Parallel Processing Approaches for Multi Disciplinary Optimization
Florin B. Manolache
Dept. of Mathematical Sciences
Carnegie Mellon University
Pittsburgh, PA 15213, USA
United Technologies Co.
UTRC, 411 Silver Ln.
Hartford, CT 06108, USA
Disciplinary Optimization (MDO) problems are often encountered in many
industrial areas. MDO refers to the optimization of systems of
subsystems (disciplines). The optimization of the full system is
often reduced to a hierarchy of optimizations at subsystem and system
levels. This paper presents a concise survey of major MDO approaches
and discusses opportunities of parallel processing (PP) at four
algorithmic levels of the approaches, i.e., the subsystem solver level, and the sequence of problems level. Advantages of different PP implementations of the MDO approaches are outlined. Special emphasis is put on vertical PP processing, where one thread treats hierarchical structure (e.g., a full system evaluation), inter-thread communication is low, and processor loads are uniform.
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