Analysis of Hotspot Methods in JVM for Best-Effort Run-Time Parallelization

A fully automated run-time parallelization of an application without any input from the user is the ultimate target of research efforts in High Performance Computing. As run-time methodologies are typically sensitive to analysis and modification overheads, there should be a stricter selection criteria rather than analyzing all code. A hotspot method marked for Just-In-Time (JIT) compilation is a potential candidate for analysis because of its high execution rate. Our work is an attempt to analyze bare minimum portions of code identified by the profiling mechanism of Java Virtual Machine for potential loop parallelism. Our approach is best-effort as we do not force parallelization where it may not be effective i.e., only in hotspot methods. We analyzed hotspot methods of more than fifty java applications of varying categories and found that function call to another method was the major hurdle in run-time parallelization. However, minor changes in source code can make them parallelizable on run-time. Some test applications showed improved performance.