GeNN is a framework for neuronal network simulations on NVIDIA
graphical processing units (GPUs). It uses a code generation approach to
generate efficient simulation engines for neuronal network models that are
specified through a simple interface. The generated code compiles with
NVIDIA CUDA to run on any CUDA-enabled NVIDIA GPU. This project is in
active development, please contact me if you are interested in contributing.
Brian2GeNN - the Brian 2 frontend to the GeNN simulator
Brian2GeNN is Python based software that allows to run Brian 2
models on the GPU accelerated GeNN backend. Depending on the model
and available GPU hardware, this can allow considerable
speed-up. The manual
for Brian2GeNN is hosted on ReadTheDocs. There are many install
options including conda, pip and manual install
or tarball. Refer to
for details of install and use.
The Dynamic Clamp protocol, developed indepently by Sharp
et. al. (J. Neurophysiol. 69:992-995, 1993) and Robinson and Kawai (J
Neurosci Methods 49(3):157-65, 1993) allows "insertion" of simulated
membrane conductances in, and/or simulated synapses between
biological neurons. Reynaldo Pinto et al. developed a very nice clamp
implementation for windows platforms called DYNCLAMP2/4. StdpC
is the next generation dynamic clamp based on his original design.