Performance and scalability of finite-difference and finite-element wave-propagation modeling on Intel's Xeon Phi

Abstract

With the rapid developments in parallel compute architectures, algorithms for seismic modeling and imaging need to be reconsidered in terms of parallelization. The aim of this paper is to compare scalability of seismic modeling algorithms: finite differences, continuous mass-lumped finite elements and discontinuous Galerkin finite elements. The performance for these methods is considered for a given accuracy. The experiments were performed on an Intel Sandy Bridge dual 8-core machine and on Intel's 61-core Xeon Phi, which is based on the Many Integrated Core architecture. The codes ran without any modifications. On the Sandy Bridge, the scalability is similar for all methods. On the Xeon Phi, the finite elements outperform finite differences on larger number of cores in terms of scalability.