What to draw? When to draw?: an essay on parallel program visualization
Journal of Parallel and Distributed Computing - Special issue on tools and methods for visualization of parallel systems and computations
Visualizing the Performance of Parallel Programs
IEEE Software
Visualization of Do-Loop Performance
HPCN Europe '97 Proceedings of the International Conference and Exhibition on High-Performance Computing and Networking
A Trace-Scaling Agent for Parallel Application Tracing
ICTAI '02 Proceedings of the 14th IEEE International Conference on Tools with Artificial Intelligence
An Algebra for Cross-Experiment Performance Analysis
ICPP '04 Proceedings of the 2004 International Conference on Parallel Processing
Toward Scalable Performance Visualization with Jumpshot
International Journal of High Performance Computing Applications
A test suite for parallel performance analysis tools: Research Articles
Concurrency and Computation: Practice & Experience - European–American Working Group on Automatic Performance Analysis (APART)
Preserving time in large-scale communication traces
Proceedings of the 22nd annual international conference on Supercomputing
Evaluating similarity-based trace reduction techniques for scalable performance analysis
Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis
Visualization of repetitive patterns in event traces
PARA'06 Proceedings of the 8th international conference on Applied parallel computing: state of the art in scientific computing
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
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
Towards scalable event tracing for high end systems
HPCC'07 Proceedings of the Third international conference on High Performance Computing and Communications
Trace profiling: Scalable event tracing on high-end parallel systems
Parallel Computing
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Parallel event trace visualizations can aid in discovery of the root causes of certain performance problems on high-end systems. However, traditional trace visualizations are not inherently scalable and require considerable effort on the part of the user to identify similarities and differences in performance across parallel entities. In this work, we evaluate several methods for deciding when traces of different processes in a run are similar enough that only one of the traces needs to be retained and rendered in the visualization. We show visualizations of reduced traces and evaluate them for compression, error, and retention of correct diagnostic information.