A two-level parallelization strategy for Genetic Algorithms applied to optimum shape design
This paper presents a two-level strategy for the parallelization of a Genetic Algorithm (GA) coupled to a compressible flow solver designed on unstructured triangular meshes. The parallel implementation is based on MPI and makes use of the process group features of this environment. The resulting algorithm is used for the optimum shape design of aerodynamic configurations. Numerical and performance results are presented for the optimization of two-dimensional airfoils for calculations performed on the following systems: an SGI Origin 2000 and an IBM SP-2 MIMD systems; an Pentium Pro (P6/200 MHz) cluster where the interconnection is realized through a FastEthernet (100 Mbits/s) switch.
parallelization strategy genetic algorithms optimization optimum shape design computational fluid dynamics euler equations