Enhancing the Scalability of Simulations by Embracing Multiple Levels of Parallelization

Infinity Pub Date : 2010-09-30 DOI:10.1109/PDMC-HIBI.2010.17
J. Himmelspach, Roland Ewald, Stefan Leye, A. Uhrmacher
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引用次数: 13

Abstract

Current and upcoming architectures of desktop and high performance computers offer increasing means for parallel execution. Since the computational demands induced by ever more realistic models increase steadily, this trend is of growing importance for systems biology. Simulations of these models may involve the consideration of multiple parameter combinations, their replications, data collection, and data analysis - all of which offer different opportunities for parallelization. We present a brief theoretical analysis of these opportunities in order to show their potential impact on the overall computation time. The benefits of using more than one opportunity for parallelization are illustrated by a set of benchmark experiments, which furthermore show that parallelizability should be exploited in a flexible manner to achieve speedup.
通过采用多层并行化来增强仿真的可扩展性
当前和即将到来的桌面和高性能计算机体系结构为并行执行提供了越来越多的手段。由于越来越现实的模型引起的计算需求稳步增长,这一趋势对系统生物学越来越重要。这些模型的模拟可能涉及考虑多个参数组合、它们的复制、数据收集和数据分析——所有这些都为并行化提供了不同的机会。我们对这些机会进行了简要的理论分析,以显示它们对总体计算时间的潜在影响。通过一组基准实验说明了使用多个并行机会的好处,这些实验进一步表明,应该以灵活的方式利用并行性来实现加速。
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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来源期刊
CiteScore
2.30
自引率
0.00%
发文量
26
审稿时长
10 weeks
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