The Journal of Supercomputing, 28, 91--117, 2004

We describe and evaluate a novel approach for the automatic parallelization of programs that use pointer-based dynamic data structures, written in Java. The approach exploits parallelism among methods by creating an asynchronous thread of execution for each method invocation in a program. At compile time, methods are analyzed to determine the data they access, parameterized by their context. A description of these data accesses is transmitted to a run-time system during program execution. The runtime system utilizes this description to determine when a thread may execute, and to enforce dependences among threads. This run-time system is the main focus of this paper. More specifically, the paper details the representation of data accesses in a method and the framework used by the run-time system to detect and enforce dependences among threads. Experimental evaluation of an implementation of the run-time system on a four-processor Sun multiprocessor indicates that close to ideal speedup can be obtained for a number of benchmarks. This validates our approach

OpenMP Extensions for Thread Groups and

This paper presents a set of proposals for the OpenMP shared-- memory programming model oriented towards the definition of thread groups in the framework of nested parallelism. The paper also describes the additional functionalities required in the runtime library supporting the parallel execution. The extensions have been implemented in the OpenMP NanosCompiler and evaluated in a set of real applications and benchmarks. In this paper we present experimental results for one of these applications