This work is a user guide to the FEMPAR scientific software library. FEMPAR is an open-source object-oriented framework for the simulation of partial differential equations (PDEs) using finite element methods on distributed-memory platforms. It provides a rich set of tools for numerical discretization and built-in scalable solvers for the resulting linear systems of equations. An application expert that wants to simulate a PDE-governed problem has to extend the framework with a description of the weak form of the PDE at hand (and additional perturbation terms for non-conforming approximations). We show how to use the library by going through three different tutorials. The first tutorial simulates a linear PDE (Poisson equation) in a serial environment for a structured mesh using both continuous and discontinuous Galerkin finite element methods. The second tutorial extends it with adaptive mesh refinement on octree meshes. The third tutorial is a distributed-memory version of the previous one that combines a scalable octree handler and a scalable domain decomposition solver. The exposition is restricted to linear PDEs and simple geometries to keep it concise. The interested user can dive into more tutorials available in the FEMPAR public repository to learn about further capabilities of the library, e.g., nonlinear PDEs and nonlinear solvers, time integration, multi-field PDEs, block preconditioning, or unstructured mesh handling.

中文翻译：

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并行有限元库 FEMPAR v1.0.0 的教程驱动介绍

本作品是 FEMPAR 科学软件库的用户指南。FEMPAR 是一个开源的面向对象框架，用于在分布式内存平台上使用有限元方法模拟偏微分方程 (PDE)。它提供了一套丰富的数值离散化工具和用于生成线性方程组的内置可扩展求解器。想要模拟 PDE 控制问题的应用程序专家必须使用手头的 PDE 弱形式的描述（以及非一致近似值的附加扰动项）来扩展框架。我们通过三个不同的教程展示了如何使用该库。第一个教程使用连续和不连续 Galerkin 有限元方法在串行环境中为结构化网格模拟线性 PDE（泊松方程）。第二个教程通过八叉树网格上的自适​​应网格细化对其进行了扩展。第三个教程是前一个教程的分布式内存版本，它结合了可扩展的八叉树处理程序和可扩展的域分解求解器。说明仅限于线性偏微分方程和简单的几何结构以保持简洁。感兴趣的用户可以深入了解 FEMPAR 公共存储库中提供的更多教程，以了解该库的更多功能，例如非线性 PDE 和非线性求解器、时间积分、多场 PDE、块预处理或非结构化网格处理。说明仅限于线性偏微分方程和简单的几何结构以保持简洁。感兴趣的用户可以深入了解 FEMPAR 公共存储库中提供的更多教程，以了解该库的更多功能，例如非线性 PDE 和非线性求解器、时间积分、多场 PDE、块预处理或非结构化网格处理。说明仅限于线性偏微分方程和简单的几何结构以保持简洁。感兴趣的用户可以深入了解 FEMPAR 公共存储库中提供的更多教程，以了解该库的更多功能，例如非线性 PDE 和非线性求解器、时间积分、多场 PDE、块预处理或非结构化网格处理。