.. currentmodule:: brian.experimental.cuda
Brian has some experimental support for doing numerical integration only using
GPUs, using the `PyCUDA package <http://mathema.tician.de/software/pycuda>`__.
Note that only numerical integration is done on the GPU, which means that
variables that can be altered on the CPU (via synapses or user operations) need
to be copied to and from the GPU each time step, as well as variables that are
used for thresholding and reset operations. This creates a memory bandwidth
bottleneck, which means that for the moment the GPU code is only useful for
complicated neuron models such as Hodgkin-Huxley type neurons (although in this
case it can lead to very substantial speed improvements).
.. autoclass:: GPUNeuronGroup