libhpc: Intelligent Component-based Development of HPC Applications

Libhpc的目标是为基于组件的HPC应用程序构建和演示环境。该环境将使方法实现者能够将他们的贡献发布和共享为多实现可适应的组件，可跨域和架构共享，从而使它们本质上更具可重用性。最终用户将能够在不参考底层机器或处理器架构的情况下编写应用程序。Libhpc的目标是启动一种以知识获取和重用为核心的HPC软件开发模式。libhpc将基于两个长期研究的结合：Sherwin教授在开发和应用光谱/HP元素代码方面的研究，以及Darlington教授在开发创新应用程序开发方法方面的研究。该项目将以Nektar方法库及其在主动脉弓血流建模中的应用为起点。将对该应用程序和库进行重构，以确定必要的可重复使用的组件和所需的协调形式。这些组件将针对各种架构进行设计和实施，包括分布式内存集群、共享内存集群和GPU处理器。将与应用程序构建和绘图工具一起构建一个具有支持元数据的软件方法库。然后，该环境将用于重新表达主动脉建模应用程序，并将其系统地映射到许多不同的架构和机器配置。将对这些应用程序进行基准测试，以评估它们的性能以及人类生产力和可重用性的提高。

Libhpc aims build and demonstrate an environment for the component-based construction of HPC applications. This environment will enable method implementers to publish and share their contributions as multi-implementation adaptable components, shareable across domains and architectures, making them inherently more re-usable. End users will then be able to compose applications without reference to underlying machine or processor architectures. The aim of libhpc is to initiate a software development pattern for HPC that has knowledge capture and re-use at its core.Libhpc will be based on the combination of two long lines of research: that of Professor Sherwin in the development and application of spectral/hp element codes and that of Professor Darlington in the development of innovative application development methodologies. The project will take as its starting point the Nektar++ methods library and its application to the modelling of blood flow through an aortic arch. This application and the library will be re-factored to identify the necessary re-usable components and co-ordination forms required. These components will be designed and implemented, targeted at a variety of architectures, including, distributed memory clusters, shared memory clusters and GPU processors. A software methods repository with supporting meta-data will be constructed along with application-construction and mapping tools. This environment will then be used to re-express the aortic modelling application and map it systematically to a number of different architectures and machine configurations. These applications will be benchmarked to assess their performance and the improvement in human productivity and reusability gained.