A parallel loop self-scheduling on grid computing environments

Kuan-Wei Cheng, Chao-Tung Yang, Chuan-Lin Lai, Shun-Chyi Chang
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引用次数: 26

Abstract

Internet computing and grid technologies promise to change the way we tackle complex problems. They will enable large-scale aggregation and sharing of computational, data and other resources across institutional boundaries. And harnessing these new technologies effectively will transform scientific disciplines ranging from high-energy physics to the life sciences. In this paper, a grid computing environment is proposed and constructed on multiple PC clusters by using Globus Toolkit (GT) and SUN Grid Engine (SGE). The experimental results are also conducted by using the matrix multiplication to demonstrate the performance. On the other hand, the approaches to deal with scheduling and load balancing on multiple heterogeneous PC clusters computer system are not mature. Self-scheduling schemes which are suitable for parallel loops with independent iterations on heterogeneous cluster computer system have been designed in the past. However, these schemes, such as FSS, GSS and TSS, can not achieve load balancing in extremely heterogeneous environment. We propose a heuristic approach based upon a two-phase scheme to solve parallel regular loop scheduling problem on an extremely heterogeneous grid computing environment.
网格计算环境下的并行循环自调度
互联网计算和网格技术有望改变我们处理复杂问题的方式。它们将使计算、数据和其他资源的大规模聚合和共享成为可能。有效地利用这些新技术将改变从高能物理学到生命科学等科学学科。本文利用Globus Toolkit (GT)和SUN grid Engine (SGE),提出并构建了一个基于PC机集群的网格计算环境。利用矩阵乘法进行了实验,验证了该算法的性能。另一方面,处理多异构PC集群计算机系统的调度和负载均衡的方法还不成熟。针对异构集群计算机系统中具有独立迭代的并行循环问题,已经设计了一些自调度方案。然而,这些方案,如FSS、GSS和TSS,不能在极端异构的环境中实现负载均衡。提出了一种基于两阶段方案的启发式方法来解决极端异构网格计算环境下的并行规则循环调度问题。
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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