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Lookup NU author(s): Dr Gary Ushaw, Professor Graham MorganORCiD
This is the authors' accepted manuscript of a conference proceedings (inc. abstract) that has been published in its final definitive form by ACM, 2019.
For re-use rights please refer to the publisher's terms and conditions.
In this paper we propose a solution to delivering scalable real-time physics simulations. Although high performance computing simulations of physics related problems do exist, these are not real-time and do not model the real-time intricate interactions of rigid bodies for visual effect common in video games (favouring accuracy over real-time). As such, this paper presents the first approach to real-time delivery of scalable, commercial grade, video game quality physics. This is achieved by taking the physics engine out of the player's machine and deploying it across standard cloud based infrastructures. The simulation world is then divided into sections that are then allocated to servers. A server maintains the physics for all simulated objects in its section. Our contribution is the ability to maintain a scalable simulation by allowing object interaction across section boundaries using predictive migration techniques. We allow each object to project an aura that is used to determine object migration across servers to ensure seamless physics interactions between objects. The validity of our results is demonstrated through experimentation and benchmarking. Our approach allows player interaction at any point in real-time (influencing the simulation) in the same manner as any video game. We believe that this is the first successful demonstration of scalable real-time physics.
Author(s): Brown A, Ushaw G, Morgan G
Editor(s): Sheldon Andrews, Natalya Tatarchuk
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games
Year of Conference: 2019
Print publication date: 21/05/2019
Online publication date: 21/05/2019
Acceptance date: 15/02/2019
Date deposited: 04/03/2019
Publisher: ACM
URL: https://doi.org/10.1145/3306131.3317021
DOI: 10.1145/3306131.3317021
