PCクラスタにおける並列計算の動的負荷分散

A PC cluster is one of the parallel computers and it is constructed with a number of commodity PCs and free software. Therefore we can obtain such a system with ease and reasonable cost. Dynamic load balancing is one of the methods to execute a program for parallel computing in PC clusters effectively. We introduce a general method for dynamic load balancing and propose a new one. This paper is constructed with two parts. In the first part, we introduce some concepts of PC Clusters, Parallel Computing, Dynamic Load Balancing, and Computational Reflection. In the second part, we propose a method of dynamic load balancing based on the framework of computational reflection

Development of Cluster Computing –A Review

This paper presents the review work of “Cluster Computing” in depth and detail.  Cluster Computing: A Mobile Code Approach by R.B.Patel and Manpreet Singh (2006); Performance Evaluation of Parallel Applications Using Message Passing Interface In Network of Workstations Of Different Computing Powers by Rajkumar Sharma, Priyesh Kanungo and Manohar Chandwani (2011); On the Performance of MPI-OpenMP on a 12 nodes Multi-core Cluster by Abdelgadir Tageldin, Al-Sakib Khan Pathan , Mohiuddin Ahmed (2011); Dynamic Load Balancing in Parallel Processing on Non-Homogeneous Clusters by Armando E. De Giusti, Marcelo R. Naiouf, Laura C. De Giusti, Franco Chichizola (2005); Performance Evaluation of Computation Intensive Tasks in Grid by P.Raghu, K. Sriram (2011); Automatic Distribution of Vision-Tasks on Computing Clusters by Thomas Muller, Binh An Tran and Alois Knoll (2011); Terminology And Taxonomy Parallel Computing Architecture by Amardeep Singh, Satinder Pal Singh, Vandana, Sukhnandan Kaur (2011); Research of Distributed Algorithm based on Parallel Computer Cluster System by Xu He-li, Liu Yan (2010); Cluster Computing Using Orders Based Transparent Parallelizing by Vitaliy D. Pavlenko, Victor V. Burdejnyj (2007) and VCE: A New Personated Virtual Cluster Engine for Cluster Computing by Mohsen Sharifi, Masoud Hassani, Ehsan Mousavi Khaneghah, Seyedeh Leili Mirtaheri (2008). Keywords:Cluster computing, Cluster Architectures, Dynamic and Static Load Balancing, Distributed Systems, Homogeneous and Non-Homogeneous Processors, Multicore clusters, Parallel computing, Parallel Computer Vision, Task parallelism, Terminology and taxonomy, Virtualization, Virtual Cluster

The effect of time delays on the stability of load balancing algorithms for parallel computations

A deterministic dynamic nonlinear time-delay system is developed to model load balancing in a cluster of computer nodes used for parallel computations. The model is shown to be self consistent in that the queue lengths cannot go negative and the total number of tasks in all the queues and the network are conserved (i.e., load balancing can neither create nor lose tasks). Further, it is shown that using the proposed load balancing algorithms, the system is stable in the sense of Lyapunov. Experimental results are presented and compared with the predicted results from the analytical model. In particular, simulations of the models are compared with an experimental implementation of the load balancing algorithm on a distributed computing network

Cluster-Based Load Balancing Algorithms for Grids

E-science applications may require huge amounts of data and high processing power where grid infrastructures are very suitable for meeting these requirements. The load distribution in a grid may vary leading to the bottlenecks and overloaded sites. We describe a hierarchical dynamic load balancing protocol for Grids. The Grid consists of clusters and each cluster is represented by a coordinator. Each coordinator first attempts to balance the load in its cluster and if this fails, communicates with the other coordinators to perform transfer or reception of load. This process is repeated periodically. We analyze the correctness, performance and scalability of the proposed protocol and show from the simulation results that our algorithm balances the load by decreasing the number of high loaded nodes in a grid environment.Comment: 17 pages, 11 figures; International Journal of Computer Networks, volume3, number 5, 201

Open Source Solutions for Optimization on Linux Clus- ters

Abstract: Parallel implementation of optimization algorithms is an alternative and effective paradigm to speed up the search for solutions of optimization problems. Currently a Linux Cluster is probably the best technological solution available considering both the overall system performance and its cost. Open Source community offers to researchers a set of software tools for setting up clusters and to optimize their performance. The aim of this paper is to review the open source tools are useful to build a cluster which efficiently runs parallel optimization algorithms. Particular attention is given to the OpenMosix approach to scalable computing. Keywords: Open Source, Linux Cluster, Optimization, OpenMosix, Dynamic Load Balancing INTRODUCTION Although (sequential) optimization algorithms have reached a sophisticated level of implementation allowing good computational results for a large variety of optimization problems, usually the running time required to explore the solution space associated to optimization problems can be very large With the diffusion of parallel computers and fast communication networks, parallel implementation of optimization algorithms can be an alternative and effective paradigm to speed up the search for solutions of optimization problems