Skip to content

PROGRESS: Parallel, Rapid O(N) and Graph-based Recursive Electronic Structure Solver.

License

Notifications You must be signed in to change notification settings

lanl/qmd-progress

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

This website is intended to provide some guidance on how to get and install the PROGRESS library. LA-UR number LA-UR-17-27372

Issues Pull Requests CI Docker
GitHub issues GitHub pull requests GitHub Actions Docker Pulls

A library for quantum chemistry solvers

PROGRESS: Parallel, Rapid O(N) and Graph-based Recursive Electronic Structure Solver. LA-CC-16-068

Authors

(in alphabetical order)

Contributors

Build Dependencies

  • >=OpenMP-3.1
  • >=metis-5.0 if building with PROGRESS_GRAPHLIB

Note that on some distributions, metis is available as a package. Make sure you install the -dev package. For example, Ubuntu requires libmetis-dev.

Testing in our CI container

We are switching our CI tests from Travis-CI to GitHub Actions because Travis-CI is limiting the number of builds for open source projects. Our workflow uses a custom Docker image which comes with the necessary compiler tool chain and a pre-installed bml library to build and test the qmd-progress library. Using docker is a convenient and quick way to develop, build, and test the qmd-progress library.

./scripts/run-local-docker-container.sh

Inside the container:

./build.sh compile

Alternatively, you can run one of the CI tests by executing e.g.

./scripts/ci-with-graphlib-debug.sh

Build and Install Instructions

How to build

CMAKE_PREFIX_PATH=<BML install path> ./build.sh

How to install

cd build
sudo make install

To specify the Intel Fortran compiler:

FC=ifort PKG_CONFIG_PATH=<BML install path>/lib/pkgconfig ./build.sh

To build with the gfortran compiler and OpenMP:

CC=gcc FC=gfortran \
    CMAKE_BUILD_TYPE=Release \
    PROGRESS_OPENMP=yes \
    CMAKE_PREFIX_PATH=<BML install path> \
    CMAKE_INSTALL_PREFIX=<PROGRESS install path> \
    ./build.sh configure

To build with OpenMP, MPI and testing enabled:

CC=mpicc FC=mpif90 \
    CMAKE_BUILD_TYPE=Release \
    PROGRESS_OPENMP=yes \
    PROGRESS_MPI=yes \
    PROGRESS_TESTING=yes \
    CMAKE_PREFIX_PATH=<BML install path> \
    CMAKE_INSTALL_PREFIX=<PROGRESS install path> \
    ./build.sh configure

To build with OpenMP, MPI, testing enabled and example programs built:

CC=mpicc FC=mpif90 \
        CMAKE_BUILD_TYPE=Release \
        PROGRESS_OPENMP=yes \
        PROGRESS_MPI=yes \
        PROGRESS_TESTING=yes \
        PROGRESS_EXAMPLES=yes \
        CMAKE_PREFIX_PATH=<BML install path> \
        CMAKE_INSTALL_PREFIX=<PROGRESS install path> \
        ./build.sh configure

To build with OpenMP and MPI and testing enabled and example programs built and the METIS graph partitioning library:

CC=mpicc FC=mpif90 \
        CMAKE_BUILD_TYPE=Release \
        PROGRESS_OPENMP=yes \
        PROGRESS_MPI=yes \
        PROGRESS_GRAPHLIB=yes \
        PROGRESS_TESTING=yes \
        PROGRESS_EXAMPLES=yes \
        CMAKE_PREFIX_PATH=<BML install path> \
        CMAKE_INSTALL_PREFIX=<PROGRESS install path> \
        ./build.sh configure

Citing

@misc{2016progress,
    title={\textrm{PROGRESS} Version 1.0},
    author={Niklasson, Anders M. and
            Mniszewski, Susan M and
            Negre, Christian F. A. and
            Wall, Michael E. and
            Cawkwell, Marc J., and
            Nicolas Bock},
    year={2016},
    url = {https://github.com/lanl/qmd-progress},
    institution={Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)}
}

Support acknowledges

This development is currently supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of two U.S. Department of Energy organizations (Office of Science and the National Nuclear Security Administration) responsible for the planning and preparation of a capable exascale ecosystem, including software, applications, hardware, advanced system engineering, and early testbed platforms, in support of the nation’s exascale computing imperative.

Basic Energy Sciences (LANL2014E8AN) and the Laboratory Directed Research and Development Program of Los Alamos National Laboratory. To tests these developments we used resources provided by the Los Alamos National Laboratory Institutional Computing Program, which is supported by the U.S. Department of Energy National Nuclear Security Administration