Name
Title | ||
|---|---|---|
Parallel GPU-based collision detection of irregular vessel wall for massive particles. |
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/s10586-017-0741-7 | Cluster Computing |
Keywords | Field | DocType |
GPU-based, collision detection, irregular objects, space decomposition | Collision detection,Computer graphics (images),Computer science,Personal computer,Real-time computing,Collision,Computational science,Space decomposition | Journal |
Volume | Issue | ISSN |
20 | 3 | 1573-7543 |
Citations | PageRank | References |
0 | 0.34 | 10 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Binbin Yong | 1 | 21 | 5.23 |
| Jun Shen | 2 | 234 | 40.40 |
| Hongyu Sun | 3 | 0 | 1.01 |
| Huaming Chen | 4 | 25 | 8.32 |
| Qingguo Zhou | 5 | 103 | 29.48 |