Numerical Linear Algebra on High-Performance Computers

Numerical Linear Algebra on High-Performance Computers PDF Author: Jack J. Dongarra
Publisher: SIAM
ISBN: 0898714281
Category : Computers
Languages : en
Pages : 353

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Book Description
Provides a rapid introduction to the world of vector and parallel processing for these linear algebra applications.

Numerical Linear Algebra on High-Performance Computers

Numerical Linear Algebra on High-Performance Computers PDF Author: Jack J. Dongarra
Publisher: SIAM
ISBN: 0898714281
Category : Computers
Languages : en
Pages : 353

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Book Description
Provides a rapid introduction to the world of vector and parallel processing for these linear algebra applications.

Solving Linear Systems on Vector and Shared Memory Computers

Solving Linear Systems on Vector and Shared Memory Computers PDF Author: J. J. Dongarra
Publisher: Society for Industrial and Applied Mathematics (SIAM)
ISBN:
Category : Computers
Languages : en
Pages : 274

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Book Description
Mathematics of Computing -- Parallelism.

Introduction to High Performance Scientific Computing

Introduction to High Performance Scientific Computing PDF Author: Victor Eijkhout
Publisher: Lulu.com
ISBN: 1257992546
Category : Computers
Languages : en
Pages : 536

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Book Description
This is a textbook that teaches the bridging topics between numerical analysis, parallel computing, code performance, large scale applications.

The Art of High Performance Computing for Computational Science, Vol. 1

The Art of High Performance Computing for Computational Science, Vol. 1 PDF Author: Masaaki Geshi
Publisher: Springer
ISBN: 9811361940
Category : Computers
Languages : en
Pages : 219

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Book Description
This book provides basic and practical techniques of parallel computing and related methods of numerical analysis for researchers who conduct numerical calculation and simulation. Although the techniques provided in this book are field-independent, these methods can be used in fields such as physics, chemistry, biology, earth sciences, space science, meteorology, disaster prevention, and manufacturing. In particular, those who develop software code in these areas will find this book useful. The contents are suitable for graduate students and researchers in computational science rather than novices at programming or informed experts in computer science. Starting with an introduction to the recent trends in computer architecture and parallel processing, Chapter 1 explains the basic knowledge of speedup programs with simple examples of numerical computing. Chapters 2 – 4 detail the basics of parallel programming, the message passing interface (MPI), and OpenMP and discuss hybrid parallelization techniques. Showing an actual example of adaptation, Chapter 5 gives an overview of performance tuning and communication optimizations. To deal with dense matrix calculations, Chapter 6 details the basics and practice of linear algebra calculation libraries BLAS and LAPACK, including some examples that can be easily reproduced by readers using free software. Focusing on sparse matrix calculations, Chapter 7 explains high performance algorithms for numerical linear algebra. Chapter 8 introduces the fast Fourier transform in large-scale systems from the basics. Chapter 9 explains optimization and related topics such as debug methods and version control systems. Chapter 10 discusses techniques for increasing computation accuracy as an essential topic in numerical calculation. This is the first of the two volumes that grew out of a series of lectures in the K computer project in Japan. The second volume will focus on advanced techniques and examples of applications in materials science.

Parallel Algorithms for Numerical Linear Algebra

Parallel Algorithms for Numerical Linear Algebra PDF Author: H. van der Vorst
Publisher: Elsevier
ISBN: 1483295737
Category : Computers
Languages : en
Pages : 341

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Book Description
This is the first in a new series of books presenting research results and developments concerning the theory and applications of parallel computers, including vector, pipeline, array, fifth/future generation computers, and neural computers.All aspects of high-speed computing fall within the scope of the series, e.g. algorithm design, applications, software engineering, networking, taxonomy, models and architectural trends, performance, peripheral devices.Papers in Volume One cover the main streams of parallel linear algebra: systolic array algorithms, message-passing systems, algorithms for parallel shared-memory systems, and the design of fast algorithms and implementations for vector supercomputers.

