On the design of global object space for efficient multi-threading Java computing on clusters

The popularity of Java and recent advances in compilation and execution technology for Java are making the language one of the preferred ones in the field of high-performance scientific and engineering computing. A distributed Java Virtual Machine supports transparent parallel execution of multi-threaded Java programs on a cluster of computers. It provides an alternative platform for high-performance scientific computations. In this paper, we present the design of a global object space for a distributed JVM. It virtualizes a single Java object heap across machine boundaries to facilitate transparent object accesses. We leverage runtime object connectivity information to detect distributed shared objects (DSOs) that are reachable from threads at different nodes to facilitate efficient memory management in the distributed JVM. Based on the concept of DSO, we propose a framework to characterize object access patterns, along three orthogonal dimensions. With this framework, we are able to effectively calibrate the runtime memory access patterns and dynamically apply optimized cache coherence protocols to minimize consistency maintenance overhead. The optimization devices include an object home migration method that optimizes the single-writer access pattern, synchronized method migration that allows the execution of a synchronized method to take place remotely at the home node of its locked object, and connectivity-based object pushing that uses object connectivity information to optimize the producer–consumer access pattern. Several benchmark applications in scientific computing have been tested on our distributed JVM. We report the performance results and give an in-depth analysis of the effects of the proposed adaptive solutions.