Big Data Analysis of HPC Technologies From Scientific Computing

Abstract

Recent advances in information technology and its widespread growth in the areas of business, engineering, medical and scientific studies have resulted in information explosion. HPC systems are essential for solving scientific problems involving massive data using high computation power and high throughput networks. Due to the wide spread growth of data in various fields, knowledge discovery and decision making is a challenging task and has resulted in the emerging trend of Big Data analytics. Big data is related to complex, diverse and massive data sets comprising of structured, semi-structured and unstructured data. Such data cannot be processed and analyzed with the traditional database technologies. HPC systems can be extended to Big data applications for large scale processing and analysis, shifting the paradigm from traditional scientific computing domain to data intensive domain or Big data. The aim of this paper is to present an overview of the evolution of the principles underlying HPC, starting from scientific computing to present day Big Data analytics applications.