Performance improvements of real-time crowd simulations

The current challenge for crowd simulations is the design and development of a scalable system that is capable of simulating the individual behavior of millions of complex agents populating large scale virtual worlds with a good frame rate. In order to overcome this challenge, this thesis proposes different improvements for crowd simulations. Concretely, we propose a distributed software architecture that can take advantage of the existing distributed and multi-core architectures. In turn, the use of these distributed architectures requires partitioning strategies and workload balancing techniques for distributed crowd simulations. Also, these architectures allow the use of GPUs not only for rendering images but also for computing purposes. Finally, the design and implementation of distributed visual clients is another research topic that can help to overcome this challenge.