High Performance Computing for Computational Science -- VECPAR 2010

High Performance Computing for Computational Science -- VECPAR 2010 PDF Author: José M. Laginha M. Palma
Publisher: Springer Science & Business Media
ISBN: 3642193277
Category : Computers
Languages : en
Pages : 483

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Book Description
This book constitutes the thoroughly refereed post-conference proceedings of the 9th International Conference on High Performance Computing for Computational Science, VECPAR 2010, held in Berkeley, CA, USA, in June 2010. The 34 revised full papers presented together with five invited contributions were carefully selected during two rounds of reviewing and revision. The papers are organized in topical sections on linear algebra and solvers on emerging architectures, large-scale simulations, parallel and distributed computing, numerical algorithms.

High-Performance Scientific Computing

High-Performance Scientific Computing PDF Author: Michael W. Berry
Publisher: Springer Science & Business Media
ISBN: 1447124375
Category : Computers
Languages : en
Pages : 351

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Book Description
This book presents the state of the art in parallel numerical algorithms, applications, architectures, and system software. The book examines various solutions for issues of concurrency, scale, energy efficiency, and programmability, which are discussed in the context of a diverse range of applications. Features: includes contributions from an international selection of world-class authorities; examines parallel algorithm-architecture interaction through issues of computational capacity-based codesign and automatic restructuring of programs using compilation techniques; reviews emerging applications of numerical methods in information retrieval and data mining; discusses the latest issues in dense and sparse matrix computations for modern high-performance systems, multicores, manycores and GPUs, and several perspectives on the Spike family of algorithms for solving linear systems; presents outstanding challenges and developing technologies, and puts these in their historical context.

Numerical Linear Algebra

Numerical Linear Algebra PDF Author: Frederic Magoules
Publisher: ISTE Press - Elsevier
ISBN: 9781785482441
Category : Mathematics
Languages : en
Pages : 0

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Book Description
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. Presents step-by-step patterns for parallel programming on GPU Helps to implement efficient linear algebra operations on GPU Helps to implement efficient iterative methods on GPU Proposes new techniques to speed-up algorithms through auto-tuning on GPU Proposes new preconditioning techniques on GPU Proposed new approach to measure and to predict energy consumption of a scientific application on GPU

Parallel Algorithms for Matrix Computations

Parallel Algorithms for Matrix Computations PDF Author: K. Gallivan
Publisher: SIAM
ISBN: 9781611971705
Category : Mathematics
Languages : en
Pages : 207

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Book Description
Describes a selection of important parallel algorithms for matrix computations. Reviews the current status and provides an overall perspective of parallel algorithms for solving problems arising in the major areas of numerical linear algebra, including (1) direct solution of dense, structured, or sparse linear systems, (2) dense or structured least squares computations, (3) dense or structured eigenvaluen and singular value computations, and (4) rapid elliptic solvers. The book emphasizes computational primitives whose efficient execution on parallel and vector computers is essential to obtain high performance algorithms. Consists of two comprehensive survey papers on important parallel algorithms for solving problems arising in the major areas of numerical linear algebra--direct solution of linear systems, least squares computations, eigenvalue and singular value computations, and rapid elliptic solvers, plus an extensive up-to-date bibliography (2,000 items) on related research.

Numerical Linear Algebra and Matrix Factorizations

Numerical Linear Algebra and Matrix Factorizations PDF Author: Tom Lyche
Publisher: Springer Nature
ISBN: 3030364682
Category : Mathematics
Languages : en
Pages : 376

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Book Description
After reading this book, students should be able to analyze computational problems in linear algebra such as linear systems, least squares- and eigenvalue problems, and to develop their own algorithms for solving them. Since these problems can be large and difficult to handle, much can be gained by understanding and taking advantage of special structures. This in turn requires a good grasp of basic numerical linear algebra and matrix factorizations. Factoring a matrix into a product of simpler matrices is a crucial tool in numerical linear algebra, because it allows us to tackle complex problems by solving a sequence of easier ones. The main characteristics of this book are as follows: It is self-contained, only assuming that readers have completed first-year calculus and an introductory course on linear algebra, and that they have some experience with solving mathematical problems on a computer. The book provides detailed proofs of virtually all results. Further, its respective parts can be used independently, making it suitable for self-study. The book consists of 15 chapters, divided into five thematically oriented parts. The chapters are designed for a one-week-per-chapter, one-semester course. To facilitate self-study, an introductory chapter includes a brief review of linear algebra.