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HSTREAM: A Directive-Based Language Extension for Heterogeneous Stream Computing

机译:HSTREAM:异构流计算的基于指令的语言扩展

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Big data streaming applications require utilization of heterogeneous parallel computing systems, which may comprise multiple multi-core CPUs and many-core accelerating devices such as NVIDIA GPUs and Intel Xeon Phis. Programming such systems require advanced knowledge of several hardware architectures and device-specific programming models, including OpenMP and CUDA. In this paper, we present HSTREAM, a compiler directive-based language extension to support programming stream computing applications for heterogeneous parallel computing systems. HSTREAM source-to-source compiler aims to increase the programming productivity by enabling programmers to annotate the parallel regions for heterogeneous execution and generate target specific code. The HSTREAM runtime automatically distributes the workload across CPUs and accelerating devices. We demonstrate the usefulness of HSTREAM language extension with various applications from the STREAM benchmark. Experimental evaluation results show that HSTREAM can keep the same programming simplicity as OpenMP, and the generated code can deliver performance beyond what CPUs-only and GPUs-only executions can deliver.
机译:大数据流应用程序需要利用异构并行计算系统,该系统可能包括多个多核CPU和诸如NVIDIA GPU和Intel Xeon Phis之类的多核加速设备。对此类系统进行编程,需要具备多种硬件体系结构和特定于设备的编程模型(包括OpenMP和CUDA)的高级知识。在本文中,我们介绍了HSTREAM,这是一种基于编译器指令的语言扩展,可支持用于异构并行计算系统的流计算应用程序的编程。 HSTREAM源到源编译器旨在通过使程序员能够注释并行区域以进行异构执行并生成目标特定代码,来提高编程效率。 HSTREAM运行时自动在CPU和加速设备之间分配工作负载。我们通过STREAM基准测试证明了HSTREAM语言扩展在各种应用程序中的有用性。实验评估结果表明,HSTREAM可以保持与OpenMP相同的编程简易性,并且生成的代码可以提供超越仅CPU和仅GPU执行的性能。

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