A Scalable Architecture for Crowd Simulation: Implementing a Parallel Action Server

Vigueras, Guillermo; Lozano, Miguel; Perez, C.; Ordua, J.M.

doi:10.1109/icpp.2008.20

Cited by 15 publications

(16 citation statements)

References 12 publications

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“…In previous papers, we proposed a scalable architecture for crowd simulations that can manage large crowds of autonomous agents at interactive rates [6,16]. For illustration purposes, Figure 1 shows a scheme of this architecture.…”

Section: Introductionmentioning

confidence: 98%

Improving the Performance of Partitioning Methods for Crowd Simulations

Vigueras

Lozano

Ordua

et al. 2008

2008 Eighth International Conference on Hybrid Intelligent Systems

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Simulating the realistic behavior of large crowds of autonomous agents is still a challenge for the computer graphics community. In order to handle large crowds, some scalable architectures have been proposed. Nevertheless, the effective use of distributed systems requires the use of partitioning methods that can properly assign different sets of agents to the existing distributed resources.In this paper, we propose the improvement of the partitioning method for distributed crowd simulations by using irregular shape regions. Concretely, we propose the partition of the virtual world using convex hulls. The performance evaluation results show that the Convex Hull method outperforms the rest of the considered methods in terms of both fitness function values and execution times, regardless of the movement pattern followed by the agents. These results show that the shape of the regions in the partition can improve the performance of the partitioning method, rather than the heuristic method used.

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Section: Introductionmentioning

confidence: 98%

Improving the Performance of Partitioning Methods for Crowd Simulations

Vigueras

Lozano

Ordua

et al. 2008

2008 Eighth International Conference on Hybrid Intelligent Systems

Self Cite

View full text Add to dashboard Cite

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“…The simulation world was partitioned into subregions and each one assigned to one parallel AS. A scheme of this architecture [15] is shown in Fig. 1.…”

Section: Introductionmentioning

confidence: 99%

Workload balancing in distributed crowd simulations: the partitioning method

2009

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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.

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“…In a previous work, a distributed system architecture for crowd simulation was proposed in order to take advantage of the underlying distributed computer system [16]. That software architecture is mainly composed by two elements: the action server (AS) and the client processes (CP).…”

Section: A Gpu-based Action Server For Crowd Simulationmentioning

confidence: 99%

“…The most important performance measurements in distributed systems are latency and throughput [2]. The performance improvement that a GPU-based server can provide to the distributed crowd simulation [16] would depend on the number of distributed servers in the system. In order to evaluate the worst case, we have performed simulations with one server and with different number of agents.…”

Section: Performance Evaluationmentioning

confidence: 99%

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A GPU-Based Multi-agent System for Real-Time Simulations

Vigueras

Orduña

Lozano

2010

Advances in Intelligent and Soft Computing

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The huge number of cores existing in current Graphics Processor Units (GPUs) provides these devices with computing capabilities that can be exploited by distributed applications. In particular, these capabilites have been used in crowd simulations for enhancing the crowd rendering, and even for simulating continuum crowds. However, GPUs have not been used for simulating large crowds of complex agents, since these simulations require distributed architectures that can support huge amounts of agents. In this paper, we propose a GPU-based multi-agent system for crowd simulation. Concretely, we propose the use of an on-board GPU to implement some of the tasks that a distributed server for crowd simulations should perform. The huge number of cores in the GPU is used to simultaneously validate movement requests from different agents, greatly reducing the server response time. Since this task represents the critical data path, the use of this hardware significantly increases the parallelism achieved with respect to the implementation of the same distributed server on a CPU. An application example shows that the system can support agents with complex navigational behaviors.

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A Scalable Architecture for Crowd Simulation: Implementing a Parallel Action Server

Cited by 15 publications

References 12 publications

Improving the Performance of Partitioning Methods for Crowd Simulations

Improving the Performance of Partitioning Methods for Crowd Simulations

Workload balancing in distributed crowd simulations: the partitioning method

A GPU-Based Multi-agent System for Real-Time Simulations

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