Optimizing the computation of a parallel 3D finite difference algorithm for graphics processing units
Abstract
This paper explores the possibilities of using a graphics processing unit for complex 3D finite difference computation via MUSTA‐FORCE and WENO algorithms. We propose a novel algorithm based on the new properties of CUDA surface memory optimized for 2D spatial locality and compare it with 3D stencil computations carried out via shared memory, which is currently considered to be the best approach. A case study was performed for the extensive generation of a time series of 3D grids of arbitrary size used in the computation of collisions between heavy nuclei in terms of relativistic hydrodynamics. It proved that implementation based on surface memory is as much as 23% faster than an equivalent implementation using shared memory
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Details
- Category:
- Articles
- Type:
- artykuł w czasopiśmie wyróżnionym w JCR
- Published in:
-
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
no. 27,
pages 1591 - 1602,
ISSN: 1532-0626 - Language:
- English
- Publication year:
- 2015
- Bibliographic description:
- Porter-Sobieraj J., Cygert S., Daniel K., Sikorski J., Słodkowski M.: Optimizing the computation of a parallel 3D finite difference algorithm for graphics processing units// CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE. -Vol. 27, nr. 6 (2015), s.1591-1602
- DOI:
- Digital Object Identifier (open in new tab) 10.1002/cpe.3351
- Verified by:
- Gdańsk University of Technology
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