Tree visualization with tree-maps: 2-d space-filling approach
ACM Transactions on Graphics (TOG)
Using MPI: portable parallel programming with the message-passing interface
Using MPI: portable parallel programming with the message-passing interface
CHI '99 Extended Abstracts on Human Factors in Computing Systems
Treemaps for Workload Visualization
IEEE Computer Graphics and Applications
Pajé: An Extensible Environment for Visualizing Multi-threaded Programs Executions
Euro-Par '00 Proceedings from the 6th International Euro-Par Conference on Parallel Processing
Cushion Treemaps: Visualization of Hierarchical Information
INFOVIS '99 Proceedings of the 1999 IEEE Symposium on Information Visualization
INFOVIS '01 Proceedings of the IEEE Symposium on Information Visualization 2001 (INFOVIS'01)
Interactive Information Visualization of a Million Items
INFOVIS '02 Proceedings of the IEEE Symposium on Information Visualization (InfoVis'02)
Tree-Maps: a space-filling approach to the visualization of hierarchical information structures
VIS '91 Proceedings of the 2nd conference on Visualization '91
JRastro: A Trace Agent for Debugging Multithreaded and Distributed Java Programs
SBAC-PAD '03 Proceedings of the 15th Symposium on Computer Architecture and High Performance Computing
Voronoi treemaps for the visualization of software metrics
SoftVis '05 Proceedings of the 2005 ACM symposium on Software visualization
Toward Scalable Performance Visualization with Jumpshot
International Journal of High Performance Computing Applications
DIMVisual: Data Integration Model for Visualization of Parallel Programs Behavior
CCGRID '06 Proceedings of the Sixth IEEE International Symposium on Cluster Computing and the Grid
Interactive Exploration of Data Traffic with Hierarchical Network Maps
IEEE Transactions on Visualization and Computer Graphics
Hierarchical Edge Bundles: Visualization of Adjacency Relations in Hierarchical Data
IEEE Transactions on Visualization and Computer Graphics
Grid'5000: A Large Scale And Highly Reconfigurable Experimental Grid Testbed
International Journal of High Performance Computing Applications
KAAPI: A thread scheduling runtime system for data flow computations on cluster of multi-processors
Proceedings of the 2007 international workshop on Parallel symbolic computation
SimGrid: A Generic Framework for Large-Scale Distributed Experiments
UKSIM '08 Proceedings of the Tenth International Conference on Computer Modeling and Simulation
Performance Evaluation of NoC Architectures for Parallel Workloads
NOCS '09 Proceedings of the 2009 3rd ACM/IEEE International Symposium on Networks-on-Chip
Triva: Interactive 3D visualization for performance analysis of parallel applications
Future Generation Computer Systems
Search of performance inefficiencies in message passing applications with KappaPI 2 tool
PARA'06 Proceedings of the 8th international conference on Applied parallel computing: state of the art in scientific computing
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
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The analysis of large-scale parallel applications today has several issues, such as the observation and identification of unusual behavior of processes, expected state of the application, and so on. Performance visualization tools offer a wide spectrum of techniques to visually analyze the monitoring data collected from these applications. The problem is that most of the techniques were not conceived to deal with a high number of processes, in large-scale scenarios. A common example for that is the space-time view, largely used in the performance visualization area, but limited on how much data can be analyzed at the same time. The work presented in this article addresses the problem of visualization scalability in the analysis of parallel applications, through a combination of a temporal integration technique, an aggregation model and treemap representations. Results show that our approach can be used to analyze applications composed of several thousands of processes in large-scale and dynamic scenarios.