Performance measurement of dynamically compiled Java executions

With the development of dynamic compilers for Java, Java's performance promises to rival that of equivalent C/C++ binary executions. This should ensure that Java will become the platform of choice for ubiquitous Web-based supercomputing. Therefore, being able to build performance tools for dynamically compiled Java executions will become increasingly important. In this paper we discuss those aspects of dynamically compiled Java executions that make performance measurement di cult: (1) some Java application methods may be transformed from byte-code to native code at run-time; and (2), even in native form, application code may interact with the Java virtual machine. We describe Paradyn-J, an experimental version of the Paradyn Parallel Performance Tool that addresses this environment by describing performance data from dynamically compiled executions in terms of the multiple execution forms (interpreted byte-code and directly executed native code) of a method, costs of the dynamic compilation, and costs of residual dependencies of the application on the virtual machine. We use performance data from Paradyn-J to tune a Java application method, and improve its interpreted byte-code execution by 11% and its native form execution by 10%. As a result of tuning just one method, we improve the application's total execution time by 11% when run under Sun's ExactVM (included in the Platform2 release of JDK). The results of our work are a guide to virtual machine designers as to what type of performance data should be available through Java VM performance tool APIs.