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
[Chacon & Vladimirsky, 2012]. 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.