β Scribed by T. L. Freeman, C. Phillips
No coin nor oath required. For personal study only.
With the increasing use of more powerful multiprocessor computer systems comes the need to develop parallel implementations of numerical methods which were originally developed for use with uniprocessors. Focusing on shared and local memory MIMD parallel computer systems, this volume is designed to help applications programmers make the not-so-straightforward transition from a serial to a parallel environment. It covers both synchronization and message-passing paradigms; discusses code development using parallel extensions to Fortran; emphasizes linear algebra, but covers other areas - ordinary differential equations, optimization - in detail.
π SIMILAR VOLUMES
<span>An introductory textbook for students of computer science. The book looks at the art of changing efficient algorithms that meets their specifications and discusses the calculational style of programing.</span>
Focusing on grid computing and asynchronism, Parallel Iterative Algorithms explores the theoretical and practical aspects of parallel numerical algorithms. Each chapter contains a theoretical discussion of the topic, an algorithmic section that fully details implementation examples and specific algo
<p>Our aim in this book is to present and enlarge upon those aspects of parallel computing that are needed by practitioners of computational science. Today alΒ most all classical sciences, such as mathematics, physics, chemistry and biology, employ numerical methods to help gain insight into nature.
This book addresses a kind of computing that has become common, in terms of physical resources, but that has been difficult to exploit properly. It's not cluster computing, where processors tend to be homogeneous and communications have low latency. It's not the "SETI at home" model, with extreme he