A Tool for Scalable Profiling and Tracing of Java and Native Code Interactions

Abstract

Java workloads have two different execution spaces: one in JVM and the other in the native environment. Understanding workload activity in native and non-native (Java) spaces and its impact on the overall resource consumption of Java workloads can be very useful. For example, this knowledge can be exploited in code optimization and for efficient process level scheduling especially in emerging hybrid systems. Existing Java run time tracing tools are quite heavyweight and/or offer limited useful information for understanding Java and native space interactions. We developed an extremely lightweight tracing tool for enterprise Java workloads. The tool captures detailed per-thread statistics related to resource usage and activity in JVM and native spheres. Efficient design based on innovative thread and memory management principles enables us to achieve scalable monitoring with our tool on multi-core systems running enterprise workloads. The information captured by the tool is used to build workload profiles which can then be used for predictive performance of Java workloads in emerging systems and architectures.