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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:大数据流应用需要利用异构并行计算系统,其可以包括多个多核CPU和许多核心加速设备,例如NVIDIA GPU和英特尔Xeon Phis。编程此类系统需要高级了解多个硬件架构和设备特定的编程模型,包括OpenMP和CUDA。在本文中,我们呈现HSTR流,基于编译器指令的语言扩展,以支持用于异构并行计算系统的编程流计算应用程序。 HSTREM源到源编译器旨在通过使程序员向非均匀执行并生成目标特定代码来增加编程生产力并通过启用异构执行并生成特定代码。 HSTREM运行时会自动将工作负载自动分配CPU和加速设备。我们展示了来自流基准的各种应用程序的HSTR流语言扩展的有用性。实验评估结果表明,HSTR流可以保持与OpenMP相同的编程简单性,并且生成的代码可以提供超出CPU和仅GPU的执行可以提供的性能。

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