Advanced numerical simulations that use adaptive mesh refinement (AMR) methods have now become routine in engineering and science. Originally developed for computational fluid dynamics applications these methods have propagated to fields as diverse as astrophysics, climate modeling, combustion, biophysics and many others. The underlying physical models and equations used in these disciplines are rather different, yet algorithmic and implementation issues facing practitioners are often remarkably similar. Unfortunately, there has been little effort to review the advances and outstanding issues of adaptive mesh refinement methods across such a variety of fields. This book attempts to bridge this gap. The book presents a collection of papers by experts in the field of AMR who analyze past advances in the field and evaluate the current state of adaptive mesh refinement methods in scientific computing.The threshold is used to adjust the quality of load balancing, whose value influences the efficiency of the overall DLB scheme. ... Distributed DLB address the heterogeneity of processors by generating a relative performance weight for each processor. ... One of the key issues for global balancing phase is to decide when such an action should be performed and whether it is advantageous to do so.
|Title||:||Adaptive Mesh Refinement - Theory and Applications|
|Author||:||Tomasz Plewa, Timur Linde, V. Gregory Weirs|
|Publisher||:||Springer Science & Business Media - 2005-12-20|