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Tuning and hybrid parallelization of a genetic-based multi-point statistics simulation code

Autor
Peredo, O.; Ortiz, J.; Herrero, J.; Samaniego,C.A.
Tipus d'activitat
Article en revista
Revista
Parallel computing
Data de publicació
2014-05
Volum
40
Número
5-6
Pàgina inicial
144
Pàgina final
158
DOI
https://doi.org/10.1016/j.parco.2014.04.005 Obrir en finestra nova
Resum
One of the main difficulties using multi-point statistical (MPS) simulation based on annealing techniques or genetic algorithms concerns the excessive amount of time and memory that must be spent in order to achieve convergence. In this work we propose code optimizations and parallelization schemes over a genetic-based MPS code with the aim of speeding up the execution time. The code optimizations involve the reduction of cache misses in the array accesses, avoid branching instructions and incre...
Paraules clau
Code optimization, Genetic algorithms, Geostatistics, Multi-point statistics, Parallel computing, Stochastic simulation
Grup de recerca
CAP - Grup de Computació d'Altes Prestacions

Participants