A performance modeling method is presented to predict the execution time of a parallel Monte Carlo (MC) radiative transfer simulation code for ocean color applications. The execution time of MC simulations is predicted using a multi-layer perceptron (MLP) neural network regression model trained with past execution time measurements in different execution environments and simulation cases. On the basis of the MLP performance model, a complementary job-environment mapping algorithm enables an efficient utilization of available high-performance computing resources minimizing the total execution time of the simulation jobs distributed in multiple environments.
|Title of host publication||Proceedings of the International Conference on Computational Science (ICCS 2011), Procedia Computer Science, Vol.4|
|Publication status||Published - 1 Jan 2011|
|Event||International Conference on Computational Science (ICCS 2011) - |
Duration: 1 Jan 2011 → …
|Conference||International Conference on Computational Science (ICCS 2011)|
|Period||1/01/11 → …|