Author : Richard M. Fujimoto
Publisher : Wiley-Interscience
Page : 324 pages
File Size : 46,2 MB
Release : 2000-01-03
Category : Computers
ISBN :
From the preface, page xv: [...] My goal in writing Parallel and Distributed Simulation Systems, is to give an in-depth treatment of technical issues concerning the execution of discrete event simulation programs on computing platforms composed of many processores interconnected through a network"
Author : Fayez Gebali
Publisher : John Wiley & Sons
Page : 372 pages
File Size : 20,65 MB
Release : 2011-03-29
Category : Computers
ISBN : 0470934638
There is a software gap between the hardware potential and the performance that can be attained using today's software parallel program development tools. The tools need manual intervention by the programmer to parallelize the code. Programming a parallel computer requires closely studying the target algorithm or application, more so than in the traditional sequential programming we have all learned. The programmer must be aware of the communication and data dependencies of the algorithm or application. This book provides the techniques to explore the possible ways to program a parallel computer for a given application.
Author : Wan Fokkink
Publisher : MIT Press
Page : 242 pages
File Size : 39,63 MB
Release : 2013-12-06
Category : Computers
ISBN : 0262026775
A comprehensive guide to distributed algorithms that emphasizes examples and exercises rather than mathematical argumentation.
Author : Dimitri Bertsekas
Publisher : Athena Scientific
Page : 832 pages
File Size : 37,3 MB
Release : 2015-03-01
Category : Mathematics
ISBN : 1886529159
This highly acclaimed work, first published by Prentice Hall in 1989, is a comprehensive and theoretically sound treatment of parallel and distributed numerical methods. It focuses on algorithms that are naturally suited for massive parallelization, and it explores the fundamental convergence, rate of convergence, communication, and synchronization issues associated with such algorithms. This is an extensive book, which aside from its focus on parallel and distributed algorithms, contains a wealth of material on a broad variety of computation and optimization topics. It is an excellent supplement to several of our other books, including Convex Optimization Algorithms (Athena Scientific, 2015), Nonlinear Programming (Athena Scientific, 1999), Dynamic Programming and Optimal Control (Athena Scientific, 2012), Neuro-Dynamic Programming (Athena Scientific, 1996), and Network Optimization (Athena Scientific, 1998). The on-line edition of the book contains a 95-page solutions manual.
Author : Alireza Poshtkohi
Publisher : CRC Press
Page : 426 pages
File Size : 11,3 MB
Release : 2023-04-13
Category : Computers
ISBN : 1000860132
Parallel and distributed systems (PADS) have evolved from the early days of computational science and supercomputers to a wide range of novel computing paradigms, each of which is exploited to tackle specific problems or application needs, including distributed systems, parallel computing, and cluster computing, generally called high-performance computing (HPC). Grid, Cloud, and Fog computing patterns are the most important of these PADS paradigms, which share common concepts in practice. Many-core architectures, multi-core cluster-based supercomputers, and Cloud Computing paradigms in this era of exascale computers have tremendously influenced the way computing is applied in science and academia (e.g., scientific computing and large-scale simulations). Implementing Parallel and Distributed Systems presents a PADS infrastructure known as Parvicursor that can facilitate the construction of such scalable and high-performance parallel distributed systems as HPC, Grid, and Cloud Computing. This book covers parallel programming models, techniques, tools, development frameworks, and advanced concepts of parallel computer systems used in the construction of distributed and HPC systems. It specifies a roadmap for developing high-performance client-server applications for distributed environments and supplies step-by-step procedures for constructing a native and object-oriented C++ platform. FEATURES: Hardware and software perspectives on parallelism Parallel programming many-core processors, computer networks and storage systems Parvicursor.NET Framework: a partial, native, and cross-platform C++ implementation of the .NET Framework xThread: a distributed thread programming model by combining thread-level parallelism and distributed memory programming models xDFS: a native cross-platform framework for efficient file transfer Parallel programming for HPC systems and supercomputers using message passing interface (MPI) Focusing on data transmission speed that exploits the computing power of multicore processors and cutting-edge system-on-chip (SoC) architectures, it explains how to implement an energy-efficient infrastructure and examines distributing threads amongst Cloud nodes. Taking a solid approach to design and implementation, this book is a complete reference for designing, implementing, and deploying these very complicated systems.
