Abstract
This research project delves into the performance impact of implementing parallel programming techniques in physics engine applications. With the advent of multi-core processors in contemporary computing environments, optimizing physics simulations through parallel programming has become increasingly feasible. A conventional blob collision physics engine serves as the benchmark for evaluation, and its performance is juxtaposed against a parallel-programmed variant. Experimental findings indicate a significant reduction in computational time required for collision detection and response when parallel processing is employed. This efficiency gain is particularly pronounced in scenarios involving a large number of blobs, showcasing the scalability advantages of parallelization. Moreover, parallel programming facilitates optimal harnessing of multi-core processor capabilities, thereby enhancing the overall efficiency and performance of the physics engine in question. This study not only substantiates the technical merits of applying parallel programming but also illuminates the practical benefits, including resource-efficient operation and quicker simulation times. Consequently, the research provides valuable insights for developers and engineers aiming to fully exploit the capabilities of modern computing hardware in physics-based simulations and applications.
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