The Video Game industry is maturing. Success in the video game industry relies on many things, including marketing, sound business practises, and top notch technical implementation. Games Engines are software systems that facilitate game production. The growth of the game industry has increased the demand for programmers trained in game development technologies. A simplified game engine, designed specifically for the game development courses which service the supply of graduates for the industry, could have many advantages. This dissertation analysed the requirements of such a system. We found that such a game engine would need to be extensible, reusable, modular, be easy to learn, and be open source. It would also need to at least include graphics, audio, networking and pathfinding components. Our analysis found that no game engine currently exists that fulfills all these requirements. We designed and implemented a game engine to fulll all these requirements. Our game engine is built around a module framework, where each task of the game engine is handled by a module. This modular design allows us to easily change functionality by adding, removing or updating modules. All source code of the engine is available, thus any part of the engine can be changed if needed. Open source also means the engine is free for all to use. Game engines also need to be reusable so that in the industry the development costs of creating an engine can be amortised multiple projects, but also in a university context it means that time students can continue to use the system across multiple projects. The system was tested by having students complete game development tasks using our game engine, ModEngine, and another comparable game engine. We used lines of code as a measure of code complexity and completion time as a measure of performance. We found that there is a statistically significant reduction in both the lines of code and the completion time of student's ModEngine assignments versus the comparison. Our p value (the probability that the data was due to chance alone) for lines of code is 9.662776 X 10^(-5) and for completion time is 0.018. Students were also given questionnaires to complete where they were asked about their experience using both engines. ModEngine was found to be easier to learn and was simpler to use; students can more easily explore game development concepts with ModEngine and can get started working with it much more easily.

The Weighted Histogram Analysis Method (WHAM) is a technique used to calculate free energy from molecular simulation data. WHAM recombines biased distributions of samples from multiple Umbrella Sampling simulations to yield an estimate of the global unbiased distribution. The WHAM algorithm iterates two coupled, non-linear, equations, until convergence at an acceptable level of accuracy. The equations have quadratic time complexity for a single reaction coordinate. However, this increases exponentially with the number of reaction coordinates under investigation, which makes multidimensional WHAM a computationally expensive procedure. There is potential to use general purpose graphics processing units (GPGPU) to accelerate the execution of the algorithm. Here we develop and evaluate a multidimensional GPGPU WHAM implementation to investigate the potential speed-up attained over its CPU counterpart. In addition, to avoid the cost of multiple Molecular Dynamics simulations and for validation of the implementations we develop a test system to generate samples analogous to Umbrella Sampling simulations. We observe a maximum problem size dependent speed-up of approximately 19 for the GPGPU optimized WHAM implementation over our single threaded CPU optimized version. We find that the WHAM algorithm is amenable to GPU acceleration, which provides the means to study ever more complex molecular systems in reduced time periods.