Name
Abstract | ||
|---|---|---|
We present ideas and first results on a GPU acceleration of a non-linear solver embedded into the biomedical application code CARP. The linear system solvers have been transferred already in the past and so we concentrate on how to extend the GPU acceleration to larger portions of the code. The finite element assembling of stiffness and mass matrices takes at least 50% of the CPU time and therefore we investigate this process for the bidomain equations but with focus on later use in non-linear and/or time-dependent problems. The CUDA code for matrix calculation and assembling is faster by a factor up to 90 compared to a single CPU core. The routines were integrated to CARP's main code and they are already used to assemble the FE matrices of the bidomain model. Further performance studies are still required for the bidomain-mechanics model. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-662-43880-0_1 | Lecture Notes in Computer Science |
Field | DocType | Volume |
Bidomain model,Central processing unit,Linear system,CUDA,Computer science,Matrix (mathematics),Parallel computing,Finite element method,Acceleration,Solver | Conference | 8353 |
ISSN | Citations | PageRank |
0302-9743 | 1 | 0.41 |
References | Authors | |
7 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Caroline Mendonça Costa | 1 | 10 | 4.59 |
| G Haase | 2 | 161 | 21.27 |
| M Liebmann | 3 | 109 | 11.97 |
| A Neic | 4 | 41 | 6.46 |
| G Plank | 5 | 201 | 33.05 |