Empowering R with High Performance Computing Resources for Big Data Analytics

2016 ◽  
pp. 191-217 ◽  
Author(s):  
Weijia Xu ◽  
Ruizhu Huang ◽  
Hui Zhang ◽  
Yaakoub El-Khamra ◽  
David Walling
Keyword(s):  
Big Data ◽  
High Performance Computing ◽  
Data Analytics ◽  
High Performance ◽  
Big Data Analytics ◽  
Performance Computing

scholarly journals Toward High-Performance Computing and Big Data Analytics Convergence: The Case of Spark-DIY

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 156929-156955
Author(s):  
Silvina Caino-Lores ◽  
Jesus Carretero ◽  
Bogdan Nicolae ◽  
Orcun Yildiz ◽  
Tom Peterka
Keyword(s):  
Big Data ◽  
High Performance Computing ◽  
Data Analytics ◽  
High Performance ◽  
Big Data Analytics ◽  
Performance Computing

High-Performance Computing Based Big Data Analytics for Smart Manufacturing

2018 ◽  
Author(s):  
Yuhang Yang ◽  
Y. Dora Cai ◽  
Qiyue Lu ◽  
Yifang Zhang ◽  
Seid Koric ◽  
...  
Keyword(s):  
Big Data ◽  
High Performance Computing ◽  
Data Analytics ◽  
High Performance ◽  
Manufacturing Industry ◽  
Rapid Development ◽  
Big Data Analytics ◽  
Smart Manufacturing ◽  
Intelligent Decision Making ◽  
Performance Computing

With the rapid development of sensing, communication, and computing technologies and infrastructure, today’s manufacturing industry is marching towards a big data era and a new generation of digitalization and intelligence. The availability of big data provides us with a golden opportunity to promote smart manufacturing. Nevertheless, the deployment and popularization of big data analytics in manufacturing is still at its nascent stage. One critical challenge results from the lack of high-performance computing (HPC) capability, which is crucial for responsive and intelligent decision-making in the modern manufacturing industry. To address this challenge, this paper proposes a framework and some general guidelines for implementing big data analytics in an HPC environment. The details of the whole workflow, from the prototype to the final application, are high-lighted. A case study for intelligent 3D sensing with real-world manufacturing data is presented to demonstrate the effectiveness of the proposed framework.

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