pyMOR - Sustainable Software for Model Order Reduction

偏微分方程（PDEs）描述的数学模型的数值模拟是当今几乎所有科学学科研究的重要工具。然而，这种模型的使用通常受到可用计算资源的限制。在过去的十年中，已经开发了各种算法，用于计算给定的数值PDE模型，可以在原始模型解所需时间的一小部分内模拟数学认证的代理。这些技术被称为模型降阶（MOR），现在正成为许多仿真工作流程中不可或缺的一部分，否则即使在最大的可用超级计算机上也是不可行的。使用pyMOR (http://pymor.org/)，我们开发了一个功能强大的MOR软件库，它可以很容易地与PDE求解器库集成，允许将MOR技术应用于由这些库实现的PDE模型。该项目的主要目标是开发基础设施，以支持pyMOR和相关研究软件的可持续发展和部署。首先，我们将开发和部署一个面向研究的云服务，它将提供基于应用程序容器的统一开发、持续交付和部署工作流。该服务将为各种用例提供研究软件，如持续集成、软件演示、教学或大规模研究应用。其次，我们将为科学计算领域的研究软件的单元测试制定指导方针。这些指导方针将帮助开发人员系统地为他们的软件编写全面的单元测试，确保产品的质量和长期可维护性。基于这些基础设施措施，我们将提高pyMOR的可用性，使我们的软件成为各种基于pde的科学计算应用程序的通用MOR工具。

The numerical simulation of mathematical models described by partial differential equations (PDEs) is nowadays an important tool for research in almost every scientific discipline. Yet, the use of such models is often limited by the available computational resources.Over the last decade, a variety of algorithms have been developed which compute, for a given numerical PDE model, a mathematically certified surrogate that can be simulated in a small fraction of the time required for the solution of the original model. These techniques, known as model order reduction (MOR), are now becoming an integral part in many simulation workflows which otherwise would be infeasible, even on the largest available supercomputers. With pyMOR (http://pymor.org/), we have developed a powerful MOR software library which can be easily integrated with PDE solver libraries, allowing application of MOR techniques to PDE models implemented with these libraries.The main goal of this project is the development of infrastructures to support the sustainable development and deployment of pyMOR and related research software.First, we will develop and deploy a research oriented cloud service which will offer a unified development, continuous delivery and deployment workflow based on application containers. Research software will be delivered by this service for various use cases, such as continuous integration, software demonstration, teaching or large-scale research applications.Second, we will develop guidelines for unit testing of research software in the field of scientific computing. These guidelines will help developers to systematically write comprehensive unit tests for their software, assuring the quality and long-term maintainability of their product.Based on these infrastructural measures, we will improve pyMOR's usability to establish our software as a universal MOR tool for various PDE-based scientific computing applications.