Parallel Algorithms in Computational Science and Engineering

Ananth Grama

ISBN 10: 3030437388 / ISBN 13: 9783030437381

Verlag: Springer Nature Switzerland AG, CH, 2021

Beschreibung

This contributed volume highlights two areas of fundamental interest in high-performance computing: core algorithms for important kernels and computationally demanding applications. The first few chapters explore algorithms, numerical techniques, and their parallel formulations for a variety of kernels that arise in applications. The rest of the volume focuses on state-of-the-art applications from diverse domains. By structuring the volume around these two areas, it presents a comprehensive view of the application landscape for high-performance computing, while also enabling readers to develop new applications using the kernels. Readers will learn how to choose the most suitable parallel algorithms for any given application, ensuring that theory and practicality are clearly connected. Applications using these techniques are illustrated in detail, including:Computational materials science and engineeringComputational cardiovascular analysisMultiscale analysis of wind turbines and turbomachineryWeather forecastingMachine learning techniquesParallel Algorithms in Computational Science and Engineering will be an ideal reference for applied mathematicians, engineers, computer scientists, and other researchers who utilize high-performance computing in their work.

Bestandsnummer des Verkäufers LU-9783030437381

Bibliografische Details

• Titel: Parallel Algorithms in Computational Science and Engineering
• Verlag: Springer Nature Switzerland AG, CH
• Erscheinungsjahr: 2021
• Sprache: Englisch
• ISBN-10: 3030437388
• ISBN-13: 9783030437381
• Einband: Paperback
• Auflage: 2020 ed.
• Zustand: New

Über diesen Titel

Inhaltsangabe

This contributed volume highlights two areas of fundamental interest in high-performance computing: core algorithms for important kernels and computationally demanding applications. The first few chapters explore algorithms, numerical techniques, and their parallel formulations for a variety of kernels that arise in applications. The rest of the volume focuses on state-of-the-art applications from diverse domains. By structuring the volume around these two areas, it presents a comprehensive view of the application landscape for high-performance computing, while also enabling readers to develop new applications using the kernels. Readers will learn how to choose the most suitable parallel algorithms for any given application, ensuring that theory and practicality are clearly connected. Applications using these techniques are illustrated in detail, including:

• Computational materials science and engineering
• Computational cardiovascular analysis
• Multiscale analysis of wind turbines and turbomachinery
• Weather forecasting
• Machine learning techniques

Parallel Algorithms in Computational Science and Engineering will be an ideal reference for applied mathematicians, engineers, computer scientists, and other researchers who utilize high-performance computing in their work.