ANNarchy (Artificial Neural Networks architect) is a parallel and hybrid simulator for distributed rate-coded or spiking neural networks. The core of the library is written in C++ and distributed using openMP or CUDA. It provides an interface in Python for the definition of the networks. It is released under the GNU GPL v2 or later.
- Source code: github.com/ANNarchy/ANNarchy
- Documentation: annarchy.github.io
- Forum: google forum
- Bug reports and feature requests: Issue Tracker.
If you use ANNarchy for your research, we would appreciate if you cite the following paper:
Vitay J, Dinkelbach HÜ and Hamker FH (2015). ANNarchy: a code generation approach to neural simulations on parallel hardware. Frontiers in Neuroinformatics 9:19. doi:10.3389/fninf.2015.00019
- Julien Vitay ([email protected]).
- Helge Ülo Dinkelbach ([email protected]).
- Fred Hamker ([email protected]).
Using pip, you can install the latest stable release:
pip install ANNarchy
See https://annarchy.github.io/Installation for further instructions.
- GNU/Linux
- MacOS X
- Windows (inside WSL2)
python
>= 3.10 (with the development files, e.g.python-dev
orpython-devel
)g++
>= 7.4 orclang++
>= 3.4make
>= 3.0setuptools
>= 65.0cython
>= 3.0numpy
>= 1.21sympy
>= 1.11scipy
>= 1.9matplotlib
>= 3.0tqdm
>= 4.60
Recommended:
lxml
(to save the networks in.xml
format).pandoc
(forreport()
).tensorflow
(for theann_to_snn_conversion
extension)tensorboardX
(for thelogging
extension).