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dc.contributor.authorAlba, E.
dc.contributor.authorAlmeida, F.
dc.contributor.authorBlesa Aguilera, Maria Josep
dc.contributor.authorCotta, C.
dc.contributor.authorDíaz, M.
dc.contributor.authorDorta, I.
dc.contributor.authorGabarró Vallès, Joaquim
dc.contributor.authorGonzález, J.
dc.contributor.authorLeón, C.
dc.contributor.authorMoreno de Antonio, Luz Marina
dc.contributor.authorPetit Silvestre, Jordi
dc.contributor.authorRoda, J.
dc.contributor.authorRojas, A.
dc.contributor.authorXhafa Xhafa, Fatos
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.identifier.citationAlba, E., Almeida, F., Blesa, M., Cotta, C., Díaz, M., Dorta, I., Gabarro, J., González, J., León, C., Moreno, L., Petit, J., Roda, J., Rojas, A., Xhafa, F. "MALLBA: towards a combinatorial optimization library for geographically distributed systems". 2001.
dc.description.abstractProblems arising in different areas such as numerical methods, simulation or optimization can be efficiently solved by parallel super-computing. However, it is not always possible to buy and maintain parallel super-computers. A geographically distributed network of PC clusters is an interesting low-cost alternative. The possibility of connecting different clusters of PCs through Internet opens a new approach to distributed and massive computing. The MALLBA project tackles the resolution of combinatorial optimization problems using algorithmic skeletons implemented in CPP under this approach. MALLBA offers three families of generic resolution methods: exact, heuristic and hybrid. Moreover, for each resolution method it offers three implementations: sequential, LAN and WAN. This paper surveys the current state of the MALLBA project.
dc.format.extent6 p.
dc.subjectÀrees temàtiques de la UPC::Informàtica
dc.subject.otherCombinatorial optimization
dc.subject.otherGeographically distributed environments
dc.subject.otherAlgorithmic skeletons
dc.subject.otherExact/heuristic/hybrid methods
dc.titleMALLBA: towards a combinatorial optimization library for geographically distributed systems
dc.typeExternal research report
dc.rights.accessOpen Access
dc.description.versionPostprint (published version)
local.citation.authorAlba, E.; Almeida, F.; Blesa, M.; Cotta, C.; Díaz, M.; Dorta, I.; Gabarro, J.; González, J.; León, C.; Moreno, L.; Petit, J.; Roda, J.; Rojas, A.; Xhafa, F.

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