GPU-BASED SIMULATION OF BRAIN NEURON MODELS

The human brain is an incredible system which can process, store, and transfer information with high speed and volume. Inspired by such system, engineers and scientists are cooperating to construct a digital brain with these characteristics. The brain is composed by billions of neurons which can be modeled by mathematical equa-tions. The first step to reach that goal is to be able to construct these neuron models in real time. The Inferior Olive (IO) model is a selected model to achieve the real time simulation of a large neuron network. The model is quite complex with three compart-ments which are based on the Hodgkin Huxley model. Although the Hodgkin Huxley model is considered as the most biological plausible model, it has quite high complexity. The three compartments also make the model become even more computationally intensive. A CPU platform takes a long time to simulate such a complex model. Besides, FPGA platform does not handle effectively floating poin