期刊
ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE
卷 43, 期 3, 页码 -出版社
ASSOC COMPUTING MACHINERY
DOI: 10.1145/2998441
关键词
Abstraction; code generation; UFL
资金
- Engineering and Physical Sciences Research Council [EP/I00677X/1, EP/L000407/1, EP/I012036/1]
- Natural Environment Research Council [NE/G523512/1, NE/I021098/1, NE/K006789/1, NE/K008951/1]
- Grantham Institute, Imperial College London
- Engineering and Physical Sciences Research Council [EP/M011054/1, 1253177] Funding Source: researchfish
- EPSRC [EP/M011054/1, EP/I00677X/1, EP/I012036/1, EP/L000407/1] Funding Source: UKRI
- NERC [NE/K006789/1, NE/I021098/1, NE/K008951/1] Funding Source: UKRI
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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