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The Read-Copy Update ( RCU) synchronization method was designed to cope with multiprocessor scalability some years ago, and it was included in the Linux kernel October of 2002. Recently, libraries providing user-space access to this method have been released, although they still have not been used in complex applications. In this paper, we propose the evaluation of the RCU synchronization method for two different cases of use in a distributed system architecture for crowd simulations. We have compared the RCU implementation with a parallel implementation based on Mutex, a traditional locking synchronization method for solving race conditions among threads in parallel applications. The performance evaluation results show that the use of RCU significantly decreases the system response time and increases the system throughput, supporting a higher number of agents while providing the same latency levels. The reason for this behavior is that the RCU method allows read accesses in parallel with write accesses to dynamic data structures, avoiding the sequential access that a Mutex represents for these data structures. In this way, it can better exploit the existing number of processor cores. These results show the potential of this synchronization method for improving parallel and distributed applications. [ABSTRACT FROM AUTHOR]

The simulation of large crowds of autonomous agents with a realistic behavior is still a challenge for several computer research communities. Distributed architectures can provide scalability to crowd simulations, but they require the use of efficient partitioning methods. Although convex hulls have been shown as very efficient structures for crowd partitioning, providing efficient workload balancing to large scale simulations is still an open issue. In this paper, we propose the integration of a workload balancing technique for crowd simulations within a partitioning method based on convex hulls. The region-based balancing technique reassigns agents to servers using a criterion of distance. The performance evaluation results show that this technique ensures the saturation avoidance of the servers in an homogeneous distributed system. This feature can increase the scalability of crowd simulations. [ABSTRACT FROM AUTHOR]