Install

How to install dexp

Prerequisites:

dexp works on OSX and Windows, but it is recomended to use the latest version of Ubuntu. We recommend a machine with NVIDIA graphics card with at least 12G.

First, make sure to have a working python installation . Second, make sure to have a compatible and functional CUDA installation .

Once these prerequisites are satified, you can install dexp.

Installation:

dexp can simply be installed with:

To installs dexp with GPU support (CUDA 11.2) do:

conda install cupy
pip install dexp[optional,colored]

If instead you do not wish to add CUDA support, you can instead do:

pip install dexp[optional,colored]

Quick conda environment setup and installation:

There are multiple options when using a conda environment.

You can create our suggested DEXP (and some additional packages) environment by, it requires GPU:

conda env create --name dexp --file env-linux-gpu.yaml

Or create your own conda environment from scratch with the commands delete any existing dexp environment, recreate it, install dexp with CUDA support and napari:

conda deactivate
conda env remove --name dexp
conda create -y --name dexp python=3.9
conda activate dexp
conda install cupy
pip install dexp[optional,colored]
pip install napari[all]

If you are having problems with the cuda/cuda-toolkit the best is to use conda to install the correct version of the cudatoolkit:

conda install -c conda-forge cudatoolkit==11.2.2

You can check here for the best matching version.

Notes: - You might get some error messages recommending you install missing libraries such as CUDNN, CuTensor, nccl, etc… These messages often come with instructions on what to do. - Adjust your driver version (here 11.2) to your card(s) and drivers. - Windows users should call conda install -c conda-forge pyopencl() before running the second to last step.

Leveraging extra CUDA libraries for faster processing:

If you want you dexp CUDA-based processing to be even faster, you can install additional libraries such as CUDNN and CUTENSOR with the following command:

conda install -y -c conda-forge cudnn cutensor nccl

or

dexp-install cudalibs 11.2

Change the CUDA version accordingly.