Steering and In-situ Visualization for Simulation of Seismic Wave Propagation on Graphics Cards

Simulation of large scale seismic wave propagation is an important tool in seismology for efficient strong motion analysis and risk mitigation. Being particularly CPU-consuming, this three-dimensional problem has been early ported on graphics cards to improve the performance by several order of magnitude. Scientific visualization of data produced by these simulations is essential for a good comprehension of the physical phenomena involved. In the same time, post-petascale architectures demonstrates that the I/O turn to become a major performance bottleneck. This situation is worsened with GPU-based systems because of the gap between I/O bandwidth and computational capabilities. In this paper, we introduce a prototype of computational steering and in-situ visualization suitable for seismic wave propagation on hybrid architecture. We detail the overall architecture of the system we set up and comment on the parallel performance measured.

[1]  R. Madariaga Dynamics of an expanding circular fault , 1976, Bulletin of the Seismological Society of America.

[2]  J. Virieux P-SV wave propagation in heterogeneous media: Velocity‐stress finite‐difference method , 1986 .

[3]  A. Levander Fourth-order finite-difference P-SV seismograms , 1988 .

[4]  James Arthur Kohl,et al.  Cumulvs: Providing Fault Toler. Ance, Visualization, and Steer Ing of Parallel Applications , 1996, Int. J. High Perform. Comput. Appl..

[5]  Carolina Cruz-Neira,et al.  VR Juggler: a virtual platform for virtual reality application development , 2001, Proceedings IEEE Virtual Reality 2001.

[6]  Laurence E. Turner,et al.  Graphics processor unit (GPU) acceleration of finite-difference time-domain (FDTD) algorithm , 2004, 2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512).

[7]  Thomas Eickermann,et al.  Steering UNICORE applications with VISIT , 2005, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[8]  Roland Martin,et al.  An unsplit convolutional perfectly matched layer technique improved at grazing incidence for the viscoelastic wave equation , 2009 .

[9]  Kwan-Liu Ma,et al.  In Situ Visualization at Extreme Scale: Challenges and Opportunities , 2009, IEEE Computer Graphics and Applications.

[10]  Henri Calandra,et al.  Fast seismic modeling and Reverse Time Migration on a GPU cluster , 2009, 2009 International Conference on High Performance Computing & Simulation.

[11]  Paulius Micikevicius,et al.  3D finite difference computation on GPUs using CUDA , 2009, GPGPU-2.

[12]  Dimitri Komatitsch,et al.  Accelerating a three-dimensional finite-difference wave propagation code using GPU graphics cards , 2010 .

[13]  Fabrice Dupros,et al.  Finite Difference Simulations of Seismic Wave Propagation for the 2007 Mw 6.6 Niigata-ken Chuetsu-Oki Earthquake: Validity of Models and Reliable Input Ground Motion in the Near-Field , 2011, Pure and Applied Geophysics.