Portable profiling and tracing for parallel, scientific applications using C++
SPDT '98 Proceedings of the SIGMETRICS symposium on Parallel and distributed tools
Design issues for efficient implementation of MPI in Java
JAVA '99 Proceedings of the ACM 1999 conference on Java Grande
Performance technology for complex parallel and distributed systems
Distributed and parallel systems
Computing in Science and Engineering
MPIJAVA: An Object-Oriented JAVA Interface to MPI
Proceedings of the 11 IPPS/SPDP'99 Workshops Held in Conjunction with the 13th International Parallel Processing Symposium and 10th Symposium on Parallel and Distributed Processing
Performance observability
Performance measurement of interpreted, just-in-time compiled, and dynamically compiled executions
Performance measurement of interpreted, just-in-time compiled, and dynamically compiled executions
Java virtual machine profiler interface
IBM Systems Journal
Monitoring of distributed Java applications
Future Generation Computer Systems - Tools for program development and analysis
CAMP: a common API for measuring performance
LISA'07 Proceedings of the 21st conference on Large Installation System Administration Conference
Building problem-solving environments with the Arches framework
Journal of Systems and Software
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Parallel Java environments present challenging problems for performance tools because of Java's rich language system and its multi-level execution platform combined with the integration of native-code application libraries and parallel runtime software. In addition to the desire to provide robust performance measurement and analysis capabilities for the Java language itself, the coupling of different software execution contexts under a uniform performance model needs careful consideration of how events of interest are observed and how cross-context parallel execution information is linked. This paper relates our experience in extending the TAU performance system to a parallel Java environment based on mpiJava. We describe the complexities of the instrumentation model used, how performance measurements are made, and the overhead incurred. A parallel Java application simulating the game of Life is used to show the performance system's capabilities.