High rayleigh number mantle convection on GPU

David A. Sanchez, Christopher Gonzalez, David A. Yuen, Grady B. Wright, Gregory A. Barnett

Research output: Chapter in Book/Report/Conference proceedingChapter (Book)Researchpeer-review


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.

Original languageEnglish
Title of host publicationGPU Solutions to Multi-scale Problems in Science and Engineering
EditorsDavid A Yuen, Long Wang, Xuebin Chi
Place of PublicationHeidelberg Germany
Number of pages18
ISBN (Electronic)9783642164057
ISBN (Print)9783642164040
Publication statusPublished - 1 Jan 2013
Externally publishedYes

Publication series

NameLecture Notes in Earth System Sciences
ISSN (Print)2193-858X
ISSN (Electronic)2193-8571

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