swMATH ID: 14128
Software Authors: A.P. Davison, D. Brüderle, J. Eppler, J. Kremkow, E. Muller, D. Pecevski, L. Perrinet, P. Yger
Description: Pynn: A common interface for neuronal network simulators. PyNN (pronounced ’pine’) is a simulator-independent language for building neuronal network models. In other words, you can write the code for a model once, using the PyNN API and the Python programming language, and then run it without modification on any simulator that PyNN supports (currently NEURON, NEST, PCSIM and Brian). The PyNN API aims to support modelling at a high-level of abstraction (populations of neurons, layers, columns and the connections between them) while still allowing access to the details of individual neurons and synapses when required. PyNN provides a library of standard neuron, synapse and synaptic plasticity models, which have been verified to work the same on the different supported simulators. PyNN also provides a set of commonly-used connectivity algorithms (e.g. all-to-all, random, distance-dependent, small-world) but makes it easy to provide your own connectivity in a simulator-independent way, either using the Connection Set Algebra (Djurfeldt, 2010) or by writing your own Python code.
Homepage: http://neuralensemble.org/PyNN/
Related Software: NEST; NEURON; Brian; Python; SpiNNaker; PyNEST; Nengo; TensorFlow; PyTorch; GeNN; NxTF; SpikeCoding; MNIST; Keras; Neko; ANNarchy; Chainer; Caffe; cuDNN; MXNet
Cited in: 8 Publications

Citations by Year