GPGPU
General-Purpose Computation Using Graphics Hardware

Introduction

GPGPU stands for General-Purpose computation on GPUs. With the increasing programmability of commodity graphics processing units (GPUs), these chips are capable of performing more than the specific graphics computations for which they were designed. They are now capable coprocessors, and their high speed makes them useful for a variety of applications. The goal of this page is to catalog the current and historical use of GPUs for general-purpose computation.

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A Comparison of Acceleration Structures for GPU Assisted Ray Tracing

Recently, ray tracing on consumer level graphics hardware has been introduced. So far, most published studies on this topic use the uniform grid spatial subdivision structure for reducing the number of ray/triangle intersection tests. For many types of scenes, a hierarchical acceleration structure is more appropriate. This thesis by Lars Ole Simonsen and Niels Thrane of University of Aarhus compares GPU based traversal of kd-trees and uniform grids with a novel bounding volume hierarchy traversal scheme. The three implementations are compared in terms of performance and usefulness on the GPU. The thesis concludes that on the GPU, the bounding volume hierarchy traversal technique is up to 9 times faster than its implementations of uniform grid and kd-tree. Additionally, this technique proves the simplest to implement and the most memory efficient. (Lars Ole's Website or Direct link to thesis PDF.)

Posted: 23 Aug 2005 [GPGPU /Advanced Rendering/Global Illumination] #


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