Performance Analysis for Large-Scale Parallel Microscopic Traffic Simulation System

Abstract

PMTS (Parallel Microscopic Traffic Simulation) is a large-scale microscopic traffic network simulation system using a real traffic network of Shanghai, China. It describes traffic events in object oriented mode, uses MPI (Message Passing Interface) as communicate middleware, partitions the simulation traffic network into subnetworks, and runs simulations of subnetworks concurrently on a cluster of processors connected by high-speed Ethernet. To optimize the performance of PMTS, a number of challenges need to be solved, including traffic network partition, subnetworks communication and synchronization, and workload balance. The parallelization of PMTS is domain decomposition, which means that the geographical region for simulation is decomposed into several domains of similar size and each processor of the PC cluster is responsible for a different geographical area. The partition method needs to fulfill two conditions to make it efficient: minimize the communication overhead and partition the subnetworks of the equal computation load. The goals of maximizing the parallelization and minimizing the communication overhead is conflict, and the tradeoff should be made. PVTM simulates the vehicles activities on the traffic network, and the computation overhead for one vehicle is certain. The time overhead on one processor depends on the number of vehicles for simulation. The individual simulation of vehicle activity includes: vehicle generation, vehicle running, and the vehicle going through the boundary zone. The derivation of the predictive performance is demonstrated and the calculation of the time cost for one processor with a certain number of vehicles is provided. In order to be efficient, the load on different processors should be as similar as possible. The load depends on the actual vehicle number on the respective processor that also varies as the simulation run. In each time step, the workload is collected for each processor. For the next iteration, the information will be fed back to the load-balancer, which will move the boundary of the grid to balance the vehicle numbers among the domains. The performance metrics of the simulation system mainly depend on the load balance, scalability, speedup, and efficiency. The performance optimization of PMTS has been proved to be effective when it is put into use and the experiment results are also provided which match the analysis.