Author : Cameron Hughes
Publisher : Addison-Wesley Professional
Page : 736 pages
File Size : 15,14 MB
Release : 2004
Category : Computers
ISBN : 9780131013766
This text takes complicated and almost unapproachable parallel programming techniques and presents them in a simple, understandable manner. It covers the fundamentals of programming for distributed environments like Internets and Intranets as well as the topic of Web Based Agents.
Author : Gregory V. Wilson
Publisher : MIT Press
Page : 796 pages
File Size : 30,62 MB
Release : 1996-07-08
Category : Computers
ISBN : 9780262731188
Foreword by Bjarne Stroustrup Software is generally acknowledged to be the single greatest obstacle preventing mainstream adoption of massively-parallel computing. While sequential applications are routinely ported to platforms ranging from PCs to mainframes, most parallel programs only ever run on one type of machine. One reason for this is that most parallel programming systems have failed to insulate their users from the architectures of the machines on which they have run. Those that have been platform-independent have usually also had poor performance. Many researchers now believe that object-oriented languages may offer a solution. By hiding the architecture-specific constructs required for high performance inside platform-independent abstractions, parallel object-oriented programming systems may be able to combine the speed of massively-parallel computing with the comfort of sequential programming. Parallel Programming Using C++ describes fifteen parallel programming systems based on C++, the most popular object-oriented language of today. These systems cover the whole spectrum of parallel programming paradigms, from data parallelism through dataflow and distributed shared memory to message-passing control parallelism. For the parallel programming community, a common parallel application is discussed in each chapter, as part of the description of the system itself. By comparing the implementations of the polygon overlay problem in each system, the reader can get a better sense of their expressiveness and functionality for a common problem. For the systems community, the chapters contain a discussion of the implementation of the various compilers and runtime systems. In addition to discussing the performance of polygon overlay, several of the contributors also discuss the performance of other, more substantial, applications. For the research community, the contributors discuss the motivations for and philosophy of their systems. As well, many of the chapters include critiques that complete the research arc by pointing out possible future research directions. Finally, for the object-oriented community, there are many examples of how encapsulation, inheritance, and polymorphism can be used to control the complexity of developing, debugging, and tuning parallel software.
Author : Veeravalli Bharadwaj
Publisher : John Wiley & Sons
Page : 320 pages
File Size : 10,33 MB
Release : 1996-10-14
Category : Computers
ISBN : 9780818675218
This book provides an in-depth study concerning a claqss of problems in the general area of load sharing and balancing in parallel and distributed systems. The authors present the design and analysis of load distribution strategies for arbitrarily divisible loads in multiprocessor/multicomputer systems subjects to the system constraints in the form of communication delays. In particular, two system architecture-single-level tree or star network, and linear network-are thoroughly analyzed. The text studies two different cases, one of processors with front-ends and the other without. It concentrates on load distribution strategies and performance analysis, and does not cover issues related to implementation of these strategies on a specific system. The book collates research results developed mainly by two groups at the Indian Institute of Science and the State University of New York at Stony Brook. It also covers results by other researchers that have either appeared or are due to appear in computer science literature. The book also provides relevant but easily understandable numerical examples and figures to illustrate important concepts. It is the first book in this area and is intended to spur further research enabling these ideas to be applied to a more general class of loads. The new methodology introduced here allows a close examination of issues involving the integration of communication and computation. In fact, what is presented is a new "calculus" for load sharing problems.
