Abstract
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.
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Long, L.N. (2016). Toward Human-Level Massively-Parallel Neural Networks with Hodgkin-Huxley Neurons. In: Steunebrink, B., Wang, P., Goertzel, B. (eds) Artificial General Intelligence. AGI 2016. Lecture Notes in Computer Science(), vol 9782. Springer, Cham. https://doi.org/10.1007/978-3-319-41649-6_32
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DOI: https://doi.org/10.1007/978-3-319-41649-6_32
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