并行处理是计算机系统中能同时执行两个或多个处理的一种计算方法;并行处理可同时工作于同一程序的不同方面;并行处理的主要目的是节省大型和复杂问题的解决时间。
并行处理(Parallel Processing)是计算机系统中能同时执行两个或多个处理的一种计算方法。并行处理可同时工作于同一程序的不同方面。
并行处理的主要目的是节省大型和复杂问题的解决时间。
为使用并行处理,首先需要对程序进行并行化处理,也就是说将工作各部分分配到不同处理进程(线程)中。
并行处理由于存在相互关联的问题,因此不能自动实现。另外,并行也不能保证加速。从理论上讲,在 n 个并行处理的执行速度可能会是在单一处理机上执行的速度的 n 倍。
特点
只有部分应用程序在满足以下条件的情况下可利用并行处理:具有充足的能充分利用多处理机的应用程序; 并行化目标应用程序或用户需进行新的编码来利用并行程序。
传统上,多处理机专为“并行计算机”所设计,沿着这样的思路,当前 Linux 支持 SMP 奔腾系统,在该系统中多处理机共享单个计算机中的单个存储器和总线接口。每个运行 Linux 的机器组都有可能通过网络互相连接形成并行处理群。第三种选择是使用 Linux 系统作为“主机”,提供专门的相关并行处理机(attached parallel processor)。第四种新选择是寄存器内 SIMD 并行,应用于多媒体扩展(MMX)。
并行处理所需要提供的典型硬件环境有:
单处理机上的单个区;
多处理机(SMP)中的单个区;
多区配置
一个处理机(MPP)中的各区 ;
多处理机(SMP 群)中的各区;
逻辑数据库区(在 AIX 第1版的 DB2 并行版 - DB2 PE 中也称之为多逻辑代码或 MLN)
并行计算机具有代表性的应用领域有:天气预报建摸、VLSI电路的计算机辅助设计、大型数据库管理、人工智能、犯罪控制和国防战略研究等,而且它的应用范围还在不断地扩大。并行处理技术主要是以算法为核心,并行语言为描述,软硬件作为实现工具的相互联系而又相互制约的一种结构技术。
算法基本策略
在并行处理技术中所使用的算法主要遵循三种策略:
1、分而治之法:也就是把多个任务分解到多个处理器或多个计算机中,然后再按照一定的拓扑结构来进行求解。
2、重新排序法:分别采用静态或动态的指令词度方式。
3、显式/隐式并行性结合:显式指的是并行语言通过编译形成并行程序,隐式指的是串行语言通过编译形成并行程序,显式/隐式并行性结合的关键就在于并行编译,而并行编译涉及到语句、程序段、进程以及各级程序的并行性。
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