Parallel Computing Of Partial Differential Equations Based Applications

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Parallel Computing Of Partial Differential Equations Based Applications
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Author : Siham Tabik
language : en
Publisher: Universidad Almería
Release Date : 2008-05-12
Parallel Computing Of Partial Differential Equations Based Applications written by Siham Tabik and has been published by Universidad Almería this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-05-12 with Computers categories.
La mayoría de los modelos matemáticos empleados para describir fenómenos físicos reales en ciencia e ingeniería están gobernados por ecuaciones parciales diferenciales no-lineales dependientes del tiempo PDEs (Partial Differential Equations). Generalmente, la solución de dichas ecuaciones requiere una discretización usando métodos como los de diferencias finitas, elementos finitos, volúmenes finitos o métodos de los momentos. El análisis del comportamiento de los modelos matemáticos basados en PDEs para sistemas reales es muy costoso desde el punto de vista computacional, y los costes pueden ser tan enormes que su implementación paralela se convierte en la única solución. Adicionalmente, la reciente disponibilidad en el mercado de la computación de alta prestación de arquitecturas de nodos de memoria compartida conectados entre si ha incrementado la importancia de diseñar códigos eficientes apropiados para explotar estas plataformas. Dichas plataformas soportan tres paradigmas de comunicación: 1) el paradigma de memoria compartida, 2) el paradigma de paso de mensajes, y 3) el paradigma híbrido, que consiste en la combinación de los dos paradigmas anteriores. Cada uno de los paradigmas ofrece ventajas y desventajas en función de las características de la plataforma paralela y del problema. Esta tesis analiza la solución numérica de tres aplicaciones científicas en física y en el campo del tratamiento de imágenes gobernadas por ecuaciones diferenciales, tridimensionales, independientes del tiempo. En particular, la primera aplicación es un método dependiente del tiempo que resuelve la ecuación integral del campo eléctrico para el análisis de la interacción entre hilos finos conductores y ondas electromagnéticas; la segunda aplicación es un método de diferencias finitas que resuelve la ecuación de difusión altamente acoplada con un sistemas masivo para filtrar imágenes 3D en biología celular y biomedicina; y la tercera aplicación es un conjunto de cuatro ecuaciones de reacción-difusión para simular el fenómeno de bursting en tres dimensiones, un fenómeno común en numerosos sistemas naturales. Para ello, se analizan las características de los paradigmas de comunicación conforme se aplican para obtener las soluciones numéricas de las tres aplicaciones descritas anteriormente. Los resultados indican que es posible establecer una abstracción de los modelos de comunicación que permite un desarrollo eficiente, simple y robusto de los modelos de comunicación que son independientes de las arquitecturas de las diferentes plataformas usadas.
Parallel Computing Fundamentals Applications And New Directions
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Author : E.H. D'Hollander
language : en
Publisher: Elsevier
Release Date : 1998-07-22
Parallel Computing Fundamentals Applications And New Directions written by E.H. D'Hollander and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-07-22 with Computers categories.
This volume gives an overview of the state-of-the-art with respect to the development of all types of parallel computers and their application to a wide range of problem areas. The international conference on parallel computing ParCo97 (Parallel Computing 97) was held in Bonn, Germany from 19 to 22 September 1997. The first conference in this biannual series was held in 1983 in Berlin. Further conferences were held in Leiden (The Netherlands), London (UK), Grenoble (France) and Gent (Belgium). From the outset the aim with the ParCo (Parallel Computing) conferences was to promote the application of parallel computers to solve real life problems. In the case of ParCo97 a new milestone was reached in that more than half of the papers and posters presented were concerned with application aspects. This fact reflects the coming of age of parallel computing. Some 200 papers were submitted to the Program Committee by authors from all over the world. The final programme consisted of four invited papers, 71 contributed scientific/industrial papers and 45 posters. In addition a panel discussion on Parallel Computing and the Evolution of Cyberspace was held. During and after the conference all final contributions were refereed. Only those papers and posters accepted during this final screening process are included in this volume. The practical emphasis of the conference was accentuated by an industrial exhibition where companies demonstrated the newest developments in parallel processing equipment and software. Speakers from participating companies presented papers in industrial sessions in which new developments in parallel computing were reported.
Petsc For Partial Differential Equations Numerical Solutions In C And Python
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Author : Ed Bueler
language : en
Publisher: SIAM
Release Date : 2020-10-22
Petsc For Partial Differential Equations Numerical Solutions In C And Python written by Ed Bueler and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-22 with Mathematics categories.
