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A solver for sets of linear systems for neural network simuations in CUDA

Orientador: Prof. Raphael Yokoingawa de Camargo / Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Neurociência e Cognição, 2014. / Nowadays, utilizing co-processors, accelerators and specially GPGPU computation are widely
accepted as a new paradigm of High Performance Computing (HPC). However, developing
softwares that can utilize available resources still remains a challenging task. In other side,
scientist have used legacy CPU-based simulators for decades and many of them are still the
main tools in different fields of science. In fact, any activity that can combine the legacy
simulators with powerful co-processors devices is in the main interest.
In this project, we design and develop a simulation engine, Parallel Neural Network Simulator
(PN2S), to communicate with MOOSE simulator (A well-known tools by Neuroscientists) and
provide CUDA based execution for simulating realistic neural network models. The simulation
engine maps the voltage distribution in neuron¿s body to sets of linear systems and solve them on GPU. To provide usable functionality, we also developed solver for active channels which support Hodgkin-Huxley model of ionic channels.
We compared the engine with CPU version for both homogeneous simple models and randomly generated heterogeneous network. The evaluation focused on performance and also covered the accuracy of the simulation. The experimental results, showed that by facilitating PN2S engine, we can significantly increase the performance of a simulation engine, since its execution is quite transparent to the users and major parts of the host simulator.

Identiferoai:union.ndltd.org:IBICT/oai:BDTD:76960
Date January 2014
CreatorsShariati, Saeed
ContributorsCamargo, Raphael Yokoingawa de, Reyes, Marcelo Bussotti, Song, Siang Wun
Source SetsIBICT Brazilian ETDs
LanguageInglês
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/publishedVersion, info:eu-repo/semantics/masterThesis
Formatapplication/pdf, 67 f. : il.
Sourcereponame:Repositório Institucional da UFABC, instname:Universidade Federal do ABC, instacron:UFABC
Rightsinfo:eu-repo/semantics/openAccess
Relationhttp://biblioteca.ufabc.edu.br/index.php?codigo_sophia=76960&midiaext=70203, http://biblioteca.ufabc.edu.br/index.php?codigo_sophia=76960&midiaext=70204, Cover: http://biblioteca.ufabc.edu.brphp/capa.php?obra=76960

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