Middleware for Writing Distributed Applications on Physical Computing Devices

Michael Lescisin, Q. Mahmoud
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引用次数: 2

Abstract

A computer program, at its most basic level is a series of low level processor instructions which are executed sequentially. These instructions take time to execute, thus longer programs have longer execution times. One way to decrease the execution time for a program is to decrease the required time for each instruction. This is called frequency scaling. The disadvantage of frequency scaling is that running a processor at higher speeds causes it to generate more heat and consume more power. The physical properties of transistors also impose limits on how fast a microprocessor can be built. The solution to the problem of frequency scaling is to, instead of decreasing the time to execute an instruction, increase the number of instructions that can be run in a given amount of time, by running these instructions in parallel. This is known as parallel computing, and in this paper we present a solution for using many off-the-shelf computers to build a computing cluster which will accelerate computing performance by running tasks in parallel. To this end, we introduce a middleware for writing distributed applications on physical computing devices, such as the Raspberry Pi computer.
在物理计算设备上编写分布式应用程序的中间件
最基本的计算机程序是一系列按顺序执行的低级处理器指令。这些指令的执行需要时间,因此较长的程序需要较长的执行时间。减少程序执行时间的一种方法是减少每条指令所需的时间。这就是所谓的频率缩放。频率扩展的缺点是,以更高的速度运行处理器会产生更多的热量,消耗更多的电能。晶体管的物理特性也限制了微处理器的运行速度。解决频率扩展问题的办法是,通过并行运行指令,增加在给定时间内可运行的指令数量,而不是减少执行指令的时间。这就是所谓的并行计算,在本文中,我们提出了一种解决方案,利用许多现成的计算机来构建一个计算集群,通过并行运行任务来加速计算性能。为此,我们引入了一个中间件,用于在树莓派电脑等物理计算设备上编写分布式应用程序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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