TY - GEN
T1 - A Graph partitioning algorithm for parallel agent-based road traffic simulation
AU - Xu, Yadong
AU - Cai, Wentong
AU - Eckhoff, David
AU - Nair, Suraj
AU - Knoll, Alois
N1 - Publisher Copyright:
© 2017 ACM.
PY - 2017/5/16
Y1 - 2017/5/16
N2 - A common approach of parallelising an agent-based road traffic simulation is to partition the road network into sub-regions and assign computations for each subregion to a logical process (LP). Inter-process communication for synchronisation between the LPs is one of the major factors that affect the performance of parallel agent-based road traffic simulation in a distributed memory environment. Synchronisation overhead, i.e., the number of messages and the communication data volume exchanged between LPs, is heavily dependent on the employed road network partitioning algorithm. In this paper, we propose Neighbour-Restricting Graph-Growing (NRGG), a partitioning algorithm which tries to reduce the required communication between LPs by minimising the number of neighbouring partitions. Based on a road traffic simulation of the city of Singapore, we show that our method not only outperforms graph partitioning methods such as METIS and Buffoon, for the synchronisation protocol used, but also is more resilient than stripe spatial partitioning when partitions are cut more finely.
AB - A common approach of parallelising an agent-based road traffic simulation is to partition the road network into sub-regions and assign computations for each subregion to a logical process (LP). Inter-process communication for synchronisation between the LPs is one of the major factors that affect the performance of parallel agent-based road traffic simulation in a distributed memory environment. Synchronisation overhead, i.e., the number of messages and the communication data volume exchanged between LPs, is heavily dependent on the employed road network partitioning algorithm. In this paper, we propose Neighbour-Restricting Graph-Growing (NRGG), a partitioning algorithm which tries to reduce the required communication between LPs by minimising the number of neighbouring partitions. Based on a road traffic simulation of the city of Singapore, we show that our method not only outperforms graph partitioning methods such as METIS and Buffoon, for the synchronisation protocol used, but also is more resilient than stripe spatial partitioning when partitions are cut more finely.
KW - Agent-based traffic simulation
KW - Graph partitioning
KW - Neighbour-Restricting Graph-Growing
KW - Parallel simulation
UR - http://www.scopus.com/inward/record.url?scp=85020697220&partnerID=8YFLogxK
U2 - 10.1145/3064911.3064914
DO - 10.1145/3064911.3064914
M3 - Conference contribution
AN - SCOPUS:85020697220
T3 - SIGSIM-PADS 2017 - Proceedings of the 2017 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation
SP - 209
EP - 219
BT - SIGSIM-PADS 2017 - Proceedings of the 2017 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation
PB - Association for Computing Machinery, Inc
T2 - 5th ACM SIGSIM Conference on Principles of Advanced Discrete Simulation, SIGSIM-PADS 2017
Y2 - 24 May 2017 through 26 May 2017
ER -