在分布式系统上测试并行算法的高效共享内存

M. S. Atkins
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引用次数: 2

摘要

本文概述了一种称为MOOSE(可修改对象结构)的分布式数据结构,它既足够高效又足够通用,可以被各种并行算法使用。MOOSE结构的目标是一个松散耦合的分布式系统,其中多个处理器通过局域网连接。该系统采用高级分布式编程语言SR在运行Unix操作系统的Sun-2和Sun-3工作站上实现,并通过以太网连接。MOOSE共享内存的设计具有可定制的特性,以提高在这种环境中的实现效率。这使得研究并行算法在非共享内存硬件上的通信和计算性能成为可能。如果应用程序在多个网络节点上后台运行,则可以实现自动负载均衡,并且程序可以在计算过程中容忍节点故障
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient shared memory for testing parallel algorithms on distributed systems
A distributed data structure called a MOOSE (modifiable object structure), which is both efficient enough and general enough to be used by a wide variety of parallel algorithms, is outlined. The MOOSE structure is aimed at a loosely coupled distributed system in which several processors are connected over a local area network. It is implemented in the high-level distributed programming language SR on several Sun-2 and Sun-3 workstations running the Unix operating system and connected by an Ethernet. The MOOSE shared memory has been designed with customizable features for efficiency of implementation in such an environment. This enables the communication and computation performance of parallel algorithms on non-shared-memory hardware to be studied. If the application is run in the background on several network nodes, automatic load balancing is achieved and the programs may be tolerant of node failure during the computation.<>
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