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