Parallel Algorithms in Computational Science and Engineering: Modeling and Simulation in Science, Engineering and Technology
Editat de Ananth Grama, Ahmed H. Samehen Limba Engleză Paperback – 7 iul 2021
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.
Toate formatele și edițiile | Preț | Express |
---|---|---|
Paperback (1) | 771.67 lei 6-8 săpt. | |
Springer International Publishing – 7 iul 2021 | 771.67 lei 6-8 săpt. | |
Hardback (1) | 777.56 lei 6-8 săpt. | |
Springer International Publishing – 7 iul 2020 | 777.56 lei 6-8 săpt. |
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Specificații
ISBN-13: 9783030437381
ISBN-10: 3030437388
Pagini: 417
Ilustrații: XII, 417 p. 189 illus., 159 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.6 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Birkhäuser
Seria Modeling and Simulation in Science, Engineering and Technology
Locul publicării:Cham, Switzerland
ISBN-10: 3030437388
Pagini: 417
Ilustrații: XII, 417 p. 189 illus., 159 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.6 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Birkhäuser
Seria Modeling and Simulation in Science, Engineering and Technology
Locul publicării:Cham, Switzerland
Cuprins
State-of-the-Art Sparse Direct Solvers.- The Effect of Various Sparsity Structures on Parallelism and Algorithms to Reveal Those Structures.- Structure-Exploiting Interior Point Methods.- Parallel Hybrid Sparse Linear System Solvers.- Computational Material Science and Engineering.- Computational Cardiovascular Analysis with the Variational Multiscale Methods and Isogeometric Discretization.- ALE and Space-Time Variational Multiscale Isogeometric Analysis of Wind Turbines and Turbomachinery.- Variational Multiscale Flow Analysis in Aerospace, Energy, and Transportation Technologies.- Multiscale Crowd Dynamics Modeling and Safety Problems Towards Parallel Computing.- HPC for Weather Forecasting.- A Simple Study of Pleasing Parallelism on Multicore Computers.- Parallel Fast Time-Domain Integral-Equation Methods for Transient Electromagnetism Analysis.- Parallel Optimization Techniques for Machine Learning.
Textul de pe ultima copertă
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.
Caracteristici
Presents core algorithms and compute kernels alongside high-performance science and engineering applications Describes efficient solutions to a wide variety of computationally demanding applications that are ordinarily time-consuming Provides a state-of-the-art reference for researchers and practitioners