Testing Tesla architecture for scientific computing: The performance of matrix-vector product
Cracow University of Technology, Insitute of Computer Modelling, ul. Warszawska 24, 31-155 Krakow, Poland
International Multiconference on Computer Science and Information Technology, 2008. IMCSIT 2008
@inproceedings{maciol2008testing,
title={Testing tesla architecture for scientific computing: The performance of matrix-vector product},
author={Maciol, P. and Banas, K.},
booktitle={Computer Science and Information Technology, 2008. IMCSIT 2008. International Multiconference on},
pages={285–291},
year={2008},
organization={IEEE}
}
The paper presents results of several experiments evaluating the performance of NVIDIA processors, implementing a new Tesla architecture, in matrix-vector multiplication. Three matrix forms, dense, banded and sparse, are considered together with three hardware platforms: NVIDIA Tesla C870 computing board, NVIDIA GeForce 8800 GTX graphics card and one of the newest Intel Xeon processors, E5462, with 1.6 GHz front side bus speed. The conclusions from experiments indicate what speed-ups can be expected when, instead of standard CPUs, accelerators in the form of presented GPUs are used for considered computational kernels.
July 10, 2011 by hgpu
