Adaptive Mesh Refinement (AMR)
J. C. Brown
U.T. Austin Computer Science
Adaptive Mesh Refinement (AMR)
Motivation for using AMR
Motivation for using AMR
Principles of AMR
Principles of AMR
Implementation Features
Time Integration
Time Integration
PP Presentation
PP Presentation
Error Estimation based on Richardson Expansion
Error Estimation
PP Presentation
Shadow Hierarchy
Re-gridding
Re-gridding and Clustering
Clustering
Clustering: Bisection Method
Clustering: Bisection Method
Clustering: Minimal SpanningTree
Clustering: Minimal Spanning Tree
Re-gridding revisited
Re-gridding revisited
Grid-to-grid interactions
Modified Berger-Oliger Algorithm
Modified Berger-Oliger Algorithm
Modified Berger-Oliger Algorithm
Modified Berger-Oliger Algorithm
Modified Berger-Oliger Algorithm
Modified Berger-Oliger Algorithm
Supercomputing ‘97
Objective: A Common Infrastructure for Computational Grand Challenges
Overview
Parallel Application Development
Static Parallel Applications
Dynamic Parallel Applications
PSE for Parallel Adaptive Computations
Software Engineering
Software Engineering in the Small
Separation of Concerns => Hierarchical Abstractions
Infrastructures for Parallel AMR
LPARX/KELP (UC San Diego))
A++/P++/AMR++ (LANL)
Global Arrays (PNL)
DAGH: Overview
DAGH: Distributed Data-Structures
Constructing DAGH Data-Structures
Programming Abstractions
Programming Abstraction for AMR
DAGH: Programming Abstractions
DAGH Programming Interface
AMR Algorithm
GridHierarchy Abstraction
Grid Geometry Abstractions
GridFunction Abstraction
Ghost Communications
Region-based Communications
Data-parallel forall operator
Inter-Level Transfer
Regridding
DAGH: Applications
Conclusions