Parallel and High-Performance Computing in Artificial Intelligence [Hardcover]

1. Introduction to High Performance Computing Architectures ?2. High Performance Computing: Use Cases, APIs and Applications 3. Parallelization Techniques 4. High Performance Computing for Machine Learning 5. Implementation of Parallel Computing with Artificial Intelligence in Big Data Analytics 6. D-UNet: Deep Learning Architecture for Colon Polyp Segmentation in Endoscopic Images 7. Early-Stage Plant Disease Detection using YOLOv8 8. Landslide Detection Using Custom Deep Convolutional Neural Network 9. GPU in Big Data: An Acceleration Technique 10. Use of NLP Techniques and High-Performance Computing for Automated Knowledge-based Ontology Construction of Saffron Crop 11. Implementing High-performance Computing with Artificial Intelligence in Healthcare Systems 12. BLMP2CE: Design of a Dual-Bioinspired Low-Complexity Data Mining Engine with Parallel Processing for Automatic Cluster Analysis via Ensemble Learning Operations 13. Deep Learning and Edge Computing with HPC 14. Usage of IoT, High Performance Computing, Machine and Deep Learning in a Human Activity Recognition (HAR) System: Challenges and Opportunities 15. Artificial Intelligence in Industry: An Approach to Automation 16. Usage of IoT, Artificial Intelligence and Machine Learning with HPC: Issues, Challenges, and a Case Study 17. Advancing High-Performance Computing for AI in the Era of Large-Scale Models: A Research Roadmap

The book explores high-performance architectures for data-intensive applications, as well as efficient analytical strategies, to speed up data processing in applications in automation, machine learning, deep learning, bioinformatics, natural language processing, and vision intelligence.

Dr. M. M. Raghuwanshi is the Dean of Engineering at?S.B.Jain Institute of Technology Management and Research, Nagpur, India.

Dr. Pradnya Borkar is an Associate Professor at the Department of Computer Sl-