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SUPS : ウィキペディア英語版
SUPS
In computational neuroscience, SUPS (for Synaptic Updates Per Second) or formerly CUPS (Connections Updates Per Second) is a measure of a neuronal network performance, useful in fields of neuroscience, cognitive science, artificial intelligence, and computer science.
==Computing==
For a processor or computer designed to simulate a neural network SUPS is measured as the product of simulated neurons N and average connectivity c(synapses) per neuron per second:
SUPS = c \times N
Depending on the type of simulation it is usual equal to the total number of synapses simulated.
In an "asynchronous" dynamic simulation if a neuron spikes at \upsilon Hz, the average rate of synaptic updates provoked by the activity of that neuron is \upsilon cN. In a synchronous simulation with step \Delta t the number of synaptic updates per second would be \frac. As \Delta t has to be chosen much smaller than the average interval between two successive afferent spikes, which implies \Delta t < \frac, giving an average of synaptic updates equal to \upsilon c N^2. Therefore, spike-driven synaptic dynamics leads to a linear scaling of computational complexity O(N) per neuron, compared with the O(N2) in the "synchronous" case.

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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