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Performance optimization of PVM based parallel applications using optimal number of slaves

机译:使用最佳从站数量,基于PVM的并行应用程序的性能优化

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Parallel computing operates on the principle that large problems can often be divided into smaller ones, which are then solved concurrently which results in saving time to solve larger problems and to provide concurrency using desktop PC's. The main aim is to form a cluster based parallel computing architecture for demonstrating PVM based parallel applications which works on the Master-Slave computing paradigm. The master will monitor the progress and be able to report the time taken to solve the problem, taking into account the time spent in breaking the problems into sub-tasks and combining the results along with the communication delay. The slaves are capable of accepting sub problems from the master and finding the solution and sending back to the master. We aim to evaluate these time statistics of parallel execution for solving matrix multiplication problem and find the relation between the number of cores and number of slaves utilized for computation. When the number of nodes required for the computation is fixed by the user, the computation time mainly depends on the number of slaves specified for computation. In our work, we find the optimal number of slaves required for PVM based parallel computation when the number of nodes is fixed by a user. The analysis is made for the computation of different sizes of matrices over the different number of nodes.
机译:并行计算的原理是,通常可以将大问题划分为较小的问题,然后并行解决这些问题,从而节省了时间来解决较大的问题并使用台式机提供并发性。主要目的是形成一个基于集群的并行计算体系结构,以演示基于PVM的并行应用程序,该应用程序可在Master-Slave计算范式上工作。主机将监视进度,并能够报告解决问题所花费的时间,并考虑将问题分解为子任务并将结果与​​通信延迟结合在一起所花费的时间。从站能够从主站接受子问题并找到解决方案,然后发送回主站。我们旨在评估并行执行的这些时间统计信息,以解决矩阵乘法问题,并找到内核数量与用于计算的从设备数量之间的关系。当计算所需的节点数由用户确定时,计算时间主要取决于为计算指定的从站数。在我们的工作中,当节点数量由用户确定时,我们发现基于PVM的并行计算所需的最佳从设备数量。进行分析是为了计算在不同数量的节点上的不同大小的矩阵。

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