Optimizing Agent-Based Simulations for the GPU
2018
会议录名称PROCEEDINGS 2018 INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING & SIMULATION (HPCS)
页码171-179
发表状态已发表
DOI10.1109/HPCS.2018.00042
摘要Agent-based simulation (ABS) is a powerful tool to analyze the behavior of agents interacting with each other. Many simulations contain a large number of agents or require multiple executions with different parameters, making the simulation-based experimentation slow. In recent years, graphics processing units (GPUs) have proven to be a powerful platform for accelerating ABS. In this paper, we propose several novel techniques to further improve the efficiency of GPU-based ABS. Our techniques reduce the total amount of computation in ABS, improve memory access patterns, and exploit temporal locality to minimize redundant calculations. Furthermore, the optimizations can be implemented as a layer on top of existing simulators, as we demonstrate by modifying the popular GPU-based simulator FLAME. We perform experiments using the Boids and Social Force simulations, and show that our techniques improve overall performance by up to 3.2x and 2.1x respectively compared to the original FLAME.
关键词Agent-based simulation GPU FLAME
出版地345 E 47TH ST, NEW YORK, NY 10017 USA
会议地点Orleans, France
会议日期16-20 July 2018
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收录类别CPCI ; CPCI-S ; EI
语种英语
WOS研究方向Computer Science ; Engineering
WOS类目Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号WOS:000450677700026
出版者IEEE
EI入藏号20184906170852
EI主题词Computer graphics ; Program processors ; Systems analysis
EI分类号Computer Applications:723.5 ; Systems Science:961
WOS关键词PARALLEL SIMULATION
原始文献类型Proceedings Paper
来源库IEEE
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文献类型会议论文
条目标识符https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/28978
专题信息科学与技术学院_PI研究组_范睿组
通讯作者Nguyen Quang Anh Pham
作者单位
1.Nanyang Technol Univ, Sch Engn & Comp Sci, Singapore, Singapore
2.ShanghaiTech Univ, Sch Informat Sci & Technol, Shanghai, Peoples R China
推荐引用方式
GB/T 7714
Nguyen Quang Anh Pham,Fan, Rui,Cai, Wentong. Optimizing Agent-Based Simulations for the GPU[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2018:171-179.
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