Large-Scale Design and Optimization Using Cluster Computers

INTRODUCTION The NASA/JPL goal to reduce payload in future space missions while increasing mission capability demands miniaturization and integration of active and passive sensors, analytical instruments and communication systems among others. Currently, typical system requirements include the detection of particular spectral lines, associated data processing, and communication of the acquired data to other systems. At high frequencies, advances in lithography and deposition methods result in more advanced components for space application, with submicron resolution opening a vast design space. Even relatively low frequency systems demand confined volume, low mass and component integration. Though an experimental exploration of this widening design space—searching for optimized performance by repeated fabrication efforts—is unfeasible, it does motivate the development of reliable software design tools. These tools necessitate models based on the fundamental physics and mathematics of the component for an accurate model. The software tools must lead to convenient turn-around times and include interfaces that promote efficient use. The first issue is addressed by the application of high-performance computers and the second by the development of graphical user interfaces driven by properly developed data structures. These tools can then be integrated into an optimization environment, and with the available memory capacity and computational speed of high performance parallel platforms, simulation of optimized components can proceed. In this paper we outline the use of a genetic algorithm running on cluster computers to synthesize optimized designs for infrared filters and a synthetic aperture radar antenna. A standard genetic algorithm package, integrated with design software specific to the filter or antenna, and executing on cluster computers is described. This framework is being developed for a wide range of applications. It is also currently being used in nanotechnology modeling efforts.