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Título
Blending Extensibility and Performance in Dense and Sparse Parallel Data Management
Año del Documento
2014
Editorial
IEEE
Descripción
Producción Científica
Documento Fuente
IEEE Transactions on Parallel and Distributed Systems, Vol. 25, no. 10, October 2014, pages 2509-2519, ISSN 1045-9219
Abstract
Dealing with both dense and sparse data in parallel environments usually leads to two different approaches: To rely on a monolithic, hard-to-modify parallel library, or to code all data management details by hand. In this paper we propose a third approach, that delivers good performance while the underlying library structure remains modular and extensible. Our solution integrates dense and sparse data management using a common interface, that also decouples data representation, partitioning, and layout from the algorithmic and parallel strategy decisions of the programmer. Our experimental results in different parallel environments show that this new approach combines the flexibility obtained when the programmer handles all the details with a performance comparable to the use of a state-of-the-art, sparse matrix parallel library.
Materias (normalizadas)
Informática
Materias Unesco
1203 Ciencia de Los Ordenadores
3304 Tecnología de Los Ordenadores
Palabras Clave
Data partition
Mapping techniques
sparse structures
Parallel libraries
ISSN
1045-9219
Revisión por pares
SI
Patrocinador
This research is partly supported by the Castilla-Leon Regional Government (VA172A12-2); Ministerio de Industria, Spain (CENIT OCEANLIDER); MICINN (Spain) and the European Union FEDER (Mogecopp project TIN2011-25639, CAPAP-H3 network TIN2010-12011-E, CAPAP-H4 network TIN2011-15734-E); and the HPC-EUROPA2 project (project number: 228398) with the support of the European Commission—Capacities Area—Research Infrastructures Initiative.
Version del Editor
Idioma
eng
Tipo de versión
info:eu-repo/semantics/publishedVersion
Derechos
openAccess
Collections
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