臺灣博碩士論文加值系統

傳統編譯器最佳化選項自動選取工具，大都是奠基於像基因演算法這類的全域搜尋演算法。這類搜尋演算法為了找到全域最佳解，通常都會在龐大的搜尋空間花上大量的搜尋時間。由於現存的最佳化層級，對程式效能已有不錯的提升效果。本論文利用爬山法這類的區域搜尋演算法快速地去找出比原先結果還要好的區域最佳解。我們並且針對弁鈱

The traditional tools for automatic selection of compiler optimization options are usually based on global search algorithms like genetic algorithms. This kind of global search algorithms usually take a large amount of time and explore huge search space to find global optimum. Since optimization levels usually provide good improvement, this thesis investigates the effect of using local search algorithms like hill-climbing algorithms to quickly find local optimum. This thesis also investigates a procedure to find new optimization levels for domain specific groups of applications.

摘要 I
ABSTRACT II
目錄 III
圖目錄 V
表目錄 VII
第1章 概論 1
1-1 研究動機 1
1-2 研究目的 1
1-3 研究貢獻 2
1-4 論文架構 2
第2章 相關研究 3
2-1 調適性編譯技術 3
2-2 最佳化搜尋演算法 3
2-3 編譯時間的改善 5
2-4 程式集的效能評估 6
第3章 系統架構 8
3-1 系統流程 8
3-2 系統模組說明 10
3-3 使用者環境設置 12
第4章 系統實作 14
4-1 資料結構 14
4-2 演算法 17
第5章 區域搜尋法的效能評估 20
5-1 評量程式 20
5-2 實驗環境 21
5-3 實驗結果 22
第6章 新最佳化選項組合的效能評估 31
6-1 新最佳化選項組合的搜尋 31
6-1-1 流程說明 32
6-2 實驗結果 32
第7章 結論及未來展望 38
參考文獻 39

參考文獻
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