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Record Nr. |
UNISA996465715503316 |
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Titolo |
Parallel Processing and Applied Mathematics [[electronic resource] ] : 11th International Conference, PPAM 2015, Krakow, Poland, September 6-9, 2015. Revised Selected Papers, Part I / / edited by Roman Wyrzykowski, Ewa Deelman, Jack Dongarra, Konrad Karczewski, Jacek Kitowski, Kazimierz Wiatr |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
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ISBN |
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Edizione |
[1st ed. 2016.] |
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Descrizione fisica |
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1 online resource (XXIV, 622 p. 229 illus.) |
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Collana |
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Theoretical Computer Science and General Issues, , 2512-2029 ; ; 9573 |
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Disciplina |
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Soggetti |
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Software engineering |
Algorithms |
Application software |
Computer programming |
Computer networks |
Computer science—Mathematics |
Software Engineering |
Computer and Information Systems Applications |
Programming Techniques |
Computer Communication Networks |
Mathematics of Computing |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Nota di contenuto |
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Parallel Architectures and Resilience -- Numerical Algorithms and Parallel Scientific Computing -- Parallel Non-Numerical Algorithms -- Tools and Environments for Parallel/Distributed/Cloud Computing -- Application of Parallel Computing -- Neural Networks, Evolutionary Computing and Metaheuristics -- Minisymposium on GPU Computing -- Special Session on Efficient Algorithms for Problems with Matrix and Tensor Decompositions. |
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Sommario/riassunto |
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This two-volume set LNCS 9573 and LNCS 9574 constitutes the |
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refereed proceedings of the 11th International Conference of Parallel Processing and Applied Mathematics, PPAM 2015, held in Krakow, Poland, in September 2015. The 111 revised full papers presented in both volumes were carefully reviewed and selected from 196 submissions. The focus of PPAM 2015 was on models, algorithms, and software tools which facilitate efficient and convenient utilization of modern parallel and distributed computing architectures, as well as on large-scale applications, including big data problems. |
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