Complexity Enabled Design Space Exploration

被引:0
|
作者
Tamaskar, S. [1 ]
Neema, K. [1 ]
Kotegawa, T. [1 ]
DeLaurentis, D. [1 ]
机构
[1] Purdue Univ, Sch Aeronaut & Astronaut, W Lafayette, IN 47907 USA
来源
2011 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC) | 2011年
关键词
design space exploration; genetic algorithm; system complexity; flexibility; adaptability;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The proposed paper presents a framework for complexity enabled design space exploration. A circuit problem is introduced where different designs are generated from a component library to create a low pass filter circuit. Performance and complexity metrics are defined to measure the fitness of the design. A scheme for complexity enabled design space exploration is introduced and the results obtained are compared to the traditional performance based exploration. It is found that the complexity enabled exploration results in identification of regions within the performance-complexity trade space which are difficult to obtain using a performance based exploration. Characteristic features of designs that result in high performance but low complexity are also identified. Later a scheme for local design space exploration is proposed which investigates the designs in the nearest neighborhood of a particular design. This provides insights about the flexibility and adaptability of the design.
引用
收藏
页码:1250 / 1255
页数:6
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