SIMULATION OPTIMIZATION BASED ON A HETEROGENEOUS COMPUTING ENVIRONMENT

Abstract

We solve a simulation optimization using a deterministic nonlinear solver based on the sample-path concept. The method used a quadratic model built from a collection of surrounding simulation points. The scheme does not require the modification of the original simulation source code and is carried out automatically. Due to the large number of simulation runs, the highthroughput computing environment, Condor, is used. Simulation computations are distributed over a network of heterogeneous machines and execute on entirely different computer architectures. Additionally, a resource failure is automatically handled using the checkpoint and migration feature of the Condor environment. To reduce the scheduling overhead, we use a Master-Worker Condor PVM implementation that improves overall execution times.