Performance Comparison of the Digital Neuromorphic Hardware SpiNNaker and the Neural Network Simulation Software NEST for a Full-Scale Cortical Microcircuit Model

The digital neuromorphic hardware SpiNNaker has been developed with the aim of enabling large-scale neural network simulations in real time and with low power consumption. Real-time performance is achieved with 1 ms integration time steps, and thus applies to neural networks for which faster time sc...

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Główni autorzy:	Sacha J. van Albada, Andrew G. Rowley, Johanna Senk, Michael Hopkins, Maximilian Schmidt, Alan B. Stokes, David R. Lester, Markus Diesmann, Steve B. Furber
Format:	Artigo
Język:	Inglês
Wydane:	Frontiers Media S.A. 2018-05-01
Seria:	Frontiers in Neuroscience
Hasła przedmiotowe:	neuromorphic computing high-performance computing parallel computing accuracy of simulation energy to solution benchmarking
Dostęp online:	https://www.frontiersin.org/article/10.3389/fnins.2018.00291/full
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