We measured the impact of long-range exponentially decaying intra-areal lateral connectivity on the scaling and memory occupation of a distributed spiking neural network simulator compared to that of short-range Gaussian decays. Indeed, while previous studies adopted short-range connectivity, recent experimental neurosciences studies are pointing out the role of longer-range intra-areal connectivity with implications on neural simulation platforms. Two-dimensional grids of cortical columns composed by up to 11 M point-like spiking neurons with spike frequency adaption were connected by up to 30 G synapses using short- A nd long-range connectivity models. The MPI processes composing the distributed simulator were run on up to 1024 hardware cores, hosted on a 64 nodes server platform. 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 2.40G Hz, interconnected through an InfiniBand network, equipped with 4 QDR switches.

Gaussian and Exponential Lateral Connectivity on Distributed Spiking Neural Network Simulation / Pastorelli, Elena; Paolucci, Pier Stanislao; Simula, Francesco; Biagioni, Andrea; Capuani, Fabrizio; Cretaro, Paolo; De Bonis, Giulia; Lo Cicero, Francesca; Lonardo, Alessandro; Martinelli, Michele; Pontisso, Luca; Vicini, Piero; Ammendola, Roberto. - (2018), pp. 658-665. (Intervento presentato al convegno PDP2018 tenutosi a Cambridge) [10.1109/PDP2018.2018.00110].

Gaussian and Exponential Lateral Connectivity on Distributed Spiking Neural Network Simulation

Pastorelli, Elena
;
Simula, Francesco;Biagioni, Andrea;Capuani, Fabrizio;Cretaro, Paolo;De Bonis, Giulia;Lonardo, Alessandro;Martinelli, Michele;
2018

Abstract

We measured the impact of long-range exponentially decaying intra-areal lateral connectivity on the scaling and memory occupation of a distributed spiking neural network simulator compared to that of short-range Gaussian decays. Indeed, while previous studies adopted short-range connectivity, recent experimental neurosciences studies are pointing out the role of longer-range intra-areal connectivity with implications on neural simulation platforms. Two-dimensional grids of cortical columns composed by up to 11 M point-like spiking neurons with spike frequency adaption were connected by up to 30 G synapses using short- A nd long-range connectivity models. The MPI processes composing the distributed simulator were run on up to 1024 hardware cores, hosted on a 64 nodes server platform. 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 2.40G Hz, interconnected through an InfiniBand network, equipped with 4 QDR switches.
2018
PDP2018
Cortical simulation; Distributed Computing; Hardware/software co-design; Lateral synaptic connectivity; Spiking Neural Network; Computer Networks and Communications; Hardware and Architecture
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Gaussian and Exponential Lateral Connectivity on Distributed Spiking Neural Network Simulation / Pastorelli, Elena; Paolucci, Pier Stanislao; Simula, Francesco; Biagioni, Andrea; Capuani, Fabrizio; Cretaro, Paolo; De Bonis, Giulia; Lo Cicero, Francesca; Lonardo, Alessandro; Martinelli, Michele; Pontisso, Luca; Vicini, Piero; Ammendola, Roberto. - (2018), pp. 658-665. (Intervento presentato al convegno PDP2018 tenutosi a Cambridge) [10.1109/PDP2018.2018.00110].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1183970
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