Euro-Par 2016: Parallel Processing Workshops: Lecture Notes in Computer Science, cartea 10104
Editat de Frédéric Desprez, Sascha Hunold, Stephen L. Scott, Stefan Lankes, Josef Weidendorfer, Pierre-François Dutot, Christos Kaklamanis, Loris Marchal, Korbinian Molitorisz, Laura Ricci, Vittorio Scarano, Miguel A. Vega-Rodríguez, Ana Lucia Varbanescuen Limba Engleză Paperback – 28 mai 2017
The volume includes the papers from the following workshops: Euro-EDUPAR (Second European Workshop on Parallel and Distributed Computing Education for Undergraduate Students) – HeteroPar 2016 (the 14th International Workshop on Algorithms, Models and Tools for Parallel Computing on Heterogeneous Platforms) – IWMSE (5th International Workshop on Multicore Software Engineering) – LSDVE (Fourth Workshop on Large-Scale Distributed Virtual Environments) - PADABS (Fourth Workshop on Parallel and Distributed Agent-Based Simulations) – PBio (Fourth International Workshop on Parallelism in Bioinformatics) – PELGA (Second Workshop on Performance Engineering for Large-Scale Graph Analytics) – REPPAR (Third International Workshop on Reproducibility in Parallel Computing) – Resilience (9th Workshop in Resilience in High Performance Computing in Clusters, Clouds, and Grids) – ROME (Fourth Workshop on Runtime and Operating Systems for the Many-Core Era) – UCHPC (9th Workshop on UnConventional High-Performance Computing).
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Specificații
ISBN-13: 9783319589428
ISBN-10: 3319589423
Pagini: 872
Ilustrații: XXXIX, 829 p. 281 illus.
Dimensiuni: 155 x 235 x 47 mm
Greutate: 1.29 kg
Ediția:1st edition 2017
Editura: Springer
Colecția Lecture Notes in Computer Science
Seria Lecture Notes in Computer Science
Locul publicării:Cham, Switzerland
ISBN-10: 3319589423
Pagini: 872
Ilustrații: XXXIX, 829 p. 281 illus.
Dimensiuni: 155 x 235 x 47 mm
Greutate: 1.29 kg
Ediția:1st edition 2017
Editura: Springer
Colecția Lecture Notes in Computer Science
Seria Lecture Notes in Computer Science
Locul publicării:Cham, Switzerland
Cuprins
Parallel and distributed computing education for undergraduate students.– Algorithms, models and tools for parallel computing on heterogeneous platforms.- Multicore software engineering.- Large-scale distributed virtual environments.- Parallel and distributed agent-based simulations.- Parallelism in bioinformatics.-Performance engineering for large-scale graph analytics.- Reproducibility in parallel computing.- Resilience in high performance computing in clusters, clouds, and grids.- Runtime and operating systems for the many-core era).- UnConventional high-performance computing.
Caracteristici
Includes supplementary material: sn.pub/extras