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Biologically-Inspired Massively Parallel Computation (BIMPC) Demonstrator

In BIMPC we use inspiration from brain structure to propose new theories of massively parallel computation to run in real time on our SpiNNaker platform. Our work covers a range of different areas:

  • Neural memory. Investigating how reliable memories can form in networks of strongly interconnected neurons, how to make them resistant to degradation and how their encoding can change over time to assimilate them, forming a coherent database of knowledge

  • Symbolic computation: How to represent symbols and symbol structures using populations of neurons

  • Problem solving using constraints: Investigating ways of using big networks to search for possible solutions to constrained problems, like Sudoku

  • NENGO and SPAUN: Working with a group at the University of Waterloo in Canada, who developed a neural specification language called NENGO and have used it to produce a 2.4 million neuron multi-function reasoning architecture called SPAUN. We are going to run SPAUN in real-time for the first time, on SpiNNaker!