From trace generation to visualization: a performance framework for distributed parallel systems
Proceedings of the 2000 ACM/IEEE conference on Supercomputing
A Dynamic Periodicity Detector: Application to Speedup Computation
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
DiP: A Parallel Program Development Environment
Euro-Par '96 Proceedings of the Second International Euro-Par Conference on Parallel Processing-Volume II
An Integrated Performance Visualizer for MPI/OpenMP Programs
WOMPAT '01 Proceedings of the International Workshop on OpenMP Applications and Tools: OpenMP Shared Memory Parallel Programming
A Dynamic Tracing Mechanism for Performance Analysis of OpenMP Applications
WOMPAT '01 Proceedings of the International Workshop on OpenMP Applications and Tools: OpenMP Shared Memory Parallel Programming
Toward Scalable Performance Visualization with Jumpshot
International Journal of High Performance Computing Applications
Preserving time in large-scale communication traces
Proceedings of the 22nd annual international conference on Supercomputing
ScalaTrace: Scalable compression and replay of communication traces for high-performance computing
Journal of Parallel and Distributed Computing
A parallel trace-data interface for scalable performance analysis
PARA'06 Proceedings of the 8th international conference on Applied parallel computing: state of the art in scientific computing
Performance measuring framework for grid market middleware
EPEW'07 Proceedings of the 4th European performance engineering conference on Formal methods and stochastic models for performance evaluation
Scalable parallel trace-based performance analysis
EuroPVM/MPI'06 Proceedings of the 13th European PVM/MPI User's Group conference on Recent advances in parallel virtual machine and message passing interface
| Hi-index | 0.00 |
Performance analysis tools are an important component of the parallel program development and tuning cycle. To obtain the raw performance data, an instrumented application is run with probes that take measures of specific events or performance indicators. Tracing parallel programs can easily lead to huge trace files of hundreds of Megabytes. Several problems arise in this context: The storage requirement of the high number of traces from executions under slightly changed conditions; visualization packages have difficulties in showing large traces efficiently leading to slow response time; large trace files often contain huge amounts of redundant information. In this paper we propose and evaluate a dynamic scalable tracing mechanism for OpenMP based parallel applications. Our results show: With scaled tracing the size of the trace files becomes significantly reduced. The scaled traces contain only the noniterative data. The scaled trace reveals important performance information faster to the performance analyst and identifies the application structure.