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Learn to develop GPU-accelerated physics simulations on manifolds using Julia in this conference talk that addresses the dual challenges of understanding complex physical systems and overcoming computational limitations. Discover how a research team tackled slow, computationally demanding simulations by exploring GPU acceleration while managing the complexities of parallelism and performance optimization. Explore a comprehensive framework designed for modeling complex physical phenomena on manifolds with emphasis on precision, scalability, and usability, including practical examples such as fluid dynamics on spheres and tori, transport phenomena like diffusion and flow processes in manifold geometries, particle interactions in granular systems studying collisions and clustering, geodesic motion simulations analyzing particle dynamics on non-Euclidean spaces, and coupled processes in multiphysics environments including active matter systems and electromagnetic field interactions. Understand how this project contributes to Julia's GPU computing ecosystem by providing accessible tools that lower technical barriers and encourage adoption of GPU programming while showcasing Julia's capabilities in high-performance parallel computing for diverse computational physics applications.
