3-Clause license

Copyright

Copyright (c) 2015 Institute of Computational Science - USI Università della Svizzera Italiana, ETH-Z Eidgenössische Technische Hochschule Zürich

Cite MARS

If you use MARS CPU please use the following bibliographic entry

#!bibtex

@misc{marscpu,
    author = {Zulian, Patrick and Ganellari, Daniel and Rovi, Gabriele and Ramelli, Dylan},
    title = {{MARS} - {M}esh {A}daptive {R}efinement for {S}upercomputing. {G}it repository},
    url = {https://bitbucket.org/zulianp/mars},
    year = {2018}
}

If you use MARS GPU please use the following bibliographic entry

#!bibtex

@misc{marsgpu,
    author = {Ganellari, Daniel and Zulian, Patrick and Rovi, Gabriele and Ramelli, Dylan},
    title = {{MARS} - {M}esh {A}daptive {R}efinement for {S}upercomputing. {G}it repository},
    url = {https://bitbucket.org/zulianp/mars},
    year = {2018}
}

mars's People

Contributors

delyank avatar dganellari avatar dylanreidramelli avatar edopao avatar finkandreas avatar millakaragyaur avatar nuraiman avatar zulianp avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.