4.5 Article

Firedrake: Automating the Finite Element Method by Composing Abstractions

期刊

出版社

ASSOC COMPUTING MACHINERY
DOI: 10.1145/2998441

关键词

Abstraction; code generation; UFL

资金

  1. Engineering and Physical Sciences Research Council [EP/I00677X/1, EP/L000407/1, EP/I012036/1]
  2. Natural Environment Research Council [NE/G523512/1, NE/I021098/1, NE/K006789/1, NE/K008951/1]
  3. Grantham Institute, Imperial College London
  4. Engineering and Physical Sciences Research Council [EP/M011054/1, 1253177] Funding Source: researchfish
  5. EPSRC [EP/M011054/1, EP/I00677X/1, EP/I012036/1, EP/L000407/1] Funding Source: UKRI
  6. NERC [NE/K006789/1, NE/I021098/1, NE/K008951/1] Funding Source: UKRI

向作者/读者索取更多资源

Firedrake is a new tool for automating the numerical solution of partial differential equations. Firedrake adopts the domain-specific language for the finite element method of the FEniCS project, but with a pure Python runtime-only implementation centered on the composition of several existing and new abstractions for particular aspects of scientific computing. The result is a more complete separation of concerns that eases the incorporation of separate contributions from computer scientists, numerical analysts, and application specialists. These contributions may add functionality or improve performance. Firedrake benefits from automatically applying new optimizations. This includes factorizing mixed function spaces, transforming and vectorizing inner loops, and intrinsically supporting block matrix operations. Importantly, Firedrake presents a simple public API for escaping the UFL abstraction. This allows users to implement common operations that fall outside of pure variational formulations, such as flux limiters.

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