Towards a finite volume model on a many-core platform

Authors:
Pablo Igounet;Pablo Alfaro;Gabriel Usera;Pablo Ezzatti
Affiliations:
Computer Science Institute, School of Engineering, Universidad de la Republica, J. Herrera y Reissig 565, Montevideo, 11300, Uruguay.;Computer Science Institute, School of Engineering, Universidad de la Republica, J. Herrera y Reissig 565, Montevideo, 11300, Uruguay.;Institute of Fluid Mechanics and Environmental Engineering, School of Engineering, Universidad de la Republica, J. Herrera y Reissig 565, Montevideo, 11300, Uruguay.;Computer Science Institute, School of Engineering, Universidad de la Republica, J. Herrera y Reissig 565, Montevideo, 11300, Uruguay
Venue:
International Journal of High Performance Systems Architecture
Year:
2012

Citing 5
Cited 0

A Parallel Strongly Implicit Algorithm for Solving of Diffusion Equations

ParNum '99 Proceedings of the 4th International ACPC Conference Including Special Tracks on Parallel Numerics and Parallel Computing in Image Processing, Video Processing, and Multimedia: Parallel Computation
Accurate three-dimensional lid-driven cavity flow

Journal of Computational Physics
Exploiting the capabilities of modern GPUs for dense matrix computations

Concurrency and Computation: Practice & Experience
Programming Massively Parallel Processors: A Hands-on Approach

Programming Massively Parallel Processors: A Hands-on Approach
Using hybrid CPU-GPU platforms to accelerate the computation of the matrix sign function

Euro-Par'09 Proceedings of the 2009 international conference on Parallel processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

This article presents a study of porting the finite volume model, caffa3d.MB, to GPU in order to improve its computational efficiency. In particular, we evaluated all the stages of the aforementioned model and implemented on GPU the most costly one, the linear systems resolution by means of the strongly implicit procedure (SIP) method. The experimental evaluation of the proposed implementation of the solver demonstrates that a significant runtime reduction can be attained (acceleration values up to 18×) when compared with a CPU version, and this improvement significantly reduces the total runtime of the model. This results evidence a promising prospect for a full GPU-based implementation of finite volume flow solvers like caffa3d.MB.