Skip to content

hbrunie/asgard

 
 

Repository files navigation

ASGarD - Adaptive Sparse Grid Discretization

To cite the ASGarD code in your work, please use: (TODO)

The ASGarD project has the goal of building an solver specifically targeting high-dimensional PDEs where the "curse-of-dimensionality" has previously precluded useful continuum / Eularian (grid or mesh based as opposed to Monte-Carlo sampling) simulation. Our approach is based on a Discontinuous-Galerkin finite-element solver build atop an adaptive hierarchical sparse-grid (note this is different from the "combination tecnique" when applied to sparse-grids).

The developer documentation contains information about how to contribute to the ASGarD project.

  • (TODO) user docs about building/using the code
  • (TODO) docs about the method

Contact Us

Issues are a great way to discuss all aspects of the ASGarD project, whether it is to ask a general question, request a new feature, or propose a contribution to the code base.

The ASGarD project is led by David Green ([email protected]) at Oak Ridge National Laboratory.

Automated Test Status

Test Status (Develop)
format/clang Build Status
warnings/clang Build Status
unit/g++ Build Status
unit/clang++ Build Status
unit/g++/mpi Build Status
unit/g++/cuda Build Status
unit/g++/io Build Status

Dependencies

  • C++17
  • cmake 3.13
  • blas

Optional depedencies

  • cuda
  • mpi
  • highfive/hdf5

Quickstart

Download and build

git clone https://github.com/project-asgard/asgard.git
cd asgard
mkdir build && cd build
cmake ../
make
ctest
./asgard

For best performance (especially on accelerators) please pass -DCMAKE_BUILD_TYPE=Release to disable asserts when building the code.

To see a list of available PDEs, run ./asgard --available_pdes. The listed PDEs can be selected using the -p argument to asgard.

To see the list of all runtime options, run ./asgard --help.

For specific platform build instructions, see this wiki page.

About

No description, website, or topics provided.

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages

  • C++ 97.3%
  • CMake 2.7%