Installation
Prerequisites
Please make sure you have an NVIDIA GPU and a working installation of CUDA and cudNN. If you don’t have an NVIDIA GPU then the convolution will default to the CPU, and be very slow.
SyMBac is meant to be run interactively (in a notebook + with a small Qt/GTK interface), so make sure that you are running this on a local machine (you should have access to the machine’s display).
If you are running SyMBac on a remote machine, say through an SSH tunnel, you can still use it, but you will need to ensure you have an active VNC screen available, as SyMBac needs access to a screen to render the live simulation. You do not need to be actively accessing the VNC session, it just needs to be running.
Installation
pip install SyMBac
Or to install the development version (recommended for now), run:
pip install git+https://github.com/georgeoshardo/SyMBac
Activate the Jupyter widgets extension. This is needed to interact with slides in the notebooks to optimise images.
jupyter nbextension enable --py widgetsnbextension
If you’re using a GPU
Check the version of CUDA you have installed using nvcc –version and install the appropriate version of cupy. For example, if you have CUDA 11.4 you would install as follows:
pip install cupy-cuda114
If you installed CUDA on Ubuntu 18.04+ using the new Nvidia supplied repositories, it is a real possibility that nvcc won’t work. Instead check your CUDA version using nvidia-smi.
If you aren’t using a GPU
See FAQs “Do I need to have a GPU?”