Big fast crowds on PS3

Crowds and other flock-like group motion are often modeled as interacting particle systems. These multi-agent simulations are computationally expensive because each agent must consider all of the others, if only to identify its neighbors. For large crowds, simple implementations are too slow since computation grows as the square of agent population. Faster approaches often rely on spatial hashing where a partitioning of space is used to accelerate crowd simulation. This same partitioning can form the basis of a scalable multi-processor approach to large, fast crowd simulations, as in [Quinn et al. 2003]. This paper describes an implementation of that approach for PLAYSTATION®3 which supports simulation and display of simple crowds of up to 15,000 individuals at 60 frames per second.

[1]  Eric Bouvier,et al.  From crowd simulation to airbag deployment: particle systems, a new paradigm of simulation , 1997, J. Electronic Imaging.

[2]  Craig W. Reynolds.  Interaction with Groups of Autonomous Characters , 2000 .

[3]  Francis H. Harlow,et al.  The Particle-And-Force Computing Method for Fluid Dynamics , 1961 .

[4]  Anthony Steed,et al.  Partitioning crowded virtual environments , 2003, VRST '03.

[5]  F. H. Harlow,et al.  Human collective dynamics: Two groups in adversarial encounter. [melete code] , 1988 .

[6]  Franco Tecchia,et al.  Agent Behaviour Simulator (ABS):a platform for urban behaviour development , 2001 .

[7]  Karl Sims,et al.  Particle animation and rendering using data parallel computation , 1990, SIGGRAPH.

[8]  Demetri Terzopoulos,et al.  Autonomous pedestrians , 2005, SCA '05.

[9]  J. Monaghan,et al.  Smoothed particle hydrodynamics: Theory and application to non-spherical stars , 1977 .

[10]  Jaswinder Pal Singh.  Dynamic Load Balancing for Cluster Computing , 2005 .

[11]  Michael B. Dillencourt,et al.  Load balancing in individual-based spatial applications , 1998, Proceedings. 1998 International Conference on Parallel Architectures and Compilation Techniques (Cat. No.98EX192).

[12]  Nicolas Courty,et al.  Simulation of large crowds in emergency situations including gaseous phenomena , 2005, International 2005 Computer Graphics.

[13]  Vittorio Scarano,et al.  Massive Simulation using GPU of a distributed behavioral model of a flock with obstacle avoidance , 2004, VMV.

[14]  Yizhou Yu,et al.  Particle-based simulation of granular materials , 2005, SCA '05.

[15]  Bo Zhou,et al.  Parallel simulation of group behaviors , 2004, Proceedings of the 2004 Winter Simulation Conference, 2004..

[16]  Michael J. Quinn,et al.  PARALLEL IMPLEMENTATION OF THE SOCIAL FORCES MODEL , 2003 .

[17]  Efficient Navigation Mesh Implementation , 2004, J. Game Dev..

[18]  Miha Mraz,et al.  Simulating flocks on the wing: the fuzzy approach. , 2005, Journal of Theoretical Biology.

[19]  N. Badler,et al.  Crowd simulation incorporating agent psychological models, roles and communication , 2005 .

[20]  Francis H. Harlow,et al.  The Particle-In-Cell Method for Hydrodynamic Calculations , 1957 .

[21]  Markus H. Gross,et al.  Optimized Spatial Hashing for Collision Detection of Deformable Objects , 2003, VMV.

[22]  S. Asano,et al.  The design and implementation of a first-generation CELL processor , 2005, ISSCC. 2005 IEEE International Digest of Technical Papers. Solid-State Circuits Conference, 2005..

[23]  Adrien Treuille,et al.  Continuum crowds , 2006, SIGGRAPH 2006.

[24]  Steve Plimpton,et al.  Fast parallel algorithms for short-range molecular dynamics , 1993 .

[25]  Craig W. Reynolds.  Flocks, herds, and schools: a distributed behavioral model , 1998 .

[26]  Fachbereich Informatik,et al.  Parallel Bird Flocking Simulation , 1993 .