Parallel GPU-based collision detection of irregular vessel wall for massive particles

被引：1

作者：

Yong, Binbin ^{[1
]}

Shen, Jun ^{[2
]}

Sun, Hongyu ^{[3
]}

Chen, Huaming ^{[2
]}

Zhou, Qingguo ^{[1
]}

机构：

[1] Lanzhou Univ, Sch Informat Sci & Engn, Lanzhou, Gansu, Peoples R China

[2] Univ Wollongong, Sch Comp & Informat Technol, Wollongong, NSW, Australia

[3] Swinburne Univ Technol, Comp Sci, Melbourne, Vic, Australia

来源：

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS | 2017年 / 20卷 / 03期

基金：

中国国家自然科学基金;

关键词：

GPU-based; collision detection; irregular objects; space decomposition;

D O I：

10.1007/s10586-017-0741-7

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we present a novel GPU-based limit space decomposition collision detection algorithm (LSDCD) for performing collision detection between a massive number of particles and irregular objects, which is used in the design of the Accelerator Driven Sub-Critical (ADS) system. Test results indicate that, the collisions between ten million particles and the vessel can be detected on a general personal computer in only 0.5 s per frame. With this algorithm, the collision detection of maximum sixty million particles are calculated in 3.488030 s. Experiment results show that our algorithm is promising for fast collision detection.

引用

下载

页码：2591 / 2603

页数：13

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