Time-constrained high-fidelity rendering on local desktop grids

Parallel computing has been frequently used for reducing the rendering time of high-fidelity images, since the generation of such images has a high computational cost. Numerous algorithms have been proposed for parallel rendering but they primarily focus on utilising shared memory machines or dedicated distributed clusters. A local desktop grid, composed of arbitrary computational resources connected to a network such as those in a lab or an enterprise, provides an inexpensive alternative to dedicated clusters. The computational power offered by such a desktop grid is time-variant as the resources are not dedicated. This paper presents fault-tolerant algorithms for rendering high-fidelity images on a desktop grid within a given time-constraint. Due to the dynamic nature of resources, the task assignment does not rely on subdividing the image into tiles. Instead, a progressive approach is used that encompasses aspects of the entire image for each task and ensures that the time-constraints are met. Traditional reconstruction techniques are used to calculate the missing data. This approach is designed to avoid redundancy to maintain time-constraints. As a further enhancement, the algorithm decomposes the computation into components representing different tasks to achieve better visual quality considering the time-constraint and variable resources. This paper illustrates how the component-based approach maintains a better visual fidelity considering a given time-constraint while making use of volatile computational resources

High-fidelity rendering on shared computational resources

The generation of high-fidelity imagery is a computationally expensive process and parallel computing has been traditionally employed to alleviate this cost. However, traditional parallel rendering has been restricted to expensive shared memory or dedicated distributed processors. In contrast, parallel computing on shared resources such as a computational or a desktop grid, offers a low cost alternative. But, the prevalent rendering systems are currently incapable of seamlessly handling such shared resources as they suffer from high latencies, restricted bandwidth and volatility. A conventional approach of rescheduling failed jobs in a volatile environment inhibits performance by using redundant computations. Instead, clever task subdivision along with image reconstruction techniques provides an unrestrictive fault-tolerance mechanism, which is highly suitable for high-fidelity rendering. This thesis presents novel fault-tolerant parallel rendering algorithms for effectively tapping the enormous inexpensive computational power provided by shared resources. A first of its kind system for fully dynamic high-fidelity interactive rendering on idle resources is presented which is key for providing an immediate feedback to the changes made by a user. The system achieves interactivity by monitoring and adapting computations according to run-time variations in the computational power and employs a spatio-temporal image reconstruction technique for enhancing the visual fidelity. Furthermore, algorithms described for time-constrained offline rendering of still images and animation sequences, make it possible to deliver the results in a user-defined limit. These novel methods enable the employment of variable resources in deadline-driven environments

High-fidelity graphics using unconventional distributed rendering approaches

High-fidelity rendering requires a substantial amount of computational resources to accurately simulate lighting in virtual environments. While desktop computing, with the aid of modern graphics hardware, has shown promise in delivering realistic rendering at interactive rates, real-time rendering of moderately complex scenes is still unachievable on the majority of desktop machines and the vast plethora of mobile computing devices that have recently become commonplace. This work provides a wide range of computing devices with high-fidelity rendering capabilities via oft-unused distributed computing paradigms. It speeds up the rendering process on formerly capable devices and provides full functionality to incapable devices. Novel scheduling and rendering algorithms have been designed to best take advantage of the characteristics of these systems and demonstrate the efficacy of such distributed methods. The first is a novel system that provides multiple clients with parallel resources for rendering a single task, and adapts in real-time to the number of concurrent requests. The second is a distributed algorithm for the remote asynchronous computation of the indirect diffuse component, which is merged with locally-computed direct lighting for a full global illumination solution. The third is a method for precomputing indirect lighting information for dynamically-generated multi-user environments by using the aggregated resources of the clients themselves. The fourth is a novel peer-to-peer system for improving the rendering performance in multi-user environments through the sharing of computation results, propagated via a mechanism based on epidemiology. The results demonstrate that the boundaries of the distributed computing typically used for computer graphics can be significantly and successfully expanded by adapting alternative distributed methods