High Performance Computing and Big Data Analytics Paradigms and Challenges

Abstract

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.

High-performance computing for computational modelling in built environment-related studies – a scientometric review

“…In more recent times, such mathematical models have either been replaced by complex CMs or validated by them, and these are achieved by running computer codes (UK Government Office for Science, 2018). The rise of HPC has helped in the development of such codes and testing the validity of these mathematical models (Tulasi et al, 2015). These have been made possible through the series of programming languages embedded into the HPC which makes execution of tasks possible.…”

“…Earlier languages are FORTRAN and COBOL, while more recently Python, R program, MATLAB among others have been found as useful programming languages useful for computational science. Furthermore, these computational codes take a lot of time to execute, but with the advent of HPC with a processing speed of 3.5 GH z , a lot of computational time is saved (Tulasi et al, 2015).…”

“…The general feature of highly powerful Graphics Processing Units (GPU) of HPC has made ease of data visualisation a reality. HPC is made up of GPUs such as NVIDIA GTX 480 Spec series, which are designed to speed up graphics-oriented tasks like image rendering (Tulasi et al, 2015). With the aid of such data visualisation techniques, theories represented as a model can also be simplified for further deductions.…”

“…Thus, HPC is a machine that combines many processors and makes their combined computing power available to use. The introduction of supercomputers has been the bedrock of high-performance computing, and this has led to the ease in the development of CMs (Tulasi et al, 2015).…”

Design of High-Performance Computing System for Big Data Analytics

“…The convergence of HPC and BDA presents both challenges and opportunities. To design an HPC system for BDA, it is important to consider factors such as data storage, parallel processing, networking infrastructure, software tools, and skilled personnel [11].…”