Parallel continuous collision detection for high-performance GPU cluster
Peng Du, Elvis S. Liu, Toyotaro Suzumura · 2017
Continuous collision detection (CCD) is a process to interpolate the trajectory of polygons and detect collisions between successive time steps. However, primitive-level CCD is a very time-consuming process especially for a large number of moving polygons. Over the years, a number of approaches have been proposed to improve the computational efficiency of CCD by culling out the non-colliding primitives before exact overlap tests. These approaches have two fundamental disadvantages. First, they are mainly designed for self-and pairwise CCD and thus the performance gain would be limited when they are applied to large-scale scenes that contain thousands of moving polygons. Second, they are designed as sequential processes appropriate for execution on a single processor. Therefore, deploying them on high-performance parallel computing systems would not increase their computational efficiency.