Name
Abstract | ||
|---|---|---|
Finding a fast solver for the Poisson equation is important for many scientific applications. In this work, we design and develop a matrix decomposition based Conjugate Gradient (CG) solver, which leverages Graphics Processing Unit (GPU) clusters to accelerate the calculation of the Poisson equation. Our experiments show that the new CG solver is highly scalable and achieves significant speedup over a CPU-based Multi-Grid (MG) solver. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/SC.Companion.2012.286 | SC Companion |
Keywords | Field | DocType |
graphics processing unit,scientific application,cpu-based multigrid solver,graphics processing units,conjugate gradient solver,significant speedup,mathematics computing,new cg solver,poisson equation,matrix decomposition,matrix decomposition based conjugate gradient solver,gpu clusters,graphics processing unit (gpu),graphics processing unit clusters,conjugate gradient,cpu-based multi-grid,fast solver,conjugate gradient (cg) solver,conjugate gradient methods,cg solver | Conjugate gradient method,Cluster (physics),Poisson's equation,Computer science,Matrix decomposition,Parallel computing,Computational science,Solver,Graphics processing unit,Speedup,Scalability | Conference |
ISBN | Citations | PageRank |
978-1-4673-6218-4 | 2 | 0.37 |
References | Authors | |
2 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hang Liu | 1 | 835 | 90.79 |
| JungHee Seo | 2 | 9 | 1.89 |
| Rajat Mittal | 3 | 170 | 17.59 |
| H. Howie Huang | 4 | 537 | 40.29 |