Install NEST GPU

The NEST GPU installation procedure is similar to the one of NEST CPU (compare with Install NEST from source).

Requirements

  • Currently NEST GPU supports only NVIDIA GPUs and can only be installed on linux systems.

  • To build NEST GPU you need CMake (version 3.17 or higher). You also need the NVIDIA drivers for the GPU card installed in your machine and the NVIDIA CUDA development toolkit. If you are using Ubuntu, here you can find a guide to install the NVIDIA drivers for the GPU card on your machine.

  • To use the NEST GPU Python interface you need Python 3, Numpy, Scipy, and Matplotlib. If you want to run parallel simulations with MPI (on per default), you can use Open MPI and also get MPI4Py.

  • You can obtain the base packages from your system, for example:

sudo apt update

sudo apt install -y \
nvidia-cuda-toolkit \
libomp-dev \
cmake \
openmpi-bin \
openmpi-common \
libopenmpi-dev

  • The Python packages can be installed using a venv environment (recommended):

python3 -m venv nestgpu-env
source nestgpu-env/bin/activate
pip install --upgrade pip

pip install numpy scipy matplotlib mpi4py

or also directly from your system:

sudo apt update

sudo apt install -y \
python3-all-dev \
python3-numpy \
python3-scipy \
python3-matplotlib \
python3-mpi4py

NEST GPU installation from source

  • Define the directory where your source code should be available, for example:

export SOURCE_DIR=$HOME/repositories/nest-gpu

  • Get the source code from GitHub. If you want to use the main branch, run:

git clone git@github.com:nest/nest-gpu.git $SOURCE_DIR

Alternatively, you can checkout a specific release or also download a version as a tarball from https://github.com/nest/nest-gpu/releases and unpack it:

tar -xzvf nest-gpu-x.tar.gz -C $SOURCE_DIR

  • Define the name of your installation, and provide the paths to your preferred build and install directories, then change to the build directory:

export NAME=nest-gpu-x
export BUILD_DIR=$HOME/software/nest-gpu/$NAME/build
export INSTALL_DIR=$HOME/software/nest-gpu/$NAME/install

mkdir -pv $BUILD_DIR
cd $BUILD_DIR

  • Configure NEST GPU. For additional cmake options see the CMake Options, but for a default installation just run:

cmake -DCMAKE_INSTALL_PREFIX:PATH=$INSTALL_DIR $SOURCE_DIR

  • Compile and install NEST GPU - note that you can speed up make by using as many jobs as you have cores available (e.g., make -j 8):

make
make install

  • NEST GPU should now be successfully installed on your system.

Environment variables

  • To find the installation, the following environmental variables are defined in nestgpu_vars.sh:

Variable

Description

PYTHONPATH

Search path for non-standard Python module locations. Will be newly set or prepended to the already existing variable if it is already set.

PATH

Search path for binaries. Will be newly set or prepended to the already existing variable if it is already set.

  • You can set the environment variables in your active shell session:

source $INSTALL_DIR/bin/nestgpu_vars.sh

  • You may want to include this line in your .bashrc file, so that the environment variables are set automatically whenever you open a new terminal. If you installed using a venv environment, make sure that this is also loaded.

  • If Python does not find the nestgpu module, your path variables may not be set correctly. This may also be the case if Python cannot load the nestgpu module due to missing or incompatible libraries.

Installation tests

  • For a quick installation check, just run:

python3 -c "import nestgpu"

  • To check the correctness of NEST GPU installation more in depth you can find some tests in the directory SOURCE_DIR/python/test. Each Python script tests a specific feature of the library, and to perform all the tests you can run the bash scripts test_all.sh (which runs all the tests that do not employ MPI) and test_mpi.sh. If everything worked well, for every test you should see a line indicating TEST PASSED or MPI TEST PASSED.

  • If some test did not pass, you can have a look at the log.txt file given in output by the bash scripts to see the output of the Python tests.