Firedrake中可扩展有限元仿真的代码生成
Code generation for productive portable scalable finite element simulation in Firedrake
摘要：
创建可扩展的，高性能的基于偏微分方程的模拟需要一个适当的组合离散化，微分算子，预处理器和求解器。所需的组合随应用和可用硬件而变化，但软件开发时间对大多数科学家和工程师来说是非常有限的资源。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的机制，可以从很少的用户代码行创建高性能模拟。我们证明，从一个超级计算机移动到另一个可能需要显着的算法变化，以实现可扩展的性能，但代码生成的方法，使这些算法的变化，以实现最小的开发工作。
英文摘要：
Creating scalable, high performance PDE-based simulations requires a suitable combination of discretizations, differential operators, preconditioners 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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
