平行天际线求解器的性能预测及其在大型结构分析中的实现

Sang Y. Synn, Robert E. Fulton
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引用次数: 6

摘要

本文提出了在两台机器(BBN, KSRI)上使用两种不同的内存方案(全局共享、共享/本地内存)来预测并行天际线求解器时间复杂度的简化公式。计算公式考虑了数值运算次数和数据通信费用。在此基础上,提出了一种涵盖子结构分析初始计算阶段和重计算阶段的处理器映射算法,并对两种实际结构模型的并行全局方法和并行子结构方法的性能进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The performance prediction of a parallel skyline solver and its implementation for large scale structure analysis

In this paper, we propose simplified formulas to predict the time complexity in a parallel skyline solver using two different memory schemes (Global Shared, Shared/Local memory) on two machines (BBN, KSRI). Numerical operation counts and data communication costs are considered for the formulas. Based on these formulas, we developed a processor mapping algorithm to cover the initial computation stage and the recomputation stage of substructure analysis, and also compared the performances of parallel global approach and parallel substructure approach for two practical structure models.

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