Report
Gaussian and exponential lateral connectivity on distributed spiking neural network simulation
| العنوان: | Gaussian and exponential lateral connectivity on distributed spiking neural network simulation |
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| المؤلفون: | Pastorelli, Elena, Paolucci, Pier Stanislao, Simula, Francesco, Biagioni, Andrea, Capuani, Fabrizio, Cretaro, Paolo, De Bonis, Giulia, Cicero, Francesca Lo, Lonardo, Alessandro, Martinelli, Michele, Pontisso, Luca, Vicini, Piero, Ammendola, Roberto |
| سنة النشر: | 2018 |
| المجموعة: | Computer Science Quantitative Biology |
| مصطلحات موضوعية: | Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Neural and Evolutionary Computing, Quantitative Biology - Neurons and Cognition |
| الوصف: | 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. 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- and 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 2.40 G Hz, interconnected through an InfiniBand network, equipped with 4x QDR switches. Comment: 9 pages, 9 figures, added reference to final peer reviewed version on conference paper and DOI |
| نوع الوثيقة: | Working Paper |
| DOI: | 10.1109/PDP2018.2018.00110 |
| URL الوصول: | http://arxiv.org/abs/1803.08833 |
| رقم الانضمام: | edsarx.1803.08833 |
| قاعدة البيانات: | arXiv |
| DOI: | 10.1109/PDP2018.2018.00110 |
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