异构机器上优先级约束应用的最优调度

A. Santiago, Carlos Soto, H. Fraire, B. Dorronsoro
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引用次数: 2

摘要

图形抽象抽象。高性能计算(HPC)是当今技术社会日益增长的需求,高性能计算需要高负载的并行计算任务,优化并行应用任务调度是满足用户需求的首要任务。分支定界算法(BB)和数学规划(MP)以最优的方式解决复杂的优化问题,一些分支定界算法或数学规划(MP)甚至具有并行计算能力,使其成为解决现实问题的合适方法。在本文中,我们提出了两种精确的算法,一个BB和一个MP模型,用于调度优先级约束的应用程序,在异构计算系统上,据我们所知,这是目前最先进的同类算法。这项工作的一个主要贡献是在两种方法中提出了目标函数的公式。实验结果从文献中得到了20多个适合合成应用的最优值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal Scheduling for Precedence-Constrained Applications on Heterogeneous Machines
Graphical Abstract Abstract. High-Performance Computing (HPC) is a growing necessity of our technological society, HPC demands high loads of parallel computing jobs, an optimal scheduling of the parallel applications tasks is a priority to meet the demands of its users on time. Branch-and-bound (BB) Algorithms and Mathematical Programming (MP) solve complex optimization problems in an optimal manner, some MP or BB even have parallel computing capabilities, making them suitable solutions to solve realworld problems. In this paper, we propose two exact algorithms, a BB and an MP Model for scheduling precedence-constrained applications, on heterogeneous computing systems, as far as we known the first ones on his kind presented in the state of the art. One major contribution of the work is the proposed formulations of the objective function in both methods. Experimental results obtained more than twenty optimal values for synthetic applications from the literature.
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