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Installation with CMake

At the exaNBody level, a mini MD app is avaiable for benchmark and optimization purposes. That mini app only contains the Lennard-Jones and the SNAP potentials. Below are the minimal instructions to build that mini app.

The following installation consists in first building both the ONIKA HPC platform and the exaNBody particle simulation platform. Below are instructions for building both as well as final instruction for running the SNAP case where the initial system is read from a dump file.

For all the codes, a single installation method through the use of CMake is provided, dedicated to both users and developer. The use of CMake allows the full support on both CPU and GPU architectures.

Minimal requirements

YAML library

All three platforms extensively use the YAML Library. To build YAML from sources, read the following instructions. Installations procedures using spack, apt-get or CMake are provided.

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sudo apt-get install libyaml-cpp-dev

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spack install yaml-cpp@0.6.3
spack load yaml-cpp@0.6.3

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# 1. Retrieve yaml-cpp-0.6.3 sources into temporary folder

YAMLTMPFOLDER=${path_to_tmp_yaml}
mkdir ${YAMLTMPFOLDER} && cd ${YAMLTMPFOLDER}
git clone --depth 1 --branch yaml-cpp-0.6.3 git@github.com:jbeder/yaml-cpp.git

# 2. Setup environment variable for installation directory (add this to your .bashrc)

export YAML_CPP_INSTALL_DIR=${HOME}/local/yaml-cpp-0.6.3

# 3. Build and install using CMake

cd ${YAMLTMPFOLDER} && mkdir build && cd build
cmake -DCMAKE_BUILD_TYPE=Debug \
      -DCMAKE_INSTALL_PREFIX=${YAML_CPP_INSTALL_DIR} \
      -DYAML_BUILD_SHARED_LIBS=OFF \
      -DYAML_CPP_BUILD_CONTRIB=ON \
      -DYAML_CPP_BUILD_TESTS=OFF \
      -DYAML_CPP_BUILD_TOOLS=OFF \
      -DYAML_CPP_INSTALL=ON \
      -DCMAKE_CXX_FLAGS=-fPIC \
      ../yaml-cpp
make -j4 install

# 4. Remove the temporary folder
cd ../../
rm -r ${YAMLTMPFOLDER}

At this point, you should have YAML installed on your system. Please note that the installation procedure of YAML from sources using CMake also works on HPC clusters. In the following, remember to add the `-DCMAKE_PREFIX_PATH=${YAML_CPP_INSTALL_DIR} argument to your cmake command.

Onika

onika (Object Network Interface for Knit Applications), is a component based HPC software platform to build numerical simulation codes. It is the foundation for the exaNBody particle simulation platform but is not bound to N-Body problems nor other domain specific simulation code. onika uses industry grade standards and widely adopted technologies such as CMake and C++20 for development and build, YAML for user input files, MPI and OpenMP for parallel programming, Cuda and HIP for GPU acceleration. To build onika from sources, read the following instructions. First, create and go to a directory in which you'll download the sources and declare some environment variables.

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cd ${HOME}/dev
git clone git@github.com:Collab4exaNBody/onika.git
export ONIKA_SRC_DIR=${HOME}/dev/onika
export ONIKA_INSTALL_DIR=${HOME}/local/onika

Finally, build and install onika using the following instructions depending on the platform. Available instructions are for Linux machines with and without Cudasupport.

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mkdir build_onika && cd build_onika
ONIKA_SETUP_ENV_COMMANDS=""
eval ${ONIKA_SETUP_ENV_COMMANDS}
cmake -DCMAKE_BUILD_TYPE=Release \
      -DCMAKE_INSTALL_PREFIX=${ONIKA_INSTALL_DIR} \
      -DCMAKE_PREFIX_PATH=${YAML_CPP_INSTALL_DIR} \
      -DONIKA_BUILD_CUDA=OFF \
      -DONIKA_SETUP_ENV_COMMANDS="${ONIKA_SETUP_ENV_COMMANDS}" \
      ${ONIKA_SRC_DIR}
make -j4 install

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mkdir build_onika && cd build_onika
ONIKA_SETUP_ENV_COMMANDS=""
PATH_TO_NVCC=$(which nvcc)
eval ${ONIKA_SETUP_ENV_COMMANDS}
cmake -DCMAKE_BUILD_TYPE=Release \
      -DCMAKE_INSTALL_PREFIX=${ONIKA_INSTALL_DIR} \
      -DCMAKE_PREFIX_PATH=${YAML_CPP_INSTALL_DIR} \
      -DONIKA_BUILD_CUDA=ON \
      -DCMAKE_CUDA_COMPILER=${PATH_TO_NVCC} \
      -DCMAKE_CUDA_ARCHITECTURES=${ARCH} \
      -DONIKA_SETUP_ENV_COMMANDS="${ONIKA_SETUP_ENV_COMMANDS}" \
      ${ONIKA_SRC_DIR}
make -j4 install

exaNBody x microStamp

exaNBody is a software platform to build-up numerical simulations solving N-Body like problems. To build exaNBody from sources, read the following instructions. First, create and go to a directory in which you'll download the sources and declare some environment variables.

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cd ${HOME}/dev
git clone git@github.com:Collab4exaNBody/exaNBody.git
export XNB_SRC_DIR=${HOME}/dev/exaNBody
export XNB_INSTALL_DIR=${HOME}/local/exaNBody

Finally, build and install exaNBody using the following instructions. First sourcing the onika environment will automatically update whether cuda support is available. To build the support for the microStamp MD miniapp, you need to declare the 

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mkdir build_exaNBody && cd build_exaNBody
source ${ONIKA_INSTALL_DIR}/bin/setup-env.sh
cmake -DCMAKE_BUILD_TYPE=Release \
      -DCMAKE_INSTALL_PREFIX=${XNB_INSTALL_DIR} \
      -Donika_DIR=${ONIKA_INSTALL_DIR} \
      -DEXANB_BUILD_CONTRIB_MD=ON \
      -DEXANB_BUILD_MICROSTAMP=ON \
      -DSNAP_CPU_USE_LOCKS=ON \
      -DSNAP_FP32_MATH=OFF \
      ${XNB_SRC_DIR}
make -j4 install

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mkdir build_exaNBody && cd build_exaNBody
source ${ONIKA_INSTALL_DIR}/bin/setup-env.sh
cmake -DCMAKE_BUILD_TYPE=Release \
      -DCMAKE_INSTALL_PREFIX=${XNB_INSTALL_DIR} \
      -Donika_DIR=${ONIKA_INSTALL_DIR} \
      -DEXANB_BUILD_CONTRIB_MD=ON \
      -DEXANB_BUILD_MICROSTAMP=ON \
      -DSNAP_CPU_USE_LOCKS=ON \
      -DSNAP_FP32_MATH=OFF \
      ${XNB_SRC_DIR}
make -j4 install