Collaborative High-fidelity Rendering over Peer-to-peer Networks

Abstract

Due to the computational expense of high-fidelity graphics, parallel and distributed systems have frequently been employed to achieve faster rendering times. The form of distributed computing used, with a few exceptions such as the use of GRID computing, is limited to dedicated clusters available to medium to large organisations. Recently, a number of applications have made use of shared resources in order to alleviate costs of computation. Peer-to-peer computing has arisen as one of the major models for off-loading costs from a centralised computational entity to benefit a number of peers participating in a common activity. This work introduces a peer-to-peer collaborative environment for improving rendering performance for a number of peers where the program state, that is the result of some computation among the participants, is shared. A peer that computes part of this state shares it with the others via a propagation mechanism based on epidemiology. In order to demonstrate this approach, the traditional Irradiance Cache algorithm is extended to account for sharing over a network within the presented collaborative framework introduced. Results, which show an overall speedup with little overheads, are presented for scenes in which a number of peers navigate shared virtual environments.