This book examines how integrating High-Performance Computing (HPC) and Artificial Intelligence (AI) drives breakthroughs across industries. This book provides a clear understanding of how HPC enhances AI's ability to process massive amounts of data, accelerate model training, and tackle complex problems, while AI helps optimize HPC systems, making them smarter and more efficient. Together, these technologies shape innovations in healthcare, climate science, finance, and manufacturing.Through real-world examples and insights into future trends, this book showcases how organizations leverage HPC and AI's power to solve critical challenges. It also addresses the infrastructure and strategies needed to manage these systems effectively. High-Performance Computing and AI: Synergy for the Future is an essential resource for anyone interested in how these rapidly advancing technologies transform how we approach complex computing tasks and drive innovation.
Dr Muralidhar Kurni is an Associate Professor at Anantha Lakshmi Institute of Technology & Sciences in India. He is a senior member of the Institute of Electrical and Electronic Engineers and Association for Computing Machinery, author of several textbooks, and reviewer for reputed international journals and conferences.Mr Ramesh Krishnamaneni is a Solutions Architect at the International Business Machines Corporation in the USA, specializing in Hybrid Cloud, Artificial Intelligence, High-Performance Computing, and Quantum Computing. He leads enterprise cloud strategy projects for clients and optimizes workflows for efficiency.Mr Ashwin N Murthy is an Engineering Manager at Amazon in the USA, having previously worked on LinkedIn, Yahoo, and Google. He focuses on Recommendation Systems, Personalization, and High-Performance Computing, delivering high-impact solutions.Mr Souptik Sen is a Software Engineer at Snowflake in the USA, working on Distributed Data Infrastructure, High-Performance Computing, and Real-time Streaming. His experience includes LinkedIn's data analytics platform, with a background in Machine Learning and Federated Learning research from Carnegie Mellon University, USA.
