An implementation of the tile QR factorization for a GPU and multiple CPUs
Department of Electrical Engineering and Computer Science, University of Tennessee
Applied Parallel and Scientific Computing, Lecture Notes in Computer Science, Volume 7134/2012, 248-257, 2012
@article{kurzak2012implementation,
title={An implementation of the tile QR factorization for a GPU and multiple CPUs},
author={Kurzak, J. and Nath, R. and Du, P. and Dongarra, J.},
journal={Applied Parallel and Scientific Computing},
pages={248–257},
year={2012},
publisher={Springer}
}
The tile QR factorization provides an efficient and scalable way for factoring a dense matrix in parallel on multicore processors. This article presents a way of efficiently implementing the algorithm on a system with a powerful GPU and many multicore CPUs.
April 14, 2012 by hgpu
