Structured Adaptive Mesh Refinement (SAMR)
SAMR, phase-field simulation of dendritic growth during solidification. (Image courtesy of Chin Yi Chee at IHPC)
Structured adaptive mesh refinement (SAMR) is a technique for improving the computational performance of simulations on structured grids by focusing computational resources where it is needed. More precisely, SAMR achieves high accuracy while controlling computational cost by restricting the use of high resolution computational grids to regions where physical or numerical considerations indicate that it is required.
To rapidly develop SAMR-based simulations, I leverage the Structured Adaptive Mesh Refinement Application Infrastructure (SAMRAI) developed in the Center for Applied Scientific Computing at Lawrence Livermore National Laboratory. SAMRAI is a large, C++ library that is designed to support large-scale, parallel, structured adaptive mesh refinement (SAMR) simulations without requiring application developers to implement low-level parallel and/or SAMR algorithms. For example, SAMRAI shields application developers from the low-level programming details involved with management of bookkeeping for SAMR data structures and parallel communication. In addition, by adopting a patch-based (as opposed to a cell-based) refinement mechanism, SAMRAI makes it relatively easy to migrate from serial codes written to solve problems on simple, uniform grids to parallel and/or SAMR numerical simulations.
I am currently involved in various projects where SAMR is used to improve the computational performance of material science and biophysics simulations.
References
- Chu, K. T. (2007). A SAMRAI Primer. PRISM. [pdf]