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A COMPARISON OF TWO METHODS FOR GEOMETRIC MILLING SIMULATION ACCELERATED BY GPU

机译:GPU加速几何铣削仿真的两种方法的比较

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For detecting potential problems of a cutter path, cutting force simulation in the NC milling process is necessary prior to actual machining. A milling operation is geometrically equivalent to a Boolean subtraction of the swept volume of a cutter moving along a path from a solid model representing the stock shape. In order to precisely estimate the cutting force, the subtraction operation must be executed for every small motion of the cutter. The performance and the cost of the polygon rendering LSI called GPU are dramatically improved these days. By using GPU, the required time for critical computations in the geometric milling simulation can be drastically reduced. In this paper, the computation speed of two known GPU accelerated milling simulation methods, which are the depth buffer based method and the parallel processing based method with CUDA language, are compared. Computational experiments with complex milling simulations show that the implementation with CUDA is several times faster than the depth buffer based method when the cutter motion in the simulation process is sufficiently small.
机译:为了检测刀具路径的潜在问题,必须在实际加工之前在NC铣削过程中模拟切削力。铣削操作在几何上等同于沿从表示坯料形状的实体模型沿路径移动的刀具扫掠体积的布尔减法。为了精确估计切削力,必须对刀具的每个小运动都执行减法运算。如今,称为GPU的多边形渲染LSI的性能和成本得到了显着提高。通过使用GPU,可以大大减少几何铣削仿真中关键计算所需的时间。在本文中,比较了两种已知的GPU加速铣削仿真方法的计算速度,它们是基于深度缓冲区的方法和基于CUDA语言的基于并行处理的方法。复杂铣削仿真的计算实验表明,当仿真过程中的刀具运动足够小时,使用CUDA的实现比基于深度缓冲区的方法快几倍。

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