Geodesic
Implementing an interior point method for linear programs on a CPU-GPU system
Electronic transactions on numerical analysis, Tome 28 (2008).

Voir la notice de l'article provenant de la source Electronic Library of Mathematics

Summary: Graphics processing units (GPUs), present in every laptop and desktop computer, are potentially powerful computational engines for solving numerical problems. We present a mixed precision CPU-GPU algorithm for solving linear programming problems using interior point methods. This algorithm, based on the rectangular-packed matrix storage scheme of Gunnels and Gustavson, uses the GPU for computationally intensive tasks such as matrix assembly, Cholesky factorization, and forward and back substitution. Comparisons with a CPU implementation demonstrate that we can improve performance by using the GPU for sufficiently large problems. Since GPU architectures and programming languages are rapidly evolving, we expect that GPUs will be an increasingly attractive tool for matrix computation in the future.
Classification : 90C05, 90C51, 15A23, 68W10
Keywords: GPGPU, Cholesky factorization, matrix decomposition, forward and back substitution, linear programming, interior point method, rectangular packed format 
@article{ETNA_2008__28__a2,
     author = {Jung, Jin Hyuk and O'leary, Dianne P.},
     title = {Implementing an interior point method for linear programs on a {CPU-GPU} system},
     journal = {Electronic transactions on numerical analysis},
     publisher = {mathdoc},
     volume = {28},
     year = {2008},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/ETNA_2008__28__a2/}
}
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Jung, Jin Hyuk; O'leary, Dianne P. Implementing an interior point method for linear programs on a CPU-GPU system. Electronic transactions on numerical analysis, Tome 28 (2008). http://geodesic.mathdoc.fr/item/ETNA_2008__28__a2/