Efficient parallel LAN/WAN algorithms for optimization: The mallba project

The mallba project tackles the resolution of combinatorial optimization problems using generic algorithmic skeletons implemented in C++. A skeleton in the mallba library implements an optimization method in one of the three families of generic optimization techniques offered: exact, heuristic and hy...

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Detalles Bibliográficos
Autores: Alba, E., Almeida, F., Blesa Aguilera, Maria Josep|||0000-0001-8246-9926, Cotta Porras, Carlos, Díaz, M., Dorta, Isabel, Gabarró Vallès, Joaquim|||0000-0003-3771-2813, León Hernández, Coromoto, Luque, G., Petit Silvestre, Jordi|||0000-0001-8331-8126, Rodríguez, C., Rojas, A., Xhafa Xhafa, Fatos|||0000-0001-6569-5497
Tipo de recurso: artículo
Fecha de publicación:2006
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/129277
Acceso en línea:https://hdl.handle.net/2117/129277
https://dx.doi.org/10.1016/j.parco.2006.06.007
Access Level:acceso abierto
Palabra clave:Parallel algorithms
Combinatorial optimization
Software engineering
mallba library
Exact techniques
Metaheuristics
Hybridization
Local and wide area implementations
Algorismes paral·lels
Optimització combinatòria
Àrees temàtiques de la UPC::Informàtica::Informàtica teòrica
Descripción
Sumario:The mallba project tackles the resolution of combinatorial optimization problems using generic algorithmic skeletons implemented in C++. A skeleton in the mallba library implements an optimization method in one of the three families of generic optimization techniques offered: exact, heuristic and hybrid. Moreover, for each of those methods, mallba provides three different implementations: sequential, parallel for Local Area Networks, and parallel for Wide Area Networks. This paper introduces the architecture of the mallba library, details some of the implemented skeletons, and offers computational results for some classical optimization problems to show the viability of our library. Among other conclusions, we claim that the design used to develop the optimization techniques included in the library is generic and efficient at the same time.