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    Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/69760

    Título
    Performance improvement of the triangular matrix product in commodity clusters
    Autor
    Santamaria Valenzuela, Inmaculada
    Carratalá Sáez, Rocío
    Torres de la Sierra, YuriAutoridad UVA Orcid
    Llanos Ferraris, Diego RafaelAutoridad UVA Orcid
    González Escribano, ArturoAutoridad UVA Orcid
    Año del Documento
    2024
    Editorial
    Springer
    Documento Fuente
    Performance improvement of the triangular matrix product in commodity clusters, I. Santamaria-Valenzuela, R. Carratalá-Sáez, Y. Torres, Diego R. Llanos, A. Gonzalez-Escribano. The Journal of Supercomputing, vol. 80, pp 166320-16653, 2024
    Zusammenfassung
    There are many works devoted to improving the matrix product computation, as it is used in a wide variety of scientific applications arising from many different fields. In this work, we propose alternative data distribution policies and communication patterns to reduce the elapsed time when computing triangular matrix products in distributed memory environments. In particular, we focus on commodity clusters, where the number of nodes is limited, proposing alternatives to traditional approaches in order to improve this operation’s performance. Our proposal overcomes the performance results associated with the state-of-the-art libraries, such as ScaLAPACK and SLATE, offering execution times that are up to 30% faster.
    Materias (normalizadas)
    Informática
    Materias Unesco
    1203 Ciencia de Los Ordenadores
    3304 Tecnología de Los Ordenadores
    Palabras Clave
    Commodity clusters · Triangular matrix product · TRMM · SLATE · ScaLAPACK
    ISSN
    0920-8542
    Revisión por pares
    SI
    DOI
    10.1007/s11227-024-06097-7
    Patrocinador
    This work was supported in part by the Spanish Ministerio de Ciencia e Innovación and by the European Regional Development Fund (ERDF) program of the European Union, under Grant PID2022-142292NB-I00 (NATASHA Project); and in part by the Junta de Castilla y León - FEDER Grants, under Grant VA226P20 (PROPHET-2 Project), Junta de Castilla y León, Spain. This work was also supported in part by grant TED2021-130367B-I00, funded by MCIN/AEI/10.13039/501100011033 and by “European Union NextGenerationEU/PRTR“. The CESGA - Finisterrae III supercomputing resources were accessed thanks to the project IM-2023-3-0020 from the Red Española de Supercomputación (RES).
    Version del Editor
    https://link.springer.com/article/10.1007/s11227-024-06097-7
    Idioma
    eng
    URI
    https://uvadoc.uva.es/handle/10324/69760
    Tipo de versión
    info:eu-repo/semantics/publishedVersion
    Derechos
    openAccess
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    • DEP41 - Artículos de revista [108]
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    Performance_improvement_of_the_triangular_matrix_p.pdf
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