At the recent High Performance Computing and Simulation 2009 conference held in Leipzig, Germany from June 21-24, a paper on GPU Acceleration took home the Best Paper Award. The paper, “Fast Seismic Modeling and Reverse Time Migration on a GPU Cluster” from Rached Abdelkhalek, Henri Calandra, Olivier Coulad, Jean Roman, and Guillaume Latu was presented in the Workshop on Architecture-Aware Simulation and Computing. The abstract of the winning paper reads:
We have designed a fast parallel simulator that solves the acoustic wave equation on a GPU cluster. Solving the acoustic wave equation in an oil exploration industrial context aims at speeding up seismic modeling and Reverse Time Migration. We consider a finite difference approach on a regular mesh, in both 2D and 3D cases. The acoustic wave equation is solved in either a constant density or a variable density domain. All the computations are done in single precision, since double precision is not required in our context. We use CUDA to take advantage of the GPUs computational power. We study different implementations and their impact on the application performance. We obtain a speed up of 10 for Reverse Time Migration and up to 30 for the modeling application over a code running on general purpose CPUs.
I haven’t actually been able to find the PDF of the paper yet. Anyone have it?
via GPGPU Paper Wins Best Paper Award at HPCS’09 :: GPGPU.org.
The paper can be found at http://hal.archives-ouvertes.fr/IRMA/inria-00403933/en// I am looking for a hybrid CPU-GPU Cluster preferrably using MPI. Since the GPUs are shared resources over all processes running on the same thread, I will look into GPU context migration. If anybody knows that well, can you ping me ? Cheers!