1. High Performance Computing: Strategies and Technologies for Maximizing Computational Efficiency in Scientific Research, Engineering, and Data-Driven Industries
Written by Sam Green, this book is a comprehensive guide that explores various strategies and technologies that can be used to maximize computational efficiency. With the emphasis on scientific research, engineering, and data-driven industries, you’ll learn how to implement and manage high-performance computing systems effectively. This book not only covers theoretical concepts but also provides practical insights and case studies that make it invaluable for professionals and researchers alike.
2. Scientific Computing with Python: High-performance scientific computing with NumPy, SciPy, and pandas, 2nd Edition
This updated edition by Claus Führer, Jan Erik Solem, and Olivier Verdier brings you into the world of scientific computing using Python. As programming languages evolve, Python stands out for its ease of use coupled with powerful libraries like NumPy, SciPy, and pandas. This book provides syntax, useful libraries, and practical examples to help you perform high-performance scientific computing efficiently. It’s a must-read for anyone wanting to harness the power of Python in data analysis and scientific research.
3. Silicon Photonics for High-Performance Computing and Beyond
Authored by a diverse team including Mahdi Nikdast, Sudeep Pasricha, Gabriela Nicolescu, Ashkan Seyedi, and Di Liang, this book delves into the role of silicon photonics in high-performance computing. As the demand for faster data transfer grows, the authors provide insights on how silicon photonics can enhance computing capabilities. This is an essential read for researchers looking to explore cutting-edge technologies that offer improvements in speed and efficiency in data processing.
4. Principles of High-Performance Processor Design: For High Performance Computing, Deep Neural Networks and Data Science
Junichiro Makino’s work provides a thorough examination of the principles behind high-performance processor design. It dives deep into modern processor architectures that are crucial for deep neural networks and data science applications. This book is perfect for engineers and technologists aiming to grasp the complexities of processor design while staying focused on real-world applications in computing and AI.
5. High-Performance Big Data Computing (Scientific and Engineering Computation)
The authors, Dhabaleswar K. Panda, Xiaoyi Lu, and Dipti Shankar, bring their collective expertise to tackle the challenges present in big data computing. This book is a goldmine of techniques and insights for efficiently handling big data workflows. With the ever-increasing volume of data generated, mastering big data solutions has never been more crucial. This resource is ideal for data scientists and analysts who want to marry high-performance computing with big data technologies.
6. Operating Systems for Supercomputers and High Performance Computing
In this essential volume by Balazs Gerofi, Yutaka Ishikawa, Rolf Riesen, and Robert W. Wisniewski, the focus is on the operating systems that drive supercomputers and high-performance computing systems. The authors dissect the operating systems that optimize performance, reliability, and scalability, crucial for enterprises leveraging large-scale computing. If you’re keen on understanding how supercomputers operate, this book is a gateway into the world of advanced computing systems.
7. High-Performance Computing Using FPGAs
Wim Vanderbauwhede and Khaled Benkrid delve into the specialized field of FPGA computing, exploring its role in high-performance computing applications. With the increase in demand for computational resources, hardware acceleration via FPGAs has become crucial. Their insightful exploration guides you through both theoretical and practical aspects, making this an indispensable read for hardware engineers and computer scientists interested in optimizing performance through advanced architectures.
8. A Practical Approach to High-Performance Computing
This book, written by Sergei Kurgalin and Sergei Borzunov, offers practical insights into high-performance computing for modern applications. The authors cover best practices and methodologies that ensure effective resource utilization. With an emphasis on real-world projects, this guide serves as both a theoretical foundation and a practical toolkit. Researchers and practitioners aiming to enhance their understanding and skills in high-performance computing will find it an invaluable resource.
9. High Performance Cluster Computing: Programming and Applications, Volume 2
Rajkumar Buyya’s classic text focuses on programming techniques for high-performance cluster computing. This second volume dives deeper into applications and programming strategies for utilizing clusters efficiently. If you are interested in exploring parallel processing and the utilization of cluster systems in scientific computing, this book is a foundational text that offers both theory and practical insights.
10. Problem-solving in High Performance Computing: A Situational Awareness Approach with Linux
Igor Ljubuncic provides a unique perspective on problem-solving in high-performance computing environments. The book explores situational awareness techniques that help anticipate and mitigate issues before they arise. With a focus on Linux systems, you’ll learn how to leverage system features to enhance computing efficiency. This book is essential for sysadmins and researchers who need to address challenges dynamically and efficiently.
