GPU based Position Based Dynamics for Surgical Simulators.

Doga Demirel, Jason Smith, Sinan Kockara, Tansel Halic
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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 128x128, the CPU implementation carried out physics calculations in 7900ms while our implementation carried out the same physics calculations in 820ms.

基于GPU的手术模拟器位置动力学。
基于位置的动力学是计算机图形学中最流行的模拟动态系统的方法。然而,在虚拟场景中,具有线性变形时间的体绘制仍然是一个挑战。在这项工作中,我们将基于图形处理单元(GPU)的基于位置的动力学实现到iMSTK, iMSTK是一个用于快速原型交互多模态手术模拟的开源工具包。我们使用了NVIDIA的CUDA工具包来实现,并在GPU内核上进行矢量计算,同时确保线程不会覆盖其他计算中使用的数据。我们将我们的结果与可用的基于gpu的基于位置的动力学求解器进行了比较。我们在两台不同规格的计算机上收集了结果,使用的是价格合理的gpu。顶点(959个顶点)和四面体网格元素(2591个元素)计数在所有计算中保持相同。我们的实现能够将物理计算速度提高近10倍。对于128x128的大小,CPU实现在7900ms内完成物理计算,而我们的实现在820ms内完成相同的物理计算。
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