Runtime Locality Optimizations of Distributed Java Applications

In distributed Java environments, locality of objects and threads is crucial for the performance of parallel applications. We introduce dynamic locality optimizations in the context of JavaParty, a programming and runtime environment for parallel Java applications. Until now, an optimal distribution of the individual objects of an application has to be found manually, which has several drawbacks. Based on a former static approach, we develop a dynamic methodology for automatic locality optimizations. By measuring processing and communication times of remote method calls at runtime, a placement strategy can be computed that maps each object of the distributed system to its optimal virtual machine. Objects then are migrated between the processing nodes in order to realize this placement strategy. We evaluate our approach by comparing the performance of two benchmark applications with manually distributed versions. It is shown that our approach is particularly suitable for dynamic applications where the optimal object distribution varies at runtime.