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Optimised finite difference computation from symbolic equations (1707.03776v1)

Published 12 Jul 2017 in cs.MS

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.

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Authors (7)
  1. Michael Lange (22 papers)
  2. Navjot Kukreja (13 papers)
  3. Fabio Luporini (21 papers)
  4. Mathias Louboutin (42 papers)
  5. Charles Yount (2 papers)
  6. Jan Hückelheim (18 papers)
  7. Gerard J. Gorman (19 papers)
Citations (8)

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