High Rayleigh Number Mantle Convectionon GPU
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| Дата: | 2010 |
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| Автори: | , , , |
| Формат: | Стаття |
| Мова: | English |
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Інститут геофізики ім. С.I. Субботіна НАН України
2010
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| Назва видання: | Геофизический журнал |
| Онлайн доступ: | http://dspace.nbuv.gov.ua/handle/123456789/103098 |
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| Назва журналу: | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| Цитувати: | High Rayleigh Number Mantle Convectionon GPU / D. Sanchez, D. Yuen, G. Wright, Jr. G. Barnett // Геофизический журнал. — 2010. — Т. 32, № 4. — С. 143. — англ. |
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High Rayleigh Number Mantle Convectionon GPU
D. Sanchez1, D. Yuen1, G. Wright2, G. Barnett Jr.3, 2010
1Minnesota Supercomputing Institute, University of Minnesota, USA
2Department of Mathematics, Boise State University, USA
3Department of Applied Mathematics, University of Colorado, Boulder, USA
The performance, potential growth, availability,
and affordability of GPUs has made them attractive
to scientists for many years. Although historically
cumbersome and difficult to use for scientific soft-
ware, the introduction and refinement of high-level
development tools, such as CUDA, have made GPU
computing accessible. With the advent of architec-
tures, such as NVIDIA's Fermi, which explicitly ca-
ter to scientists by enabling more memory, faster
access to that memory, and better double-precision
support than ever before, members of the computa-
tional world are finding GPU difficult to ignore.
Using finite-difference methods with second-or-
der accuracy in space and third-order accuracy in
time, we investigate 2D and 3D thermal convection
at the infinite Prandtl number limit, at resolutions Fig. 1. Performance scaling with grid size on Tesla C1060.
on the order of 1000 2000 2D and 400 400 200 3D
grid points. Our CUDA code makes extensive use of
highly-optimized CUBLAS routines, allowing us to
unlock a significant fraction of GPU's performance.
This performance has enabled us to study the beha-
vior of high Rayleigh number simulations, on the order
of 109, in 2D and 107 in 3D over sufficient time scales
to see evidence of flow-reversal (Fig. 1).
We compare our CUDA code's performance with
Jacket-accelerated Matlab code and CPU-only
Matlab code across the Tesla C1060, Tesla C2050,
and GTX 480 (Fig. 2).Fig. 2. 2D mantle convection at a Rayleigh number of 109.
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irk-123456789-1030982016-06-14T03:04:09Z High Rayleigh Number Mantle Convectionon GPU Sanchez, D. Yuen, D. Wright, G. Barnett Jr., G. 2010 Article High Rayleigh Number Mantle Convectionon GPU / D. Sanchez, D. Yuen, G. Wright, Jr. G. Barnett // Геофизический журнал. — 2010. — Т. 32, № 4. — С. 143. — англ. 0203-3100 http://dspace.nbuv.gov.ua/handle/123456789/103098 en Геофизический журнал Інститут геофізики ім. С.I. Субботіна НАН України |
| institution |
Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| collection |
DSpace DC |
| language |
English |
| format |
Article |
| author |
Sanchez, D. Yuen, D. Wright, G. Barnett Jr., G. |
| spellingShingle |
Sanchez, D. Yuen, D. Wright, G. Barnett Jr., G. High Rayleigh Number Mantle Convectionon GPU Геофизический журнал |
| author_facet |
Sanchez, D. Yuen, D. Wright, G. Barnett Jr., G. |
| author_sort |
Sanchez, D. |
| title |
High Rayleigh Number Mantle Convectionon GPU |
| title_short |
High Rayleigh Number Mantle Convectionon GPU |
| title_full |
High Rayleigh Number Mantle Convectionon GPU |
| title_fullStr |
High Rayleigh Number Mantle Convectionon GPU |
| title_full_unstemmed |
High Rayleigh Number Mantle Convectionon GPU |
| title_sort |
high rayleigh number mantle convectionon gpu |
| publisher |
Інститут геофізики ім. С.I. Субботіна НАН України |
| publishDate |
2010 |
| url |
http://dspace.nbuv.gov.ua/handle/123456789/103098 |
| citation_txt |
High Rayleigh Number Mantle Convectionon GPU / D. Sanchez, D. Yuen, G. Wright, Jr. G. Barnett // Геофизический журнал. — 2010. — Т. 32, № 4. — С. 143. — англ. |
| series |
Геофизический журнал |
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2025-07-07T13:17:15Z |
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2025-07-07T13:17:15Z |
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