Towards a Performance-Aware Partitioning Algorithm for Cloud-Based Microscopic Vehicle Traffic Simulations

被引:0
|
作者
Siguenza-Torres, Anibal [1 ]
Cai, Wentong [2 ]
Knoll, Alois [3 ]
机构
[1] Tech Univ Munich, Huawei Munich Res Ctr, Munich, Germany
[2] Nanyang Technol Univ, Singapore, Singapore
[3] Tech Univ Munich, Munich, Germany
关键词
D O I
10.1145/3573900.3593629
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Distributed computing is one of the ways to scale up agent-based microscopic vehicle traffic simulations. A key factor for performance is the partitioning of the road network providing computation load balancing and minimizing communication cost. Many approaches use the number of agents as proxy to estimate the computational and communication costs, assuming a direct relation. However this assumption does not hold in a heterogeneous computing environment, e.g. on the cloud. This work discusses a novel proposal to improve the prediction of the computational and communication costs by using information of the simulation's run-time environment. Preliminary evidence indicates that making the partitioning performance-aware results in higher performance.
引用
收藏
页码:44 / 45
页数:2
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