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Towards a High Level Approach for the Programming of Heterogeneous Clusters

机译:朝着高水平的方法来编程异构集群

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The programming of heterogeneous clusters is inherently complex, as these architectures require programmers to manage both distributed memory and computational units with a very different nature. Fortunately, there has been extensive research on the development of frameworks that raise the level of abstraction of cluster-based applications, thus enabling the use of programming models that are much more convenient that the traditional one based on message-passing. One of such proposals is the Hierarchically Tiled Array (HTA), a data type that represents globally distributed arrays on which it is possible to perform a wide range of data-parallel operations. In this paper we explore for the first time the development of heterogeneous applications for clusters using HTAs. In order to use a high level API also for the heterogeneous parts of the application, we developed them using the Heterogeneous Programming Library (HPL), which operates on top of OpenCL but providing much better programmability. Our experiments show that this approach is a very attractive alternative, as it obtains large programmability benefits with respect to a traditional implementation based on MPI and OpenCL, while presenting average performance overheads just around 2%.
机译:异构集群的编程本质上是复杂的,因为这些架构要求程序员管理具有截然不同的性质的分布式内存和计算单元。幸运的是,对提高基于群集应用程序的抽象水平的框架的发展已经进行了广泛的研究,从而使使用比较方便的编程模型基于消息传递更方便。这样的提案之一是分层划线阵列(HTA),其代表全局分布式阵列的数据类型,其中可以执行广泛的数据并行操作。在本文中,我们首次探索使用HTAS的群集的异构应用的开发。为了使用高水平的API,对于应用程序的异构部分,我们使用异构编程库(HPL)开发了它们,其在OpenCL之上运行,但提供更好的可编程性。我们的实验表明,这种方法是一个非常有吸引力的替代方案,因为它在基于MPI和OpenCL的传统实现中获得了大量的可编程性效益,同时呈现平均性能超过2%的性能开销。

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