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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 廖世偉(Shih-Wei Liao) | |
| dc.contributor.author | Jian-Hua Chen | en |
| dc.contributor.author | 陳建華 | zh_TW |
| dc.date.accessioned | 2021-06-15T01:16:31Z | - |
| dc.date.available | 2012-08-06 | |
| dc.date.copyright | 2009-08-06 | |
| dc.date.issued | 2009 | |
| dc.date.submitted | 2009-07-28 | |
| dc.identifier.citation | [1] C. Dubach, J. Cavazos, B. Franke, M. O’Boyle, G. Fursin, and O. Temam. Fast compiler optimisation evaluation using code-feature based performance prediction. In ACM International Conference on Computing Frontiers, pages 131–142, 2007.
[2] B. Mendelson, P. Barnard, E. Ashton, E. Courtois, F. Bodin, E. Bonilla, J. Thomson, H. Leather, C. Williams, and M. O’Boyle, “Milepost gcc: machine learning based research compiler,” in Proceedings of the GCC Developers’ Summit, 2008 [3] H. Wu, E. Park, M. Kaplarevic, and Y. Zhang. Dynamic optimization option search in GCC. In Proceedings of the GCC Developers Summit 2007, 2007 [4] Lamia Djoudi , William Jalby. Automatic Analysis for Managing and Optimizing Performance-Code Quality. Conference on Programming Language Design and Implementation ,Proceedings of the 2008 workshop on Static analysis, 2008 [5] J. Cavazos, G. Fursin, F. Agakov, E. Bonilla, M. F. P. O'Boyle, and O. Temam. Rapidly selecting good compiler optimizations using performance counters. In Proceedings of the International Symposium on Code Generation and Optimization (CGO), pages 185–197, 2007 [6] K. Hoste and L. Eeckhout. Cole: Compiler optimization level exploration. In Proceedings of the International Symposium on Code Generation and Optimization (CGO), 2008 [7] L.-N. Pouchet, C. Bastoul, A. Cohen, and N. Vasilache. Iterative optimization in the polyhedral model: Part I, one-dimensional time. In CGO '07: Proceedings of the International Symposium on Code Generation and Optimization, pages 144–156, 2007. [8] L.-N. Pouchet, C. Bastoul, J. Cavazos, and A. Cohen. Iterative optimization in the polyhedral model: Part ii, multidimensional time. In PLDI '08: Proceedings of the ACM SIGPLAN 2008 conference on Programming language design and implementation, 2008. [9] Keith D. Cooper, Philip J. Schielke, and Devika Subramanian. Optimizing for reduced code space using genetic algorithms. In Proceedings of the 1999 Workshop on Languages, Compilers, and Tools for Embedded Systems (LCTES), 1999 [10] Z. Pan and R. Eigenmann. Rating compiler optimizations for automatic performance tuning. In SC2004: High Performance Computing, Networking and Storage Conference, 2004. [11] Z. Pan and R. Eigenmann. Fast and effective orchestration of compiler optimizations for automatic performance tuning. In CGO, pages 319–332, 2006. [12] Z. Pan and R. Eigenmann. Fast automatic procedure-level performance tuning. In IEEE PACT, Seattle, WA, 2006. [13] G. Bashkansky and Y. Yaari. Black box approach for selecting optimization options using budget-limited genetic algorithms. SMART ’07. [14] M. Haneda, P. M. W. Knijnenburg, and H. A. G. Wijshoff. Code size reduction by compiler tuning. In Proc. Workshop on Embedded computer Systems: Architectures, Modeling, and Simulation (SAMOS), pages 186–195, 2006. [15] M. Haneda, P. M. W. Knijnenburg, and H. A. G. Wijshoff. Optimizing general purpose compiler optimization. In Proc. Computing Frontiers, pages 180–188, 2005. [16] R. P. J. Pinkers, P. M. W. Knijnenburg, M. Haneda, and H. A. G. Wijshoff. Statistical selection of compiler options. In The IEEE Computer Societys 12th annual International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems (MASCOTS’ 04), pages 494–501, Volendam, The Netherlands,October 2004. [17] G. Fursin, C. Miranda, S. Pop, A. Cohen, and O. Temam: Practical run-time adaptation with procedure cloning to enable continuous collective compilation, In Proceedings of the 5th GCC Developer’s Summit, Ottawa, Canada, July 2007. [18] F. Agakov, E. Bonilla, J.Cavazos, B.Franke,G. Fursin, M. O’Boyle, J. Thomson,M. Toussaint, and C. Williams. Using machine learning to focus iterative optimization. In Proceedings of the International Symposium on Code Generation and Optimization (CGO), 2006 [19] GCC, the GNU Compiler Collection. http://gcc.gnu.org/ [20] SPEC CPU2006. http://www.spec.org/cpu2006/ [21] Android - An Open Handset Alliance Project. http://code.google.com/intl/zh-TW/android/ | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/42568 | - |
