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Heterogeneous distributed computing based on high-level abstractions

机译:基于高级抽象的异构分布式计算

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The rise of heterogeneous systems has given place to great challenges for users as they involve new concepts, restrictions, and frameworks. Their exploitation is further complicated in the context of distributed memory systems, which require the usage of additional different programming paradigms and tools. In this paper, we propose a novel approach to program heterogeneous clusters that is basedonhigh-level abstractions such as tiles andhierarchical decomposition combined with the powerful APIs that data types and embedded languages can provide in languages such as C++. Rather than building our proposal from scratch, we have implemented it as a natural integration of the existingHierarchically TiledArrays (HTA) andHeterogeneous Programming Library (HPL) projects, ie, the first one being focused on distributed computing and the second one on heterogeneous processing. The result, called Heterogeneous Hierarchically Tiled Arrays (H2TA), is very intuitive and easy to use thanks to the global view of the data and the single-threaded view of the execution that it provides at cluster level together with the transparency it provides with respect to the management of the heterogeneous devices. An evaluation comparing our proposal with MPI-based implementationsshowsits large programmability advantagesandthe reasonable overhead incurred.
机译:异构系统的兴起给用户带来了巨大挑战,因为它们涉及新的概念,限制和框架。在分布式存储系统的情况下,它们的开发更加复杂,这需要使用其他不同的编程范例和工具。在本文中,我们提出了一种新颖的异构集群编程方法,该方法基于诸如瓦片和分层分解等高级抽象,并结合了强大的API,数据类型和嵌入式语言可以使用C ++等语言提供这些API。我们不是从头开始构建我们的建议,而是将其实现为现有的Hierarchically TiledArrays(HTA)和异构编程库(HPL)项目的自然集成,即第一个专注于分布式计算,第二个专注于异构处理。由于数据的全局视图和在群集级别提供的执行的单线程视图以及相对于透明性的透明性,该结果称为异构分层平铺数组(H2TA),非常直观且易于使用。异构设备的管理。通过将我们的提议与基于MPI的实现进行比较的评估显示,它具有较大的可编程性优势和合理的开销。

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