Optimization and performance evaluation of the IDR iterative Krylov solver on GPUs

Journal article


Publication Details

Author(s): Anzt H, Kreutzer M, Ponce E, Peterson GD, Wellein G, Dongarra J
Journal: International Journal of High Performance Computing Applications
Publisher: SAGE Publications (UK and US)
Publication year: 2016
ISSN: 1094-3420


Abstract


In this paper, we present an optimized GPU implementation for the induced dimension reduction algorithm. We improve data locality, combine it with an efficient sparse matrix vector kernel, and investigate the potential of overlapping computation with communication as well as the possibility of concurrent kernel execution. A comprehensive performance evaluation is conducted using a suitable performance model. The analysis reveals efficiency of up to 90%, which indicates that the implementation achieves performance close to the theoretically attainable bound.



FAU Authors / FAU Editors

Kreutzer, Moritz
Regionales Rechenzentrum Erlangen (RRZE)
Wellein, Gerhard Prof. Dr.
Professur für Höchstleistungsrechnen


How to cite

APA:
Anzt, H., Kreutzer, M., Ponce, E., Peterson, G.D., Wellein, G., & Dongarra, J. (2016). Optimization and performance evaluation of the IDR iterative Krylov solver on GPUs. International Journal of High Performance Computing Applications. https://dx.doi.org/10.1177/1094342016646844

MLA:
Anzt, Hartwig, et al. "Optimization and performance evaluation of the IDR iterative Krylov solver on GPUs." International Journal of High Performance Computing Applications (2016).

BibTeX: 

Last updated on 2018-19-04 at 03:29