A real-time reconfigurable multi-chip architecture for large-scale biophysically-accurate neuron simulation

A. Zjajo, J. Hofmann, G.J. Christiaanse, M. van Eijk, G. Smaragdos, C. Strydis, A. de Graaf, Carlo Galuzzi, R. van Leuken

    Research output: Contribution to journalArticleAcademicpeer-review

    Abstract

    Simulation of brain neurons in real-time using biophysically meaningful models is a prerequisite for comprehensive understanding of how neurons process information and communicate with each other, in effect efficiently complementing in-vivo experiments. State-of-the-art neuron simulators are, however, capable of simulating at most few tens/hundreds of biophysically accurate neurons in real-time due to the exponential growth in the interneuron communication costs with the number of simulated neurons. In this paper, we propose a real-time, reconfigurable, multichip system architecture based on localized communication, which effectively reduces the communication cost to a linear growth. All parts of the system are generated automatically, based on the neuron connectivity scheme. Experimental results indicate that the proposed system architecture allows the capacity of over 3000 to 19 200 (depending on the connectivity scheme) biophysically accurate neurons over multiple chips.
    Original languageEnglish
    Pages (from-to)326-337
    Number of pages12
    JournalIeee Transactions on Biomedical Circuits and Systems
    Volume12
    Issue number2
    DOIs
    Publication statusPublished - Apr 2018

    Keywords

    • BURSTS
    • Biophysically accurate neuron simulation
    • COMMUNICATION
    • FIRING PATTERNS
    • INFORMATION
    • MODEL
    • NETWORKS
    • SPIKING NEURONS
    • UNIT
    • multichip data-flow architecture
    • neuron network

    Cite this

    Zjajo, A., Hofmann, J., Christiaanse, G. J., van Eijk, M., Smaragdos, G., Strydis, C., de Graaf, A., Galuzzi, C., & van Leuken, R. (2018). A real-time reconfigurable multi-chip architecture for large-scale biophysically-accurate neuron simulation. Ieee Transactions on Biomedical Circuits and Systems, 12(2), 326-337. https://doi.org/10.1109/TBCAS.2017.2780287