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Mathematics of Computing -- Parallelism.
Mathematics of Computing -- Parallelism.
A complete source of information on almost all aspects of parallel computing from introduction, to architectures, to programming paradigms, to algorithms, to programming standards. It covers traditional Computer Science algorithms, scientific computing algorithms and data intensive algorithms.
MIMD supercomputers, software, and issues Parallel Supercomputing in MIMD Architectures is devoted to supercomputing on a wide variety of Multiple-Instruction-Multiple-Data (MIMD)-class parallel machines. The book describes architectural concepts, commercial and research hardware implementations, major programming concepts, algorithmic methods, representative applications, and benefits and drawbacks. Commercial machines described include Connection Machine 5, NCUBE, Butterfly, Meiko, Intel iPSC, iPSC/2 and iWarp, DSP3, Multimax, Sequent, and Teradata. Research machines covered include the J-Machine, PAX, Concert, and ASP. Operating systems, languages, translating sequential programs to parallel, and semiautomatic parallelizing are aspects of MIMD software addressed in Parallel Supercomputing in MIMD Architectures. MIMD issues such as scalability, partitioning, processor utilization, and heterogenous networks are discussed as well. Packed with important information and richly illustrated with diagrams and tables, Parallel Supercomputing in MIMD Architectures is an essential reference for computer professionals, program managers, applications system designers, scientists, engineers, and students in the computer sciences.
The year 2019 marked four decades of cluster computing, a history that began in 1979 when the first cluster systems using Components Off The Shelf (COTS) became operational. This achievement resulted in a rapidly growing interest in affordable parallel computing for solving compute intensive and large scale problems. It also directly lead to the founding of the Parco conference series. Starting in 1983, the International Conference on Parallel Computing, ParCo, has long been a leading venue for discussions of important developments, applications, and future trends in cluster computing, parallel computing, and high-performance computing. ParCo2019, held in Prague, Czech Republic, from 10 – 13 September 2019, was no exception. Its papers, invited talks, and specialized mini-symposia addressed cutting-edge topics in computer architectures, programming methods for specialized devices such as field programmable gate arrays (FPGAs) and graphical processing units (GPUs), innovative applications of parallel computers, approaches to reproducibility in parallel computations, and other relevant areas. This book presents the proceedings of ParCo2019, with the goal of making the many fascinating topics discussed at the meeting accessible to a broader audience. The proceedings contains 57 contributions in total, all of which have been peer-reviewed after their presentation. These papers give a wide ranging overview of the current status of research, developments, and applications in parallel computing.
Designed for undergraduate/graduate-level parallel programming courses. This nontheoretical text - which is linked to real parallel programming software - covers the techniques of parallel programming in a practical manner that enables students to write and evaluate their parallel programs
Mathematics of Computing -- Parallelism.
Foreword -- Foreword to the First Printing -- Preface -- Chapter 1 -- Introduction -- Chapter 2 -- Message Switching Layer -- Chapter 3 -- Deadlock, Livelock, and Starvation -- Chapter 4 -- Routing Algorithms -- Chapter 5 -- CollectiveCommunicationSupport -- Chapter 6 -- Fault-Tolerant Routing -- Chapter 7 -- Network Architectures -- Chapter 8 -- Messaging Layer Software -- Chapter 9 -- Performance Evaluation -- Appendix A -- Formal Definitions for Deadlock Avoidance -- Appendix B -- Acronyms -- References -- Index.
The book provides a practical guide to computational scientists and engineers to help advance their research by exploiting the superpower of supercomputers with many processors and complex networks. This book focuses on the design and analysis of basic parallel algorithms, the key components for composing larger packages for a wide range of applications.
In modern computer science, there exists no truly sequential computing system; and most advanced programming is parallel programming. This is particularly evident in modern application domains like scientific computation, data science, machine intelligence, etc. This lucid introductory textbook will be invaluable to students of computer science and technology, acting as a self-contained primer to parallel programming. It takes the reader from introduction to expertise, addressing a broad gamut of issues. It covers different parallel programming styles, describes parallel architecture, includes parallel programming frameworks and techniques, presents algorithmic and analysis techniques and discusses parallel design and performance issues. With its broad coverage, the book can be useful in a wide range of courses; and can also prove useful as a ready reckoner for professionals in the field.