Collision detection is a well-studied and active research field where the main problem is to determine if one or more objects collide with each other in 3D virtual space. Collision detection is an issue affecting many different fields of study, including computer animation, physical-based simulation, robotics, video games and haptic applications. There is a big variety of collision detection algorithms of witch spatial subdivision, octree and sort and sweep are three of them. In this document we provide a short summary of collision detection algorithms, but the main focus will be on analyzing and increasing their performance working on CPU (orig. Central processing unit) and GPU (orig. Graphics processing unit) separately by making use of CUDA (orig.Compute Unified Device Architecture) technology. This technology is a part of Nvidia, witch helps the use of graphics processor for general-purpose computation. Main goal of this research is achieved by performing analysis of implemented spatial subdivision, octree and sort and sweep algorithms. This analysis consists of both general performance, parallelization performance and various performance affecting factors analyses. At the end of the document, the advantages of parallel programming adapted to the present subject are discussed.


    Access

    Download


    Export, share and cite



    Title :

    Susidūrimų paieškos, naudojant lygiagrečius skaičiavimus, metodų tyrimas ; Collision detection methods using parallel computing



    Publication date :

    2013-06-04


    Type of media :

    Theses


    Type of material :

    Electronic Resource


    Language :

    Lithuanian , English



    Classification :

    DDC:    629