Profile-guided code optimization

现代面向对象编程语言，特别是Java和C#，依靠一种称为“即时”(JIT)编译的技术来实现良好的性能。JIT编译器在程序执行时生成机器码。然而，JIT编译器不能花费太多时间对程序进行广泛的分析，以充分优化程序，从而进一步提高性能。所提出的研究涉及在程序运行时收集最少量的信息，以确定程序中花费了大部分执行时间的热门部分。根据该信息，可以重新编译程序的选定部分。在重新编译的部分中，计算已经移出程序的热部分，移到冷部分，从而提高了程序的整体性能。

Modern object-oriented programming languages, Java and C# in particular, rely on a technology called 'just-in-time' (JIT) compilation to achieve good performance. JIT compilers generate machine code while the program executes. However a JIT compiler cannot afford to spend much time on extensive analysis of the program to optimize it fully, and thus to improve performance further.The proposed research involves collecting a minimal amount of information while the program runs to identify 'hot' parts of the program, where a large proportion of the execution time is spent. In the light of this information, selected portions of the program can be recompiled. In the recompiled portions, computations have been moved out of hot parts of the program and moved to cold parts, thus improving the program's overall performance.