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Code Generation for Productive, Portable, and Scalable Finite Element Simulation in Firedrake
Computing in Science & Engineering ( IF 2.1 ) Pub Date : 2021-06-07 , DOI: 10.1109/mcse.2021.3085102
Jack D. Betteridge 1 , Patrick E. Farrell 2 , David A. Ham 1
Affiliation  

Creating scalable, high-performance PDE-based simulations requires an appropriate combination of models, discretizations, and solvers. The required combination changes with the application and with the available hardware, yet software development time is a severely limited resource for most scientists and engineers. Here we demonstrate that generating simulation code from a high-level Python interface provides an effective mechanism for creating high-performance simulations from very few lines of user code. We demonstrate that moving from one supercomputer to another can require significant algorithmic changes to achieve scalable performance, but that the code generation approach enables these algorithmic changes to be achieved with minimal development effort.

中文翻译:

Firedrake 中用于高效、便携和可扩展的有限元仿真的代码生成

创建可扩展、高性能的基于 PDE 的仿真需要模型、离散化和求解器的适当组合。所需的组合随着应用程序和可用硬件的变化而变化,但对于大多数科学家和工程师来说,软件开发时间是非常有限的资源。在这里,我们演示了从高级 Python 接口生成模拟代码提供了一种有效机制,可以从很少的用户代码行中创建高性能模拟。我们证明,从一台超级计算机迁移到另一台超级计算机可能需要对算法进行重大更改才能实现可扩展的性能,但代码生成方法能够以最少的开发工作实现这些算法更改。
更新日期:2021-07-30
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