Victorita Dolean – författare
Visar alla böcker från författaren Victorita Dolean. Handla med fri frakt och snabb leverans.
2 produkter
2 produkter
Introduction to Domain Decomposition Methods
Algorithms, Theory, and Parallel Implementation
Häftad, Engelska, 2015
1 005 kr
Skickas inom 5-8 vardagar
The purpose of this book is to offer an overview of the most popular domain decomposition methods for partial differential equations (PDEs). These methods are widely used for numerical simulations in solid mechanics, electromagnetism, flow in porous media, etc., on parallel machines from tens to hundreds of thousands of cores. The appealing feature of domain decomposition methods is that, contrary to direct methods, they are naturally parallel. The authors focus on parallel linear solvers.The authors present:All popular algorithms both at the PDE level and at the discrete level in terms of matrices.Systematic scripts for sequential implementation in a free open-source finite element package as well as some parallel scripts.A new coarse space construction (two-level method) that adapts to highly heterogeneous problems.
3 672 kr
Kommande
Domain decomposition is an active interdisciplinary area of research in the mathematical analysis and computational implementation of decoupling and coupling strategies for models of natural and engineered physical systems, networks, and graphs. Since the advent of distributed-memory supercomputers, it has been motivated by considerations of concurrency and locality for a wide variety of large-scale problems, continuous and discrete. Historically, it emerged from the analysis of partial differential equations, beginning with the work of Schwarz in 1870. This volume contains fifty papers originally presented at the 28th International Conference on Domain Decomposition Methods at the King Abdullah University of Science and Technology in Saudi Arabia in 2024 by scientists from 24 countries, updated post-conference to 2026, spanning from fluid flow to Helmholtz problems, from optimization to neural networks.