The Portable, Extensible Toolkit for Scientific Computation (PETSc) is an open-source library of advanced data structures and methods for solving linear and nonlinear equations and for managing discretizations. This book uses these modern numerical tools to demonstrate how to solve nonlinear partial differential equations (PDEs) in parallel. It starts from key mathematical concepts, such as Krylov space methods, preconditioning, multigrid, and Newton’s method. In PETSc these components are composed at run time into fast solvers. Discretizations are introduced from the beginning, with an emphasis on finite difference and finite element methodologies. The example C programs of the first 12 chapters, listed on the inside front cover, solve (mostly) elliptic and parabolic PDE problems. Discretization leads to large, sparse, and generally nonlinear systems of algebraic equations. For such problems, mathematical solver concepts are explained and illustrated through the examples, with sufficient context to speed further development. PETSc for Partial Differential Equations addresses both discretizations and fast solvers for PDEs, emphasizing practice more than theory. Well-structured examples lead to run-time choices that result in high solver performance and parallel scalability. The last two chapters build on the reader’s understanding of fast solver concepts when applying the Firedrake Python finite element solver library. This textbook, the first to cover PETSc programming for nonlinear PDEs, provides an on-ramp for graduate students and researchers to a major area of high-performance computing for science and engineering. It is suitable as a supplement for courses in scientific computing or numerical methods for differential equations.
Solving Partial Differential Equations On Parallel Computers
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Author : Jian Ping Zhu
language : en
Publisher: World Scientific
Release Date : 1994-02-24
Solving Partial Differential Equations On Parallel Computers written by Jian Ping Zhu and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994-02-24 with Computers categories.
This is an introductory book on supercomputer applications written by a researcher who is working on solving scientific and engineering application problems on parallel computers. The book is intended to quickly bring researchers and graduate students working on numerical solutions of partial differential equations with various applications into the area of parallel processing.The book starts from the basic concepts of parallel processing, like speedup, efficiency and different parallel architectures, then introduces the most frequently used algorithms for solving PDEs on parallel computers, with practical examples. Finally, it discusses more advanced topics, including different scalability metrics, parallel time stepping algorithms and new architectures and heterogeneous computing networks which have emerged in the last few years of high performance computing. Hundreds of references are also included in the book to direct interested readers to more detailed and in-depth discussions of specific topics.
Numerical Solution Of Partial Differential Equations On Parallel Computers
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Author : Are Magnus Bruaset
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-03-05
Numerical Solution Of Partial Differential Equations On Parallel Computers written by Are Magnus Bruaset and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-03-05 with Mathematics categories.
Since the dawn of computing, the quest for a better understanding of Nature has been a driving force for technological development. Groundbreaking achievements by great scientists have paved the way from the abacus to the supercomputing power of today. When trying to replicate Nature in the computer’s silicon test tube, there is need for precise and computable process descriptions. The scienti?c ?elds of Ma- ematics and Physics provide a powerful vehicle for such descriptions in terms of Partial Differential Equations (PDEs). Formulated as such equations, physical laws can become subject to computational and analytical studies. In the computational setting, the equations can be discreti ed for ef?cient solution on a computer, leading to valuable tools for simulation of natural and man-made processes. Numerical so- tion of PDE-based mathematical models has been an important research topic over centuries, and will remain so for centuries to come. In the context of computer-based simulations, the quality of the computed results is directly connected to the model’s complexity and the number of data points used for the computations. Therefore, computational scientists tend to ?ll even the largest and most powerful computers they can get access to, either by increasing the si e of the data sets, or by introducing new model terms that make the simulations more realistic, or a combination of both. Today, many important simulation problems can not be solved by one single computer, but calls for parallel computing.
Proceedings Of The Seventh Siam Conference On Parallel Processing For Scientific Computing
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Author : David H. Bailey
language : en
Publisher: SIAM
Release Date : 1995-01-01
Proceedings Of The Seventh Siam Conference On Parallel Processing For Scientific Computing written by David H. Bailey and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-01-01 with Science categories.
Proceedings -- Parallel Computing.
Introductory Guide To Partial Differential Equations
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Author : Sameer Kulkarni
language : en
Publisher: Educohack Press
Release Date : 2025-02-20
Introductory Guide To Partial Differential Equations written by Sameer Kulkarni and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Science categories.
"Introductory Guide to Partial Differential Equations" is an accessible and comprehensive introduction to Partial Differential Equations (PDEs) for undergraduate students. We provide a solid foundation in the theory and applications of PDEs, catering to students in mathematics, engineering, physics, and related fields. We present fundamental concepts of PDEs in a clear and engaging manner, emphasizing both theoretical understanding and practical problem-solving skills. Starting with basic concepts such as classification of PDEs, boundary and initial conditions, and solution techniques, we gradually progress to advanced topics including Fourier series, separation of variables, and the method of characteristics. Real-world applications of PDEs are woven throughout the book, demonstrating the relevance of this mathematical theory in fields such as heat conduction, fluid dynamics, quantum mechanics, and finance. Numerous examples, exercises, and applications are included to reinforce learning and encourage active engagement with the material. Whether you're preparing for further study in mathematics or seeking to apply PDEs in your chosen field, this book equips you with the knowledge and skills necessary to tackle a wide range of problems involving partial differential equations. We hope this text will inspire curiosity and confidence in approaching the rich and diverse world of PDEs.
Recent Advances In Numerical Methods For Partial Differential Equations And Applications
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Author : Xiaobing Feng
language : en
Publisher: American Mathematical Soc.
