Imperial College London > Talks@ee.imperial > CAS Talks > Spiking Neural Network Implementation on Distributed Reconfigurable Cluster Architecture

Spiking Neural Network Implementation on Distributed Reconfigurable Cluster Architecture

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  • UserShahsavari, Mahyar
  • ClockMonday 05 October 2020, 16:00-17:00
  • HouseTeams.

If you have a question about this talk, please contact George A Constantinides.

Spiking Neural Networks (SNNs) are known as a branch of neuromorphic computing, and are currently used in neuroscience applications to understand and model the biological brain. SNNs could also potentially be used in many other application domains such as classification, pattern recognition, and autonomous control. This work presents a highly-scalable hardware platform called POETS , and uses it to implement SNN on a very large number of parallel and reconfigurable FPGA -based processors. The current system consists of 48 FPG As, providing 3072 processing cores and 49152 threads. We use this hardware to implement up to four million neurons with one thousand synapses. Comparison to other similar platforms shows that the current POETS system is twenty times faster than the Brian simulator, and at least two times faster than SpiNNaker.

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