Efficient Simulation of Sparse Graphs of Point Processes

IF 0.7 4区计算机科学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

ACM Transactions on Modeling and Computer Simulation Pub Date : 2023-02-28 DOI:https://dl.acm.org/doi/10.1145/3565809

Cyrille Mascart, David Hill, Alexandre Muzy, Patricia Reynaud-Bouret

引用次数: 0

Abstract

We derive new discrete event simulation algorithms for marked time point processes. The main idea is to couple a special structure, namely the associated local independence graph, as defined by Didelez, with the activity tracking algorithm of Muzy for achieving high-performance asynchronous simulations. With respect to classical algorithms, this allows us to drastically reduce the computational complexity, especially when the graph is sparse.

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点过程稀疏图的高效模拟

我们为标记时间点过程导出了新的离散事件模拟算法。其主要思想是将Didelez定义的特殊结构(即关联的局部独立图)与Muzy的活动跟踪算法相结合，以实现高性能的异步仿真。与经典算法相比，这使我们能够大大降低计算复杂度，特别是当图是稀疏的时候。

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

ACM Transactions on Modeling and Computer Simulation 工程技术-计算机：跨学科应用

CiteScore

2.50

自引率

22.20%

发文量

审稿时长

>12 weeks

期刊介绍： The ACM Transactions on Modeling and Computer Simulation (TOMACS) provides a single archival source for the publication of high-quality research and developmental results referring to all phases of the modeling and simulation life cycle. The subjects of emphasis are discrete event simulation, combined discrete and continuous simulation, as well as Monte Carlo methods. The use of simulation techniques is pervasive, extending to virtually all the sciences. TOMACS serves to enhance the understanding, improve the practice, and increase the utilization of computer simulation. Submissions should contribute to the realization of these objectives, and papers treating applications should stress their contributions vis-á-vis these objectives.