Optimised finite difference computation from symbolic equations
Title | Optimised finite difference computation from symbolic equations |
Publication Type | Conference |
Year of Publication | 2017 |
Authors | Michael Lange, Navjot Kukreja, Fabio Luporini, Mathias Louboutin, Charles Yount, Jan Hückelheim, Gerard Gorman |
Conference Name | Python in Science Conference Proceedings |
Month | 07 |
Keywords | domain-specific languages, finite difference, symbolic Python |
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. |
Notes | (SciPy, Texas) |
URL | http://conference.scipy.org/proceedings/scipy2017/michael_lange.html |
Presentation | |
Citation Key | lange2017SCIPYofd |