A parallel Heap-Cell Method for Eikonal equations
Provides a fast parallel solver for Eikonal equations, benefiting scientific computing applications that require efficient numerical solutions.
The paper parallelizes the Heap-Cell Method for Eikonal equations on shared memory architectures, achieving good scaling and fast performance in 3D numerical experiments.
Numerous applications of Eikonal equations prompted the development of many efficient numerical algorithms. The Heap-Cell Method (HCM) is a recent serial two-scale technique that has been shown to have advantages over other serial state-of-the-art solvers for a wide range of problems. This paper presents a parallelization of HCM for a shared memory architecture. The numerical experiments in $R^3$ show that the parallel HCM exhibits good algorithmic behavior and scales well, resulting in a very fast and practical solver. We further explore the influence on performance and scaling of data precision, early termination criteria, and the hardware architecture. A shorter version of this manuscript (omitting these more detailed tests) has been submitted to SIAM Journal on Scientific Computing in 2012.