  Recent experimental neuroscience studies are pointing out the role of
long-range intra-areal connectivity that can be modeled by a distance dependent
exponential decay of the synaptic probability distribution. This short report
provides a preliminary measure of the impact of exponentially decaying lateral
connectivity compared to that of shorter-range Gaussian decays on the scaling
behaviour and memory occupation of a distributed spiking neural network
simulator (DPSNN). Two-dimensional grids of cortical columns composed by
point-like spiking neurons have been connected by up to 30 billion synapses
using exponential and Gaussian connectivity models. Up to 1024 hardware cores,
hosted on a 64 nodes server platform, executed the MPI processes composing the
distributed simulator. The hardware platform was a cluster of IBM NX360 M5
16-core compute nodes, each one containing two Intel Xeon Haswell 8-core
E5-2630 v3 processors, with a clock of 2.40GHz, interconnected through an
InfiniBand network. This study is conducted in the framework of the CORTICONIC
FET project, also in view of the next -to-start activities foreseen as part of
the Human Brain Project (HBP), SubProject 3 Cognitive and Systems Neuroscience,
WaveScalES work-package.

Distributed, Parallel, and Cluster Computing;Neurons and Cognition