1384

Multi GPU Performance of Conjugate Gradient Algorithm with Staggered Fermions

Hyung-Jin Kim, Weonjong Lee
Lattice Gauge Theory Research Center, FPRD, and CTP, Department of Physics and Astronomy, Seoul National University, Seoul, 151-747, South Korea
arXiv:1010.4782v2 [hep-lat] (22 Oct 2010)

@article{kim2010multi,

   title={Multi GPU Performance of Conjugate Gradient Algorithm with Staggered Fermions},

   author={Kim, H.J. and Lee, W.},

   journal={Arxiv preprint arXiv:1010.4782},

   year={2010}

}

Download Download (PDF)   View View   Source Source   

599

views

We report results of the performance test of GPUs obtained using the conjugate gradient (CG) algorithm for staggered fermions on the MILC fine lattice ($28^3 times 96$). We use GPUs of nVIDIA GTX 295 model for the test. When we turn off the MPI communication and use only a single GPU, the performance is 35 giga flops in double precision, which corresponds to 47% of the peak. When we turn on the MPI communication and use multi-GPUs, the performance is reduced down to 12.3 giga flops. The data transfer through the infiniband network and PCI-E bus I/O is a main bottle neck. We suggest two potential solutions of how to optimize the data transfer.
No votes yet.
Please wait...

* * *

* * *

HGPU group © 2010-2017 hgpu.org

All rights belong to the respective authors

Contact us: