Pressio：为大规模非线性动力系统启用基于投影的模型降阶
Pressio: Enabling projection-based model reduction for large-scale nonlinear dynamical systems
摘要：
这项工作介绍Pressio，一个开源项目，旨在使领先的基于投影的降阶模型（ROM）的大规模非线性动力系统在科学和工程。Pressio提供了模型简化方法，可以减少任何动力系统的空间和时间自由度的数量，这些动力系统可以表示为参数化常微分方程（ODE）系统。我们利用这个简单的，表现力的数学框架作为一个关键的设计选择，使一个最小的应用程序编程接口（API），是自然的动态系统。Pressio的核心组件是一个C++11头文件库，它利用泛型编程来支持具有任意数据类型和任意复杂编程模型的应用程序。这与Python绑定相辅相成，以将这些C++功能公开给Python用户，开销可以忽略不计，并且没有用户需要的绑定代码。我们讨论了Pressio相对于现有的模型简化库的区别特征，概述了其关键设计功能，描述了用户如何与它交互，并提出了两个测试用例-其中一个具有超过2000万自由度-突出了Pressio的性能结果，并说明了它可以解决的问题。
英文摘要：
This work introduces Pressio, an open-source project aimed at enabling leading-edge projection-based reduced order models (ROMs) for large-scale nonlinear dynamical systems in science and engineering. Pressio provides model-reduction methods that can reduce both the number of spatial and temporal degrees of freedom for any dynamical system expressible as a system of parameterized ordinary differential equations (ODEs). We leverage this simple, expressive mathematical framework as a pivotal design choice to enable a minimal application programming interface (API) that is natural to dynamical systems. The core component of Pressio is a C++11 header-only library that leverages generic programming to support applications with arbitrary data types and arbitrarily complex programming models. This is complemented with Python bindings to expose these C++ functionalities to Python users with negligible overhead and no user-required binding code. We discuss the distinguishing characteristics of Pressio relative to existing model-reduction libraries, outline its key design features, describe how the user interacts with it, and present two test cases -- including one with over 20 million degrees of freedom -- that highlight the performance results of Pressio and illustrate the breath of problems that can be addressed with it.
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