Download

Jump right in using a Jupyter notebook directly in your browser, using binder.

The recommended way to install Stride is through Anaconda’s package manager (version >=4.9), which can be downloaded in:

A Python version above 3.8 is recommended to run Stride.

To install Stride, follow these steps:

git clone https://github.com/trustimaging/stride.git
cd stride
conda env create -f environment.yml
conda activate stride
pip install -e .

You can also start using Stride through Docker:

git clone https://github.com/trustimaging/stride.git
cd stride
docker-compose up stride

which will start a Jupyter server within the Docker container and display a URL on your terminal that looks something like https://127.0.0.1:8888/?token=XXX. To access the server, copy-paste the URL shown on the terminal into your browser to start a new Jupyter session.

Additional packages

To access the 3D visualisation capabilities, we also recommend installing MayaVi:

conda install -c conda-forge mayavi

and installing Jupyter notebook is recommended to access all the examples:

conda install -c conda-forge notebook

GPU support

The Devito library uses OpenACC to generate GPU code. The recommended way to access the necessary compilers is to install the NVIDIA HPC SDK.

wget https://developer.download.nvidia.com/hpc-sdk/21.2/nvhpc_2021_212_Linux_x86_64_cuda_multi.tar.gz
tar xpzf nvhpc_2021_212_Linux_x86_64_cuda_multi.tar.gz
cd nvhpc_2021_212_Linux_x86_64_cuda_multi/
sudo ./install

During the installation, select the single system install option.

Once the installation is done, you can add the following lines to your ~/.bashrc:

export PATH=/opt/nvidia/hpc_sdk/Linux_x86_64/2021/compilers/bin/:$PATH
export LD_LIBRARY_PATH=/opt/nvidia/hpc_sdk/Linux_x86_64/2021/compilers/lib/:$LD_LIBRARY_PATH
export PATH=/opt/nvidia/hpc_sdk/Linux_x86_64/2021/comm_libs/mpi/bin/:$PATH
export LD_LIBRARY_PATH=/opt/nvidia/hpc_sdk/Linux_x86_64/2021/comm_libs/mpi/lib/:$LD_LIBRARY_PATH