Collision detection between deformable models is one of fundamental tools of various applications including games. Collision detection can be classified into two categories: discrete and continuous collision detection methods. Discrete collision detection (DCD) has been demonstrated to show the interactive performance by using bounding volume hierarchies… (More)
We present a novel, hybrid parallel continuous collision detection (HPCCD) method that exploits the availability of multi-core CPU and GPU architectures. HPCCD is based on a bounding volume hierarchy (BVH) and selectively performs lazy reconstructions. Our method works with a wide variety of deforming models and supports self-collision detection. HPCCD… (More)
Bounding volume hierarchies (BVHs) are widely used to accelerate the performance of various geometric and graphics applications. These applications include ray tracing, collision detection, visibility queries, dynamic simulation, and motion planning. These applications typically precompute BVHs of input models and traverse the BVHs at runtime in order to… (More)
We propose a novel, multi-resolution method to efficiently perform large-scale cloth simulation. Our cloth simulation method is based on a triangle-based energy model constructed from a cloth mesh. We identify that solutions of the linear system of cloth simulation are smooth in certain regions of the cloth mesh and solve the linear system on those regions… (More)
Simulating complex phenomena such as fracture requires collision detection (CD) methods to avoid any inter-collisions among deforming models and self-collisions (i.e. intra-collisions) within each deforming model. CD is typically the main computational bottleneck of simulating such complex phenomena.
To meet the demand of higher realism, a high number of particles are used for particle-based fluid simulations, resulting in various out-of-core issues. In this paper, we present an out-of-core proximity computation, especially, ε-Nearest Neighbor (ε-NN) search, commonly used for particle-based fluid simulations, to handle such big data sets consisting of… (More)
We present a novel, linear programming (LP)-based scheduling algorithm that exploits heterogeneous multicore architectures such as CPUs and GPUs to accelerate a wide variety of proximity queries. To represent complicated performance relationships between heterogeneous architectures and different computations of proximity queries, we propose a simple, yet… (More)