Event-driven simulation of arbitrary spiking neural networks on SpiNNaker

Thomas Sharp, Luis A. Plana, Francesco Galluppi, Steve Furber

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Programming supercomputers correctly and optimally is non-trivial, which presents a problem for scientists simulating large areas of the brain. Researchers face the challenges of learning how to fully exploit hardware whilst avoiding the numerous pitfalls of parallel programming such as race conditions, deadlock and poor scaling. The SpiNNaker architecture is designed to exploit up to a million processors in modelling as many as one billion neurons in real-time. We present a programming interface for the architecture to allow modelling of arbitrary neuron and synapse dynamics using standard sequential C code, without concern for parallel-programming techniques or interprocessor communication mechanisms. An example is presented in which SpiNNaker is programmed to model multiple synaptic dynamics that are exchanged on the fly and the results of the different synaptic efficacies are shown. © 2011 Springer-Verlag.
Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.
Place of PublicationBerlin / Heidelberg
PublisherSpringer Nature
Number of pages6
ISBN (Print)9783642249648
Publication statusPublished - 2011
Event18th International Conference on Neural Information Processing, ICONIP 2011 - Shanghai
Duration: 1 Jul 2011 → …


Conference18th International Conference on Neural Information Processing, ICONIP 2011
Period1/07/11 → …


  • C
  • callbacks
  • event driven
  • kernel
  • neural simulation
  • parallel programming
  • SpiNNaker
  • tasks


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