Multi GPU Performance of Conjugate Gradient Algorithm with Staggered Fermions

Details Multi GPU Performance of Conjugate Gradient Algorithm with Staggered Fermions Multi GPU Performance of Conjugate Gradient Algorithm with Staggered Fermions

2010-10-22

arxiv.org/abs/1010.4782v2

PoS LAT2010 (2010) 028

Physics

High Energy Physics

High Energy Physics - Lattice

7 pages, 1 figure, Lattice 2010 Proceeding, references updated

Scientific paper

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.

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