Large-scale simulation of neuronal systems
Year: 2009
Type: dissertation
Abstract: Biologically detailed computational models of large-scale neuronal networks have now become feasible due to the development of increasingly powerful massively parallel supercomputers. We report here about the methodology involved in simulation of very large neuronal networks. Using conductance-based multicompartmental model neurons based on Hodgkin-Huxley formalism, we simulate a neuronal network model of layers II/III of the neocortex. These simulations, the largest of this type ever performed, were made on the Blue Gene/L supercomputer and comprised up to 8 million neurons and 4 billion synapses. Such model sizes correspond to the cortex of a small mammal. After a series of optimization steps, performance measurements show linear scaling behavior both on the Blue Gene/L supercomputer and on a more conventional cluster computer. Results from the simulation of a model based on more abstract formalism, and of considerably larger size, also shows linear scaling behavior on both computer architectures.
Author: Mikael Djurfeldt
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W1661951673