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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 and average connectivity (synapses) per neuron per second:
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 Hz, the average rate of synaptic updates provoked by the activity of that neuron is . In a synchronous simulation with step the number of synaptic updates per second would be . As has to be chosen much smaller than the average interval between two successive afferent spikes, which implies , giving an average of synaptic updates equal to . 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)』 ■ウィキペディアで「SUPS」の詳細全文を読む
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