Smart-DASH: Smart Data Structures and Algorithms with Support for Hierarchical Locality

Smart-DASH：支持分层局部性的智能数据结构和算法

• 批准号: 230673419
• 负责人: Dr. Karl Fürlinger
• 金额: --
• 依托单位: Zentrum für Informationsdienste und Hochleistungsrechnen (ZIH)
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 财政年份: 2012
• 资助国家: 德国
• 起止时间: 2011-12-31 至 2020-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/230673419?language=en
• 关键词: Smart; DASH; Data; Structures; Algorithms

We propose Smart-DASH, a continuation and extension of our work with DASH, with which we would like to make a contribution towards efficient data-centric programming on current and upcoming parallel architectures. Smart-DASH builds upon our previous work with DASH, a data-structure oriented C++ template library that can exploit hierarchical organization afforded by machines and algorithms. Smart-DASH extends this work by addressing some of the most pressing challenges on the way to Exascale. The runtime and C++ template library will be extended to support a task-based execution model and with the notion of memory spaces, Smart-DASH will be able to exploit the complex memory architecture of upcoming machines. Several case studies will explore the utility of these new features in the context of important scientific problem classes. We will develop smart data structures that capture frequently encountered application scenarios such as N-dimensional arrays with built-in support for halo regions to enable a productive transition onto new hardware platforms and assist in code modernization efforts. To address fault-tolerance and reliability, we will explore concepts for the redundant storage of data items and with the DASH data dock we will explore the usage of the PGAS approach in general and NVRAM in particular for the coupling of applications. We will test this approach in the context of a real-world astro-particle application.

我们提出了Smart-Dash，这是我们与DASH工作的延续和扩展，我们希望通过它为在当前和即将到来的并行体系结构上高效地进行以数据为中心的编程做出贡献。Smart-Dash建立在我们之前使用DASH的基础上，DASH是一个面向数据结构的C++模板库，可以利用机器和算法提供的分层组织。Smart-Dash通过解决在迈向艾斯卡的道路上面临的一些最紧迫的挑战来扩展这项工作。运行时和C++模板库将被扩展以支持基于任务的执行模型，并且通过内存空间的概念，Smart-dash将能够利用即将到来的机器的复杂内存架构。几个案例研究将探索这些新功能在重要科学问题类的背景下的效用。我们将开发智能数据结构，以捕获经常遇到的应用场景，例如具有对光环区域的内置支持的N维数组，以实现向新硬件平台的高效过渡，并协助代码现代化工作。为了解决容错和可靠性问题，我们将探讨数据项冗余存储的概念，并通过DASH数据底座探讨PGAS方法的一般用法和NVRAM特别是用于应用程序耦合的方法。我们将在一个真实的天文粒子应用程序的上下文中测试该方法。