Overview
- Describes advanced and practical techniques for performance optimization in high parallelization
- Features applications around material science
- Includes many exercises to help readers gain a better understanding
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About this book
Chapter 1 outlines supercomputers and includes a brief explanation of the history of hardware. Chapter 2 presents procedures for performance evaluation, while Chapter 3 describes the set of tuned applications in materials science, nanoscience and nanotechnology, earth science and engineering on the K computer. Introducing the order-N method, based on density functional theory (DFT) calculation, Chapter 4 explains how to extend the applicability of DFT to large-scale systems by reducing the computational complexity. Chapter 5 discusses acceleration and parallelization in classical molecular dynamics simulations, and lastly, Chapter 6 explains techniques for large-scale quantum chemical calculations, including the order-N method.
This is the second of the two volumes that grew out of a series of lectures in the K computer project in Japan. The first volume addresses more basic techniques, and this second volume focuses on advanced and concrete techniques.
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Table of contents (6 chapters)
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Bibliographic Information
Book Title: The Art of High Performance Computing for Computational Science, Vol. 2
Book Subtitle: Advanced Techniques and Examples for Materials Science
Editors: Masaaki Geshi
DOI: https://doi.org/10.1007/978-981-13-9802-5
Publisher: Springer Singapore
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Singapore Pte Ltd. 2019
Hardcover ISBN: 978-981-13-9801-8Published: 15 October 2019
Softcover ISBN: 978-981-13-9804-9Published: 15 October 2020
eBook ISBN: 978-981-13-9802-5Published: 01 October 2019
Edition Number: 1
Number of Pages: IX, 206
Number of Illustrations: 92 b/w illustrations, 7 illustrations in colour
Topics: Programming Techniques, Computer Applications in Chemistry, Simulation and Modeling