The particle tracing method uses a stochastic approach for global illumination computation of three-dimensional environments. As with many graphics techniques the computation associated with the image generation is complex. Parallel processing offers the potential for solving the computationally complex particle tracing method more rapidly. Distributed memory parallel systems are scalable and readily available. However, large environmental models are often bigger than individual node storage capabilities requiring data management to distribute and control the movement of environmental data as computation proceeds. Prefetch data management attempts to reduce idle time associated with remote data fetches by anticipating the latency and requesting required data items prior to their actual use during computation. This paper demonstrates how attention to work division and supply coupled with prefetch data management can be utilised to minimise overheads associated with a parallel implementation and reduce overall image synthesis time.