Abstract
Position Based Dynamics is the most popular approach for simulating dynamic systems in computer graphics. However, volume rendering with linear deformation times is still a challenge in virtual scenes. In this work, we implemented Graphics Processing Unit (GPU)-based Position-Based Dynamics to iMSTK, an open-source toolkit for rapid prototyping interactive multi-modal surgical simulation. We utilized NVIDIA’s CUDA toolkit for this implementation and carried out vector calculations on GPU kernels while ensuring that threads do not overwrite the data used in other calculations. We compared our results with an available GPU-based Position-Based Dynamics solver. We gathered results on two computers with different specifications using affordable GPUs. The vertex (959 vertices) and tetrahedral mesh element (2591 elements) counts were kept the same for all calculations. Our implementation was able to speed up physics calculations by nearly 10x. For the size of 128 × 128, the CPU implementation carried out physics calculations in 7900 ms while our implementation carried out the same physics calculations in 820 ms.
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Acknowledgments
This project was supported by grants from the National Institutes of Health (NIH)/ NIBIB 1R01EB033674-01A1, 5R01EB025241–04, 3R01EB005807-09A1S1, and 5R01EB005807–10.
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Demirel, D., Smith, J., Kockara, S., Halic, T. (2023). GPU Based Position Based Dynamics for Surgical Simulators. In: Fang, X. (eds) HCI in Games. HCII 2023. Lecture Notes in Computer Science, vol 14046. Springer, Cham. https://doi.org/10.1007/978-3-031-35930-9_6
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DOI: https://doi.org/10.1007/978-3-031-35930-9_6
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