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國立清華大學 資訊工程學系 石維寬所指導 陳聖裕的 A Profiling Mechanism to Enhance Android Dalvik JIT through Co-operating with Ahead of Time Compilation Framework （2010），提出APK.TW 電子書關鍵因素是什麼，來自於嵌入式系統、Android、Dalvik虛擬機器、即時編譯器、效能分析。
A Profiling Mechanism to Enhance Android Dalvik JIT through Co-operating with Ahead of Time Compilation Framework
為了解決APK.TW 電子書 的問題，作者陳聖裕 這樣論述：
Immediately after Google launched the Android software platform, hardware and software developers around the world started investing in Android-based research development projects, hoping to take advantage of business opportunities relating to the new platform. The result has been a recent increase
in Android-based smart phones, and it seems that these devices will become increasingly popular over time.However, one of the biggest drawbacks of the Android platform stems from its lackluster speed and performance. In response to this problem, Google has migrated a Just-in-Time compiler (JIT) to
the latest version of the Android SDK (Software-Development-Kit). However, for a resource-limited embedded system like an Android smart phone, dynamic compilation will directly influence user-response time at startup, making deeper optimization levels unachievable. As a result, I propose a mechanism
to speed up the Android application performance, which can serve as a complement to the Dalvik JIT and improve its performance. This mechanism sent Static-Time profiling information to Dalvik Virtual Machine，in order to reduce Just in Time Compiler (JIT) overhead of Profiling and Compilation in run
-time. Then, appending an Ahead-of-Time compiler (AOTC): translate hot-spot code into native code to avoid VM`s Interpreter`s overhead in off-line. In addition, the Static-Time Profiling in this mechanism can base on the feature of Ahead-of-Time Compiler (AOTC) and Just in Time Compiler (JIT) to dis
tinguish method categories. By combining the advantages of the two compilers, improve the Android application performance.In this paper, I describe the implementation of each section in the mechanism. On average, our cooperating mechanism improves performance by 1.16 times the original JIT-only Dalv
ik Virtual Machine. While plus AOTC can improve its performance on average 3.05 times.