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W. Yu, Franz Franchetti, James C. Hoe, José M. F. Moura and Tsuhan Chen (Proc. High Performance Extreme Computing (HPEC), 2011)

**Performance Portable Tracking of Evolving Surfaces**

Preprint (525 KB)

Bibtex

Tracking the continuous evolution of surfaces such as a shock wavefront has a wide range of real world applications. The level set algorithm is a widely used tool for tracking evolving surfaces[4]. It embeds the surface into a higher dimensional function defined on a structural grid discretized volume, and performs numerical computation on the fixed Cartesian grid. The narrow band level set[4] is a variation of the level set method that can significantly reduce the computational cost without noticeable change in quality, by constraining computation to a neighborhood region around the interface which is called narrow band. The narrow band level set algorithm performs a computation similar to iteratively solving partial differential equations with stencils, but on a irregular shaped and dynamically evolving narrow band. Usually, the interface motion is tracked for a large number of iterations, thus having the potential for a high data reuse rate. However, extracting data reuse on the highly irregular computational pattern is difficult. The major contribution of the paper is that we develop a framework to generate highly efficient code for this algorithm on mainstream CPUs with multicore, deep memory hierarchies and SIMD instructions. Related work. This work is closely related to prior works on optimization of stencils [3, 2] and sparse linear algebra[5, 6]. Prior work on stencils has been primarily focusing on the dense structural grid. Sparse matrix solvers are usually memory-bound because of the low data reuse rate. We combined concepts from both areas, and develop a novel framework for the narrow band level set algorithm.

Portability, Evolving surfaces