Numerical Linear Algebra

Erscheinungsjahr 2018
ISBN: 978-1-78548-244-1
Verlag: Elsevier Science

Buch, Englisch, 200 Seiten, Format (B × H): 152 mm x 229 mm

As per the constant need to solve larger and larger numerical problems, it is not possible to neglect the opportunity that comes from the close adaptation of computational algorithms and their implementations for particular features of computing devices, i.e. the characteristics and performance of available workstations and servers. In the last decade, the advances in hardware manufacturing, the decreasing cost and the spread of GPUs have attracted the attention of researchers for numerical simulations, given that for some problems, GPU-based simulations can significantly outperform the ones based on CPUs. The objective of this book is first to present how to design in a context of GPGPU numerical methods in order to obtain the highest efficiency. A second objective of this book is to propose new auto-tuning techniques to optimize access on GPU. A third objective of this book is to propose new preconditioning techniques for GPGPU. Finally, an original energy consumption model is proposed, leading to a robust and accurate energy consumption prediction model.

Zielgruppe

Our book mainly targets Engineers and Professionals working in all fields involving numerical simulation of large problems (mechanical and chemical Engineering, mechanics, fluid dynamics, acoustics, power systems, biology, etc.) and dealing with parallel systems. This book will also be of interest to Academics, Researchers and Students who wish to address scientific computing with Graphics Processing Units technology.

Autoren/Hrsg.

Magoules, Frederic

Cheik Ahamed, Abal-Kassim

Fachgebiete

• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Numerische Mathematik
• Mathematik | Informatik Mathematik Algebra Lineare und multilineare Algebra, Matrizentheorie

Inhaltsverzeichnis

1. GPU Computing2. Basics of numerical matrix analysis3. Linear Algebra Operations4. Direct Methods5. Iterative Methods6. Parallel Iterative Methods7. Parallel Preconditioning Methods8. Energy Consumption

Über Autor(innen)

Magoules, Frederic
Frederic Magoules graduated with a B.Sc. in Engineering Sciences in 1993, a M.Sc. in Applied Mathematics in 1994 and a M.Sc. in Numerical Analysis in 1995, from Universite Pierre & Marie Curie. He received his Ph.D. in Applied Mathematics from Universite Pierre Marie Curie in 2000. He then post-doc'ed and taught there for one year, as Assistant Professor of Numerical Analysis, prior to joining Universite Henri Poincare in 2000 as Assistant and then Associate Professor of Applied Mathematics and Engineering. He received his HDR (Habilitation a Diriger des Recherches) from Universite Pierre & Marie Curie in 2005. He joined Ecole Centrale des Arts et Manufactures in 2006 as Professor of Applied Mathematics (in 2015, Ecole Centrale des Arts et Manufactures merged with Supelec and became CentraleSupelec, Universite Paris-Saclay).

With backgrounds in Computational Science and Engineering, Applied Mathematics, Computer Science, and consulting experience with industry and national laboratories, Frederic Magoules works at the algorithmic interface between parallel computing and the numerical analysis of partial differential equations and algebraic differential equations. Frederic Magoules and his research group design, analyze, develop, and validate mathematical models and computational methods for the high-performance simulation of multidisciplinary scientific and engineering problems.

Author or co-author of over 150 refeered publications in Computational Science and Engineering, Applied Mathematics, and Computer Science, Frederic Magoules has authored 11 books, and edited 9 books.

Cheik Ahamed, Abal-Kassim
Abal-Kassim Cheik Ahamed received his French Baccalauréat S. (Scientific) in Mayotte, France, in 2006. In 2008, he graduated with three B.Sc. Degree at the Université de Pau et des Pays de l'Adour and Université de Cergy- Pontoise, France. He graduated with Engineer degree in the Department of HPC and Scientific Computing at the Ecole Internationale des Sciences du traitement de l'information (EISTI), France, in 2011. He also graduated with a M.Sc. degree in the Department of Science, Technology and Health at the Université de Cergy-Pontoise, France, in 2011. In 2015, he graduated with PhD degree in applied mathematics and computer science at Ecole Centrale Paris (Applied Mathematics and Systems Laboratory), Châtenay-Malabry, France. Thesis: Numerical methods for the accelerated resolution of large scale linear systems on massively parallel hybrid architectures, Univ. de Franche Comté; Mr. Che-Lun Hung, Providence Univ. His major research interests are oriented to the acceleration of numerical methods using both GPU Computing and Parallel Computing.
Currently, he is a postdoctoral fellow at CentraleSupélec, Université Paris-Saclay, France.
He is currently assistant professor at CentraleSupélec for different courses: Introduction to databases, Algorithms, Advanced Programming and software development, and diverse projects.