本篇論文係提出針對應用程式虛擬機器的效能、空間成本與結構的改善技術，並且以Java虛擬機器為應用範例。其中基礎工作是以Java虛擬器的規格自行開發了一個Java虛擬機器-Gabi (咖啡的台語發音，Java的隱含的意思即是咖啡)。在虛擬機器的效能議題上，首先應用平行處理技術將Java的應用程式執行分散至分散式系統-由成功大學電機系所發展的分散式分享記憶體系統Teamster，一個顯著的加速例子是512x512矩陣乘法運算的效能在一個四節點的系統上被加速了3.83倍。本論文在應用程式虛擬機器的效能議題上的另一貢獻是：虛擬機器的開發者傾向使用靜態暫存器配置暫存器給那些存取頻繁的變數，如程式計數器或堆疊指標，以預期可以得到虛擬機器的效能提升；然而，這樣的方式對虛擬機器的效能提升並非有決定性的影響，本篇論文針對這一個現象做一個深度的探討。
在虛擬機器的結構議題上，本篇論文針對直譯器的結構進行探討。虛擬機器的核心是虛擬指令的分派元件-直譯器，直譯器的實作方式相當多，其中以直接線程直譯器 (Directly threaded interpreter) 有較佳的指令分派效率。然而，由於要對原有的方式進行轉換，必須在直譯器內部插入一個與直譯器無關的轉換器，導致這樣的一個直譯器的設計除了指令直譯功能外尚需另有一個指令轉換器配合，使得直譯器功能模組的設計具備了不良的低偶合度特性。因此，本論文從結構上的角度提出一個新的指令包裝形式的轉換器 (Instruction-coated Translation)來解決上述的問題。
在虛擬機器的空間成本議題上，本論文針對直接線程直譯器所產生的空間成本進行改善。由於直接線程直譯器必須對原有以位元碼形式的方法轉換成32位元或64位元寬的位址形式方法，方法所使用的記憶空間於是被擴大四或八倍，於是空間成本大增，本篇論文提出Shortcode線程直譯器來改善直接線程直譯器的空間成本，此方法相較於直接線器直譯器於32位元定址形式只需一半；64位元定址形式只需四分之一的空間成本。此方式可以在不減損指令分派速度過大的情況下，節省及固定Java虛擬機器的空間成本，此方法有助於記憶體有限的嵌入式系統上的虛擬機器。

The dissertation focuses on accelerating, memory-saving, and restructuring techniques for application virtual machines using Java virtual machine (JVM) as an example. Our JVM, Gabi (the assonance of ‘café’ in Taiwanese), and later called ES-JVM, where ES-JVM is both the JVM for Embedded System and the JVM developed by Department of Engineering Science, National Cheng Kung University, was developed from scratch as a foundation of later works. A distributed version of ES-JVM was integrated into the distributed-shared memory system, Teamster (developed by department of EE, NCKU), where the multiplication of 512x512 matrices was accelerated by a factor of 3.83 on a four-node cluster. An anomaly was found that using GCC source-code-level register allocation to assign important variables of a program to hard registers would not improve performance. A new restructuring technique, instruction-coated translation, was developed to improve the cohesion of a directly threaded interpreter from communication cohesion to functional cohesion. A new technique, called Shortcode threading, was developed to have a comparable speedup to a directly threading with less memory space: one half in a 32-bit addressing machine and one quarter in a 64-bit addressing machine, respectively.

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