Author : Sushil K Prasad
Publisher : Morgan Kaufmann
Page : 359 pages
File Size : 14,26 MB
Release : 2015-09-16
Category : Computers
ISBN : 0128039388
Topics in Parallel and Distributed Computing provides resources and guidance for those learning PDC as well as those teaching students new to the discipline. The pervasiveness of computing devices containing multicore CPUs and GPUs, including home and office PCs, laptops, and mobile devices, is making even common users dependent on parallel processing. Certainly, it is no longer sufficient for even basic programmers to acquire only the traditional sequential programming skills. The preceding trends point to the need for imparting a broad-based skill set in PDC technology. However, the rapid changes in computing hardware platforms and devices, languages, supporting programming environments, and research advances, poses a challenge both for newcomers and seasoned computer scientists. This edited collection has been developed over the past several years in conjunction with the IEEE technical committee on parallel processing (TCPP), which held several workshops and discussions on learning parallel computing and integrating parallel concepts into courses throughout computer science curricula. - Contributed and developed by the leading minds in parallel computing research and instruction - Provides resources and guidance for those learning PDC as well as those teaching students new to the discipline - Succinctly addresses a range of parallel and distributed computing topics - Pedagogically designed to ensure understanding by experienced engineers and newcomers - Developed over the past several years in conjunction with the IEEE technical committee on parallel processing (TCPP), which held several workshops and discussions on learning parallel computing and integrating parallel concepts
Author : Robert Robey
Publisher : Simon and Schuster
Page : 702 pages
File Size : 31,60 MB
Release : 2021-08-24
Category : Computers
ISBN : 1638350388
Parallel and High Performance Computing offers techniques guaranteed to boost your code’s effectiveness. Summary Complex calculations, like training deep learning models or running large-scale simulations, can take an extremely long time. Efficient parallel programming can save hours—or even days—of computing time. Parallel and High Performance Computing shows you how to deliver faster run-times, greater scalability, and increased energy efficiency to your programs by mastering parallel techniques for multicore processor and GPU hardware. About the technology Write fast, powerful, energy efficient programs that scale to tackle huge volumes of data. Using parallel programming, your code spreads data processing tasks across multiple CPUs for radically better performance. With a little help, you can create software that maximizes both speed and efficiency. About the book Parallel and High Performance Computing offers techniques guaranteed to boost your code’s effectiveness. You’ll learn to evaluate hardware architectures and work with industry standard tools such as OpenMP and MPI. You’ll master the data structures and algorithms best suited for high performance computing and learn techniques that save energy on handheld devices. You’ll even run a massive tsunami simulation across a bank of GPUs. What's inside Planning a new parallel project Understanding differences in CPU and GPU architecture Addressing underperforming kernels and loops Managing applications with batch scheduling About the reader For experienced programmers proficient with a high-performance computing language like C, C++, or Fortran. About the author Robert Robey works at Los Alamos National Laboratory and has been active in the field of parallel computing for over 30 years. Yuliana Zamora is currently a PhD student and Siebel Scholar at the University of Chicago, and has lectured on programming modern hardware at numerous national conferences. Table of Contents PART 1 INTRODUCTION TO PARALLEL COMPUTING 1 Why parallel computing? 2 Planning for parallelization 3 Performance limits and profiling 4 Data design and performance models 5 Parallel algorithms and patterns PART 2 CPU: THE PARALLEL WORKHORSE 6 Vectorization: FLOPs for free 7 OpenMP that performs 8 MPI: The parallel backbone PART 3 GPUS: BUILT TO ACCELERATE 9 GPU architectures and concepts 10 GPU programming model 11 Directive-based GPU programming 12 GPU languages: Getting down to basics 13 GPU profiling and tools PART 4 HIGH PERFORMANCE COMPUTING ECOSYSTEMS 14 Affinity: Truce with the kernel 15 Batch schedulers: Bringing order to chaos 16 File operations for a parallel world 17 Tools and resources for better code
