Optimised finite difference computation from symbolic equations
Mathematical Software
2017-07-13 v1
Abstract
Domain-specific high-productivity environments are playing an increasingly important role in scientific computing due to the levels of abstraction and automation they provide. In this paper we introduce Devito, an open-source domain-specific framework for solving partial differential equations from symbolic problem definitions by the finite difference method. We highlight the generation and automated execution of highly optimized stencil code from only a few lines of high-level symbolic Python for a set of scientific equations, before exploring the use of Devito operators in seismic inversion problems.
Cite
@article{arxiv.1707.03776,
title = {Optimised finite difference computation from symbolic equations},
author = {Michael Lange and Navjot Kukreja and Fabio Luporini and Mathias Louboutin and Charles Yount and Jan Hückelheim and Gerard J. Gorman},
journal= {arXiv preprint arXiv:1707.03776},
year = {2017}
}
Comments
Accepted for publication in Proceedings of the 16th Python in Science Conference (SciPy 2017)