Adaptive Synchronization and Pacing Control for Visual Interactive Simulation

IF 0.7 4区 计算机科学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS ACM Transactions on Modeling and Computer Simulation Pub Date : 2024-06-19 DOI:10.1145/3673898
Zhuoxiao Meng, Mingyue Gao, Margherita Grossi, Anibal Siguenza-Torres, Stefano Bortoli, Christoph Sommer, Alois Knoll
{"title":"Adaptive Synchronization and Pacing Control for Visual Interactive Simulation","authors":"Zhuoxiao Meng, Mingyue Gao, Margherita Grossi, Anibal Siguenza-Torres, Stefano Bortoli, Christoph Sommer, Alois Knoll","doi":"10.1145/3673898","DOIUrl":null,"url":null,"abstract":"<p>Parallel and distributed computing enable the execution of large and complex simulations. Yet, the usual separation of (headless) simulation execution and (subsequent, offline) output analysis often renders the simulation endeavor long and inefficient. Recently, Visual Interactive Simulation (VIS) tools and methods that address this end-to-end efficiency are gaining relevance, offering <i>in-situ</i> visualization, real-time debugging, and computational steering. Here, the typically distributed computing nature of the simulation execution poses synchronization challenges between the headless simulation engine and the user-facing frontend required for Visual Interactive Simulation. To the best of our knowledge, state-of-the-art synchronization approaches fall short due to their rigidity and inability to adapt to real-time user-centric changes. This paper introduces a novel adaptive algorithm to dynamically adjust the simulation’s pacing through a buffer-based framework, informed by predictive workload analysis. Our extensive experimental evaluation across diverse synthetic scenarios illustrates our method’s effectiveness in enhancing runtime efficiency and synchronicity, significantly reducing end-to-end time while minimizing user interaction delays, thereby addressing key limitations of existing synchronization strategies.</p>","PeriodicalId":50943,"journal":{"name":"ACM Transactions on Modeling and Computer Simulation","volume":null,"pages":null},"PeriodicalIF":0.7000,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Modeling and Computer Simulation","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1145/3673898","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

Abstract

Parallel and distributed computing enable the execution of large and complex simulations. Yet, the usual separation of (headless) simulation execution and (subsequent, offline) output analysis often renders the simulation endeavor long and inefficient. Recently, Visual Interactive Simulation (VIS) tools and methods that address this end-to-end efficiency are gaining relevance, offering in-situ visualization, real-time debugging, and computational steering. Here, the typically distributed computing nature of the simulation execution poses synchronization challenges between the headless simulation engine and the user-facing frontend required for Visual Interactive Simulation. To the best of our knowledge, state-of-the-art synchronization approaches fall short due to their rigidity and inability to adapt to real-time user-centric changes. This paper introduces a novel adaptive algorithm to dynamically adjust the simulation’s pacing through a buffer-based framework, informed by predictive workload analysis. Our extensive experimental evaluation across diverse synthetic scenarios illustrates our method’s effectiveness in enhancing runtime efficiency and synchronicity, significantly reducing end-to-end time while minimizing user interaction delays, thereby addressing key limitations of existing synchronization strategies.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
视觉交互仿真的自适应同步和步调控制
并行和分布式计算使大型复杂仿真得以执行。然而,(无头)仿真执行和(随后的离线)输出分析通常是分离的,这往往导致仿真工作时间长、效率低。近来,可视化交互仿真(VIS)工具和方法越来越受到重视,它们提供了现场可视化、实时调试和计算引导功能,从而提高了端到端的效率。在这里,仿真执行的典型分布式计算特性给无头仿真引擎和可视化交互仿真所需的面向用户的前端之间的同步带来了挑战。据我们所知,最先进的同步方法由于僵化和无法适应以用户为中心的实时变化而存在不足。本文介绍了一种新颖的自适应算法,可通过基于缓冲区的框架动态调整仿真步调,并以预测性工作量分析为依据。我们在各种合成场景中进行了广泛的实验评估,结果表明我们的方法能有效提高运行效率和同步性,在最大限度减少用户交互延迟的同时显著缩短端到端时间,从而解决了现有同步策略的主要局限性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
ACM Transactions on Modeling and Computer Simulation
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
29
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.
期刊最新文献
Reproducibility Report for the Paper "Performance Evaluation of Spintronic-Based Spiking Neural Networks Using Parallel Discrete-Event Simulation" Data Farming the Parameters of Simulation-Optimization Solvers Modeling of biogas production from hydrothermal carbonization products in a continuous anaerobic digester. Optimized Real-Time Stochastic Model of Power Electronic Converters based on FPGA Virtual Time III, Part 3: Throttling and Message Cancellation
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1