How a Java VM can get more from a hardware performance monitor

This paper describes our sampling-based profiler that exploits a processor's HPM (Hardware Performance Monitor) to collect information on running Java applications for use by the Java VM. Our profiler provides two novel features: Java-level event profiling and lightweight context-sensitive event profiling. For Java events, we propose new techniques to leverage the sampling facility of the HPM to generate object creation profiles and lock activity profiles. The HPM sampling is the key to achieve a smaller overhead compared to profilers that do not rely on hardware helps. To sample the object creations with the HPM, which can only sample hardware events such as executed instructions or cache misses, we correlate the object creations with the store instructions for Java object headers. For the lock activity profile, we introduce an instrumentation-based technique, called ProbeNOP, which uses a special NOP instruction whose executions are counted by the HPM. For the context-sensitive event profiling, we propose a new technique called CallerChaining, which detects the calling context of HPM events based on the call stack depth (the value of the stack frame pointer). We show that it can detect the calling contexts in many programs including a large commercial application. Our proposed techniques enable both programmers and runtime systems to get more valuable information from the HPM to understand and optimize the programs without adding significant runtime overhead.