Mahmoudi, Sidi ; Université de Mons > Faculté Polytechnique > Informatique, Logiciel et Intelligence artificielle
Manneback, Pierre ; Université de Mons > Faculté Polytechnique > Informatique, Logiciel et Intelligence artificielle
Language :
English
Title :
Taking Advantage of GPU/CPU Architectures for Sparse Conjugate Gradient Solver Computation
Publication date :
23 November 2015
Event name :
Third World Conference on Complex Systems
Event place :
Marrakech, Morocco
Event date :
2015
Research unit :
F114 - Informatique, Logiciel et Intelligence artificielle
Research institute :
R300 - Institut de Recherche en Technologies de l'Information et Sciences de l'Informatique R450 - Institut NUMEDIART pour les Technologies des Arts Numériques
R. Li, and Y. Saad, "GPU-Accelerated preconditioned iterative linear solvers". The Journal of Supercomputing, 2013, vol. 63, no. 2, p. 443-466.
N. Kasmi, S. A. Mahmoudi, M. Zbakh, and P. Manneback, "Performance evaluation of sparse matrix-vector product (SpMV) computation on GPU architecture". In 2014 Second World Conference on Complex Systems (WCCS), IEEE, 2014. p. 23-27.
NVIDIA Documentation, Cuda C programming guide, Version 5.5. February, 2014.
M. Bauer, H. Cook, and B. Khailany, "CudaDMA: optimizing GPU memory bandwidth via warp specialization". In Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis, ACM, 2011. p. 12.
Cook, Shane. CUDA programming: A developers guide to parallel computing with GPUs. Newnes, 2012.
Y. H. Dai, and Y. Yuan, "A nonlinear conjugate gradient method with a strong global convergence property", SIAM Journal on Optimization, 1999, vol. 10, no 1, p. 177-182.
T. A. Davis and Y. Hu, The university of Florida sparse matrix collection, ACM Trans. Math. Softw., Nov. 2011, vol. 38, no. 1, pp. 125.
Y. H. Dai, and C. X. Kou, "A nonlinear conjugate gradient algorithm with an optimal property and an improved Wolfe line search", 2013, SIAM Journal on Optimization, 2013, vol. 23, no 1, p. 296-320.
Y. Saad, "Iterative methods for sparse linear systems", 2003, Siam.
J. W. Demmel, "Applied numerical linear algebra", 1997, Siam.
D. Lukarski, "Parallel Sparse Linear Algebra for Multi-core and Manycore Platforms: Parallel Solvers and Preconditioners". In Doctoral dissertation, Karlsruhe, Karlsruher Institut fr Technologie (KIT), Diss., 2012.
J. C. Ikuno, M. Wrulich, and M. Rupp, "System level simulation of LTE networks". In Vehicular Technology Conference (VTC 2010-Spring), 2010 IEEE 71st, pp. 1-5.
D. Shreiner, G. Sellers, J. M. Kessenich, and B. M. Licea-Kane, "OpenGL programming guide: The Official guide to learning OpenGL", version 4.3. Addison-Wesley.
S. Sengupta, M. Harris, Y. Zhang, and J. D. Owens "Scan primitives for GPU computing. In Graphics hardware", 2007, Vol. 2007, pp. 97-106.
R. Koenker and P. Ng, SparseM: A sparse matrix package for R, CRAN Packag. Arch., N. 2002, pp. 19, 2011.
N. Trost, J. Jimnez, D. Lukarski, and V. Sanchez. "Accelerating COBAYA3 on multi-core CPU and GPU systems using PARALUTION". Annals of Nuclear Energy, 2014.
M. Benzi, Preconditioning Techniques for Large Linear Systems: A Survey, Journal of Computational Physics, 182 (2002), pp. 418-477