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并行化思路实现dijkstra算法。假设有p个处理器，N个顶点。给每个处理器分配N/p个顶点，求出局部的最小值，复杂度为O (N/p)。然后后一半的处理器将自己的最小值发送给第前p/2个处理器。前一半处理器接收到传来的值后，与局部的最小值比较，作为新值。继续循环，直到剩下一个处理器为止。-Parallelized dijkstra algorithm. Suppose there is p a processor, N vertex. Give each processor distributi
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大量平行處理器程式設計訓練課程Programming Massively Parallel Processors: the CUDA experience -Introduction and Motivation
The CUDA Programming Model
CUDA Memories
CUDA Threads
Performance Tuning
Floating-Point Considerations and CUDA for MultiCore CPU
A
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Parallel LBM in C++
In which, as a counterpoint to abstract virtual generic templated meta-programming, we present a concrete code to simulate on precisely two computational nodes using a 1D lattice Boltzmann model with omega = 1 the heating of one
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设计一个有 N个进程并行的进程调度程序,采用最高优先数优先的调度算法（即把处理机分配给优先数最高的进程）和先来先服务算法.-Design of a parallel process, N a process scheduler, using the highest priority number of priority scheduling algorithm (ie the number of processors allocated to the highest priority to th
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C语言和OpenMP编写的可在多核或SMP处理器上进行多线程运行的最短路径算法。可了解多核多线程和OpenMP的并行编程技术。-C language and can be prepared OpenMP or multi-core processors on SMP multi-threading to run the shortest path algorithm. Learn to multi-core multi-thread and OpenMP parallel programming
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介绍行列划分算法和矩阵相乘并行算法M P I 程序, 给出基于矩阵相乘并行算法的M P I 实现, 分析和讨
论处理器数目、复杂性、矩阵划分、B 子块传递、死锁避免和矩阵数据的获取等问题.-Introduction into the ranks of the matrix multiplication algorithm and parallel algorithm for MPI procedures, give parallel algorithm based on matrix mul
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Using the equations for partitioning a list of numbers into m partitions that are added separately show that the optimum value for m to give the minimum parallel execution time is when , where there are n processors. (Clue: Differentiate the parallel
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摘要图像特征的提取是视觉图像识别的重要方法之一，采用细胞神经网络（&’’）并行处理器进行图像特征的提取
具有实时快速的优点。该文将介绍&’’ 并行处理器的基本工作原理及其实现图像特征处理的逻辑组合通用方法，并以
图像的纹理分割与识别为例来说明&’’ 并行处理器应用于视觉图像识别的通用编程方法。-Abstract image feature extraction is a visual image to identify one of the important ways, the use
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本实例详细讲解了处理器上双机并口通信的过程，让我们了解ＰＣ机上通信的奥秘！-Detailed account of the examples of two-plane parallel processors on the process of communication, let us understand the PC, the mysteries of communication!
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Parallel Python (PP)
PP is a python module which provides mechanism for parallel execution of python code on SMP (systems with multiple processors or cores) and clusters (computers connected via network).
It is light, easy to install and int
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Intel出版的多核编程，介绍通过软件的多线程方式来提高性能的方法。分为介绍多核变成，线程的综述，并行的基本概念，线程以及并行编程的结构，线程的API，OpenMP技术，并行编程的常规问题，多线程debug方法，Intel多核处理器的线程及其开发工具等。-Intel multi-core programming, published to introduce the way through the software to improve performance of multi-threaded
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近年来，计算机图形处理器(GI．apllics Processing Unit,GPU)得到了极大地发展，从最初局限于图形渲染的图形卡，发展为如今可编程的并行计算平台。与CPU的串行计算模式不同，GPU是一种高度并行的流处理器，具有更强的浮点计算能力，在物理模拟、信号分析等许多领域人们将高强度的计算任务以适当的方式转化为流数据计算模式，通过编程在GPU中进行加速计算，通常能获得一个数量级的速度提高，这也是当今的热点研究问题之一。-In recent years, computer graphic
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深入浅出地全面介绍了计算机系统结构的基本原理。内容包括计算机系统结构的基本概念、指令系统、输入输出系统、标量处理机、互联网络、并行处理机和多处理机等。-Layman' s language and a comprehensive introduction to the basic principles of computer architecture. Covers the basic concepts of computer architecture, instruction set,
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NVIDIA Fellow David Kirk and UIUC Professor Wen-mei Hwu have published their landmark textbook, Programming Massively Parallel Processors: A Hands-on Approach. This book will enable generations of programmers to understand and exploit the massively p
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In this webinar you will learn how you can use Parallel Computing Toolbox™ to speed up MATLAB applications by using hardware you already have. You will learn how minimal programming efforts can speed up your applications on widely available desk
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Programming
Massively Parallel
Processors
A Hands-on Approach
by David B. Kirk and Wen-mei W. Hwu
English version
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使用虚拟处理器的SPMD
并行程序，我将介绍使用虚拟处理器的一些结果
技术，并行计算程序的一些SPMD。 “
测试的技术真正的处理器是英特尔超线程，
和程序，浮点计算的MATLAB脚本。
工作的关注实用和限制的结论
使用的方法。主要结果是，使用虚拟处理器
不仅为改善并行程序是一个很好的技术
基于内存的计算，但在大量的磁盘存储的情况下
操作太多。
-Using virtual processors for SPMD
parallel programs，I
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《大规模并行处理器编程实战》英文版，全球第一本介绍CUDA的教程。由于书名太长，只能用其英文缩写，望见谅。-Programming Massively Parallel Processors:A Hands-on Approach,a book which is the first book in the world that provide a perfect guide for learning CUDA.
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DNA sequence alignment is the most
commonly application in computational biology. It is
essential pre-requisite of many other operations in
computational biology applications. Optimal alignment
for a large scale size DNA sequence dataset is a
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Emulation of system, that split tasks by processors.
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