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

Interactive global illumination on the CPU

Computing realistic physically-based global illumination in real-time remains one of the major goals in the fields of rendering and visualisation; one that has not yet been achieved due to its inherent computational complexity. This thesis focuses on CPU-based interactive global illumination approaches with an aim to develop generalisable hardware-agnostic algorithms. Interactive ray tracing is reliant on spatial and cache coherency to achieve interactive rates which conflicts with needs of global illumination solutions which require a large number of incoherent secondary rays to be computed. Methods that reduce the total number of rays that need to be processed, such as Selective rendering, were investigated to determine how best they can be utilised. The impact that selective rendering has on interactive ray tracing was analysed and quantified and two novel global illumination algorithms were developed, with the structured methodology used presented as a framework. Adaptive Inter- leaved Sampling, is a generalisable approach that combines interleaved sampling with an adaptive approach, which uses efficient component-specific adaptive guidance methods to drive the computation. Results of up to 11 frames per second were demonstrated for multiple components including participating media. Temporal Instant Caching, is a caching scheme for accelerating the computation of diffuse interreflections to interactive rates. This approach achieved frame rates exceeding 9 frames per second for the majority of scenes. Validation of the results for both approaches showed little perceptual difference when comparing against a gold-standard path-traced image. Further research into caching led to the development of a new wait-free data access control mechanism for sharing the irradiance cache among multiple rendering threads on a shared memory parallel system. By not serialising accesses to the shared data structure the irradiance values were shared among all the threads without any overhead or contention, when reading and writing simultaneously. This new approach achieved efficiencies between 77% and 92% for 8 threads when calculating static images and animations. This work demonstrates that, due to the flexibility of the CPU, CPU-based algorithms remain a valid and competitive choice for achieving global illumination interactively, and an alternative to the generally brute-force GPU-centric algorithms

MPI-parallelized Radiance on SGI CoW and SMP

. For lighting simulations in architecture there is the need for correct illumination calculation of virtual scenes. The Radiance Synthetic Imaging System delivers an excellent solution to that problem. Unfortunately, simulating complex scenes leads to long computation times even for one frame. This paper proposes a parallelization strategy which is suited for scenes with medium to high complexity to decrease calculation time. For a set of scenes the obtained speedup indicates the good performance of the chosen load balancing method. The use of MPI delivers a platform independent solution for clusters of workstations (CoWs) as well as for shared-memory multiprocessors (SMPs). 1 Introduction Both ray-tracing and radiosity represent a solution for one of the two main global lighting eects, specular and diuse interreection. To extend one of the two models to get a complete solution for arbitrary global lighting suers from long lasting calculations even for scenes with mediu..

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