Challanges and Directions in Java Virtual Machines

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Available core counts are going up, up, up! Intel is shipping quad-core chips; Sun’s Rock has (effectively) 64 CPUs and Azul’s hardware nearly a thousand cores. How do we use all those cores effectively? The JVM proper can directly make use of a small number of cores (JIT compilation, profiling), and garbage collection can use about 20 percent more cores than the application is using to make garbage–but this hardly gets us to four cores. Application servers and transactional—J2EE/bean–applications scale well with thread pools to about 40 or 60 CPUs, and then internal locking starts to limit scaling. Unless your application has embarrassingly parallel data (e.g. data mining; risk analysis; or, heaven forbid, Fortran-style weather-prediction), how can you use more CPUs to get more performance? How do you debug the million-line concurrent program?

“Locking” paradigms (lock ranking, visual inspection) appear to be nearing the limits of program sizes that are understandable and maintainable. “Transactions,” the hot new academic solution to concurrent-programming woes, has its own unsolved issues (open nesting, “wait,” livelock, significant slowdowns without contention). Neither locks nor transactions provide compiler support for keeping the correct variables guarded by the correct synchronization, such as atomic sets. Application-specific programming, such as stream programming or graphics, is, well, application-specific. Tools (debuggers, static analyzers, profilers) and libraries (e.g. the JDK concurrency utilities) are necessary but not sufficient. Where is the general-purpose concurrent programming model? This session’s speaker claims that we need another revolution in thinking about programs.