Detalle de: A fast band-Krylov eigensolver for macromolecular functional motion simulation on multicore architectures and graphics processors
| Title | A fast band-Krylov eigensolver for macromolecular functional motion simulation on multicore architectures and graphics processors |
| Abstract |
We introduce a new iterative Krylov subspace-based eigensolver for the simulation of macromolecular motions on desktop multithreaded platforms equipped with multicore processors and, possibly, a graphics accelerator (GPU). The method consists of two stages, with the original problem first reduced into a simpler band-structured form by means of a high-performance compute-intensive procedure. This is followed by a memory-intensive but low-cost Krylov iteration, which is off-loaded to be computed on the GPU by means of an efficient data-parallel kernel.The experimental results reveal the performance of the new eigensolver. Concretely, when applied to the simulation of macromolecules with a few thousands degrees of freedom and the number of eigenpairs to be computed is small to moderate, the new solver outperforms other methods implemented as part of high-performance numerical linear algebra packages for multithreaded architectures. |
| Apa Reference | Aliaga, J. I., Alonso, P., Badía, J. M., Chacón, P., Davidović, D., López-Blanco, J. R., & Quintana-Ortí, E. S. (2016). A fast band–Krylov eigensolver for macromolecular functional motion simulation on multicore architectures and graphics processors. Journal of Computational Physics, 309, 314–323. 10.1016/j.jcp.2016.01.007 |
| Doi | 10.1016/j.jcp.2016.01.007 |
| Publication Date | Mar 2016 |
| Publication Type | Article |
| Researcher | Pablo Chacón |
| Ontology | Computational models and simulations, High-performance Computing, Parallel Computing |
| Research Groups | Structural Bioinformatics |
| Tools |
