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Acceleration Of Spiking Neural Networks On Multicore Architectures, Rommel Jalasutram

All Theses

The human cortex is the seat of learning and cognition. Biological scale
implementations of cortical models have the potential to provide significantly more
power problem solving capabilities than traditional computing algorithms. The large
scale implementation and design of these models has attracted significant attention
recently. High performance implementations of the models are needed to enable such
large scale designs. This thesis examines the acceleration of the spiking neural network
class of cortical models on several modern multicore processors. These include the
Izhikevich, Wilson, Morris-Lecar, and Hodgkin-Huxley models. The architectures
examined are the STI Cell, Sun UltraSPARC T2+, and Intel Xeon …