Smart Inventory System for Expiry Date Tracking
Volume-7 | Issue-2

AI based Identification of Students Dress Code in Schools and Universities
Volume-6 | Issue-1

Exploiting Vulnerabilities in Weak CAPTCHA Mechanisms within DVWA
Volume-7 | Issue-2

Gamification in Mobile Apps: Assessing the Effects on Customer Engagement and Loyalty in the Retail Industry
Volume-5 | Issue-4

Investigating Process Scheduling Techniques for Optimal Performance and Energy Efficiency in Operating Systems
Volume-6 | Issue-4

Classification of Remote Sensing Image Scenes Using Double Feature Extraction Hybrid Deep Learning Approach
Volume-3 | Issue-2

Review on Sanskrit Sandhi Splitting using Deep Learning Techniques
Volume-6 | Issue-2

Survey: Unconventional Categories of Chatbots that make use of Machine Learning Techniques
Volume-5 | Issue-3

Light Weight CNN based Robust Image Watermarking Scheme for Security
Volume-3 | Issue-2

Getis-Ord (Gi*) based Farmer Suicide Hotspot Detection
Volume-4 | Issue-2

AUTOMATION USING IOT IN GREENHOUSE ENVIRONMENT
Volume-1 | Issue-1

Principle of 6G Wireless Networks: Vision, Challenges and Applications
Volume-3 | Issue-4

Classification of Remote Sensing Image Scenes Using Double Feature Extraction Hybrid Deep Learning Approach
Volume-3 | Issue-2

Light Weight CNN based Robust Image Watermarking Scheme for Security
Volume-3 | Issue-2

VIRTUAL REALITY GAMING TECHNOLOGY FOR MENTAL STIMULATION AND THERAPY
Volume-1 | Issue-1

Design of Digital Image Watermarking Technique with Two Stage Vector Extraction in Transform Domain
Volume-3 | Issue-3

Analysis of Natural Language Processing in the FinTech Models of Mid-21st Century
Volume-4 | Issue-3

PROGRESS AND PRECLUSION OF KNEE OSTEOARTHRITIS: A STUDY
Volume-3 | Issue-3

Image Augmentation based on GAN deep learning approach with Textual Content Descriptors
Volume-3 | Issue-3

Comparative Analysis for Personality Prediction by Digital Footprints in Social Media
Volume-3 | Issue-2

Home / Archives / Volume-5 / Issue-4 / Article-4

Volume - 5 | Issue - 4 | december 2023

Contemporary High-Performance Computing for Big Data Applications Open Access
S. Ayyasamy   90
Pages: 375-384
Cite this article
Ayyasamy, S.. "Contemporary High-Performance Computing for Big Data Applications." Journal of Information Technology and Digital World 5, no. 4 (2023): 375-384
Published
22 January, 2024
Abstract

High-performance computing (HPC) involves leveraging parallel data processing to enhance computer performance and handle difficult tasks. HPC meets these aims by pooling computing capacity, enabling efficient, reliable, and prompt execution of even complex programs according to user demands and expectations. The rapid growth of HPDA in many sectors has led to the extension of the HPC market into new territory. HPC as well as Big Data systems differ not just in terms of technology but also in ecosystems. Extensive research in this sector has led to the emergence of various Big Data analytics models in recent years. As Big Data analytics spreads across several fields, new challenges about the usefulness of analytical paradigms also emerge. This article discusses the key analytical models, as well as the difficulties and challenges associated with high-performance data analytics. This research work aims to identify the factors influencing the integration of HPC with big data, including present and future trends. The study also proposes an architecture for big data with HPC convergence based on design principles.

Keywords

High-Performance Data Analytics Big Data HPC Convergence Efficiently Reliably

×

Currently, subscription is the only source of revenue. The subscription resource covers the operating expenses such as web presence, online version, pre-press preparations, and staff wages.

To access the full PDF, please complete the payment process.

Subscription Details

Category Fee
Article Access Charge
15 USD
Open Access Fee Nil
Annual Subscription Fee
200 USD
After payment,
please send an email to irojournals.contact@gmail.com / journals@iroglobal.com requesting article access.
Subscription form: click here