.. currentmodule:: brian.experimental.cuda GPU/CUDA ======== Brian has some experimental support for doing numerical integration only using GPUs, using the `PyCUDA package `__. 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