A real-time reconfigurable multi-chip architecture for large-scale biophysically-accurate neuron simulation
| Autor: | Rene van Leuken, Gerrit Jan Christiaanse, Carlo Galuzzi, Georgios Smaragdos, Alexander de Graaf, Martijn F. van Eijk, Christos Strydis, Jaco Hofmann, Amir Zjajo |
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| Přispěvatelé: | DKE Scientific staff, RS: FSE DACS, Internal Medicine, Neurosciences |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Scheme (programming language)
Interneuron Scale (ratio) INFORMATION Computer science multichip data-flow architecture Distributed computing Models Neurological Biomedical Engineering 02 engineering and technology COMMUNICATION Olivary Nucleus Mice 03 medical and health sciences 0302 clinical medicine Exponential growth FIRING PATTERNS neuron network 0202 electrical engineering electronic engineering information engineering medicine BURSTS Animals Computer Simulation Electrical and Electronic Engineering Architecture Field-programmable gate array computer.programming_language Neurons SPIKING NEURONS 020208 electrical & electronic engineering NETWORKS MODEL medicine.anatomical_structure UNIT Systems architecture Neural Networks Computer Neuron computer 030217 neurology & neurosurgery Biophysically accurate neuron simulation |
| Zdroj: | Ieee Transactions on Biomedical Circuits and Systems, 12(2), 326-337. IEEE IEEE Transactions on Biomedical Circuits and Systems IEEE Transactions on Biomedical Circuits and Systems, 12(2), 326-337. Institute of Electrical and Electronics Engineers Inc. |
| ISSN: | 1932-4545 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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