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Using OpenMP: Portable Shared Memory Parallel Programming

学习OpenMP的书籍, 不过是英文版的, 有兴趣的可以下载看看
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Using OpenMP Portable Shared.Memory Parallel Programming

麻省2007年10月出版的有关OpenMP编程书籍

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Using OpenMP Portable Shared Memory Parallel Programming书中的程序代码

Using OpenMP Portable Shared Memory Parallel Programming书中程序的代码,还有例子文件的使用指导。

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3积分/C币
MPI, OpenMP, CUDA, OpenCL, OpenACC,

Brief Introduction to OpenMP-PPT,CUDA-C编程-作图,CUDA-C编程,MPI The Complete Reference,MPICH User’s Guide,mpich-3.0.4-installguide,MPI并行程序设计-完整版-高性能计算之并行编程技术,OpenACC应用编程接口-v2.0-中文版-小小河20130826,Opencl2.0-高性能计算-中文版,Opencl规范中文版,OpenHMPP,OpenMP,OpenMP简易教程,OpenMP编译原理及实现技术,Parallel Programming with MPI on Clusters,《Intel_OpenMP白皮书》,《OpenMP并行计算程序设计基础(C++)》,《Parallel Programming in OpenMP(Fortran)》,《Using OpenMP - Portable Shared Memory Parallel Programming(Fortran,C)》,《OpenMP入门》,《OpenMP编程》PPT,并行计算导论-张林波

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Parallel.Programming.in.C.with.Mpi.and.Openmp

Parallel.Programming.in.C.with.Mpi.and.Openmp,.Quinn,.MGH,.2003,.258s.pdf

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10积分/C币
OpenMP Application Program Interface Version 4.0

The collection of compiler directives, library routines, and environment variables described in this document collectively define the specification of the OpenMP Application Program Interface (OpenMP API) for shared-memory parallelism in C, C++ and Fortran programs. This specification provides a model for parallel programming that is portable across shared memory architectures from different vendors. Compilers from numerous vendors support the OpenMP API. More information about the OpenMP API can be found at the following web site

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Parallel Programming in OpenMP

Parallel Programming in OpenMP

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Using OpenMP-Portable Shared Memory Parallel ProgrammingOct 2007

很难得的一本讲述openmp的书,效果非常好. 很难才找到的. 讲述了多线程方面的很多东西.

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parallel programming in openmp

parallel programming in openmp, english edition

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并行程序设计 第2版 高清完整版 pdf

并行程序设计 第2版 高清完整版 pdf 作者: Barry Wilkinson / Michael Allen / 陆鑫达 出版社: 机械工业出版社 原作名: Parallel Programming: Techniques and Applications Using Networked Workstations and Parallel Computers 译者: 陆鑫达 出版年: 2005-5-1 页数: 354 装帧: 平装(无盘) 丛书: 计算机科学丛书 ISBN: 9787111162605

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Parallel and Distributed Programming Using C++-Addison Wesley(2003).pdf

Parallel and Distributed Programming

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10积分/C币
Parallel Programming in Fortran 95 using OpenMP

关于fortran95的openmp并行计算指导书,非常实用,简单明了。

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Parallel Programming in OpenMP(英文)

一本专门介绍OpenMP编程的书。<br/>

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Shared Memory Application Programming

Shared Memory Application Programming

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10积分/C币
using openMP

using openMP - a good book if you want to get into parallel computing

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Lab3 Parallel implementation of calculating the value of pi using OpenMP

Lab3 Parallel implementation of calculating the value of pi using OpenMP (Required) 华中科技大学 并行实验 多线程计算π OpenMP

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OpenMP Tutorials

OpenMP is an Application Program Interface (API), jointly defined by a group of major computer hardware and software vendors. OpenMP provides a portable, scalable model for developers of shared memory parallel applications. The API supports C/C++ and Fortran on multiple architectures, including UNIX &amp; Windows NT. This tutorial covers most of the major features of OpenMP, including its various constructs and directives for specifying parallel regions, work sharing, synchronization and data environment. Runtime library functions and environment variables are also covered. This tutorial includes both C and Fortran example codes and a lab exercise.

