...
首页> 外文期刊>Journal of Computational and Applied Mathematics >Experimental study of scheduling with memory constraints using hybrid methods
【24h】

Experimental study of scheduling with memory constraints using hybrid methods

机译:混合约束条件下内存约束调度的实验研究

获取原文
获取原文并翻译 | 示例
           

摘要

In this paper we study divisible load scheduling in systems with limited memory. Divisible loads are parallel computations which can be divided into independent parts processed in parallel on remote computers, and the part sizes may be arbitrary. The distributed system is a heterogeneous single level tree. The total size of processor memories is too small to accommodate the whole load at any moment of time. Therefore, the load is distributed in many rounds. Memory reservations have block nature. The problem consists in distributing the load taking into account communication time, computation time, and limited memory buffers so that the whole processing finishes as early as possible. This problem is both combinatorial and algebraic in nature. Therefore, hybrid algorithms are given to solve it. Two algorithms are proposed to solve the combinatorial component. A branch-and-bound algorithm is nearly unusable due to its complexity. Then, a genetic algorithm is proposed with more tractable execution times. For a given solution of the combinatorial part we formulate the solution of the algebraic part as a linear programming problem. An extensive computational study is performed to analyze the impact of various system parameters on the quality of the solutions. From this we were able to infer on the nature of the scheduling problem.
机译:在本文中,我们研究了内存有限的系统中的可分割负载调度。可分割的载荷是并行计算,可以分为在远程计算机上并行处理的独立零件,零件大小可以是任意的。分布式系统是异构单级树。处理器内存的总大小太小,无法在任何时候容纳全部负载。因此,负荷分布在许多回合中。内存保留具有块性质。问题在于要考虑通信时间,计算时间和有限的内存缓冲区来分配负载,以使整个处理尽可能早地完成。这个问题本质上既是组合的又是代数的。因此,给出了混合算法来解决。提出了两种算法来求解组合分量。分支定界算法由于其复杂性而几乎无法使用。然后,提出了一种具有更易于执行时间的遗传算法。对于组合部分的给定解,我们将代数部分的解公式化为线性规划问题。进行了广泛的计算研究,以分析各种系统参数对解决方案质量的影响。由此我们可以推断出调度问题的性质。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号