| dc.description.abstract | 現今電腦系統中有許多可調整的參數（例如：網路封包的大小、作業系統排程設定、及編譯器選項設定等），而參數設定的好壞會大幅影響系統的效能以及使用率。但是，要在一個複雜的電腦系統中找出一組好的參數設定是很困難的。在本文中我們提出了一套方法，並利用其來為編譯器的選項組合找出較佳的參數設定，使得應用程式在使用該參數設定後會有較佳的效能。
現代的編譯器提供了眾多的選項供使用者設定，選項設定的好壞對程式的效能及所佔空間會有相當程度的影響。但是，要找到合適的設定，需要對各個最佳化的選項有深入的了解，才能找到適合程式特性的選項，並且還要考慮到各個選項的交互影響。種種因素使得找出好的編譯器選項的難度變得很高，對一般使用者來說不是一件容易的事情。目前已經有許多的研究專注在如何系統化的挑選出較好的編譯器選項，但是大部分只針對二元的選項做設定，也就是只有打開或是關掉某些選項，但是並沒有考慮到有多元數值設定的選項。因此本文中提出了一套基於基因演算法的參數設定方法，來同時為二元以及多元數值設定的編譯器選項來快速地找出好的參數設定。在我們的實驗中，我們提出的方法使SPEC CPU2006 Benchmark有平均11.8%的效能提升，以及減少Android系統編譯後的程式碼大小約6.6%。 | zh_TW |
| dc.description.abstract | Optimizing computer systems is essential. However, modern computer systems are complex. A key driver of performance is parameter setting. There are many tunable parameters and optimizing them is not easy. With careful selection of the parameter values, better performance and higher utilization can be achieved. In this thesis, we consider a well-recognized tunable parameter set, the compilation parameters.
Compilers provide many optimization options as part of their APIs. It is hard even for a compiler expert to predict which optimization options should be turned on for optimizing a specific application. In addition to turning on or off an optimization, it might be useful if we consider the setting of some parameters that affect the behavior of the optimizations. Therefore, we proposed a multi-objective compiler option searching approach based on genetic algorithm to fast locate options that improve the applications. We achieve 11.8% speedup on SPEC CPU2006 programs over the most aggressive optimization configuration of the GNU Compiler Collection (GCC) compiler (-O3) by tuning the parameter setting of the feedback-directed optimization options of GCC. Also, we reduce the code size of the native codes on Android system by 6.6% against its default configuration. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T01:16:31Z (GMT). No. of bitstreams: 1 ntu-98-R96922095-1.pdf: 700970 bytes, checksum: 3499c2041ce2a3be0a2b76f9d1e3198c (MD5) Previous issue date: 2009 | en |
| dc.description.tableofcontents | 致謝 i
中文摘要 ii Abstract iii List of Contents v List of Figures vii List of Tables viii 1. Introduction 1 1.1 Thesis Organization 2 2. Related Works 3 2.1 Model-based Approaches 4 2.2 Search-based Approaches 5 2.3 Our Approach 7 3. Multi-objective Compiler Option Search 9 3.1 Introduction to Genetic Algorithm (GA) 10 3.2 Compiler Option Search with GA 13 3.3 Analysis and Fine-grained Search 15 3.4 Reducing Searching Time via Multi-core Machines 16 4. Experimental Results 17 4.1 Experimental Setup 17 4.2 Case Study on SPEC CPU2006 Programs 18 4.2.1 Convergence Speed 19 4.2.2 Performance Improvement 21 4.2.3 Searching Time Reduction 22 4.3 Case study on Android system 23 4.3.1 Reducing Code Size by Changing Compiler Version 24 4.3.2 Reducing Code Size by Compiler Option Search 25 5. Conclusion and Future Work 27 References 29 | |
| dc.language.iso | en | |
| dc.title | 參數空間探索：編譯器選項之個案研究 | zh_TW |
| dc.title | Parameter Space Exploration：Case Study on Compiler Options | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 97-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 陳俊良(Chuen-liang Chen),洪士灝(Shih-Hao Hung),呂學一(Hsueh-I Lu),曾紹崟(Shau-Yin Tseng) | |
| dc.subject.keyword | 編譯器,最佳化,基因演算法,參數,GCC, | zh_TW |
| dc.subject.keyword | Compiler,Optimization,Genetic Algorithm,Parameter,GCC, | en |
| dc.relation.page | 32 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2009-07-28 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊工程學研究所 | zh_TW |
| 顯示於系所單位： | 資訊工程學系 | |
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