Autorentext
Oscar Diez has a dual role as a professor and researcher, combining academic expertise in teaching HPC courses at IE University with applied research experience at the European Commission. With over a decade of experience, he has guided students and professionals through complex computational systems, emphasizing both theory and real-world applications.

Klappentext

High-Performance Computing: Applications and Frontiers serves as an essential, up-to-date guide for those seeking to master the rapidly evolving field of HPC. Building on foundational concepts, this volume delves into specialized tools and emerging technologies shaping modern research and industry, such as parallel and distributed systems, GPU programming, quantum computing, and cloud-based solutions. Designed for advanced students, researchers, and professionals, it prepares readers to tackle real-world challenges by combining theoretical insights with practical expertise, offering a clear roadmap for navigating both established and cutting-edge HPC landscapes.

The book further distinguishes itself by exploring domain-specific applications, machine learning, and the future trajectory of high-performance computing. Key topics include containerization, AI-powered HPC, hybrid and multi-cloud strategies, as well as recent advancements in GPU and quantum technologies. With its blend of theory and hands-on examples, this book is a versatile reference that meets the growing demand for a comprehensive resource in today's data-driven world.

Inhalt

Part One: Introduction to Advanced High Performance Computing

1. Introduction to Advanced High Performance Computing
2. HPC in Health & Neurosciences
3. Computational Fluid Dynamics, MPI & OpenMP Code Integration
4. Optimizing Code for HPC Architectures

5. Advanced MPI Techniques

   Part Two: Advanced Tools and Libraries

6. Profiling, Debugging, and Performance Analysis Tools

7. Using High-Performance Libraries

   Part Three: Applications and Emerging Trends

8. Molecular Systems & Material Sciences
9. Climate and Terrestrial Systems Modeling

10. HPC in Finance and Economics

    Part Four: Machine Learning and Big Data

11. Fundamentals of Distributed Machine Learning
12. Deep Learning at Scale

13. Exploring Patterns in Hybrid Computing

    Part Five: Future of High Performance Computing

14. The Emergence of Neuromorphic Computing
15. Quantum Computing Fundamentals and Applications
16. Advanced Computing Toward the Post-Exascale Era
17. Digital Twins in HPC
18. Reflections and Future Horizons in HPC