Constructing Neuronal Network Models in Massively Parallel Environments.

ABSTRACT: Recent advances in the development of data structures to represent spiking neuron network models enable us to exploit the complete memory of petascale computers for a single brain-scale network simulation. In this work, we investigate how well we can exploit the computing power of such supercomputers for the creation of neuronal networks. Using an established benchmark, we divide the runtime of simulation code into the phase of network construction and the phase during which the dynamical state is advanced in time. We find that on multi-core compute nodes network creation scales well with process-parallel code but exhibits a prohibitively large memory consumption. Thread-parallel network creation, in contrast, exhibits speedup only up to a small number of threads but has little overhead in

SUBMITTER: Ippen T 

PROVIDER: S-EPMC5432669 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature