Name
Abstract | ||
|---|---|---|
A projection-based immersed boundary method is dominated by sparse linear algebra routines. Using the open-source Cusp library, we observe a speedup (with respect to a single CPU core) which reflects the constraints of a bandwidth-dominated problem on the GPU. Nevertheless, GPUs offer the capacity to solve large problems on commodity hardware. This work includes validation and a convergence study of the GPU-accelerated IBM, and various optimizations. |
Year | Venue | Keywords |
|---|---|---|
2011 | CoRR | immersed boundary method,linear algebra |
Field | DocType | Volume |
Immersed boundary method,Convergence (routing),Linear algebra,IBM,Mathematical optimization,Computer science,CUDA,Parallel computing,Fluid dynamics,Multi-core processor,Speedup | Journal | abs/1109.3524 |
Citations | PageRank | References |
3 | 0.41 | 2 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Simon K. Layton | 1 | 6 | 0.81 |
| Anush Krishnan | 2 | 53 | 2.19 |
| Lorena A. Barba | 3 | 52 | 7.70 |