Extending OmpSs to Support Data Analytics Workload

Marcos Maroñas
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Abstract

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.
扩展omps以支持数据分析工作负载
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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