Performance characteristics of an adaptive mesh refinement calculation on scalar and vector platforms

Adaptive mesh refinement (AMR) is a powerful technique that reduces the resources necessary to solve otherwise intractable problems in computational science. The AMR strategy solves the problem on a relatively coarse grid, and dynamically refines it in regions requiring higher resolution. However, AMR codes tend to be far more complicated than their uniform grid counterparts due to the software infrastructure necessary to dynamically manage the hierarchical grid framework. Despite this complexity, it is generally believed that future multi-scale applications will increasingly rely on adaptive methods to study problems at unprecedented scale and resolution. Recently, a new generation of parallel-vector architectures have become available that promise to achieve extremely high sustained performance for a wide range of applications, and are the foundation of many leadership-class computing systems worldwide. It is therefore imperative to understand the tradeoffs between conventional scal...

• Type: Conference
• Year: 2006
• Where: CF
• Authors: Michael L. Welcome, Charles A. Rendleman, Leonid Oliker, Rupak Biswas
• Keywords: AMR Strategy, Applied Computing, CF 2006, HyperCLaw AMR Framework, Performance