Development and application of real-time and interactive software for complex system

Soft materials have attracted considerable interest in recent years for predicting the characteristics of phase separation and self-assembly in nanoscale structures. A popular method for demonstrating and simulating the dynamic behaviour of particles (e.g. particle tracking) and to consider effects of simulation parameters is cell dynamic simulation (CDS). This is a cellular computerisation technique that can be used to investigate different aspects of morphological topographies of soft material systems. The acquisition of quantitative data from particles is a critical requirement in order to obtain a better understanding and of characterising their dynamic behaviour. To achieve this objective particle tracking methods considering quantitative data and focusing on different properties and components of particles is essential. Despite the availability of various types of particle tracking used in experimental work, there is no method available to consider uniform computational data. In order to achieve accurate and efficient computational results for cell dynamic simulation method and particle tracking, two factors are essential: computing/calculating time-scale and simulation system size. Consequently, finding available computing algorithms and resources such as sequential algorithm for implementing a complex technique and achieving precise results is critical and rather expensive. Therefore, it is highly desirable to consider a parallel algorithm and programming model to solve time-consuming and massive computational processing issues. Hence, the gaps between the experimental and computational works and solving time consuming for expensive computational calculations need to be filled in order to investigate a uniform computational technique for particle tracking and significant enhancements in speed and execution times. The work presented in this thesis details a new particle tracking method for integrating diblock copolymers in the form of spheres with a shear flow and a novel designed GPU-based parallel acceleration approach to cell dynamic simulation (CDS). In addition, the evaluation of parallel models and architectures (CPUs and GPUs) utilising the mixtures of application program interface, OpenMP and programming model, CUDA were developed. Finally, this study presents the performance enhancements achieved with GPU-CUDA of approximately ~2 times faster than multi-threading implementation and 13~14 times quicker than optimised sequential processing for the CDS computations/workloads respectively

Path manipulation strategies for rendering dynamic environments.

The current work introduces path manipulation as a tool that extends bidirectional path tracing to reuse paths in the temporal domain. Defined as an apparatus of sampling and reuse strategies, path manipulation reconstructs the subpaths that compose the light transport paths and addresses the restriction of static geometry commonly associated with Monte Carlo light transport simulations. By reconstructing and reusing subpaths, the path manipulation algorithm obviates the regeneration of the entire path collection, reduces the computational load of the original algorithm and supports scene dynamism. Bidirectional path tracing relies on local path sampling techniques to generate the paths of light in a synthetic environment. By using the information localized at path vertices, like the probability distribution, the sampling techniques construct paths progressively with distinct probability densities. Each probability density corresponds to a particular sampling technique, which accounts for specific illumination effects. Bidirectional path tracing uses multiple importance sampling to combine paths sampled with different techniques in low-variance estimators. The path sampling techniques and multiple importance sampling are the keys to the efficacy of bidirectional path tracing. However, the sampling techniques gained little attention beyond the generation and evaluation of paths. Bidirectional path tracing was designed for static scenes and thus it discards the generated paths immediately after the evaluation of their contributions. Limiting the lifespan of paths to a generation-evaluation cycle imposes a static use of paths and of sampling techniques. The path manipulation algorithm harnesses the potential of the sampling techniques to supplant the static manipulation of paths with a generation-evaluation-reuse cycle. An intra-subpath connectivity strategy was devised to reconnect the segregated chains of the subpaths invalidated by the scene alterations. Successful intra-subpath connections generate subpaths in multiple pieces by reusing subpath chains from prior frames. Subpaths are reconstructed generically, regardless of the subpath or scene dynamism type and without the need for predefined animation paths. The result is the extension of bidirectional path tracing to the temporal domain