Optimized load balancing in high‐performance computing for big data analytics

Author(s):  
Seyedeh Leili Mirtaheri ◽  
Lucio Grandinetti
IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 156929-156955
Author(s):  
Silvina Caino-Lores ◽  
Jesus Carretero ◽  
Bogdan Nicolae ◽  
Orcun Yildiz ◽  
Tom Peterka

Author(s):  
Yuhang Yang ◽  
Y. Dora Cai ◽  
Qiyue Lu ◽  
Yifang Zhang ◽  
Seid Koric ◽  
...  

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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