Name
Abstract | ||
|---|---|---|
Since the advent of programmable graphics processors (GPUs) their computational powers have been utilized for general purpose computation. Initially by "exploiting" graphics APIs and recently through dedicated parallel computation frameworks such as the Compute Unified Device Architecture (CUDA) from Nvidia. This paper investigates multiple implementations of volumetric Mass-Spring-Damper systems in CUDA. The obtained performance is compared to previous implementations utilizing the GPU through the OpenGL graphics API. We find that both performance and optimization strategies differ widely between the OpenGL and CUDA implementations. Specifically, the previous recommendation of using implicitly connected particles is replaced by a recommendation that supports unstructured meshes and run-time topological changes with an insignificant performance reduction. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-70521-5_6 | ISBMS |
Keywords | Field | DocType |
volumetric mass-spring-damper models,insignificant performance reduction,compute unified device architecture,previous recommendation,dedicated parallel computation,programmable graphics processor,cuda implementation,general purpose computation,parallel algorithms,graphics apis,opengl graphics,previous implementation,parallel computer,parallel algorithm | Graphics,Polygon mesh,Parallel algorithm,CUDA,Computer science,Parallel computing,Computational science,General-purpose computing on graphics processing units,OpenGL,CUDA Pinned memory,Computation | Conference |
Volume | ISSN | Citations |
5104 | 0302-9743 | 9 |
PageRank | References | Authors |
0.67 | 10 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Allan Rasmusson | 1 | 11 | 1.05 |
| Jesper Mosegaard | 2 | 50 | 6.82 |
| Thomas Sangild Sørensen | 3 | 42 | 5.73 |