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Efficient Image Processing Applications on a Network of Workstations

机译:工作站网络上的高效图像处理应用

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Using a cluster of networked workstations as an inexpensive parallel computational platform is an appealing idea. However, very little is known about modeling their parallel performance since most of the developed models have been designed with traditional parallel computers in mind. In this paper, we model the performance of this computing environment for synchronous parallel iterative algorithms. One specific algorithm of this class that is treated in detail in this paper is the parallel image processing convolution. Our model takes into consideration the communication capability of the network, the computing capabilities of the workstations, and load imbalance among the workstations. It was shown that our models accrately model the performance of synchronous iterative algorithms on a cluster of workstations. Moreover, this model can be used to tune various parameters in the system to enhance its performance.
机译:使用网络工作站集群作为廉价的并行计算平台是一个吸引人的想法。但是,由于大多数开发模型都是在考虑传统并行计算机的情况下设计的,因此对其并行性能建模的了解甚少。在本文中,我们为同步并行迭代算法建模了此计算环境的性能。本文将详细介绍的此类特定算法是并行图像处理卷积。我们的模型考虑了网络的通信能力,工作站的计算能力以及工作站之间的负载不平衡。结果表明,我们的模型可以准确地对工作站集群上的同步迭代算法的性能进行建模。此外,该模型可用于调整系统中的各种参数以增强其性能。

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