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

我们提出了Smart-DASH，这是我们在DASH方面工作的延续和扩展，我们希望为当前和即将到来的并行架构上的高效数据中心编程做出贡献。Smart-DASH建立在我们之前使用DASH的工作基础上，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通过解决迈向Exascale的道路上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将能够利用即将推出的机器的复杂内存架构。几个案例研究将探讨这些新功能在重要的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，例如内置支持晕圈区域的N维数组，以实现到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，我们将探索数据项冗余存储的概念，并通过DASH数据坞，我们将探索PGAS方法的一般使用，特别是NVRAM用于应用程序的耦合。我们将在现实世界的天体粒子应用程序的背景下测试这种方法。

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.