Data-Aware Support for Hybrid HPC and Big Data Applications

被引：1
|
作者：
Caino-Lores, Silvina [1 ]
Isaila, Florin [1 ]
Carretero, Jesus [1 ]
机构：
[1] Univ Carlos III Madrid, Dept Comp Sci, Leganes, Spain
来源：
2017 17TH IEEE/ACM INTERNATIONAL SYMPOSIUM ON CLUSTER, CLOUD AND GRID COMPUTING (CCGRID) | 2017年
关键词：
high-performance computing; big data; scientific computing; data management; data-intensive computing;
D O I：
10.1109/CCGRID.2017.55
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Nowadays there is a raising interest in bridging the gap between Big Data application models and data-intensive HPC. This work explores the effects that Big Data-inspired paradigms could have in current scientific applications through the evaluation of a real-world application from the hydrology domain. This evaluation led to experience that portrayed the key aspects of the HPC and Big Data paradigms that made them successful in their respective worlds. With this information, we established a research roadmap to build a platform suitable for HPC hybrid applications, with a focus on efficient data management and fault-tolerance.
引用
收藏
页码：719 / 722
页数：4
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