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ReSPIR: a response surface-based Pareto iterative refinement for application-specific design space exploration

机译：RespIR：基于响应面的pareto迭代细化，用于特定应用的设计空间探索

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Gianluca Palermo; Cristina Silvano; Senior Member; Vittorio Zaccaria;
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年度 2014
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1. ReSPIR: A Response Surface-Based Pareto Iterative Refinement for Application-Specific Design Space Exploration [J] . Palermo G., Silvano C., Zaccaria V. Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on . 2009,第12期

机译：ReSPIR：基于响应曲面的帕累托迭代优化，用于特定于应用程序的设计空间探索
2. A Variability-Aware Robust Design Space Exploration Methodology for On-Chip Multiprocessors Subject to Application-Specific Constraints [J] . GIANLUCA PALERMO, CRISTINA SILVANO, VITTORIO ZACCARIA ACM Transactions on Embedded Computing Systems . 2012,第2期

机译：受特定于应用程序约束的片上多处理器的可变性感知鲁棒设计空间探索方法
3. SPIRIT: Spectral-Aware Pareto Iterative Refinement Optimization for Supervised High-Level Synthesis [J] . Xydis S., Palermo G., Zaccaria V., Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on . 2015,第1期

机译：精神：监督高层综合的光谱感知帕累托迭代优化优化
4. Concept-based evolutionary exploration of design spaces by a resolution-relaxation-Pareto approach [C] . Moshaiov Amiram, Snir Alon, Samina Barak IEEE Congress on Evolutionary Computation . 2015

机译：分辨率-松弛-帕累托方法对设计空间进行基于概念的进化探索
5. Design Refinement by Iterative Virtual Experimentation (DRIVE): A methodology to solving engineering design problems [D] . Watson, Charles M. Matt 2015

机译：通过迭代虚拟实验（DRIVE）进行设计改进：解决工程设计问题的方法
6. A Pareto-Optimal Refinement Method for Protein Design Scaffolds [O] . Lucas Gregorio Nivón, Rocco Moretti, David Baker -1

机译：蛋白质设计支架的帕累托优化方法
7. ReSPIR: A Response Surface-Based Pareto Iterative Refinement for Application-Specific Design Space Exploration [O] . G. Palermo, C. Silvano, V. Zaccaria 2009

机译：ReSPIR：基于响应曲面的帕累托迭代优化，用于特定于应用程序的设计空间探索
8. Applications of Response Surface-Based Methods to Noise Analysis in the Conceptual Design of Revolutionary Aircraft [R] . Hill, Geoffrey A., Olson, Erik D. 2004

机译：响应面法在革命性飞机概念设计中噪声分析中的应用

ReSPIR: a response surface-based Pareto iterative refinement for application-specific design space exploration

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