Release Date : 2002
Recent Advances In Numerical Methods For Partial Differential Equations And Applications written by Xiaobing Feng and has been published by American Mathematical Soc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Mathematics categories.
This book is derived from lectures presented at the 2001 John H. Barrett Memorial Lectures at the University of Tennessee, Knoxville. The topic was computational mathematics, focusing on parallel numerical algorithms for partial differential equations, their implementation and applications in fluid mechanics and material science. Compiled here are articles from six of nine speakers. Each of them is a leading researcher in the field of computational mathematics and its applications. A vast area that has been coming into its own over the past 15 years, computational mathematics has experienced major developments in both algorithmic advances and applications to other fields. These developments have had profound implications in mathematics, science, engineering and industry. With the aid of powerful high performance computers, numerical simulation of physical phenomena is the only feasible method for analyzing many types of important phenomena, joining experimentation and theoretical analysis as the third method of scientific investigation. The three aspects: applications, theory, and computer implementation comprise a comprehensive overview of the topic. Leading lecturers were Mary Wheeler on applications, Jinchao Xu on theory, and David Keyes on computer implementation. Following the tradition of the Barrett Lectures, these in-depth articles and expository discussions make this book a useful reference for graduate students as well as the many groups of researchers working in advanced computations, including engineering and computer scientists.
Supercomputation In Nonlinear And Disordered Systems Algorithms Applications And Architectures
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Author : Luis Vazquez
language : en
Publisher: World Scientific
Release Date : 1997-10-22
Supercomputation In Nonlinear And Disordered Systems Algorithms Applications And Architectures written by Luis Vazquez and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-10-22 with categories.
This proceedings volume is devoted to simulation and parallel computing related to nonlinear problems. One of its fundamental aims is the study of how the efforts of computer and computational scientists may be combined to develop most modern simulation environments of nonlinear systems.
Parallel Processing For Scientific Computing
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Author : Michael A. Heroux
language : en
Publisher: SIAM
Release Date : 2006-01-01
Parallel Processing For Scientific Computing written by Michael A. Heroux and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-01-01 with Computers categories.
Scientific computing has often been called the third approach to scientific discovery, emerging as a peer to experimentation and theory. Historically, the synergy between experimentation and theory has been well understood: experiments give insight into possible theories, theories inspire experiments, experiments reinforce or invalidate theories, and so on. As scientific computing has evolved to produce results that meet or exceed the quality of experimental and theoretical results, it has become indispensable.Parallel processing has been an enabling technology in scientific computing for more than 20 years. This book is the first in-depth discussion of parallel computing in 10 years; it reflects the mix of topics that mathematicians, computer scientists, and computational scientists focus on to make parallel processing effective for scientific problems. Presently, the impact of parallel processing on scientific computing varies greatly across disciplines, but it plays a vital role in most problem domains and is absolutely essential in many of them. Parallel Processing for Scientific Computing is divided into four parts: The first concerns performance modeling, analysis, and optimization; the second focuses on parallel algorithms and software for an array of problems common to many modeling and simulation applications; the third emphasizes tools and environments that can ease and enhance the process of application development; and the fourth provides a sampling of applications that require parallel computing for scaling to solve larger and realistic models that can advance science and engineering. This edited volume serves as an up-to-date reference for researchers and application developers on the state of the art in scientific computing. It also serves as an excellent overview and introduction, especially for graduate and senior-level undergraduate students interested in computational modeling and simulation and related computer science and applied mathematics aspects.Contents List of Figures; List of Tables; Preface; Chapter 1: Frontiers of Scientific Computing: An Overview; Part I: Performance Modeling, Analysis and Optimization. Chapter 2: Performance Analysis: From Art to Science; Chapter 3: Approaches to Architecture-Aware Parallel Scientific Computation; Chapter 4: Achieving High Performance on the BlueGene/L Supercomputer; Chapter 5: Performance Evaluation and Modeling of Ultra-Scale Systems; Part II: Parallel Algorithms and Enabling Technologies. Chapter 6: Partitioning and Load Balancing; Chapter 7: Combinatorial Parallel and Scientific Computing; Chapter 8: Parallel Adaptive Mesh Refinement; Chapter 9: Parallel Sparse Solvers, Preconditioners, and Their Applications; Chapter 10: A Survey of Parallelization Techniques for Multigrid Solvers; Chapter 11: Fault Tolerance in Large-Scale Scientific Computing; Part III: Tools and Frameworks for Parallel Applications. Chapter 12: Parallel Tools and Environments: A Survey; Chapter 13: Parallel Linear Algebra Software; Chapter 14: High-Performance Component Software Systems; Chapter 15: Integrating Component-Based Scientific Computing Software; Part IV: Applications of Parallel Computing. Chapter 16: Parallel Algorithms for PDE-Constrained Optimization; Chapter 17: Massively Parallel Mixed-Integer Programming; Chapter 18: Parallel Methods and Software for Multicomponent Simulations; Chapter 19: Parallel Computational Biology; Chapter 20: Opportunities and Challenges for Parallel Computing in Science and Engineering; Index.