High Performance Computing and Big Data Analytics – Paradigms and Challenges

نویسندگان

  • Rupali Sunil Wagh
  • Chandan K Reddy
  • Han Hu
  • Yonggang Wen
  • Xue-Wen Chen
  • Xiaotong Lin
  • Fay Chang
  • Jeffrey Dean
  • Sanjay Ghemawat
  • Dongman Lee
چکیده

The advent of technology has led to rise in data being captured, stored and analyzed. The requirement of improving the computational models along with managing the voluminous data is a primary concern. The transition of the High Performance Computing from catering to traditional problems to the newer domains like finance, healthcare etc. necessitates the joint analytical model to include Big Data. The rise of Big Data and subsequently Big Data analytics has changed the entire perspective of data and data handling. Ever growing analytical needs for Big Data can be satisfied with extremely high performance computing models. As a result of enormous research in this field, recent years have seen the emergence diverse paradigms for Big Data analytics. With the spread of Big Data analytics in varied domains, newer concerns regarding the effectiveness of analytical paradigms are also observed. This paper highlights the major analytical models and concerns and challenges in High Performance Data Analytics.

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تاریخ انتشار 2015