Improving online performance diagnosis by the use of historical performance data
SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
Clustering Algorithms
DeBugging and Performance Tuning for Parallel Computing Systems
DeBugging and Performance Tuning for Parallel Computing Systems
Medea: A Tool for Workload Characterization of Parallel Systems
IEEE Parallel & Distributed Technology: Systems & Technology
Capturing and automating performance diagnosis: the Poirot approach
IPPS '95 Proceedings of the 9th International Symposium on Parallel Processing
Deep Start: A Hybrid Strategy for Automated Performance Problem Searches
Euro-Par '02 Proceedings of the 8th International Euro-Par Conference on Parallel Processing
Toward Scalable Performance Visualization with Jumpshot
International Journal of High Performance Computing Applications
Automatic performance debugging of SPMD-style parallel programs
Journal of Parallel and Distributed Computing
Soft computing approach to performance analysis of parallel and distributed programs
Euro-Par'05 Proceedings of the 11th international Euro-Par conference on Parallel Processing
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Tuning and debugging the performance of parallel applications is an iterative process consisting of several steps dealing with identification and localization of inefficiencies, repair, and verification of the achieved performance. In this paper, we address the analysis of the performance of parallel applications from a methodological viewpoint with the aim of identifying and localizing inefficiencies. Our methodology is based on performance metrics and criteria that highlight the properties of the applications and the load imbalance and dissimilarities in the behavior of the processors. A few case studies illustrate the application of the methodology.