Finding Convex Hulls Using Quickhull on the GPU

01/13/2012
by   Stanley Tzeng, et al.
0

We present a convex hull algorithm that is accelerated on commodity graphics hardware. We analyze and identify the hurdles of writing a recursive divide and conquer algorithm on the GPU and divise a framework for representing this class of problems. Our framework transforms the recursive splitting step into a permutation step that is well-suited for graphics hardware. Our convex hull algorithm of choice is Quickhull. Our parallel Quickhull implementation (for both 2D and 3D cases) achieves an order of magnitude speedup over standard computational geometry libraries.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
01/20/2015

A Novel Implementation of QuickHull Algorithm on the GPU

We present a novel GPU-accelerated implementation of the QuickHull algor...
research
03/19/2023

An Evaluation of GPU Filters for Accelerating the 2D Convex Hull

The Convex Hull algorithm is one of the most important algorithms in com...
research
12/23/2013

Transparent Checkpoint-Restart for Hardware-Accelerated 3D Graphics

Providing fault-tolerance for long-running GPU-intensive jobs requires a...
research
09/16/2019

Bonsai-SPH: A GPU accelerated astrophysical Smoothed Particle Hydrodynamics code

We present the smoothed-particle hydrodynamics simulation code, Bonsai-S...
research
07/05/2022

ParGeo: A Library for Parallel Computational Geometry

This paper presents ParGeo, a multicore library for computational geomet...
research
07/20/2023

GPU-accelerated Parallel Solutions to the Quadratic Assignment Problem

The Quadratic Assignment Problem (QAP) is an important combinatorial opt...

Please sign up or login with your details

Forgot password? Click here to reset