dc.creator | Martínez del Amor, Miguel Ángel | es |
dc.creator | Orellana Martín, David | es |
dc.creator | Cabarle, Francis George C. | es |
dc.creator | Pérez Jiménez, Mario de Jesús | es |
dc.creator | Adorna, Henry N. | es |
dc.date.accessioned | 2017-12-21T08:51:40Z | |
dc.date.available | 2017-12-21T08:51:40Z | |
dc.date.issued | 2017 | |
dc.identifier.citation | Martínez del Amor, M.Á., Orellana Martín, D., Cabarle, F.G.C., Pérez Jiménez, M.d.J. y Adorna, H.N. (2017). Sparse-matrix Representation of Spiking Neural P Systems for GPUs. En BWMC 2017: 15th Brainstorming Week on Membrane Computing (161-170), Sevilla, España: Fenix Editora. | |
dc.identifier.isbn | 978-84-946316-9-6 | es |
dc.identifier.uri | http://hdl.handle.net/11441/67895 | |
dc.description.abstract | Current parallel simulation algorithms for Spiking Neural P (SNP) systems
are based on a matrix representation. This helps to harness the inherent parallelism
in algebraic operations, such as vector-matrix multiplication. Although it has been
convenient for the rst parallel simulators running on Graphics Processing Units
(GPUs), such as CuSNP, there are some bottlenecks to cope with. For example, matrix
representation of SNP systems with a low-connectivity-degree graph lead to sparse
matrices, i.e. containing more zeros than actual values. Having to deal with sparse
matrices downgrades the performance of the simulators because of wasting memory and
time.
However, sparse matrices is a known problem on parallel computing with GPUs, and
several solutions and algorithms are available in the literature. In this paper, we brie
y
analyse some of these ideas and apply them to represent some variants of SNP systems.
We also conclude which variant better suit a sparse-matrix representation. | es |
dc.format | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | Fenix Editora | es |
dc.relation.ispartof | BWMC 2017: 15th Brainstorming Week on Membrane Computing (2017), p 161-170 | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Spiking Neural P systems | es |
dc.subject | Simulation Algorithm | es |
dc.subject | Sparse Matrix Representation | es |
dc.subject | GPU computing | es |
dc.subject | CUDA | es |
dc.title | Sparse-matrix Representation of Spiking Neural P Systems for GPUs | es |
dc.type | info:eu-repo/semantics/conferenceObject | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial | es |
dc.relation.publisherversion | http://www.gcn.us.es/15bwmc_proceedings | es |
dc.contributor.group | Universidad de Sevilla. TIC193: Computación Natural | es |
idus.format.extent | 14 | es |
dc.publication.initialPage | 161 | es |
dc.publication.endPage | 170 | es |
dc.eventtitle | BWMC 2017: 15th Brainstorming Week on Membrane Computing | es |
dc.eventinstitution | Sevilla, España | es |
dc.relation.publicationplace | Sevilla | es |