High Rayleigh Number Mantle Convection on GPU

Authors

David A. Sanchez, University of Minnesota
Christopher Gonzalez, University of Minnesota
David A. Yuen, University of Minnesota
Grady B. Wright, Boise State UniversityFollow
Gregory A. Barnett, University of Colorado Boulder

Document Type

Contribution to Books

Publication Date

2013

Abstract

We implemented two- and three-dimensional Rayleigh-Benard convection on Nvidia GPUs by utilizing a 2nd-order finite difference method. By exploiting the massive parallelism of GPU using both CUDA for C and optimized CUBLAS routines, we have on a single Fermi GPU run simulations of Rayleigh number up to 6×10¹⁰ (on a mesh of 2000×4000 uniform grid points) in two dimensions and up to 10⁷ (on a mesh of 450×450×225 uniform grid points) for three dimensions. On Nvidia Tesla C2070 GPUs, these implementations enjoy single-precision performance of 535 GFLOP/s and 100 GFLOP/s respectively, and double-precision performance of 230 GFLOP/s and 70 GFLOP/s respectively.

Comments

GPU Solutions to Multi-Scale Problems in Science and Engineering is part of the Lecture Notes in Earth System Sciences book series.

Publication Information

Sanchez, David A.; Gonzalez, Christopher; Yuen, David A.; Wright, Grady B.; and Barnett, Gregory A.. (2013). "High Rayleigh Number Mantle Convection on GPU". GPU Solutions to Multi-Scale Problems in Science and Engineering, 335-352. https://doi.org/10.1007/978-3-642-16405-7_22