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Parallel Programming with Microsoft.NET.pdf

Parallel Programming with Microsoft.NET

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12积分/C币
Hybrid CUDA, OpenMP, and MPI parallel programming on multicore GPU

Nowadays, NVIDIA’s CUDA is a general purpose scalable parallel programming model for writing highly parallel applications. It provides several key abstractions – a hierarchy of thread blocks, shared memory, and barrier synchronization. This model has proven quite successful at programming multithreaded many core GPUs and scales transparently to hundreds of cores: scientists throughout industry and academia are already using CUDA to achieve dramatic speedups on production and research codes. In this paper, we propose a parallel programming approach using hybrid CUDA OpenMP, and MPI programming, which partition loop iterations according to the number of C1060 GPU nodes in a GPU cluster which consists of one C1060 and one S1070. Loop iterations assigned to one MPI process are processed in parallel by CUDA run by the processor cores in the same computational node.

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并行计算

Parallel and Distributed Programming Using C++-fly.chm

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Parallel and Distributed Programming Using C++.

Parallel and Distributed Programming Using C++.

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Python Parallel Programming Cookbook

Master efficient parallel programming to build powerful applications using Python About This Book Design and implement efficient parallel software Master new programming techniques to address and solve complex programming problems Explore the world of parallel programming with this book, which is a go-to resource for different kinds of parallel computing tasks in Python, using examples and topics covered in great depth Who This Book Is For Python Parallel Programming Cookbook is intended for software developers who are well versed with Python and want to use parallel programming techniques to write powerful and efficient code. This book will help you master the basics and the advanced of parallel computing. What You Will Learn Synchronize multiple threads and processes to manage parallel tasks Implement message passing communication between processes to build parallel applications Program your own GPU cards to address complex problems Manage computing entities to execute distributed computational tasks Write efficient programs by adopting the event-driven programming model Explore the cloud technology with DJango and Google App Engine Apply parallel programming techniques that can lead to performance improvements In Detail Parallel programming techniques are required for a developer to get the best use of all the computational resources available today and to build efficient software systems. From multi-core to GPU systems up to the distributed architectures, the high computation of programs throughout requires the use of programming tools and software libraries. Because of this, it is becoming increasingly important to know what the parallel programming techniques are. Python is commonly used as even non-experts can easily deal with its concepts. This book will teach you parallel programming techniques using examples in Python and will help you explore the many ways in which you can write code that allows more than one process to happen at once. Starting with introducing you to the world of parallel computing, it moves on to cover the fundamentals in Python. This is followed by exploring the thread-based parallelism model using the Python threading module by synchronizing threads and using locks, mutex, semaphores queues, GIL, and the thread pool. Next you will be taught about process-based parallelism where you will synchronize processes using message passing along with learning about the performance of MPI Python Modules. You will then go on to learn the asynchronous parallel programming model using the Python asyncio module along with handling exceptions. Moving on, you will discover distributed computing with Python, and learn how to install a broker, use Celery Python Module, and create a worker. You will also understand the StarCluster framework, Pycsp, Scoop, and Disco modules in Python. Further on, you will learn GPU programming with Python using the PyCUDA module along with evaluating performance limitations. Next you will get acquainted with the cloud computing concepts in Python, using Google App Engine (GAE), and building your first application with GAE. Lastly, you will learn about grid computing concepts in Python and using PyGlobus toolkit, GFTP and GASS COPY to transfer files, and service monitoring in PyGlobus. Style and approach A step-by-step guide to parallel programming using Python, with recipes accompanied by one or more programming examples. It is a practically oriented book and has all the necessary underlying parallel computing concepts. Table of Contents Chapter 1: Getting Started with Parallel Computing and Python Chapter 2: Thread-based Parallelism Chapter 3: Process-based Parallelism Chapter 4: Asynchronous Programming Chapter 5: Distributed Python Chapter 6: GPU Programming with Python

