GPU Generation of Large Varied Animated Crowds

Isaac Rudomin, Benjamín Hernández, Oriam de Gyves, Leonel Toledo, Ivan Rivalcoba, Sergio Ruiz

Abstract


We discuss several steps in the process of simulating and visualizing large and varied crowds in real time for consumer-level computers and graphic cards (GPUs). Animating varied crowds using a diversity of models and animations (assets) is complex and costly. One has to use models that are expensive if bought, take a long time to model, and consume too much memory and computing resources. We discuss methods for simulating, generating, animating and rendering crowds of varied aspect and a diversity of behaviors. Efficient simulations run in low cost systems because we use the power of modern programmable GPUs. One can apply similar technology using GPU clusters and HPC for large scale problems. Such systems scale up almost linearly by using multiple nodes. One must combine parallel simulation and parallel rendering in the cluster with interaction and final rendering in lighter clients. However, in view of the latest developments such as the new family of mobile multicore chipsets and GPU-based cloud gaming platforms, the pieces are almost there for this kind of architecture to work.

Keywords


Simulation, real-time crowds, rendering and animation.

Full Text: PDF