Toward Human-Level Massively-Parallel Neural Networks with Hodgkin-Huxley Neurons
| Autor: | Lyle N. Long |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
Spiking neural network Quantitative Biology::Neurons and Cognition Artificial neural network Scale (ratio) business.industry Computer science Biological neuron model Parallel computing Hodgkin–Huxley model 03 medical and health sciences 030104 developmental biology 0302 clinical medicine Software Biological neural network business Massively parallel 030217 neurology & neurosurgery |
| Zdroj: | Artificial General Intelligence ISBN: 9783319416489 AGI |
| DOI: | 10.1007/978-3-319-41649-6_32 |
| Popis: | This paper describes neural network algorithms and software that scale up to massively parallel computers. The neuron model used is the best available at this time, the Hodgkin-Huxley equations. Most massively parallel simulations use very simplified neuron models, which cannot accurately simulate biological neurons and the wide variety of neuron types. Using C++ and MPI we can scale these networks to human-level sizes. Computers such as the Chinese TianHe computer are capable of human level neural networks. |
| Databáze: | OpenAIRE |
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