Large-Scale Scientific Computing, 1st ed. 2018 11th International Conference, LSSC 2017, Sozopol, Bulgaria, June 5-9, 2017, Revised Selected Papers Theoretical Computer Science and General Issues Series
Coordonnateurs : Lirkov Ivan, Margenov Svetozar
The 63 revised short papers together with 3 full papers presented were carefully reviewed and selected from 63 submissions.
- Hierarchical, adaptive, domain decomposition and local refinement methods;
- Robust preconditioning algorithms;
- Monte Carlo methods and algorithms;
- Numerical linear algebra;
- Control and optimization;
- Parallel algorithms and performance analysis;
- Large-scale computations of environmental, biomedical and engineering problems.
Space-Time Methods for Solving Time-Dependent PDEs.- Advanced Discretizations and Solvers for Coupled Systems of Partial Differential Equations.- Least-Squares Finite Element Methods.- Advances in Heterogeneous Numerical Methods for Multi Physics Problems.- Advanced Numerical Methods for Nonlinear Elliptic Partial Differential Equations.- Control and Optimization of Dynamical Systems.- HPC and Big Data: Algorithms and Applications.- Toward Exascale Computation.- Application of Metaheuristics to Large-Scale Problems.- Large-Scale Models: Numerical Methods, Parallel Computations and Applications.- Large-Scale Numerical Computations for Sustainable Energy Production and Storage.
Includes supplementary material: sn.pub/extras
Date de parution : 01-2018
Ouvrage de 610 p.
15.5x23.5 cm
Disponible chez l'éditeur (délai d'approvisionnement : 15 jours).
Prix indicatif 86,50 €
Ajouter au panierThèmes de Large-Scale Scientific Computing :
Mots-clés :
numerical methods; problem solving; artificial intelligence; finite element method; matrix algebra; genetic algorithms; parallel processing systems; differential equations; telecommunication networks; adaptive control systems; optimal control systems; optimal control; ad hoc networks; routers; processors; evolutionary algorithms; preconditioners; differential inclusions; simulated annealing; algorithm analysis and problem complexity