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CUDA Programming pdf

CUDA programming: a developer's guide to parallel computing with GPUs. by Shane Cook. Over the past five years there has been a revolution in computing brought about by a company that for successive years has emerged as one of the premier gaming hardware manufacturersdNVIDIA. With the introduction of the CUDA (Compute Unified Device Architecture) programming language, for the first time these hugely powerful graphics coprocessors could be used by everyday C programmers to offload computationally expensive work. From the embedded device industry, to home users, to supercomputers, everything has changed as a result of this. One of the major changes in the computer software industry has been the move from serial programming to parallel programming. Here, CUDA has produced great advances. The graphics processor unit (GPU) by its very nature is designed for high-speed graphics, which are inherently parallel. CUDA takes a simple model of data parallelism and incorporates it into a programming model without the need for graphics primitives. In fact, CUDA, unlike its predecessors, does not require any understanding or knowledge of graphics or graphics primitives. You do not have to be a games programmer either. The CUDA language makes the GPU look just like another programmable device. Throughout this book I will assume readers have no prior knowledge of CUDA, or of parallel programming. I assume they have only an existing knowledge of the C/C++ programming language. As we progress and you become more competent with CUDA, we’ll cover more advanced topics, taking you from a parallel unaware programmer to one who can exploit the full potential of CUDA. For programmers already familiar with parallel programming concepts and CUDA, we’ll be discussing in detail the architecture of the GPUs and how to get the most from each, including the latest Fermi and Kepler hardware. Literally anyone who can program in C or C++ can program with CUDA in a few hours given a little training. Getting from novice CUDA programmer, with a several times speedup to 10 times–plus speedup is what you should be capable of by the end of this book. The book is very much aimed at learning CUDA, but with a focus on performance, having first achieved correctness. Your level of skill and understanding of writing high-performance code, especially for GPUs, will hugely benefit from this text. This book is a practical guide to using CUDA in real applications, by real practitioners. At the same time, however, we cover the necessary theory and background so everyone, no matter what their background, can follow along and learn how to program in CUDA, making this book ideal for both professionals and those studying GPUs or parallel programming.

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Structured Parallel Programming - Patterns for Efficient Computation

Intel recommended book

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50积分/C币
Programming Massively Parallel Processors, Second Edition

GPU开发的后期可以看看,对于提高很有帮助的,帮你更加深入的了解GPU编程。台湾著名作者所写,在coursra上有开过课程的。

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(2nd)Programming Massively Parallel Processors 2nd Edition

一本非常经典的平行计算的学习书籍,已经是第二版的了,全书销量达几十万册,是众多平行计算开发者的必备工具书。

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10积分/C币
Parallel And Distributed Programming Using C.pdf

c语言并行与分布式编程英文参考书,英文原著影印版,

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Introduction to Computation and Programming Using Python(2nd) 英文pdf 第2版

Introduction to Computation and Programming Using Python(2nd) 英文pdf 第2版

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5积分/C币
Parallel and Distributed Programming Using C++

一本介绍并行与分布式编程的好书

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Programming Principles and Practice Using C++(2nd) 无水印pdf

Programming Principles and Practice Using C++(2nd) 英文无水印pdf 第2版 pdf所有页面使用FoxitReader和PDF-XChangeViewer测试都可以打开 本资源转载自网络,如有侵权,请联系上传者或csdn删除 本资源转载自网络,如有侵权,请联系上传者或csdn删除

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Programming -- Principles and Practice Using C++, Second Edition 英文 第2版 EPUB转PDF

Programming -- Principles and Practice Using C++, Second Edition 英文 第2版 EPUB转PDF Bjarne Stroustrup

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Using OpenMP: Portable Shared Memory Parallel Programming

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