扩展omps以支持数据分析工作负载

2017 International Conference on High Performance Computing & Simulation (HPCS) Pub Date : 2017-07-01 DOI:10.1109/HPCS.2017.136

Marcos Maroñas

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引用次数: 0

摘要

在大数据时代，天文学[1]等新的科学应用不断涌现，对高性能计算(HPC)系统和软件提出了挑战。传统上，HPC应用程序是受计算限制的，在执行开始和结束时很少使用I/O功能。相比之下，紧急应用呈现出数据密集型行为，对硬件和软件都提出了新的挑战。

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Extending OmpSs to Support Data Analytics Workload

In the era of big data, new scientific applications such as those used in astronomy [1] are emerging and challenging High Performance Computing (HPC) systems and software. Traditionally, HPC applications were compute-bounded, with a light use of the I/O capabilites at the start and end of the execution. In contrast, emergent applications present data- intensive behaviors arising several new challenges to be faced by hardware and software.

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2017 International Conference on High Performance Computing & Simulation (HPCS)

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