Geodesic
Implementation of algorithms with a~fine-grained parallelism on GPUs
Sibirskij žurnal vyčislitelʹnoj matematiki, Tome 14 (2011) no. 1, pp. 59-70.

Voir la notice de l'article provenant de la source Math-Net.Ru

The efficiency of implementations of algorithms with a fine-grained parallelism on GPUs that support the CUDA architecture is studied. For testing, cellular automata and differential schemes are used. We offer several versions of implementations and analyze their productivity. An example of the GPU application for modeling the process of carbon dioxide oxidation on the catalyst surface is given. 
@article{SJVM_2011_14_1_a5,
     author = {K. V. Kalgin},
     title = {Implementation of algorithms with a~fine-grained parallelism on {GPUs}},
     journal = {Sibirskij \v{z}urnal vy\v{c}islitelʹnoj matematiki},
     pages = {59--70},
     publisher = {mathdoc},
     volume = {14},
     number = {1},
     year = {2011},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/SJVM_2011_14_1_a5/}
}
TY  - JOUR
AU  - K. V. Kalgin
TI  - Implementation of algorithms with a~fine-grained parallelism on GPUs
JO  - Sibirskij žurnal vyčislitelʹnoj matematiki
PY  - 2011
SP  - 59
EP  - 70
VL  - 14
IS  - 1
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/SJVM_2011_14_1_a5/
LA  - ru
ID  - SJVM_2011_14_1_a5
ER  - 
%0 Journal Article
%A K. V. Kalgin
%T Implementation of algorithms with a~fine-grained parallelism on GPUs
%J Sibirskij žurnal vyčislitelʹnoj matematiki
%D 2011
%P 59-70
%V 14
%N 1
%I mathdoc
%U http://geodesic.mathdoc.fr/item/SJVM_2011_14_1_a5/
%G ru
%F SJVM_2011_14_1_a5
K. V. Kalgin. Implementation of algorithms with a~fine-grained parallelism on GPUs. Sibirskij žurnal vyčislitelʹnoj matematiki, Tome 14 (2011) no. 1, pp. 59-70. http://geodesic.mathdoc.fr/item/SJVM_2011_14_1_a5/

[1] NVIDIA CUDA Programming Guide http://www.nvidia.com/object/cuda_get.html

[2] Marchenko M. A., “Kompleks programm MONC dlya raspredelennykh vychislenii metodom Monte-Karlo”, Sib. zhurn. vychisl. matematiki, 7:1 (2004), 43–55 | Zbl

[3] Matsumoto M., Nishimura T., “Mersenne Twister: a 623-dimensionally equidistributed uniform pseudorandom number generator”, ACM Trans. on Modeling and Computer Simulation, 8:1 (1998), 3–30 | DOI | Zbl

[4] Mersenne Twister for Graphic Processors (MTGP): a new variant of Mersenne Twister http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/MTGP/index.html

[5] Saito M., Matsumoto M., “SIMD-oriented Fast Mersenne Twister: a 128-bit pseudorandom number generator”, Monte Carlo and Quasi-Monte Carlo Methods 2006, Springer, 2008, 607–622 | MR | Zbl

[6] Elokhin V. I., Latkin E. I., Matveev A. V., Gorodetskii V. V., “Application of statistical lattice models to the analysis of oscillatory and autowave processes on the reaction of carbon monoxide oxidation over platinum and palladium surfaces”, Kinetics and Catalysis, 44 (2003), 692–700 | DOI

[7] Malinetskii G. G., Stepantsov M. E., “Modelirovanie diffuzionnykh protsessov s pomoschyu kletochnykh avtomatov s okrestnostyu Margolusa”, Zhurn. vychisl. matematiki i mat. fiziki, 38:6 (1998), 1017–1020 | MR

[8] Schlogl F., “Chemical reaction models for non-equilibrium phase transitions”, Zh. Physik, 253 (1972), 147–161 | DOI

[9] Overeinder B. J., Sloot P. M. A., “Application of time warp to parallel simulations with asynchronous cellular automata”, European Simulation Symposium, Delft, The Netherlands, 1993, 397–402

[10] Kalgin K. V., “Parallelnaya realizatsiya asinkhronnykh kletochno-avtomatnykh algoritmov”, Nauchno-tekhnicheskii vestnik SPbGU ITMO, 2008, no. 2(54), 108–113

[11] Bandman O., “Parallel simulation of asynchronous cellular automata evolution”, ACRI-2006, LNCS, 4173, eds. S. Yacoubi, B. Chopard, S. Bandini, Springer, Berlin, 2006, 41–47 | MR | Zbl