Tree visualization with tree-maps: 2-d space-filling approach
ACM Transactions on Graphics (TOG)
Performance Optimization for Large Scale Computing: The Scalable VAMPIR Approach
ICCS '01 Proceedings of the International Conference on Computational Science-Part II
Flexible performance visualization of parallel and distributed applications
Future Generation Computer Systems - Tools for program development and analysis
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
Toward Scalable Performance Visualization with Jumpshot
International Journal of High Performance Computing Applications
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
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
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
A scalable approach to MPI application performance analysis
PVM/MPI'05 Proceedings of the 12th European PVM/MPI users' group conference on Recent Advances in Parallel Virtual Machine and Message Passing Interface
Multi-scale analysis of large distributed computing systems
Proceedings of the third international workshop on Large-scale system and application performance
Concurrency and Computation: Practice & Experience
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Highly distributed systems such as Grids are used today to the execution of large-scale parallel applications. The behavior analysis of these applications is not trivial. The complexity appears because of the event correlation among processes, external influences like time-sharing mechanisms and saturation of network links, and also the amount of data that registers the application behavior. Almost all visualization tools to analysis of parallel applications offer a space-time representation of the application behavior. This paper presents a novel technique that combines traces from grid applications with a treemap visualization of the data. With this combination, we dynamically create an annotated hierarchical structure that represents the application behavior for the selected time interval. The experiments in the grid show that we can readily use our technique to the analysis of large-scale parallel applications with thousands of processes.